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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>Hi Tom,<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>Thanks for investigating. Yes, the eigenvalues measure the variance in the data cloud/ellipsoid in the directions of the eigenvectors and should be positive. Negative values are likely a result of numerical instability with certain datasets. I will try to address the negative eigenvalues issue in the next update, but will probably propose to do automatic high pass filtering in this case since ICA on data that is not most zero-mean stationary is not likely to produce good results.<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>-Jason<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p><div><div style='border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0in 0in 0in'><p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> Tom Campbell [mailto:tom_campbell75@hotmail.com] <br><b>Sent:</b> Thursday, May 24, 2012 7:12 AM<br><b>To:</b> Jason Palmer; Zohre AMICA; Katsumi Minakata; eeglab list<br><b>Subject:</b> RE: [Eeglablist] Running AMICA<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><br>hello,<br><br>To clarify, the filter reduced the absolute value of minimum and maximum eigenvalues and causes the negative minimum eigenvalue to become positive:<o:p></o:p></span></p><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>Before filter (doesn't work):<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>minimum eigenvalues = -2.479795063170239E-009 -2.773409294222618E-011 <br>1.275783805586119E-011 <br>maximum eigenvalues = 161054352.739035 102447608.931233 <br>1207240.44876992 <o:p></o:p></span></p></div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> <br>After filter (works)<br> minimum eigenvalues = 2.340401990423154E-012 4.332755873716145E-012 <br>4.469738346934859E-012 <br>maximum eigenvalues = 8268465.72257646 5610773.31172101 <br>28354.5920893493 <br> <br>The range is smaller.<br> <br>I think the eigenvalue is an index of the variance explained by a component. Variance should be positive.<br> <br>T<o:p></o:p></span></p><div><div class=MsoNormal align=center style='text-align:center'><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><hr size=2 width="100%" align=center id=stopSpelling></span></div><p class=MsoNormal style='margin-bottom:12.0pt'><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From: <a href="mailto:tom_campbell75@hotmail.com">tom_campbell75@hotmail.com</a><br>To: <a href="mailto:japalmer@ucsd.edu">japalmer@ucsd.edu</a>; <a href="mailto:send2zohre@yahoo.com">send2zohre@yahoo.com</a>; <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>; <a href="mailto:kminakata@gmail.com">kminakata@gmail.com</a><br>Date: Wed, 23 May 2012 22:49:05 +0000<br>Subject: Re: [Eeglablist] Running AMICA<o:p></o:p></span></p><div><div><p class=MsoNormal style='margin-bottom:12.0pt'><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> Hi Jason, The 1Hz highpass filter seemed to work and turned the maximum and minimum eigenvalue from negative to positive and the amended runamica12_old gave a decomposition. There's deliberately a lot of smooth pursuit eyemovements in there as it is what the experiment is about, but things weren't saturating even before the 1Hz highpass. Sure, I've seen the stack overflow error even with over 50G RAM on the machine, but not with this epoched dataset. I'll test out the runamica12 approach with an initial 0.1-30 Hz rather than a 1-30Hz bandpass on other datasets and will get back to you if I can better characterise conditions when it fails. I take it eigenvalues need to be positive for amica to run the main loop.T<o:p></o:p></span></p><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> <o:p></o:p></span></p></div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><br> <o:p></o:p></span></p><div><div class=MsoNormal align=center style='text-align:center'><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><hr size=2 width="100%" align=center id=ecxstopSpelling></span></div><p class=MsoNormal style='margin-bottom:12.0pt'><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From: <a href="mailto:japalmer29@gmail.com">japalmer29@gmail.com</a><br>To: <a href="mailto:tom_campbell75@hotmail.com">tom_campbell75@hotmail.com</a>; <a href="mailto:send2zohre@yahoo.com">send2zohre@yahoo.com</a>; <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>; <a href="mailto:kminakata@gmail.com">kminakata@gmail.com</a><br>Subject: RE: [Eeglablist] Running AMICA<br>Date: Wed, 23 May 2012 14:58:10 -0700<o:p></o:p></span></p><div><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>Hi Tom,</span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>There was a runamica12.m posted with a typo up briefly, sorry you must have downloaded it in that window. It should be fixed now.</span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>There seems to be something numerically strange about the data that is giving NaNs. The minimum eigenvalue is negative, but it shouldn’t be since they are supposed to correspond to the covariance matrix … This could be resulting in NaN for the Log Likelihood. Are you removing “overload” time points, i.e. large potential spikes from the data? Does it ever fail with positive minimum eigenvalues?</span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>One other possibility is stack overflow, which can be caused by too large a block_size and too little RAM. Does it work with other datasets of the same size?</span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>-Jason</span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p><div><div style='border:none;border-top:solid windowtext 1.0pt;padding:3.0pt 0in 0in 0in;border-color:currentColor currentColor'><p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> Tom Campbell <a href="mailto:[mailto:tom_campbell75@hotmail.com]">[mailto:tom_campbell75@hotmail.com]</a> <br><b>Sent:</b> Wednesday, May 23, 2012 6:39 AM<br><b>To:</b> <a href="mailto:japalmer@ucsd.edu">japalmer@ucsd.edu</a>; <a href="mailto:send2zohre@yahoo.com">send2zohre@yahoo.com</a>; eeglab list; Katsumi Minakata<br><b>Subject:</b> RE: [Eeglablist] Running AMICA<o:p></o:p></span></p></div></div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> <o:p></o:p></span></p><div><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>Hi Jason, <br> <br>Thank you very much for your helpful response. <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>I tried using the latest runamica12 from the amica website and this gave an error early in the function (see below). So I rechristened the runamica12 from March as runamica12_old and set the flag not to optmise at line 180 </span><span style='font-size:10.0pt;font-family:"Courier New"'><br>do_opt_block = 0; <br></span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>This led to log likeliehoods of NaN that completes after a few steps. I believe this is not good news.<br> <br>I'd already done a 0.1 to 30Hz Butterworth bandpass in ERPLAB and interpolated bad channels. To test the idea that this was not sufficient to condition the data, I then did an additional highpass filter on the continuous data (1Hz cutoff as suggested) reepoched and ran amica. It took all night but with very long epochs. (runamica12 seems to place overall less demand on the cpu and seems to divide usage across cores more evenly than amica.m of eeglab 9. I think it could be faster.) More eigs are kept and the maximum and minimum eigenvalues are smaller than before the filter - - but I now see a decomposition from using runamica12_old and will test this on other datasets. I think this pattern of performance is consistent with the fact that withouth this additional filter infomax complained about rank with 168 rather than 152 components (as requires PCA).<br> <br>Some ERP researchers like not to filter, and smooth the ERP at the end, perhaps through experience of effects that are due to filtering artifacts. I think this is not an option for ica, as a decomposition is extremely slow to arrive at with unfiltered data. Other influential scientists have views about 1Hz being a maximum for the highpass filter cutoff. I usually apply a broad standard filter when interested in Long Latency Responses and narrow as necesary to best reveal the ERP component of theoretical interest with the caveat of 1Hz maximum at the back of my mind. The 1Hz rule at least puts a restraint on those who might fool themselves into optimising a filter to find effects that are not there, but the rationale is not so clear in my mind for the 1Hz rule and I wonder if it is just a "shouldbedoneness". With a view to finding components of theoretical interest by way if exposing genuine structure in the data, the eigenvalues may offer reason to adjust the highpass cutoff. What do you look for in the eigenvalues and why?<br> <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>Best regards,<o:p></o:p></span></p></div><div><p class=MsoNormal style='margin-bottom:12.0pt'><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>Tom.<br> <br> <br> <br> >> [EEG.icaweights, EEG.icasphere, mods] = runamica12(EEG.data(:,:));<br>Error: File: runamica12.m Line: 100 Column: 1<br>At least one END is missing: the statement may begin here.<br> <br>>> [EEG.icaweights, EEG.icasphere, mods] = runamica12_old(EEG.data(:,:));<br>The system cannot find the path specified. <br>The system cannot find the path specified. <br>The system cannot find the path specified. <br>No recognized parallel environment found. Run qconf -spl to get a list of available environments and use keyword use_pe.<br>Running locally ...<br>Writing data file: C:\tom\MotParEEG\code\tmpdata9754.fdt<br>A subdirectory or file C:\tom\MotParEEG\code\amicaouttmp\ already exists. <br> 1 processor name = cvcn-PC.psydomain.psych.ndsu.nodak.edu <br> 1 host_num = -988751630 <br> This is MPI process 1 of 1 ; I am process 1 of <br> 1 on node: cvcn-PC.psydomain.psych.ndsu.nodak.edu <br> 1 : node root process 1 of 1 <br>Processing arguments ... <br> num_files = 1 <br> FILES: <br> C:\tom\MotParEEG\code\tmpdata9754.fdt <br> num_dir_files = 1 <br> initial matrix block_size = 128 <br> do_opt_block = 0 <br> number of models = 1 <br> number of density mixture components = 3 <br> pdf type = 0 <br> max_iter = 2000 <br> num_samples = 1 <br> data_dim = 168 <br> field_dim = 630432 <br> do_history = 0 <br> histstep = 10 <br> share_comps = 0 <br> share_start = 100 <br> comp_thresh = 0.990000000000000 <br> share_int = 100 <br> initial lrate = 0.100000000000000 <br> minimum lrate = 1.000000000000000E-008 <br> lrate factor = 0.500000000000000 <br> initial rholrate = 5.000000000000000E-002 <br> rho0 = 1.50000000000000 <br> min rho = 1.00000000000000 <br> max rho = 2.00000000000000 <br> rho lrate factor = 0.500000000000000 <br> kurt_start = 3 <br> num kurt = 5 <br> kurt interval = 1 <br> do_newton = 1 <br> newt_start = 50 <br> newt_ramp = 10 <br> initial newton lrate = 1.00000000000000 <br> do_reject = 0 <br> num reject = 3 <br> reject sigma = 3.00000000000000 <br> reject start = 2 <br> reject interval = 3 <br> max_thrds = 2 <br> write step = 10 <br> write_nd = 0 <br> write_LLt = 1 <br> dec window = 1 <br> max_decs = 3 <br> fix_init = 0 <br> update_A = 1 <br> update_c = 1 <br> update_gm = 1 <br> update_alpha = 1 <br> update_mu = 1 <br> update_beta = 1 <br> invsigmax = 100.000000000000 <br> invsigmin = 0.000000000000000E+000 <br> do_rho = 1 <br> load_rej = 0 <br> load_c = 0 <br> load_gm = 0 <br> load_alpha = 0 <br> load_mu = 0 <br> load_beta = 0 <br> load_rho = 0 <br> load_comp_list = 0 <br> do_mean = 1 <br> do_sphere = 1 <br> doPCA = 1 <br> pcadb = 30.0000000000000 <br> byte_size = 4 <br> doscaling = 1 <br> scalestep = 1 <br>A subdirectory or file C:\tom\MotParEEG\code\amicaouttmp\ already exists. <br> output directory = C:\tom\MotParEEG\code\amicaouttmp\ <br> 1 : setting num_thrds to 2 ... <br> 1 : using 2 threads. <br> 1 : node_thrds = 2 <br> bytes in real = 1 <br> 1 : REAL nbyte = 1 <br> getting segment list ... <br> blocks in sample = 630432 <br> total blocks = 630432 <br> node blocks = 630432 <br> node 1 start: file 1 sample 1 index <br> 1 <br> node 1 stop : file 1 sample 1 index <br> 630432 <br> 1 : data = 1.56996357440948 4.14537858963013 <br> getting the mean ... <br> mean = 17.8814624526213 4.04874816619494 <br> 4.16267019397148 <br> subtracting the mean ... <br> getting the sphering matrix ... <br> cnt = 630432 <br> doing eig nx = 168 lwork = 282240 <br> minimum eigenvalues = -2.479795063170239E-009 -2.773409294222618E-011 <br> 1.275783805586119E-011 <br> maximum eigenvalues = 161054352.739035 102447608.931233 <br> 1207240.44876992 <br> num eigs kept = 166 <br> numeigs = 166 <br> sphering the data ... <br> 1 Allocating variables ... <br> 1 : Initializing variables ... <br> 1 : block size = 128 <br> 1 : entering the main loop ... <br> iter 1 lrate = 0.1000000000 LL = NaN nd = NaN, D = 0.11379E+00 0.11379E+00 ( 20.19 s, 11.2 h) <br> Reinitializaing and starting over ... <br> iter 1 lrate = 0.1000000000 LL = NaN nd = NaN, D = 0.11451E+00 0.11451E+00 ( 19.78 s, 11.0 h) <br> Reinitializaing and starting over ... <br> iter 1 lrate = 0.1000000000 LL = NaN nd = NaN, D = 0.11568E+00 0.11568E+00 ( 19.85 s, 11.0 h) <br> Reinitializaing and starting over ... <br> iter 1 lrate = 0.1000000000 LL = NaN nd = NaN, D = 0.11444E+00 0.11444E+00 ( 19.98 s, 11.1 h) <br> Reinitializaing and starting over ... <br> iter 1 lrate = 0.1000000000 LL = NaN nd = NaN, D = 0.11470E+00 0.11470E+00 ( 19.84 s, 11.0 h) <br>... done. Execution time: 0.03 h <br> output directory = C:\tom\MotParEEG\code\amicaouttmp\ <br>eeg_checkset: recomputing the ICA activation matrix ...<br>pop_eegplot() note: Baseline subtraction disabled to speed up display<br>>> EEG = pop_eegfilt( EEG, 1.0, 0, [], [0] );<br>Warning: Using firls to estimate filter coefficients. We recommend that you use fir1 instead, which yields larger attenuation. In future, fir1<br>will be used by default! <br>> In eegfilt at 104<br> In pop_eegfilt at 227 <br>eegfilt(): filter order is 768. Error using eegfilt (line 132)<br>epochframes must be at least 3 times the filtorder.<br>Error in pop_eegfilt (line 227)<br> [EEG.data, b] = eegfilt( EEG.data, options{:});<br> <br>pop_loadset(): loading file C:\tom\MotParEEG\data\bd4\bd4_track_cor.set ...<br>Reading float file 'C:\tom\MotParEEG\data\bd4\bd4_track_cor.fdt'...<br>Creating a new ALLEEG dataset 2<br>Done.<br>>> EEG = pop_eegfilt( EEG, 1.0, 0, [], [0] );<br>Warning: Using firls to estimate filter coefficients. We recommend that you use fir1 instead, which yields larger attenuation. In future, fir1<br>will be used by default! <br>> In eegfilt at 104<br> In pop_eegfilt at 218 <br>eegfilt() - performing 768-point highpass filtering.<br>eegfilt() - highpass transition band width is 0.2 Hz.<br>...................20...................40...................60...................80...................100.....EEG.data = EEG.data(1:168,:)<br>EEG.nbchan = 168<br>EEG.chanlocs = EEG.chanlocs(1:168)<br>intertrig = getintertrig(EEG);<br>EEG = pop_editeventlist(EEG, 'C:\tom\MotParEEG\code\testi.txt', ''); %may want to alter this when doing multiple conditions.<br>EEG = pop_overwritevent(EEG, 'binlabel');<br>baseline = -0.2<br>EEG = pop_epochbin(EEG, [baseline (intertrig+(-baseline))]*1000, 'pre');<br>..............120...................140...................160.........<br>EEG = <br> setname: ''<br> filename: 'bd4_track_cor.set'<br> filepath: 'C:\tom\MotParEEG\data\bd4\'<br> subject: ''<br> group: ''<br> condition: ''<br> session: []<br> comments: 'Original file: C:\tom\MotParEEG\RAW\bd4\bd4_track_01.bdf'<br> nbchan: 169<br> trials: 1<br> pnts: 570112<br> srate: 256<br> xmin: 0<br> xmax: 2.2270e+03<br> times: []<br> data: [168x570112 double]<br> icaact: []<br> icawinv: []<br> icasphere: []<br> icaweights: []<br> icachansind: []<br> chanlocs: [1x169 struct]<br> urchanlocs: []<br> chaninfo: [1x1 struct]<br> ref: 'averef'<br> event: [1x2696 struct]<br> urevent: [1x1794 struct]<br> eventdescription: {'' '' '' ''}<br> epoch: []<br> epochdescription: {}<br> reject: [1x1 struct]<br> stats: [1x1 struct]<br> specdata: []<br> specicaact: []<br> splinefile: ''<br> icasplinefile: ''<br> dipfit: []<br> history: [1x150 char]<br> saved: 'yes'<br> etc: []<br> datfile: 'bd4_track_cor.fdt'<br><br>EEG = <br> setname: ''<br> filename: 'bd4_track_cor.set'<br> filepath: 'C:\tom\MotParEEG\data\bd4\'<br> subject: ''<br> group: ''<br> condition: ''<br> session: []<br> comments: 'Original file: C:\tom\MotParEEG\RAW\bd4\bd4_track_01.bdf'<br> nbchan: 168<br> trials: 1<br> pnts: 570112<br> srate: 256<br> xmin: 0<br> xmax: 2.2270e+03<br> times: []<br> data: [168x570112 double]<br> icaact: []<br> icawinv: []<br> icasphere: []<br> icaweights: []<br> icachansind: []<br> chanlocs: [1x169 struct]<br> urchanlocs: []<br> chaninfo: [1x1 struct]<br> ref: 'averef'<br> event: [1x2696 struct]<br> urevent: [1x1794 struct]<br> eventdescription: {'' '' '' ''}<br> epoch: []<br> epochdescription: {}<br> reject: [1x1 struct]<br> stats: [1x1 struct]<br> specdata: []<br> specicaact: []<br> splinefile: ''<br> icasplinefile: ''<br> dipfit: []<br> history: [1x150 char]<br> saved: 'yes'<br> etc: []<br> datfile: 'bd4_track_cor.fdt'<br><br>EEG = <br> setname: ''<br> filename: 'bd4_track_cor.set'<br> filepath: 'C:\tom\MotParEEG\data\bd4\'<br> subject: ''<br> group: ''<br> condition: ''<br> session: []<br> comments: 'Original file: C:\tom\MotParEEG\RAW\bd4\bd4_track_01.bdf'<br> nbchan: 168<br> trials: 1<br> pnts: 570112<br> srate: 256<br> xmin: 0<br> xmax: 2.2270e+03<br> times: []<br> data: [168x570112 double]<br> icaact: []<br> icawinv: []<br> icasphere: []<br> icaweights: []<br> icachansind: []<br> chanlocs: [1x168 struct]<br> urchanlocs: []<br> chaninfo: [1x1 struct]<br> ref: 'averef'<br> event: [1x2696 struct]<br> urevent: [1x1794 struct]<br> eventdescription: {'' '' '' ''}<br> epoch: []<br> epochdescription: {}<br> reject: [1x1 struct]<br> stats: [1x1 struct]<br> specdata: []<br> specicaact: []<br> splinefile: ''<br> icasplinefile: ''<br> dipfit: []<br> history: [1x150 char]<br> saved: 'yes'<br> etc: []<br> datfile: 'bd4_track_cor.fdt'<br><br>NOTE: Event codes are numeric. So wspacekiller() was not applied.<br><br>Creating an EVENTINFO by the first time...<br>For pre-edited list of changes, user selected C:\tom\MotParEEG\code\testi.txt<br>Assigning code labels to numeric codes. Looking for numeric codes...<br> #: Event codes 3.01e+08 were labeled LeftSPEM . <br> #: Event codes 3.01e+08 were bined 1 . <br> #: Event codes 3.01e+08 were bin-labeled LeftSPEM . <br> #: Event codes 4.01e+08 were labeled RightSPEM . <br> #: Event codes 4.01e+08 were bined 2 . <br> #: Event codes 4.01e+08 were bin-labeled RightSPEM . <br> #: Event codes 31 were labeled Fixation . <br> #: Event codes 31 were bined 3 . <br> #: Event codes 31 were bin-labeled Fixation . <br>Assigning numeric codes to alphanumeric codes. Moving alphanumeric codes to code labels. Looking for alphanumeric codes...<br> #: Event codelabels LeftSPEM were encoded 301000000 . <br> #: Event codes 3.01e+08 were bin-labeled LeftSPEM . <br> #: Event codelabels LeftSPEM were bined 1 . <br> #: Event codelabels RightSPEM were encoded 401000000 . <br> #: Event codes 4.01e+08 were bin-labeled RightSPEM . <br> #: Event codelabels RightSPEM were bined 2 . <br> #: Event codelabels Fixation were encoded 31 . <br> #: Event codes 31 were bin-labeled Fixation . <br> #: Event codelabels Fixation were bined 3 . <br>Creating a EventList structure...<br>Total Events (eventcodes + pauses) = 2696 <br>Creating an EventList text file...<br>A new EventList file was created at C:\tom\MotParEEG\code\eeglabsvn\plugins\erplab_2.0.0.1\erplab_Temp\eventlist_backup_7350118204745371<br>pastebinlist(): EVENTLIST structure was added to the EEG structure successfuly!<br>Event resorted by increasing latencies. Some event indices have changed.<br> COMPLETE<br>EEG.EVENTLIST.eventinfo is correct.<br>EEG.EVENTLIST.eventinfo.binlabel will replace your EEG.event.type structure.<br>eeg_checkset note: value format of event field 'type' made uniform<br>EEG.event was updated.<br> COMPLETE<br><br>baseline =<br> -0.2000<br>pop_epochbin : START<br>* Detected non-binlabeled event codes: <br>"" <br>* Detected bin-labeled event codes: <br>B1(LeftSPEM) B2(RightSPEM) B3(Fixation) <br>eeg_checkset note: value format of event field 'type' made uniform<br>EEG.event was updated.<br>pop_epoch():597 epochs selected<br>Epoching...<br>pop_epoch():597 epochs generated<br>pop_epoch(): time limits have been adjusted to [-0.199 3.926] to fit data points limits<br>pop_epoch(): checking epochs for data discontinuity<br>Zero latencies OK.<br><br>-------------------------------------------------------------------------------<br>Warning: EEG.event and EEG.EVENTLIST.eventinfo structure will not longer match.<br>EEG.event only contains info about events within each epoch.<br>EEG.EVENTLIST.eventinfo still contains all the original (continuous) events info.<br>The purpose of this is to allow users to set flags during artifact detection,and to rebuild a continuous EVENTLIST with this info.<br>-------------------------------------------------------------------------------<br>pop_rmbase(): Removing baseline...<br>Baseline correction was performed at [-199.2188 0] <br>pop_epochbin : END<br> COMPLETE<br>>> [EEG.icaweights, EEG.icasphere, mods] = runamica12_old(EEG.data(:,:));<br>The system cannot find the path specified. <br>The system cannot find the path specified. <br>The system cannot find the path specified. <br>No recognized parallel environment found. Run qconf -spl to get a list of available environments and use keyword use_pe.<br>Running locally ...<br>Writing data file: C:\tom\MotParEEG\code\tmpdata27850.fdt<br>A subdirectory or file C:\tom\MotParEEG\code\amicaouttmp\ already exists. <br> 1 processor name = cvcn-PC.psydomain.psych.ndsu.nodak.edu <br> 1 host_num = -988751630 <br> This is MPI process 1 of 1 ; I am process 1 of <br> 1 on node: cvcn-PC.psydomain.psych.ndsu.nodak.edu <br> 1 : node root process 1 of 1 <br>Processing arguments ... <br> num_files = 1 <br> FILES: <br> C:\tom\MotParEEG\code\tmpdata27850.fdt <br> num_dir_files = 1 <br> initial matrix block_size = 128 <br> do_opt_block = 0 <br> number of models = 1 <br> number of density mixture components = 3 <br> pdf type = 0 <br> max_iter = 2000 <br> num_samples = 1 <br> data_dim = 168 <br> field_dim = 630432 <br> do_history = 0 <br> histstep = 10 <br> share_comps = 0 <br> share_start = 100 <br> comp_thresh = 0.990000000000000 <br> share_int = 100 <br> initial lrate = 0.100000000000000 <br> minimum lrate = 1.000000000000000E-008 <br> lrate factor = 0.500000000000000 <br> initial rholrate = 5.000000000000000E-002 <br> rho0 = 1.50000000000000 <br> min rho = 1.00000000000000 <br> max rho = 2.00000000000000 <br> rho lrate factor = 0.500000000000000 <br> kurt_start = 3 <br> num kurt = 5 <br> kurt interval = 1 <br> do_newton = 1 <br> newt_start = 50 <br> newt_ramp = 10 <br> initial newton lrate = 1.00000000000000 <br> do_reject = 0 <br> num reject = 3 <br> reject sigma = 3.00000000000000 <br> reject start = 2 <br> reject interval = 3 <br> max_thrds = 2 <br> write step = 10 <br> write_nd = 0 <br> write_LLt = 1 <br> dec window = 1 <br> max_decs = 3 <br> fix_init = 0 <br> update_A = 1 <br> update_c = 1 <br> update_gm = 1 <br> update_alpha = 1 <br> update_mu = 1 <br> update_beta = 1 <br> invsigmax = 100.000000000000 <br> invsigmin = 0.000000000000000E+000 <br> do_rho = 1 <br> load_rej = 0 <br> load_c = 0 <br> load_gm = 0 <br> load_alpha = 0 <br> load_mu = 0 <br> load_beta = 0 <br> load_rho = 0 <br> load_comp_list = 0 <br> do_mean = 1 <br> do_sphere = 1 <br> doPCA = 1 <br> pcadb = 30.0000000000000 <br> byte_size = 4 <br> doscaling = 1 <br> scalestep = 1 <br>A subdirectory or file C:\tom\MotParEEG\code\amicaouttmp\ already exists. <br> output directory = C:\tom\MotParEEG\code\amicaouttmp\ <br> 1 : setting num_thrds to 2 ... <br> 1 : using 2 threads. <br> 1 : node_thrds = 2 <br> bytes in real = 1 <br> 1 : REAL nbyte = 1 <br> getting segment list ... <br> blocks in sample = 630432 <br> total blocks = 630432 <br> node blocks = 630432 <br> node 1 start: file 1 sample 1 index <br> 1 <br> node 1 stop : file 1 sample 1 index <br> 630432 <br> 1 : data = 7.98771333694458 4.56790590286255 <br> getting the mean ... <br> mean = -1.00493798557990 8.072328675494686E-002 <br> 0.288139179516208 <br> subtracting the mean ... <br> getting the sphering matrix ... <br> cnt = 630432 <br> doing eig nx = 168 lwork = 282240 <br> minimum eigenvalues = 2.340401990423154E-012 4.332755873716145E-012 <br> 4.469738346934859E-012 <br> maximum eigenvalues = 8268465.72257646 5610773.31172101 <br> 28354.5920893493 <br> num eigs kept = 168 <br> numeigs = 168 <br> sphering the data ... <br> 1 Allocating variables ... <br> 1 : Initializing variables ... <br> 1 : block size = 128 <br> 1 : entering the main loop ... <br> iter 1 lrate = 0.1000000000 LL = -1.4073937085 nd = 0.0417212782, D = 0.11667E+00 0.11667E+00 ( 20.37 s, 11.3 h) <br> iter 2 lrate = 0.1000000000 LL = -1.2546004168 nd = 0.0281749957, D = 0.29315E+00 0.29315E+00 ( 20.49 s, 11.4 h) <br> iter 3 lrate = 0.1000000000 LL = -1.1854670558 nd = 0.0559715513, D = 0.38966E+00 0.38966E+00 ( 20.78 s, 11.5 h) <br> iter 4 lrate = 0.1000000000 LL = -1.1770409517 nd = 0.0719156264, D = 0.10315E+01 0.10315E+01 ( 20.39 s, 11.3 h) <br> iter 5 lrate = 0.1000000000 LL = -1.1909737042 nd = 0.1097540006, D = 0.15539E+01 0.15539E+01 ( 20.24 s, 11.2 h) <br> Likelihood decreasing! <br> iter 6 lrate = 0.1000000000 LL = -1.2050429281 nd = 0.0855699321, D = 0.27637E+01 0.27637E+01 ( 20.21 s, 11.2 h) <br> Likelihood decreasing! <br> iter 7 lrate = 0.1000000000 LL = -1.1763828642 nd = 0.0479559945, D = 0.28786E+01 0.28786E+01 ( 20.08 s, 11.1 h) <br> iter 8 lrate = 0.1000000000 LL = -1.1652098711 nd = 0.0759974671, D = 0.28013E+01 0.28013E+01 ( 20.31 s, 11.2 h) <br> iter 9 lrate = 0.1000000000 LL = -1.1548087828 nd = 0.0760115783, D = 0.28752E+01 0.28752E+01 ( 20.45 s, 11.3 h) <br> iter 10 lrate = 0.1000000000 LL = -1.1672225654 nd = 0.0875068694, D = 0.33162E+01 0.33162E+01 ( 20.49 s, 11.3 h) <br> Likelihood decreasing! <br> iter 11 lrate = 0.0500000000 LL = -1.1334088411 nd = 0.0793673040, D = 0.30140E+01 0.30140E+01 ( 29.22 s, 16.1 h) <br> iter 12 lrate = 0.0500000000 LL = -1.1208248124 nd = 0.0893221749, D = 0.31189E+01 0.31189E+01 ( 20.55 s, 11.4 h) <br> iter 13 lrate = 0.0500000000 LL = -1.1208895496 nd = 0.1240688995, D = 0.31883E+01 0.31883E+01 ( 19.87 s, 11.0 h) <br> Likelihood decreasing! <br> iter 14 lrate = 0.0500000000 LL = -1.1302510917 nd = 0.0946894512, D = 0.35648E+01 0.35648E+01 ( 20.18 s, 11.1 h) <br> Likelihood decreasing! <br> iter 15 lrate = 0.0500000000 LL = -1.1184585053 nd = 0.1287931887, D = 0.34193E+01 0.34193E+01 ( 20.08 s, 11.1 h) <br> iter 16 lrate = 0.0500000000 LL = -1.1398538641 nd = 0.1132649105, D = 0.36706E+01 0.36706E+01 ( 20.17 s, 11.1 h) <br> Likelihood decreasing! <br> iter 17 lrate = 0.0250000000 LL = -1.0973511201 nd = 0.0761838783, D = 0.34916E+01 0.34916E+01 ( 19.80 s, 10.9 h) <br> iter 18 lrate = 0.0250000000 LL = -1.0848865220 nd = 0.1374529379, D = 0.34764E+01 0.34764E+01 ( 20.14 s, 11.1 h) <br> iter 19 lrate = 0.0250000000 LL = -1.1118978858 nd = 0.1323449942, D = 0.35388E+01 0.35388E+01 ( 20.26 s, 11.2 h) <br> Likelihood decreasing! <br> iter 20 lrate = 0.0250000000 LL = -1.0947740999 nd = 0.1195005583, D = 0.35359E+01 0.35359E+01 ( 19.89 s, 10.9 h) <br> iter 21 lrate = 0.0250000000 LL = -1.0807059207 nd = 0.1348198483, D = 0.35215E+01 0.35215E+01 ( 28.32 s, 15.6 h) <br> iter 22 lrate = 0.0250000000 LL = -1.1000579251 nd = 0.1428486702, D = 0.36146E+01 0.36146E+01 ( 20.01 s, 11.0 h) <br> Likelihood decreasing! <br> iter 23 lrate = 0.0250000000 LL = -1.0788334180 nd = 0.1387814315, D = 0.36210E+01 0.36210E+01 ( 20.22 s, 11.1 h) <br> iter 24 lrate = 0.0250000000 LL = -1.0994448451 nd = 0.1703862846, D = 0.36623E+01 0.36623E+01 ( 19.91 s, 10.9 h) <br> Likelihood decreasing! <br> iter 25 lrate = 0.0125000000 LL = -1.0629537917 nd = 0.1015846576, D = 0.36375E+01 0.36375E+01 ( 19.76 s, 10.8 h) <br> iter 26 lrate = 0.0125000000 LL = -1.0568416712 nd = 0.1879900124, D = 0.36497E+01 0.36497E+01 ( 19.98 s, 11.0 h) <br> iter 27 lrate = 0.0125000000 LL = -1.0847027453 nd = 0.2128018174, D = 0.37045E+01 0.37045E+01 ( 19.84 s, 10.9 h) <br> Likelihood decreasing! <br> iter 28 lrate = 0.0125000000 LL = -1.0713710983 nd = 0.1767929582, D = 0.37060E+01 0.37060E+01 ( 19.80 s, 10.8 h) <br> iter 29 lrate = 0.0125000000 LL = -1.0657822061 nd = 0.1910606040, D = 0.37221E+01 0.37221E+01 ( 19.54 s, 10.7 h) <br> iter 30 lrate = 0.0125000000 LL = -1.0802049007 nd = 0.2219913203, D = 0.37446E+01 0.37446E+01 ( 19.98 s, 10.9 h) <br> Likelihood decreasing! <br> iter 31 lrate = 0.0125000000 LL = -1.0779892906 nd = 0.1809254372, D = 0.37680E+01 0.37680E+01 ( 28.04 s, 15.3 h) <br> iter 32 lrate = 0.0125000000 LL = -1.0621807587 nd = 0.1861195406, D = 0.37677E+01 0.37677E+01 ( 20.06 s, 11.0 h) <br> iter 33 lrate = 0.0125000000 LL = -1.0760408010 nd = 0.2156432185, D = 0.37985E+01 0.37985E+01 ( 20.08 s, 11.0 h) <br> Likelihood decreasing! <br> iter 34 lrate = 0.0062500000 LL = -1.0514038328 nd = 0.1434647028, D = 0.37839E+01 0.37839E+01 ( 20.42 s, 11.2 h) <br> iter 35 lrate = 0.0062500000 LL = -1.0431417630 nd = 0.1700906516, D = 0.37873E+01 0.37873E+01 ( 20.10 s, 11.0 h) <br> iter 36 lrate = 0.0062500000 LL = -1.0463114756 nd = 0.2484342614, D = 0.37999E+01 0.37999E+01 ( 20.37 s, 11.1 h) <br> Likelihood decreasing! <br> iter 37 lrate = 0.0062500000 LL = -1.0640113034 nd = 0.2882809805, D = 0.38091E+01 0.38091E+01 ( 20.12 s, 11.0 h) <br> Likelihood decreasing! <br> iter 38 lrate = 0.0062500000 LL = -1.0597580305 nd = 0.2244267933, D = 0.38215E+01 0.38215E+01 ( 20.22 s, 11.0 h) <br> iter 39 lrate = 0.0062500000 LL = -1.0515608016 nd = 0.2464267322, D = 0.38180E+01 0.38180E+01 ( 20.25 s, 11.0 h) <br> iter 40 lrate = 0.0062500000 LL = -1.0585260586 nd = 0.2702749063, D = 0.38327E+01 0.38327E+01 ( 20.19 s, 11.0 h) <br> Likelihood decreasing! <br> iter 41 lrate = 0.0031250000 LL = -1.0353693494 nd = 0.1342501202, D = 0.38232E+01 0.38232E+01 ( 28.28 s, 15.4 h) <br> iter 42 lrate = 0.0031250000 LL = -1.0277671209 nd = 0.2113452845, D = 0.38262E+01 0.38262E+01 ( 19.92 s, 10.8 h) <br> iter 43 lrate = 0.0031250000 LL = -1.0323284214 nd = 0.3996641530, D = 0.38315E+01 0.38315E+01 ( 20.16 s, 11.0 h) <br> Likelihood decreasing! <br> iter 44 lrate = 0.0031250000 LL = -1.0590903023 nd = 0.3904356001, D = 0.38447E+01 0.38447E+01 ( 20.03 s, 10.9 h) <br> Likelihood decreasing! <br> iter 45 lrate = 0.0031250000 LL = -1.0624355311 nd = 0.3504021215, D = 0.38457E+01 0.38457E+01 ( 20.12 s, 10.9 h) <br> Likelihood decreasing! <br> iter 46 lrate = 0.0015625000 LL = -1.0359995562 nd = 0.2144237307, D = 0.38404E+01 0.38404E+01 ( 20.22 s, 11.0 h) <br> iter 47 lrate = 0.0015625000 LL = -1.0243324193 nd = 0.2074327631, D = 0.38405E+01 0.38405E+01 ( 20.02 s, 10.9 h) <br> iter 48 lrate = 0.0015625000 LL = -1.0183631815 nd = 0.3142810573, D = 0.38420E+01 0.38420E+01 ( 20.26 s, 11.0 h) <br> iter 49 lrate = 0.0015625000 LL = -1.0248452387 nd = 0.4588770336, D = 0.38440E+01 0.38440E+01 ( 20.20 s, 10.9 h) <br> Likelihood decreasing! <br> iter 50 lrate = 0.0015625000 LL = -1.0364594655 nd = 0.0047159036, D = 0.38485E+01 0.38485E+01 ( 20.69 s, 11.2 h) <br> Likelihood decreasing! <br> Starting Newton ... setting numdecs to 0 <br> iter 51 lrate = 0.0015625000 LL = -1.0320050862 nd = 0.0044451049, D = 0.38485E+01 0.38485E+01 ( 29.23 s, 15.8 h) <br> iter 52 lrate = 0.0031250000 LL = -1.0312354749 nd = 0.0043051817, D = 0.38486E+01 0.38486E+01 ( 20.86 s, 11.3 h) <br> iter 53 lrate = 0.0062500000 LL = -1.0308789796 nd = 0.0042352594, D = 0.38488E+01 0.38488E+01 ( 20.78 s, 11.2 h) <br> iter 54 lrate = 0.0125000000 LL = -1.0305564039 nd = 0.0042070557, D = 0.38491E+01 0.38491E+01 ( 21.06 s, 11.4 h) <br> iter 55 lrate = 0.0250000000 LL = -1.0301012210 nd = 0.0041920531, D = 0.38499E+01 0.38499E+01 ( 20.86 s, 11.3 h) <br> iter 56 lrate = 0.0500000000 LL = -1.0292948277 nd = 0.0041716566, D = 0.38515E+01 0.38515E+01 ( 20.86 s, 11.3 h) <br> iter 57 lrate = 0.1000000000 LL = -1.0277690069 nd = 0.0041343027, D = 0.38551E+01 0.38551E+01 ( 21.08 s, 11.4 h) <br> iter 58 lrate = 0.2000000000 LL = -1.0248073390 nd = 0.0040922931, D = 0.38636E+01 0.38636E+01 ( 20.89 s, 11.3 h) <br> iter 59 lrate = 0.3000000000 LL = -1.0204110450 nd = 0.0040799800, D = 0.38788E+01 0.38788E+01 ( 20.96 s, 11.3 h) <br> iter 60 lrate = 0.4000000000 LL = -1.0146195799 nd = 0.0041009701, D = 0.39020E+01 0.39020E+01 ( 20.82 s, 11.2 h) <br> iter 61 lrate = 0.5000000000 LL = -1.0075630392 nd = 0.0041335421, D = 0.39324E+01 0.39324E+01 ( 29.10 s, 15.7 h) <br> iter 62 lrate = 0.6000000000 LL = -0.9994666758 nd = 0.0041488883, D = 0.39670E+01 0.39670E+01 ( 20.75 s, 11.2 h) <br> iter 63 lrate = 0.7000000000 LL = -0.9908949394 nd = 0.0038125239, D = 0.40012E+01 0.40012E+01 ( 20.85 s, 11.2 h) <br> iter 64 lrate = 0.8000000000 LL = -0.9834338586 nd = 0.0032500244, D = 0.40312E+01 0.40312E+01 ( 20.80 s, 11.2 h) <br> iter 65 lrate = 0.9000000000 LL = -0.9781875109 nd = 0.0039872041, D = 0.40554E+01 0.40554E+01 ( 21.23 s, 11.4 h) <br> iter 66 lrate = 1.0000000000 LL = -0.9726503246 nd = 0.0035749790, D = 0.40753E+01 0.40753E+01 ( 21.06 s, 11.3 h) <br> iter 67 lrate = 1.0000000000 LL = -0.9713177037 nd = 0.0066709104, D = 0.40899E+01 0.40899E+01 ( 21.11 s, 11.3 h) <br> iter 68 lrate = 1.0000000000 LL = -1.0269324609 nd = 0.0046870632, D = 0.49971E+01 0.49971E+01 ( 21.04 s, 11.3 h) <br> Likelihood decreasing! <br> iter 69 lrate = 0.6000000000 LL = -0.9892639383 nd = 0.0038633466, D = 0.50244E+01 0.50244E+01 ( 21.03 s, 11.3 h) <br> iter 70 lrate = 0.7000000000 LL = -0.9851046495 nd = 0.0031930683, D = 0.50002E+01 0.50002E+01 ( 20.58 s, 11.0 h) <br> iter 71 lrate = 0.8000000000 LL = -0.9828993216 nd = 0.0036588309, D = 0.50025E+01 0.50025E+01 ( 29.01 s, 15.5 h) <br> iter 72 lrate = 0.9000000000 LL = -0.9782784946 nd = 0.0034000063, D = 0.49874E+01 0.49874E+01 ( 20.78 s, 11.1 h) <br> iter 73 lrate = 1.0000000000 LL = -0.9692582080 nd = 0.0043235255, D = 0.49968E+01 0.49968E+01 ( 20.98 s, 11.2 h) <br> iter 74 lrate = 1.0000000000 LL = -0.9668761930 nd = 0.0038626338, D = 0.49924E+01 0.49924E+01 ( 21.10 s, 11.3 h) <br> iter 75 lrate = 1.0000000000 LL = -0.9608215468 nd = 0.0048297383, D = 0.50020E+01 0.50020E+01 ( 20.80 s, 11.1 h) <br> iter 76 lrate = 1.0000000000 LL = -0.9605851167 nd = 0.0046752279, D = 0.50006E+01 0.50006E+01 ( 20.75 s, 11.1 h) <br> iter 77 lrate = 1.0000000000 LL = -0.9587708220 nd = 0.0049920315, D = 0.50015E+01 0.50015E+01 ( 20.84 s, 11.1 h) <br> iter 78 lrate = 1.0000000000 LL = -0.9599862170 nd = 0.0050182731, D = 0.50029E+01 0.50029E+01 ( 20.88 s, 11.1 h) <br> Likelihood decreasing! <br> iter 79 lrate = 0.6000000000 LL = -0.9560292715 nd = 0.0039443959, D = 0.49643E+01 0.49643E+01 ( 21.12 s, 11.3 h) <br> iter 80 lrate = 0.7000000000 LL = -0.9558902166 nd = 0.0025347149, D = 0.48879E+01 0.48879E+01 ( 21.16 s, 11.3 h) <br> iter 81 lrate = 0.8000000000 LL = -0.9541807097 nd = 0.0042250807, D = 0.48611E+01 0.48611E+01 ( 29.23 s, 15.6 h) <br> iter 82 lrate = 0.9000000000 LL = -0.9613129981 nd = 0.0027321315, D = 0.48380E+01 0.48380E+01 ( 21.13 s, 11.3 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 83 lrate = 0.5000000000 LL = -0.9555415931 nd = 0.0027673602, D = 0.48304E+01 0.48304E+01 ( 20.87 s, 11.1 h) <br> iter 84 lrate = 0.5000000000 LL = -0.9523516686 nd = 0.0018985454, D = 0.48243E+01 0.48243E+01 ( 21.11 s, 11.2 h) <br> iter 85 lrate = 0.5000000000 LL = -0.9519685148 nd = 0.0021264834, D = 0.48192E+01 0.48192E+01 ( 20.91 s, 11.1 h) <br> iter 86 lrate = 0.5000000000 LL = -0.9508302400 nd = 0.0019119893, D = 0.48140E+01 0.48140E+01 ( 20.89 s, 11.1 h) <br> iter 87 lrate = 0.5000000000 LL = -0.9504268561 nd = 0.0020179086, D = 0.48082E+01 0.48082E+01 ( 20.86 s, 11.1 h) <br> iter 88 lrate = 0.5000000000 LL = -0.9498239402 nd = 0.0020626767, D = 0.48022E+01 0.48022E+01 ( 21.13 s, 11.2 h) <br> iter 89 lrate = 0.5000000000 LL = -0.9495369985 nd = 0.0019304021, D = 0.47953E+01 0.47953E+01 ( 21.11 s, 11.2 h) <br> iter 90 lrate = 0.5000000000 LL = -0.9491032067 nd = 0.0023772688, D = 0.47884E+01 0.47884E+01 ( 20.92 s, 11.1 h) <br> iter 91 lrate = 0.5000000000 LL = -0.9488991111 nd = 0.0018517776, D = 0.47805E+01 0.47805E+01 ( 29.46 s, 15.6 h) <br> iter 92 lrate = 0.5000000000 LL = -0.9485526896 nd = 0.0025445047, D = 0.47727E+01 0.47727E+01 ( 20.97 s, 11.1 h) <br> iter 93 lrate = 0.5000000000 LL = -0.9483361418 nd = 0.0018076301, D = 0.47639E+01 0.47639E+01 ( 21.00 s, 11.1 h) <br> iter 94 lrate = 0.5000000000 LL = -0.9479911835 nd = 0.0028196416, D = 0.47555E+01 0.47555E+01 ( 20.95 s, 11.1 h) <br> iter 95 lrate = 0.5000000000 LL = -0.9479433092 nd = 0.0017918194, D = 0.47457E+01 0.47457E+01 ( 20.97 s, 11.1 h) <br> iter 96 lrate = 0.5000000000 LL = -0.9475027814 nd = 0.0032973742, D = 0.47369E+01 0.47369E+01 ( 20.88 s, 11.0 h) <br> iter 97 lrate = 0.5000000000 LL = -0.9471462068 nd = 0.0018718305, D = 0.47261E+01 0.47261E+01 ( 21.24 s, 11.2 h) <br> iter 98 lrate = 0.5000000000 LL = -0.9471524551 nd = 0.0041798813, D = 0.47171E+01 0.47171E+01 ( 20.93 s, 11.1 h) <br> Likelihood decreasing! <br> iter 99 lrate = 0.3500000000 LL = -0.9465559707 nd = 0.0019468735, D = 0.47093E+01 0.47093E+01 ( 21.02 s, 11.1 h) <br> iter 100 lrate = 0.4500000000 LL = -0.9465861091 nd = 0.0038451279, D = 0.47008E+01 0.47008E+01 ( 21.04 s, 11.1 h) <br> Likelihood decreasing! <br> iter 101 lrate = 0.2250000000 LL = -0.9470472943 nd = 0.0042087620, D = 0.47008E+01 0.47008E+01 ( 29.26 s, 15.4 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 102 lrate = 0.1125000000 LL = -0.9470161535 nd = 0.0042568034, D = 0.47008E+01 0.47008E+01 ( 20.88 s, 11.0 h) <br> iter 103 lrate = 0.1125000000 LL = -0.9469902661 nd = 0.0042774226, D = 0.47008E+01 0.47008E+01 ( 20.94 s, 11.0 h) <br> iter 104 lrate = 0.1125000000 LL = -0.9469657642 nd = 0.0042889203, D = 0.47008E+01 0.47008E+01 ( 20.95 s, 11.0 h) <br> iter 105 lrate = 0.1125000000 LL = -0.9469425395 nd = 0.0042954260, D = 0.47008E+01 0.47008E+01 ( 20.93 s, 11.0 h) <br> iter 106 lrate = 0.1125000000 LL = -0.9469193680 nd = 0.0042988399, D = 0.47008E+01 0.47008E+01 ( 21.10 s, 11.1 h) <br> iter 107 lrate = 0.2125000000 LL = -0.9460385454 nd = 0.0026189162, D = 0.46965E+01 0.46965E+01 ( 21.00 s, 11.0 h) <br> iter 108 lrate = 0.2500000000 LL = -0.9460968003 nd = 0.0032619186, D = 0.46916E+01 0.46916E+01 ( 20.72 s, 10.9 h) <br> Likelihood decreasing! <br> iter 109 lrate = 0.2250000000 LL = -0.9459886842 nd = 0.0028993443, D = 0.46871E+01 0.46871E+01 ( 20.80 s, 10.9 h) <br> iter 110 lrate = 0.2500000000 LL = -0.9458943246 nd = 0.0029671283, D = 0.46822E+01 0.46822E+01 ( 20.66 s, 10.8 h) <br> iter 111 lrate = 0.2500000000 LL = -0.9458101691 nd = 0.0028815231, D = 0.46772E+01 0.46772E+01 ( 29.34 s, 15.4 h) <br> iter 112 lrate = 0.2500000000 LL = -0.9456949570 nd = 0.0029777480, D = 0.46722E+01 0.46722E+01 ( 21.06 s, 11.0 h) <br> iter 113 lrate = 0.2500000000 LL = -0.9456085658 nd = 0.0028812156, D = 0.46672E+01 0.46672E+01 ( 21.00 s, 11.0 h) <br> iter 114 lrate = 0.2500000000 LL = -0.9454918595 nd = 0.0030012123, D = 0.46622E+01 0.46622E+01 ( 21.06 s, 11.0 h) <br> iter 115 lrate = 0.2500000000 LL = -0.9454150773 nd = 0.0028706091, D = 0.46571E+01 0.46571E+01 ( 20.72 s, 10.8 h) <br> iter 116 lrate = 0.2500000000 LL = -0.9453121874 nd = 0.0029996748, D = 0.46521E+01 0.46521E+01 ( 20.77 s, 10.9 h) <br> iter 117 lrate = 0.2500000000 LL = -0.9452401594 nd = 0.0028714829, D = 0.46471E+01 0.46471E+01 ( 20.97 s, 11.0 h) <br> iter 118 lrate = 0.2500000000 LL = -0.9451211768 nd = 0.0030325201, D = 0.46421E+01 0.46421E+01 ( 20.31 s, 10.6 h) <br> iter 119 lrate = 0.2500000000 LL = -0.9450547471 nd = 0.0028503287, D = 0.46371E+01 0.46371E+01 ( 20.73 s, 10.8 h) <br> iter 120 lrate = 0.2500000000 LL = -0.9449543952 nd = 0.0030260866, D = 0.46321E+01 0.46321E+01 ( 21.17 s, 11.1 h) <br> iter 121 lrate = 0.2500000000 LL = -0.9448900245 nd = 0.0028527939, D = 0.46271E+01 0.46271E+01 ( 29.39 s, 15.3 h) <br> iter 122 lrate = 0.2500000000 LL = -0.9447662840 nd = 0.0030704221, D = 0.46222E+01 0.46222E+01 ( 20.83 s, 10.9 h) <br> iter 123 lrate = 0.2500000000 LL = -0.9447118412 nd = 0.0028206918, D = 0.46172E+01 0.46172E+01 ( 20.92 s, 10.9 h) <br> iter 124 lrate = 0.2500000000 LL = -0.9446049311 nd = 0.0030765426, D = 0.46123E+01 0.46123E+01 ( 20.79 s, 10.8 h) <br> iter 125 lrate = 0.2500000000 LL = -0.9445553134 nd = 0.0028111300, D = 0.46074E+01 0.46074E+01 ( 20.90 s, 10.9 h) <br> iter 126 lrate = 0.2500000000 LL = -0.9444203224 nd = 0.0031415255, D = 0.46026E+01 0.46026E+01 ( 21.16 s, 11.0 h) <br> iter 127 lrate = 0.2500000000 LL = -0.9443776144 nd = 0.0027730377, D = 0.45978E+01 0.45978E+01 ( 20.84 s, 10.8 h) <br> iter 128 lrate = 0.2500000000 LL = -0.9442626648 nd = 0.0031560210, D = 0.45930E+01 0.45930E+01 ( 21.03 s, 10.9 h) <br> iter 129 lrate = 0.2500000000 LL = -0.9442326422 nd = 0.0027456563, D = 0.45883E+01 0.45883E+01 ( 20.51 s, 10.7 h) <br> iter 130 lrate = 0.2500000000 LL = -0.9440825309 nd = 0.0032420905, D = 0.45837E+01 0.45837E+01 ( 21.01 s, 10.9 h) <br> iter 131 lrate = 0.2500000000 LL = -0.9440501438 nd = 0.0027077545, D = 0.45790E+01 0.45790E+01 ( 29.30 s, 15.2 h) <br> iter 132 lrate = 0.2500000000 LL = -0.9439173315 nd = 0.0032991712, D = 0.45745E+01 0.45745E+01 ( 20.83 s, 10.8 h) <br> iter 133 lrate = 0.2500000000 LL = -0.9438997279 nd = 0.0026508618, D = 0.45700E+01 0.45700E+01 ( 21.14 s, 11.0 h) <br> iter 134 lrate = 0.2500000000 LL = -0.9437552395 nd = 0.0033730209, D = 0.45657E+01 0.45657E+01 ( 20.70 s, 10.7 h) <br> iter 135 lrate = 0.2500000000 LL = -0.9437254259 nd = 0.0026166727, D = 0.45613E+01 0.45613E+01 ( 20.81 s, 10.8 h) <br> iter 136 lrate = 0.2500000000 LL = -0.9435955833 nd = 0.0034070143, D = 0.45571E+01 0.45571E+01 ( 20.86 s, 10.8 h) <br> iter 137 lrate = 0.2500000000 LL = -0.9435643168 nd = 0.0026082042, D = 0.45530E+01 0.45530E+01 ( 20.58 s, 10.7 h) <br> iter 138 lrate = 0.2500000000 LL = -0.9434277586 nd = 0.0034319564, D = 0.45490E+01 0.45490E+01 ( 20.65 s, 10.7 h) <br> iter 139 lrate = 0.2500000000 LL = -0.9433791381 nd = 0.0026092500, D = 0.45451E+01 0.45451E+01 ( 21.19 s, 11.0 h) <br> iter 140 lrate = 0.2500000000 LL = -0.9432621324 nd = 0.0034428781, D = 0.45413E+01 0.45413E+01 ( 21.21 s, 11.0 h) <br> iter 141 lrate = 0.2500000000 LL = -0.9432208498 nd = 0.0025940365, D = 0.45376E+01 0.45376E+01 ( 28.97 s, 15.0 h) <br> iter 142 lrate = 0.2500000000 LL = -0.9431058517 nd = 0.0034488619, D = 0.45341E+01 0.45341E+01 ( 20.83 s, 10.8 h) <br> iter 143 lrate = 0.2500000000 LL = -0.9430712166 nd = 0.0025714644, D = 0.45306E+01 0.45306E+01 ( 20.83 s, 10.7 h) <br> iter 144 lrate = 0.2500000000 LL = -0.9429453900 nd = 0.0034862189, D = 0.45272E+01 0.45272E+01 ( 20.93 s, 10.8 h) <br> iter 145 lrate = 0.2500000000 LL = -0.9429006243 nd = 0.0025630214, D = 0.45239E+01 0.45239E+01 ( 21.02 s, 10.8 h) <br> iter 146 lrate = 0.2500000000 LL = -0.9427942272 nd = 0.0034807780, D = 0.45207E+01 0.45207E+01 ( 20.85 s, 10.7 h) <br> iter 147 lrate = 0.2500000000 LL = -0.9427671093 nd = 0.0025344437, D = 0.45176E+01 0.45176E+01 ( 20.89 s, 10.8 h) <br> iter 148 lrate = 0.2500000000 LL = -0.9426405995 nd = 0.0035285100, D = 0.45145E+01 0.45145E+01 ( 21.16 s, 10.9 h) <br> iter 149 lrate = 0.2500000000 LL = -0.9425947282 nd = 0.0025311830, D = 0.45115E+01 0.45115E+01 ( 20.95 s, 10.8 h) <br> iter 150 lrate = 0.2500000000 LL = -0.9424960318 nd = 0.0035134556, D = 0.45086E+01 0.45086E+01 ( 20.86 s, 10.7 h) <br> iter 151 lrate = 0.2500000000 LL = -0.9424681103 nd = 0.0025105786, D = 0.45057E+01 0.45057E+01 ( 29.01 s, 14.9 h) <br> iter 152 lrate = 0.2500000000 LL = -0.9423483172 nd = 0.0035578831, D = 0.45028E+01 0.45028E+01 ( 21.00 s, 10.8 h) <br> iter 153 lrate = 0.2500000000 LL = -0.9422925860 nd = 0.0025323367, D = 0.44999E+01 0.44999E+01 ( 20.82 s, 10.7 h) <br> iter 154 lrate = 0.2500000000 LL = -0.9422183711 nd = 0.0035010175, D = 0.44970E+01 0.44970E+01 ( 20.97 s, 10.8 h) <br> iter 155 lrate = 0.2500000000 LL = -0.9422103726 nd = 0.0024967242, D = 0.44939E+01 0.44939E+01 ( 21.44 s, 11.0 h) <br> iter 156 lrate = 0.2500000000 LL = -0.9420742301 nd = 0.0036189527, D = 0.44909E+01 0.44909E+01 ( 20.80 s, 10.7 h) <br> iter 157 lrate = 0.2500000000 LL = -0.9419743668 nd = 0.0025731644, D = 0.44877E+01 0.44877E+01 ( 21.15 s, 10.8 h) <br> iter 158 lrate = 0.2500000000 LL = -0.9419751403 nd = 0.0034317088, D = 0.44845E+01 0.44845E+01 ( 21.05 s, 10.8 h) <br> Likelihood decreasing! <br> iter 159 lrate = 0.2250000000 LL = -0.9419898791 nd = 0.0027267148, D = 0.44815E+01 0.44815E+01 ( 20.70 s, 10.6 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 160 lrate = 0.1250000000 LL = -0.9421264063 nd = 0.0039733252, D = 0.44798E+01 0.44798E+01 ( 20.97 s, 10.7 h) <br> Likelihood decreasing! <br> iter 161 lrate = 0.1250000000 LL = -0.9419316466 nd = 0.0036427167, D = 0.44782E+01 0.44782E+01 ( 29.41 s, 15.0 h) <br> iter 162 lrate = 0.1250000000 LL = -0.9419483825 nd = 0.0036878273, D = 0.44765E+01 0.44765E+01 ( 20.95 s, 10.7 h) <br> Likelihood decreasing! <br> iter 163 lrate = 0.1250000000 LL = -0.9419206952 nd = 0.0036414985, D = 0.44748E+01 0.44748E+01 ( 20.80 s, 10.6 h) <br> iter 164 lrate = 0.1250000000 LL = -0.9418952515 nd = 0.0036533893, D = 0.44731E+01 0.44731E+01 ( 20.80 s, 10.6 h) <br> iter 165 lrate = 0.1250000000 LL = -0.9418665543 nd = 0.0036393482, D = 0.44715E+01 0.44715E+01 ( 20.89 s, 10.6 h) <br> iter 166 lrate = 0.1250000000 LL = -0.9418357660 nd = 0.0036527625, D = 0.44698E+01 0.44698E+01 ( 20.68 s, 10.5 h) <br> iter 167 lrate = 0.1250000000 LL = -0.9418074068 nd = 0.0036393243, D = 0.44681E+01 0.44681E+01 ( 21.00 s, 10.7 h) <br> iter 168 lrate = 0.1250000000 LL = -0.9417768436 nd = 0.0036547645, D = 0.44664E+01 0.44664E+01 ( 21.14 s, 10.8 h) <br> iter 169 lrate = 0.1250000000 LL = -0.9417491507 nd = 0.0036400994, D = 0.44647E+01 0.44647E+01 ( 20.97 s, 10.7 h) <br> iter 170 lrate = 0.1250000000 LL = -0.9417190255 nd = 0.0036572519, D = 0.44630E+01 0.44630E+01 ( 21.00 s, 10.7 h) <br> iter 171 lrate = 0.1250000000 LL = -0.9416918629 nd = 0.0036413038, D = 0.44613E+01 0.44613E+01 ( 29.25 s, 14.9 h) <br> iter 172 lrate = 0.1250000000 LL = -0.9416621331 nd = 0.0036597075, D = 0.44596E+01 0.44596E+01 ( 21.23 s, 10.8 h) <br> iter 173 lrate = 0.1250000000 LL = -0.9416354603 nd = 0.0036425395, D = 0.44580E+01 0.44580E+01 ( 20.95 s, 10.6 h) <br> iter 174 lrate = 0.1250000000 LL = -0.9416060514 nd = 0.0036621294, D = 0.44563E+01 0.44563E+01 ( 20.79 s, 10.5 h) <br> iter 175 lrate = 0.1250000000 LL = -0.9415799859 nd = 0.0036437334, D = 0.44546E+01 0.44546E+01 ( 20.99 s, 10.6 h) <br> iter 176 lrate = 0.1250000000 LL = -0.9415509184 nd = 0.0036644241, D = 0.44529E+01 0.44529E+01 ( 20.75 s, 10.5 h) <br> iter 177 lrate = 0.1250000000 LL = -0.9415253897 nd = 0.0036449916, D = 0.44512E+01 0.44512E+01 ( 20.97 s, 10.6 h) <br> iter 178 lrate = 0.1250000000 LL = -0.9414965594 nd = 0.0036666196, D = 0.44496E+01 0.44496E+01 ( 21.01 s, 10.6 h) <br> iter 179 lrate = 0.1250000000 LL = -0.9414716297 nd = 0.0036464899, D = 0.44479E+01 0.44479E+01 ( 20.67 s, 10.5 h) <br> iter 180 lrate = 0.1250000000 LL = -0.9414430331 nd = 0.0036685543, D = 0.44462E+01 0.44462E+01 ( 20.73 s, 10.5 h) <br> iter 181 lrate = 0.1250000000 LL = -0.9414186593 nd = 0.0036481941, D = 0.44446E+01 0.44446E+01 ( 29.22 s, 14.8 h) <br> iter 182 lrate = 0.1250000000 LL = -0.9413902620 nd = 0.0036705580, D = 0.44429E+01 0.44429E+01 ( 20.87 s, 10.5 h) <br> iter 183 lrate = 0.1250000000 LL = -0.9413664653 nd = 0.0036501419, D = 0.44413E+01 0.44413E+01 ( 20.94 s, 10.6 h) <br> iter 184 lrate = 0.1250000000 LL = -0.9413381239 nd = 0.0036727155, D = 0.44396E+01 0.44396E+01 ( 21.16 s, 10.7 h) <br> iter 185 lrate = 0.1250000000 LL = -0.9413149257 nd = 0.0036522801, D = 0.44380E+01 0.44380E+01 ( 20.75 s, 10.5 h) <br> iter 186 lrate = 0.1250000000 LL = -0.9412867822 nd = 0.0036749521, D = 0.44363E+01 0.44363E+01 ( 20.97 s, 10.6 h) <br> iter 187 lrate = 0.1250000000 LL = -0.9412642051 nd = 0.0036542338, D = 0.44347E+01 0.44347E+01 ( 20.55 s, 10.3 h) <br> iter 188 lrate = 0.1250000000 LL = -0.9412362576 nd = 0.0036771348, D = 0.44331E+01 0.44331E+01 ( 20.82 s, 10.5 h) <br> iter 189 lrate = 0.1250000000 LL = -0.9412143425 nd = 0.0036561192, D = 0.44315E+01 0.44315E+01 ( 20.97 s, 10.5 h) <br> iter 190 lrate = 0.1250000000 LL = -0.9411865980 nd = 0.0036794461, D = 0.44298E+01 0.44298E+01 ( 20.77 s, 10.4 h) <br> iter 191 lrate = 0.1250000000 LL = -0.9411653075 nd = 0.0036578859, D = 0.44282E+01 0.44282E+01 ( 29.25 s, 14.7 h) <br> iter 192 lrate = 0.1250000000 LL = -0.9411377637 nd = 0.0036819075, D = 0.44266E+01 0.44266E+01 ( 20.66 s, 10.4 h) <br> iter 193 lrate = 0.1250000000 LL = -0.9411170160 nd = 0.0036595945, D = 0.44250E+01 0.44250E+01 ( 20.85 s, 10.5 h) <br> iter 194 lrate = 0.1250000000 LL = -0.9410896288 nd = 0.0036847084, D = 0.44234E+01 0.44234E+01 ( 20.68 s, 10.4 h) <br> iter 195 lrate = 0.1250000000 LL = -0.9410694745 nd = 0.0036620183, D = 0.44218E+01 0.44218E+01 ( 20.97 s, 10.5 h) <br> iter 196 lrate = 0.1250000000 LL = -0.9410421243 nd = 0.0036885330, D = 0.44202E+01 0.44202E+01 ( 20.87 s, 10.5 h) <br> iter 197 lrate = 0.1250000000 LL = -0.9410224352 nd = 0.0036648621, D = 0.44186E+01 0.44186E+01 ( 20.90 s, 10.5 h) <br> iter 198 lrate = 0.1250000000 LL = -0.9409951884 nd = 0.0036929973, D = 0.44171E+01 0.44171E+01 ( 20.72 s, 10.4 h) <br> iter 199 lrate = 0.1250000000 LL = -0.9409760094 nd = 0.0036672139, D = 0.44155E+01 0.44155E+01 ( 21.08 s, 10.5 h) <br> iter 200 lrate = 0.1250000000 LL = -0.9409489656 nd = 0.0036970475, D = 0.44139E+01 0.44139E+01 ( 20.69 s, 10.3 h) <br> iter 201 lrate = 0.1250000000 LL = -0.9414716660 nd = 0.0043050386, D = 0.44139E+01 0.44139E+01 ( 29.15 s, 14.6 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 202 lrate = 0.0625000000 LL = -0.9414676208 nd = 0.0043030065, D = 0.44139E+01 0.44139E+01 ( 20.65 s, 10.3 h) <br> iter 203 lrate = 0.0625000000 LL = -0.9414641830 nd = 0.0043004921, D = 0.44139E+01 0.44139E+01 ( 20.93 s, 10.4 h) <br> iter 204 lrate = 0.0625000000 LL = -0.9414611072 nd = 0.0042976618, D = 0.44139E+01 0.44139E+01 ( 20.82 s, 10.4 h) <br> iter 205 lrate = 0.0625000000 LL = -0.9414582956 nd = 0.0042948027, D = 0.44139E+01 0.44139E+01 ( 20.71 s, 10.3 h) <br> iter 206 lrate = 0.0625000000 LL = -0.9414556980 nd = 0.0042919845, D = 0.44139E+01 0.44139E+01 ( 20.89 s, 10.4 h) <br> iter 207 lrate = 0.0625000000 LL = -0.9410765785 nd = 0.0041605651, D = 0.44132E+01 0.44132E+01 ( 20.71 s, 10.3 h) <br> iter 208 lrate = 0.0625000000 LL = -0.9410733529 nd = 0.0041781811, D = 0.44124E+01 0.44124E+01 ( 20.73 s, 10.3 h) <br> iter 209 lrate = 0.0625000000 LL = -0.9410594732 nd = 0.0041785611, D = 0.44116E+01 0.44116E+01 ( 20.79 s, 10.3 h) <br> iter 210 lrate = 0.0625000000 LL = -0.9410474053 nd = 0.0041799626, D = 0.44109E+01 0.44109E+01 ( 20.90 s, 10.4 h) <br> iter 211 lrate = 0.0625000000 LL = -0.9410354060 nd = 0.0041814985, D = 0.44101E+01 0.44101E+01 ( 29.24 s, 14.5 h) <br> iter 212 lrate = 0.0625000000 LL = -0.9410234938 nd = 0.0041830111, D = 0.44094E+01 0.44094E+01 ( 20.83 s, 10.3 h) <br> iter 213 lrate = 0.0625000000 LL = -0.9410116244 nd = 0.0041845705, D = 0.44086E+01 0.44086E+01 ( 20.75 s, 10.3 h) <br> iter 214 lrate = 0.0625000000 LL = -0.9409998181 nd = 0.0041860781, D = 0.44078E+01 0.44078E+01 ( 20.86 s, 10.3 h) <br> iter 215 lrate = 0.0625000000 LL = -0.9409880627 nd = 0.0041875634, D = 0.44071E+01 0.44071E+01 ( 20.76 s, 10.3 h) <br> iter 216 lrate = 0.0625000000 LL = -0.9409763362 nd = 0.0041890832, D = 0.44063E+01 0.44063E+01 ( 20.53 s, 10.2 h) <br> iter 217 lrate = 0.0625000000 LL = -0.9409646642 nd = 0.0041906718, D = 0.44056E+01 0.44056E+01 ( 20.69 s, 10.2 h) <br> iter 218 lrate = 0.0625000000 LL = -0.9409530264 nd = 0.0041922995, D = 0.44048E+01 0.44048E+01 ( 21.16 s, 10.5 h) <br> iter 219 lrate = 0.0625000000 LL = -0.9409414269 nd = 0.0041939948, D = 0.44041E+01 0.44041E+01 ( 21.03 s, 10.4 h) <br> iter 220 lrate = 0.0625000000 LL = -0.9409298811 nd = 0.0041956995, D = 0.44033E+01 0.44033E+01 ( 21.10 s, 10.4 h) <br> iter 221 lrate = 0.0625000000 LL = -0.9409183759 nd = 0.0041974949, D = 0.44026E+01 0.44026E+01 ( 29.46 s, 14.6 h) <br> iter 222 lrate = 0.0625000000 LL = -0.9409068963 nd = 0.0041993466, D = 0.44018E+01 0.44018E+01 ( 21.05 s, 10.4 h) <br> iter 223 lrate = 0.0625000000 LL = -0.9408954590 nd = 0.0042012536, D = 0.44011E+01 0.44011E+01 ( 21.01 s, 10.4 h) <br> iter 224 lrate = 0.0625000000 LL = -0.9408840458 nd = 0.0042030737, D = 0.44003E+01 0.44003E+01 ( 20.88 s, 10.3 h) <br> iter 225 lrate = 0.0625000000 LL = -0.9408726790 nd = 0.0042047948, D = 0.43996E+01 0.43996E+01 ( 20.95 s, 10.3 h) <br> iter 226 lrate = 0.0625000000 LL = -0.9408613470 nd = 0.0042063854, D = 0.43988E+01 0.43988E+01 ( 20.81 s, 10.3 h) <br> iter 227 lrate = 0.0625000000 LL = -0.9408500705 nd = 0.0042078566, D = 0.43981E+01 0.43981E+01 ( 20.81 s, 10.2 h) <br> iter 228 lrate = 0.0625000000 LL = -0.9408388339 nd = 0.0042092124, D = 0.43974E+01 0.43974E+01 ( 20.87 s, 10.3 h) <br> iter 229 lrate = 0.0625000000 LL = -0.9408276429 nd = 0.0042104860, D = 0.43966E+01 0.43966E+01 ( 20.95 s, 10.3 h) <br> iter 230 lrate = 0.0625000000 LL = -0.9408164896 nd = 0.0042117409, D = 0.43959E+01 0.43959E+01 ( 20.94 s, 10.3 h) <br> iter 231 lrate = 0.0625000000 LL = -0.9408053477 nd = 0.0042130796, D = 0.43951E+01 0.43951E+01 ( 28.85 s, 14.2 h) <br> iter 232 lrate = 0.0625000000 LL = -0.9407942351 nd = 0.0042148187, D = 0.43944E+01 0.43944E+01 ( 21.02 s, 10.3 h) <br> iter 233 lrate = 0.0625000000 LL = -0.9407831329 nd = 0.0042170931, D = 0.43937E+01 0.43937E+01 ( 20.78 s, 10.2 h) <br> iter 234 lrate = 0.0625000000 LL = -0.9407720008 nd = 0.0042197715, D = 0.43929E+01 0.43929E+01 ( 20.85 s, 10.2 h) <br> iter 235 lrate = 0.0625000000 LL = -0.9407608507 nd = 0.0042225851, D = 0.43922E+01 0.43922E+01 ( 20.86 s, 10.2 h) <br> iter 236 lrate = 0.0625000000 LL = -0.9407497211 nd = 0.0042253529, D = 0.43915E+01 0.43915E+01 ( 20.72 s, 10.2 h) <br> iter 237 lrate = 0.0625000000 LL = -0.9407386187 nd = 0.0042278475, D = 0.43907E+01 0.43907E+01 ( 20.93 s, 10.3 h) <br> iter 238 lrate = 0.0625000000 LL = -0.9407275489 nd = 0.0042298574, D = 0.43900E+01 0.43900E+01 ( 20.93 s, 10.2 h) <br> iter 239 lrate = 0.0625000000 LL = -0.9407165378 nd = 0.0042314679, D = 0.43893E+01 0.43893E+01 ( 20.61 s, 10.1 h) <br> iter 240 lrate = 0.0625000000 LL = -0.9407055806 nd = 0.0042327731, D = 0.43885E+01 0.43885E+01 ( 20.69 s, 10.1 h) <br> iter 241 lrate = 0.0625000000 LL = -0.9406946641 nd = 0.0042339499, D = 0.43878E+01 0.43878E+01 ( 29.28 s, 14.3 h) <br> iter 242 lrate = 0.0625000000 LL = -0.9406837760 nd = 0.0042350891, D = 0.43871E+01 0.43871E+01 ( 20.83 s, 10.2 h) <br> iter 243 lrate = 0.0625000000 LL = -0.9406728994 nd = 0.0042363783, D = 0.43863E+01 0.43863E+01 ( 21.06 s, 10.3 h) <br> iter 244 lrate = 0.0625000000 LL = -0.9406620338 nd = 0.0042378098, D = 0.43856E+01 0.43856E+01 ( 20.86 s, 10.2 h) <br> iter 245 lrate = 0.0625000000 LL = -0.9406511996 nd = 0.0042393537, D = 0.43849E+01 0.43849E+01 ( 20.71 s, 10.1 h) <br> iter 246 lrate = 0.0625000000 LL = -0.9406403691 nd = 0.0042409674, D = 0.43842E+01 0.43842E+01 ( 20.49 s, 10.0 h) <br> iter 247 lrate = 0.0625000000 LL = -0.9406295490 nd = 0.0042425578, D = 0.43834E+01 0.43834E+01 ( 20.75 s, 10.1 h) <br> iter 248 lrate = 0.0625000000 LL = -0.9406187535 nd = 0.0042440660, D = 0.43827E+01 0.43827E+01 ( 20.84 s, 10.1 h) <br> iter 249 lrate = 0.0625000000 LL = -0.9406079732 nd = 0.0042454766, D = 0.43820E+01 0.43820E+01 ( 20.77 s, 10.1 h) <br> iter 250 lrate = 0.0625000000 LL = -0.9405972216 nd = 0.0042467120, D = 0.43813E+01 0.43813E+01 ( 20.77 s, 10.1 h) <br> iter 251 lrate = 0.0625000000 LL = -0.9405864945 nd = 0.0042478340, D = 0.43805E+01 0.43805E+01 ( 29.32 s, 14.2 h) <br> iter 252 lrate = 0.0625000000 LL = -0.9405757907 nd = 0.0042490412, D = 0.43798E+01 0.43798E+01 ( 20.87 s, 10.1 h) <br> iter 253 lrate = 0.0625000000 LL = -0.9405651091 nd = 0.0042504759, D = 0.43791E+01 0.43791E+01 ( 20.69 s, 10.0 h) <br> iter 254 lrate = 0.0625000000 LL = -0.9405544089 nd = 0.0042520685, D = 0.43784E+01 0.43784E+01 ( 20.94 s, 10.2 h) <br> iter 255 lrate = 0.0625000000 LL = -0.9405437177 nd = 0.0042536815, D = 0.43777E+01 0.43777E+01 ( 20.99 s, 10.2 h) <br> iter 256 lrate = 0.0625000000 LL = -0.9405330415 nd = 0.0042553237, D = 0.43769E+01 0.43769E+01 ( 21.05 s, 10.2 h) <br> iter 257 lrate = 0.0625000000 LL = -0.9405223839 nd = 0.0042569680, D = 0.43762E+01 0.43762E+01 ( 20.86 s, 10.1 h) <br> iter 258 lrate = 0.0625000000 LL = -0.9405117591 nd = 0.0042586084, D = 0.43755E+01 0.43755E+01 ( 20.79 s, 10.1 h) <br> iter 259 lrate = 0.0625000000 LL = -0.9405011554 nd = 0.0042601888, D = 0.43748E+01 0.43748E+01 ( 20.58 s, 10.0 h) <br> iter 260 lrate = 0.0625000000 LL = -0.9404905637 nd = 0.0042616147, D = 0.43741E+01 0.43741E+01 ( 20.75 s, 10.0 h) <br> iter 261 lrate = 0.0625000000 LL = -0.9404800082 nd = 0.0042629830, D = 0.43733E+01 0.43733E+01 ( 29.53 s, 14.3 h) <br> iter 262 lrate = 0.0625000000 LL = -0.9404694503 nd = 0.0042642939, D = 0.43726E+01 0.43726E+01 ( 21.04 s, 10.2 h) <br> iter 263 lrate = 0.0625000000 LL = -0.9404589269 nd = 0.0042655824, D = 0.43719E+01 0.43719E+01 ( 20.71 s, 10.0 h) <br> iter 264 lrate = 0.0625000000 LL = -0.9404484480 nd = 0.0042667035, D = 0.43712E+01 0.43712E+01 ( 20.74 s, 10.0 h) <br> iter 265 lrate = 0.0625000000 LL = -0.9404379693 nd = 0.0042676495, D = 0.43705E+01 0.43705E+01 ( 20.93 s, 10.1 h) <br> iter 266 lrate = 0.0625000000 LL = -0.9404274902 nd = 0.0042685778, D = 0.43698E+01 0.43698E+01 ( 20.59 s, 9.9 h) <br> iter 267 lrate = 0.0625000000 LL = -0.9404170419 nd = 0.0042695496, D = 0.43691E+01 0.43691E+01 ( 20.68 s, 10.0 h) <br> iter 268 lrate = 0.0625000000 LL = -0.9404066041 nd = 0.0042707230, D = 0.43684E+01 0.43684E+01 ( 20.98 s, 10.1 h) <br> iter 269 lrate = 0.0625000000 LL = -0.9403961509 nd = 0.0042722057, D = 0.43676E+01 0.43676E+01 ( 20.70 s, 10.0 h) <br> iter 270 lrate = 0.0625000000 LL = -0.9403857167 nd = 0.0042738830, D = 0.43669E+01 0.43669E+01 ( 21.17 s, 10.2 h) <br> iter 271 lrate = 0.0625000000 LL = -0.9403752616 nd = 0.0042756406, D = 0.43662E+01 0.43662E+01 ( 29.26 s, 14.1 h) <br> iter 272 lrate = 0.0625000000 LL = -0.9403647962 nd = 0.0042773131, D = 0.43655E+01 0.43655E+01 ( 21.00 s, 10.1 h) <br> iter 273 lrate = 0.0625000000 LL = -0.9403543371 nd = 0.0042787935, D = 0.43648E+01 0.43648E+01 ( 20.77 s, 10.0 h) <br> iter 274 lrate = 0.0625000000 LL = -0.9403438975 nd = 0.0042801569, D = 0.43641E+01 0.43641E+01 ( 20.43 s, 9.8 h) <br> iter 275 lrate = 0.0625000000 LL = -0.9403334746 nd = 0.0042814975, D = 0.43634E+01 0.43634E+01 ( 21.06 s, 10.1 h) <br> iter 276 lrate = 0.0625000000 LL = -0.9403230845 nd = 0.0042827896, D = 0.43627E+01 0.43627E+01 ( 20.88 s, 10.0 h) <br> iter 277 lrate = 0.0625000000 LL = -0.9403127026 nd = 0.0042838543, D = 0.43620E+01 0.43620E+01 ( 21.05 s, 10.1 h) <br> iter 278 lrate = 0.0625000000 LL = -0.9403023540 nd = 0.0042847719, D = 0.43613E+01 0.43613E+01 ( 20.96 s, 10.0 h) <br> iter 279 lrate = 0.0625000000 LL = -0.9402920294 nd = 0.0042856222, D = 0.43606E+01 0.43606E+01 ( 20.85 s, 10.0 h) <br> iter 280 lrate = 0.0625000000 LL = -0.9402817233 nd = 0.0042865101, D = 0.43599E+01 0.43599E+01 ( 20.85 s, 10.0 h) <br> iter 281 lrate = 0.0625000000 LL = -0.9402714337 nd = 0.0042874936, D = 0.43592E+01 0.43592E+01 ( 29.36 s, 14.0 h) <br> iter 282 lrate = 0.0625000000 LL = -0.9402611596 nd = 0.0042885598, D = 0.43585E+01 0.43585E+01 ( 20.79 s, 9.9 h) <br> iter 283 lrate = 0.0625000000 LL = -0.9402509178 nd = 0.0042896374, D = 0.43578E+01 0.43578E+01 ( 20.95 s, 10.0 h) <br> iter 284 lrate = 0.0625000000 LL = -0.9402406739 nd = 0.0042907443, D = 0.43571E+01 0.43571E+01 ( 20.80 s, 9.9 h) <br> iter 285 lrate = 0.0625000000 LL = -0.9402304469 nd = 0.0042917834, D = 0.43564E+01 0.43564E+01 ( 20.50 s, 9.8 h) <br> iter 286 lrate = 0.0625000000 LL = -0.9402202448 nd = 0.0042926724, D = 0.43557E+01 0.43557E+01 ( 20.84 s, 9.9 h) <br> iter 287 lrate = 0.0625000000 LL = -0.9402100823 nd = 0.0042933625, D = 0.43550E+01 0.43550E+01 ( 20.95 s, 10.0 h) <br> iter 288 lrate = 0.0625000000 LL = -0.9401999483 nd = 0.0042939186, D = 0.43543E+01 0.43543E+01 ( 20.98 s, 10.0 h) <br> iter 289 lrate = 0.0625000000 LL = -0.9401898514 nd = 0.0042943883, D = 0.43536E+01 0.43536E+01 ( 21.07 s, 10.0 h) <br> iter 290 lrate = 0.0625000000 LL = -0.9401797855 nd = 0.0042948423, D = 0.43529E+01 0.43529E+01 ( 21.00 s, 10.0 h) <br> iter 291 lrate = 0.0625000000 LL = -0.9401697267 nd = 0.0042953550, D = 0.43522E+01 0.43522E+01 ( 29.23 s, 13.9 h) <br> iter 292 lrate = 0.0625000000 LL = -0.9401596795 nd = 0.0042959528, D = 0.43515E+01 0.43515E+01 ( 20.96 s, 9.9 h) <br> iter 293 lrate = 0.0625000000 LL = -0.9401496400 nd = 0.0042965507, D = 0.43508E+01 0.43508E+01 ( 20.85 s, 9.9 h) <br> iter 294 lrate = 0.0625000000 LL = -0.9401396304 nd = 0.0042971469, D = 0.43501E+01 0.43501E+01 ( 20.88 s, 9.9 h) <br> iter 295 lrate = 0.0625000000 LL = -0.9401296526 nd = 0.0042977612, D = 0.43494E+01 0.43494E+01 ( 20.78 s, 9.8 h) <br> iter 296 lrate = 0.0625000000 LL = -0.9401196964 nd = 0.0042982840, D = 0.43488E+01 0.43488E+01 ( 20.77 s, 9.8 h) <br> iter 297 lrate = 0.0625000000 LL = -0.9401097772 nd = 0.0042988391, D = 0.43481E+01 0.43481E+01 ( 20.85 s, 9.9 h) <br> iter 298 lrate = 0.0625000000 LL = -0.9400998705 nd = 0.0042993461, D = 0.43474E+01 0.43474E+01 ( 21.16 s, 10.0 h) <br> iter 299 lrate = 0.0625000000 LL = -0.9400900030 nd = 0.0042999441, D = 0.43467E+01 0.43467E+01 ( 20.66 s, 9.8 h) <br> iter 300 lrate = 0.0625000000 LL = -0.9400801418 nd = 0.0043006449, D = 0.43460E+01 0.43460E+01 ( 21.12 s, 10.0 h) <br> iter 301 lrate = 0.0625000000 LL = -0.9403953887 nd = 0.0046515461, D = 0.43460E+01 0.43460E+01 ( 29.55 s, 13.9 h) <br> Likelihood decreasing! <br> iter 302 lrate = 0.0312500000 LL = -0.9403943359 nd = 0.0046511444, D = 0.43460E+01 0.43460E+01 ( 21.08 s, 9.9 h) <br> iter 303 lrate = 0.0312500000 LL = -0.9403934370 nd = 0.0046503103, D = 0.43460E+01 0.43460E+01 ( 20.79 s, 9.8 h) <br> iter 304 lrate = 0.0312500000 LL = -0.9403926105 nd = 0.0046491850, D = 0.43460E+01 0.43460E+01 ( 21.10 s, 9.9 h) <br> iter 305 lrate = 0.0312500000 LL = -0.9403918440 nd = 0.0046479971, D = 0.43460E+01 0.43460E+01 ( 21.21 s, 10.0 h) <br> iter 306 lrate = 0.0312500000 LL = -0.9403910978 nd = 0.0046467373, D = 0.43460E+01 0.43460E+01 ( 21.00 s, 9.9 h) <br> iter 307 lrate = 0.0625000000 LL = -0.9400402972 nd = 0.0042621586, D = 0.43453E+01 0.43453E+01 ( 20.98 s, 9.9 h) <br> iter 308 lrate = 0.0625000000 LL = -0.9400584869 nd = 0.0042994622, D = 0.43446E+01 0.43446E+01 ( 21.02 s, 9.9 h) <br> Likelihood decreasing! <br> iter 309 lrate = 0.0625000000 LL = -0.9400461931 nd = 0.0042960067, D = 0.43440E+01 0.43440E+01 ( 20.66 s, 9.7 h) <br> iter 310 lrate = 0.0625000000 LL = -0.9400368084 nd = 0.0042967407, D = 0.43433E+01 0.43433E+01 ( 20.75 s, 9.7 h) <br> iter 311 lrate = 0.0625000000 LL = -0.9400271217 nd = 0.0042971638, D = 0.43426E+01 0.43426E+01 ( 29.30 s, 13.7 h) <br> iter 312 lrate = 0.0625000000 LL = -0.9400174642 nd = 0.0042978391, D = 0.43419E+01 0.43419E+01 ( 20.82 s, 9.8 h) <br> iter 313 lrate = 0.0625000000 LL = -0.9400078052 nd = 0.0042987168, D = 0.43412E+01 0.43412E+01 ( 20.82 s, 9.8 h) <br> iter 314 lrate = 0.0625000000 LL = -0.9399981462 nd = 0.0042996730, D = 0.43406E+01 0.43406E+01 ( 20.70 s, 9.7 h) <br> iter 315 lrate = 0.0625000000 LL = -0.9399885006 nd = 0.0043006154, D = 0.43399E+01 0.43399E+01 ( 20.78 s, 9.7 h) <br> iter 316 lrate = 0.0625000000 LL = -0.9399788763 nd = 0.0043013819, D = 0.43392E+01 0.43392E+01 ( 20.72 s, 9.7 h) <br> iter 317 lrate = 0.0625000000 LL = -0.9399692823 nd = 0.0043020920, D = 0.43385E+01 0.43385E+01 ( 20.88 s, 9.8 h) <br> iter 318 lrate = 0.0625000000 LL = -0.9399596961 nd = 0.0043031541, D = 0.43378E+01 0.43378E+01 ( 21.07 s, 9.8 h) <br> iter 319 lrate = 0.0625000000 LL = -0.9399500965 nd = 0.0043046297, D = 0.43372E+01 0.43372E+01 ( 20.94 s, 9.8 h) <br> iter 320 lrate = 0.0625000000 LL = -0.9399404771 nd = 0.0043063964, D = 0.43365E+01 0.43365E+01 ( 21.24 s, 9.9 h) <br> iter 321 lrate = 0.0625000000 LL = -0.9399308667 nd = 0.0043081620, D = 0.43358E+01 0.43358E+01 ( 29.21 s, 13.6 h) <br> iter 322 lrate = 0.0625000000 LL = -0.9399212683 nd = 0.0043098585, D = 0.43351E+01 0.43351E+01 ( 20.87 s, 9.7 h) <br> iter 323 lrate = 0.0625000000 LL = -0.9399116781 nd = 0.0043114600, D = 0.43344E+01 0.43344E+01 ( 20.84 s, 9.7 h) <br> iter 324 lrate = 0.0625000000 LL = -0.9399021203 nd = 0.0043129852, D = 0.43338E+01 0.43338E+01 ( 21.23 s, 9.9 h) <br> iter 325 lrate = 0.0625000000 LL = -0.9398925952 nd = 0.0043144551, D = 0.43331E+01 0.43331E+01 ( 20.78 s, 9.7 h) <br> iter 326 lrate = 0.0625000000 LL = -0.9398830848 nd = 0.0043156659, D = 0.43324E+01 0.43324E+01 ( 21.02 s, 9.8 h) <br> iter 327 lrate = 0.0625000000 LL = -0.9398735937 nd = 0.0043167517, D = 0.43317E+01 0.43317E+01 ( 21.06 s, 9.8 h) <br> iter 328 lrate = 0.0625000000 LL = -0.9398641192 nd = 0.0043176418, D = 0.43311E+01 0.43311E+01 ( 21.18 s, 9.8 h) <br> iter 329 lrate = 0.0625000000 LL = -0.9398546720 nd = 0.0043182937, D = 0.43304E+01 0.43304E+01 ( 21.01 s, 9.8 h) <br> iter 330 lrate = 0.0625000000 LL = -0.9398452527 nd = 0.0043190200, D = 0.43297E+01 0.43297E+01 ( 20.85 s, 9.7 h) <br> iter 331 lrate = 0.0625000000 LL = -0.9398358523 nd = 0.0043199056, D = 0.43290E+01 0.43290E+01 ( 29.43 s, 13.6 h) <br> iter 332 lrate = 0.0625000000 LL = -0.9398264426 nd = 0.0043207538, D = 0.43284E+01 0.43284E+01 ( 21.20 s, 9.8 h) <br> iter 333 lrate = 0.0625000000 LL = -0.9398170477 nd = 0.0043213015, D = 0.43277E+01 0.43277E+01 ( 20.82 s, 9.6 h) <br> iter 334 lrate = 0.0625000000 LL = -0.9398076669 nd = 0.0043214411, D = 0.43270E+01 0.43270E+01 ( 20.96 s, 9.7 h) <br> iter 335 lrate = 0.0625000000 LL = -0.9397982962 nd = 0.0043217160, D = 0.43263E+01 0.43263E+01 ( 21.09 s, 9.8 h) <br> iter 336 lrate = 0.0625000000 LL = -0.9397889094 nd = 0.0043228537, D = 0.43257E+01 0.43257E+01 ( 20.91 s, 9.7 h) <br> iter 337 lrate = 0.0625000000 LL = -0.9397794713 nd = 0.0043248064, D = 0.43250E+01 0.43250E+01 ( 20.83 s, 9.6 h) <br> iter 338 lrate = 0.0625000000 LL = -0.9397699911 nd = 0.0043269418, D = 0.43243E+01 0.43243E+01 ( 21.10 s, 9.7 h) <br> iter 339 lrate = 0.0625000000 LL = -0.9397605027 nd = 0.0043294079, D = 0.43236E+01 0.43236E+01 ( 20.75 s, 9.6 h) <br> iter 340 lrate = 0.0625000000 LL = -0.9397510022 nd = 0.0043322079, D = 0.43230E+01 0.43230E+01 ( 20.82 s, 9.6 h) <br> iter 341 lrate = 0.0625000000 LL = -0.9397414900 nd = 0.0043349529, D = 0.43223E+01 0.43223E+01 ( 29.18 s, 13.4 h) <br> iter 342 lrate = 0.0625000000 LL = -0.9397319866 nd = 0.0043371896, D = 0.43216E+01 0.43216E+01 ( 20.81 s, 9.6 h) <br> iter 343 lrate = 0.0625000000 LL = -0.9397225132 nd = 0.0043388716, D = 0.43210E+01 0.43210E+01 ( 20.72 s, 9.5 h) <br> iter 344 lrate = 0.0625000000 LL = -0.9397130804 nd = 0.0043402066, D = 0.43203E+01 0.43203E+01 ( 20.84 s, 9.6 h) <br> iter 345 lrate = 0.0625000000 LL = -0.9397036775 nd = 0.0043413530, D = 0.43196E+01 0.43196E+01 ( 20.95 s, 9.6 h) <br> iter 346 lrate = 0.0625000000 LL = -0.9396942933 nd = 0.0043421149, D = 0.43189E+01 0.43189E+01 ( 20.99 s, 9.6 h) <br> iter 347 lrate = 0.0625000000 LL = -0.9396849363 nd = 0.0043427899, D = 0.43183E+01 0.43183E+01 ( 20.86 s, 9.6 h) <br> iter 348 lrate = 0.0625000000 LL = -0.9396755826 nd = 0.0043432253, D = 0.43176E+01 0.43176E+01 ( 21.01 s, 9.6 h) <br> iter 349 lrate = 0.0625000000 LL = -0.9396662387 nd = 0.0043438596, D = 0.43169E+01 0.43169E+01 ( 20.93 s, 9.6 h) <br> iter 350 lrate = 0.0625000000 LL = -0.9396568729 nd = 0.0043450296, D = 0.43163E+01 0.43163E+01 ( 20.76 s, 9.5 h) <br> iter 351 lrate = 0.0625000000 LL = -0.9396474500 nd = 0.0043465999, D = 0.43156E+01 0.43156E+01 ( 29.27 s, 13.4 h) <br> iter 352 lrate = 0.0625000000 LL = -0.9396379772 nd = 0.0043483883, D = 0.43149E+01 0.43149E+01 ( 21.02 s, 9.6 h) <br> iter 353 lrate = 0.0625000000 LL = -0.9396284764 nd = 0.0043507918, D = 0.43143E+01 0.43143E+01 ( 20.83 s, 9.5 h) <br> iter 354 lrate = 0.0625000000 LL = -0.9396188989 nd = 0.0043541779, D = 0.43136E+01 0.43136E+01 ( 20.97 s, 9.6 h) <br> iter 355 lrate = 0.0625000000 LL = -0.9396092258 nd = 0.0043574926, D = 0.43129E+01 0.43129E+01 ( 20.80 s, 9.5 h) <br> iter 356 lrate = 0.0625000000 LL = -0.9395995381 nd = 0.0043603530, D = 0.43123E+01 0.43123E+01 ( 20.95 s, 9.6 h) <br> iter 357 lrate = 0.0625000000 LL = -0.9395898414 nd = 0.0043631079, D = 0.43116E+01 0.43116E+01 ( 21.13 s, 9.6 h) <br> iter 358 lrate = 0.0625000000 LL = -0.9395801099 nd = 0.0043663395, D = 0.43109E+01 0.43109E+01 ( 20.91 s, 9.5 h) <br> iter 359 lrate = 0.0625000000 LL = -0.9395702929 nd = 0.0043695389, D = 0.43103E+01 0.43103E+01 ( 21.06 s, 9.6 h) <br> iter 360 lrate = 0.0625000000 LL = -0.9395604322 nd = 0.0043722095, D = 0.43096E+01 0.43096E+01 ( 20.94 s, 9.5 h) <br> iter 361 lrate = 0.0625000000 LL = -0.9395505396 nd = 0.0043749934, D = 0.43089E+01 0.43089E+01 ( 29.18 s, 13.3 h) <br> iter 362 lrate = 0.0625000000 LL = -0.9395405903 nd = 0.0043781636, D = 0.43083E+01 0.43083E+01 ( 21.04 s, 9.6 h) <br> iter 363 lrate = 0.0625000000 LL = -0.9395305512 nd = 0.0043814989, D = 0.43076E+01 0.43076E+01 ( 21.07 s, 9.6 h) <br> iter 364 lrate = 0.0625000000 LL = -0.9395204478 nd = 0.0043856227, D = 0.43070E+01 0.43070E+01 ( 20.86 s, 9.5 h) <br> iter 365 lrate = 0.0625000000 LL = -0.9395102594 nd = 0.0043899988, D = 0.43063E+01 0.43063E+01 ( 20.76 s, 9.4 h) <br> iter 366 lrate = 0.0625000000 LL = -0.9395000128 nd = 0.0043942182, D = 0.43057E+01 0.43057E+01 ( 20.89 s, 9.5 h) <br> iter 367 lrate = 0.0625000000 LL = -0.9394897717 nd = 0.0043981421, D = 0.43050E+01 0.43050E+01 ( 20.79 s, 9.4 h) <br> iter 368 lrate = 0.0625000000 LL = -0.9394795394 nd = 0.0044021570, D = 0.43044E+01 0.43044E+01 ( 20.82 s, 9.4 h) <br> iter 369 lrate = 0.0625000000 LL = -0.9394693055 nd = 0.0044062707, D = 0.43037E+01 0.43037E+01 ( 21.01 s, 9.5 h) <br> iter 370 lrate = 0.0625000000 LL = -0.9394590869 nd = 0.0044101982, D = 0.43031E+01 0.43031E+01 ( 20.86 s, 9.4 h) <br> iter 371 lrate = 0.0625000000 LL = -0.9394489058 nd = 0.0044137546, D = 0.43025E+01 0.43025E+01 ( 29.33 s, 13.3 h) <br> iter 372 lrate = 0.0625000000 LL = -0.9394388038 nd = 0.0044166550, D = 0.43018E+01 0.43018E+01 ( 21.06 s, 9.5 h) <br> iter 373 lrate = 0.0625000000 LL = -0.9394287970 nd = 0.0044194794, D = 0.43012E+01 0.43012E+01 ( 20.60 s, 9.3 h) <br> iter 374 lrate = 0.0625000000 LL = -0.9394188545 nd = 0.0044231031, D = 0.43005E+01 0.43005E+01 ( 20.60 s, 9.3 h) <br> iter 375 lrate = 0.0625000000 LL = -0.9394089158 nd = 0.0044272087, D = 0.42999E+01 0.42999E+01 ( 21.08 s, 9.5 h) <br> iter 376 lrate = 0.0625000000 LL = -0.9393990233 nd = 0.0044314883, D = 0.42992E+01 0.42992E+01 ( 20.93 s, 9.4 h) <br> iter 377 lrate = 0.0625000000 LL = -0.9393891842 nd = 0.0044364573, D = 0.42986E+01 0.42986E+01 ( 20.78 s, 9.4 h) <br> iter 378 lrate = 0.0625000000 LL = -0.9393793619 nd = 0.0044416083, D = 0.42979E+01 0.42979E+01 ( 21.23 s, 9.6 h) <br> iter 379 lrate = 0.0625000000 LL = -0.9393695967 nd = 0.0044460029, D = 0.42973E+01 0.42973E+01 ( 20.97 s, 9.4 h) <br> iter 380 lrate = 0.0625000000 LL = -0.9393599597 nd = 0.0044501621, D = 0.42966E+01 0.42966E+01 ( 21.19 s, 9.5 h) <br> iter 381 lrate = 0.0625000000 LL = -0.9393503940 nd = 0.0044545033, D = 0.42960E+01 0.42960E+01 ( 29.57 s, 13.3 h) <br> iter 382 lrate = 0.0625000000 LL = -0.9393408833 nd = 0.0044589838, D = 0.42953E+01 0.42953E+01 ( 20.90 s, 9.4 h) <br> iter 383 lrate = 0.0625000000 LL = -0.9393314319 nd = 0.0044635198, D = 0.42947E+01 0.42947E+01 ( 20.81 s, 9.3 h) <br> iter 384 lrate = 0.0625000000 LL = -0.9393220359 nd = 0.0044678647, D = 0.42940E+01 0.42940E+01 ( 20.81 s, 9.3 h) <br> iter 385 lrate = 0.0625000000 LL = -0.9393127026 nd = 0.0044720686, D = 0.42934E+01 0.42934E+01 ( 21.12 s, 9.5 h) <br> iter 386 lrate = 0.0625000000 LL = -0.9393034248 nd = 0.0044761274, D = 0.42927E+01 0.42927E+01 ( 20.83 s, 9.3 h) <br> iter 387 lrate = 0.0625000000 LL = -0.9392942065 nd = 0.0044802348, D = 0.42920E+01 0.42920E+01 ( 21.02 s, 9.4 h) <br> iter 388 lrate = 0.0625000000 LL = -0.9392850382 nd = 0.0044843446, D = 0.42914E+01 0.42914E+01 ( 21.06 s, 9.4 h) <br> iter 389 lrate = 0.0625000000 LL = -0.9392758964 nd = 0.0044885021, D = 0.42907E+01 0.42907E+01 ( 21.22 s, 9.5 h) <br> iter 390 lrate = 0.0625000000 LL = -0.9392667812 nd = 0.0044928084, D = 0.42901E+01 0.42901E+01 ( 20.84 s, 9.3 h) <br> iter 391 lrate = 0.0625000000 LL = -0.9392576888 nd = 0.0044974606, D = 0.42894E+01 0.42894E+01 ( 29.24 s, 13.1 h) <br> iter 392 lrate = 0.0625000000 LL = -0.9392486073 nd = 0.0045021327, D = 0.42887E+01 0.42887E+01 ( 20.90 s, 9.3 h) <br> iter 393 lrate = 0.0625000000 LL = -0.9392395328 nd = 0.0045066156, D = 0.42881E+01 0.42881E+01 ( 20.67 s, 9.2 h) <br> iter 394 lrate = 0.0625000000 LL = -0.9392304966 nd = 0.0045110243, D = 0.42874E+01 0.42874E+01 ( 20.91 s, 9.3 h) <br> iter 395 lrate = 0.0625000000 LL = -0.9392214961 nd = 0.0045154840, D = 0.42867E+01 0.42867E+01 ( 21.06 s, 9.4 h) <br> iter 396 lrate = 0.0625000000 LL = -0.9392125185 nd = 0.0045193823, D = 0.42861E+01 0.42861E+01 ( 21.15 s, 9.4 h) <br> iter 397 lrate = 0.0625000000 LL = -0.9392035934 nd = 0.0045229461, D = 0.42854E+01 0.42854E+01 ( 21.04 s, 9.4 h) <br> iter 398 lrate = 0.0625000000 LL = -0.9391947170 nd = 0.0045265232, D = 0.42848E+01 0.42848E+01 ( 20.80 s, 9.3 h) <br> iter 399 lrate = 0.0625000000 LL = -0.9391858626 nd = 0.0045301192, D = 0.42841E+01 0.42841E+01 ( 21.07 s, 9.4 h) <br> iter 400 lrate = 0.0625000000 LL = -0.9391770259 nd = 0.0045337188, D = 0.42835E+01 0.42835E+01 ( 21.26 s, 9.4 h) <br> iter 401 lrate = 0.0625000000 LL = -0.9395100178 nd = 0.0049412239, D = 0.42835E+01 0.42835E+01 ( 29.29 s, 13.0 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 402 lrate = 0.0312500000 LL = -0.9395092351 nd = 0.0049428764, D = 0.42835E+01 0.42835E+01 ( 20.82 s, 9.2 h) <br> iter 403 lrate = 0.0312500000 LL = -0.9395086084 nd = 0.0049430337, D = 0.42835E+01 0.42835E+01 ( 20.76 s, 9.2 h) <br> iter 404 lrate = 0.0312500000 LL = -0.9395080529 nd = 0.0049424503, D = 0.42835E+01 0.42835E+01 ( 20.98 s, 9.3 h) <br> iter 405 lrate = 0.0312500000 LL = -0.9395075344 nd = 0.0049415257, D = 0.42835E+01 0.42835E+01 ( 21.02 s, 9.3 h) <br> iter 406 lrate = 0.0312500000 LL = -0.9395070560 nd = 0.0049404463, D = 0.42835E+01 0.42835E+01 ( 20.85 s, 9.2 h) <br> iter 407 lrate = 0.0312500000 LL = -0.9393195284 nd = 0.0047218632, D = 0.42831E+01 0.42831E+01 ( 20.92 s, 9.3 h) <br> iter 408 lrate = 0.0312500000 LL = -0.9393230843 nd = 0.0047333034, D = 0.42828E+01 0.42828E+01 ( 21.04 s, 9.3 h) <br> Likelihood decreasing! <br> iter 409 lrate = 0.0312500000 LL = -0.9393182763 nd = 0.0047338829, D = 0.42825E+01 0.42825E+01 ( 20.97 s, 9.3 h) <br> iter 410 lrate = 0.0312500000 LL = -0.9393138573 nd = 0.0047354813, D = 0.42821E+01 0.42821E+01 ( 21.06 s, 9.3 h) <br> iter 411 lrate = 0.0312500000 LL = -0.9393094024 nd = 0.0047374802, D = 0.42818E+01 0.42818E+01 ( 29.17 s, 12.9 h) <br> iter 412 lrate = 0.0312500000 LL = -0.9393049379 nd = 0.0047398985, D = 0.42815E+01 0.42815E+01 ( 20.85 s, 9.2 h) <br> iter 413 lrate = 0.0312500000 LL = -0.9393004734 nd = 0.0047427204, D = 0.42812E+01 0.42812E+01 ( 21.04 s, 9.3 h) <br> iter 414 lrate = 0.0312500000 LL = -0.9392959941 nd = 0.0047457960, D = 0.42809E+01 0.42809E+01 ( 20.89 s, 9.2 h) <br> iter 415 lrate = 0.0312500000 LL = -0.9392915227 nd = 0.0047491229, D = 0.42805E+01 0.42805E+01 ( 21.21 s, 9.3 h) <br> iter 416 lrate = 0.0312500000 LL = -0.9392870581 nd = 0.0047527230, D = 0.42802E+01 0.42802E+01 ( 20.74 s, 9.1 h) <br> iter 417 lrate = 0.0312500000 LL = -0.9392825807 nd = 0.0047564060, D = 0.42799E+01 0.42799E+01 ( 20.81 s, 9.2 h) <br> iter 418 lrate = 0.0312500000 LL = -0.9392781066 nd = 0.0047601906, D = 0.42796E+01 0.42796E+01 ( 20.81 s, 9.1 h) <br> iter 419 lrate = 0.0312500000 LL = -0.9392736297 nd = 0.0047639723, D = 0.42792E+01 0.42792E+01 ( 20.98 s, 9.2 h) <br> iter 420 lrate = 0.0312500000 LL = -0.9392691566 nd = 0.0047677983, D = 0.42789E+01 0.42789E+01 ( 20.98 s, 9.2 h) <br> iter 421 lrate = 0.0312500000 LL = -0.9392646811 nd = 0.0047718246, D = 0.42786E+01 0.42786E+01 ( 29.20 s, 12.8 h) <br> iter 422 lrate = 0.0312500000 LL = -0.9392602039 nd = 0.0047761685, D = 0.42783E+01 0.42783E+01 ( 21.25 s, 9.3 h) <br> iter 423 lrate = 0.0312500000 LL = -0.9392557139 nd = 0.0047806033, D = 0.42779E+01 0.42779E+01 ( 20.94 s, 9.2 h) <br> iter 424 lrate = 0.0312500000 LL = -0.9392512318 nd = 0.0047849340, D = 0.42776E+01 0.42776E+01 ( 20.84 s, 9.1 h) <br> iter 425 lrate = 0.0312500000 LL = -0.9392467567 nd = 0.0047890057, D = 0.42773E+01 0.42773E+01 ( 20.92 s, 9.2 h) <br> iter 426 lrate = 0.0312500000 LL = -0.9392422990 nd = 0.0047927928, D = 0.42770E+01 0.42770E+01 ( 20.97 s, 9.2 h) <br> iter 427 lrate = 0.0312500000 LL = -0.9392378551 nd = 0.0047964480, D = 0.42767E+01 0.42767E+01 ( 20.88 s, 9.1 h) <br> iter 428 lrate = 0.0312500000 LL = -0.9392334181 nd = 0.0047999623, D = 0.42763E+01 0.42763E+01 ( 20.91 s, 9.1 h) <br> iter 429 lrate = 0.0312500000 LL = -0.9392289880 nd = 0.0048035155, D = 0.42760E+01 0.42760E+01 ( 21.29 s, 9.3 h) <br> iter 430 lrate = 0.0312500000 LL = -0.9392245723 nd = 0.0048072282, D = 0.42757E+01 0.42757E+01 ( 20.91 s, 9.1 h) <br> iter 431 lrate = 0.0312500000 LL = -0.9392201490 nd = 0.0048110664, D = 0.42754E+01 0.42754E+01 ( 29.15 s, 12.7 h) <br> iter 432 lrate = 0.0312500000 LL = -0.9392157443 nd = 0.0048149056, D = 0.42751E+01 0.42751E+01 ( 21.02 s, 9.2 h) <br> iter 433 lrate = 0.0312500000 LL = -0.9392113390 nd = 0.0048186111, D = 0.42747E+01 0.42747E+01 ( 20.85 s, 9.1 h) <br> iter 434 lrate = 0.0312500000 LL = -0.9392069443 nd = 0.0048221816, D = 0.42744E+01 0.42744E+01 ( 20.75 s, 9.0 h) <br> iter 435 lrate = 0.0312500000 LL = -0.9392025707 nd = 0.0048255146, D = 0.42741E+01 0.42741E+01 ( 21.18 s, 9.2 h) <br> iter 436 lrate = 0.0312500000 LL = -0.9391982094 nd = 0.0048286130, D = 0.42738E+01 0.42738E+01 ( 20.77 s, 9.0 h) <br> iter 437 lrate = 0.0312500000 LL = -0.9391938657 nd = 0.0048314228, D = 0.42735E+01 0.42735E+01 ( 20.92 s, 9.1 h) <br> iter 438 lrate = 0.0312500000 LL = -0.9391895405 nd = 0.0048340625, D = 0.42731E+01 0.42731E+01 ( 21.05 s, 9.1 h) <br> iter 439 lrate = 0.0312500000 LL = -0.9391852384 nd = 0.0048365848, D = 0.42728E+01 0.42728E+01 ( 20.99 s, 9.1 h) <br> iter 440 lrate = 0.0312500000 LL = -0.9391809418 nd = 0.0048391516, D = 0.42725E+01 0.42725E+01 ( 21.33 s, 9.2 h) <br> iter 441 lrate = 0.0312500000 LL = -0.9391766480 nd = 0.0048418348, D = 0.42722E+01 0.42722E+01 ( 29.29 s, 12.7 h) <br> iter 442 lrate = 0.0312500000 LL = -0.9391723532 nd = 0.0048447316, D = 0.42719E+01 0.42719E+01 ( 21.08 s, 9.1 h) <br> iter 443 lrate = 0.0312500000 LL = -0.9391680617 nd = 0.0048478623, D = 0.42715E+01 0.42715E+01 ( 21.13 s, 9.1 h) <br> iter 444 lrate = 0.0312500000 LL = -0.9391637695 nd = 0.0048511403, D = 0.42712E+01 0.42712E+01 ( 20.94 s, 9.1 h) <br> iter 445 lrate = 0.0312500000 LL = -0.9391594817 nd = 0.0048545419, D = 0.42709E+01 0.42709E+01 ( 20.81 s, 9.0 h) <br> iter 446 lrate = 0.0312500000 LL = -0.9391551981 nd = 0.0048580472, D = 0.42706E+01 0.42706E+01 ( 21.09 s, 9.1 h) <br> iter 447 lrate = 0.0312500000 LL = -0.9391509227 nd = 0.0048615922, D = 0.42703E+01 0.42703E+01 ( 20.94 s, 9.0 h) <br> iter 448 lrate = 0.0312500000 LL = -0.9391466649 nd = 0.0048651411, D = 0.42699E+01 0.42699E+01 ( 20.93 s, 9.0 h) <br> iter 449 lrate = 0.0312500000 LL = -0.9391424088 nd = 0.0048686976, D = 0.42696E+01 0.42696E+01 ( 20.97 s, 9.0 h) <br> iter 450 lrate = 0.0312500000 LL = -0.9391381589 nd = 0.0048721194, D = 0.42693E+01 0.42693E+01 ( 20.91 s, 9.0 h) <br> iter 451 lrate = 0.0312500000 LL = -0.9391339306 nd = 0.0048754585, D = 0.42690E+01 0.42690E+01 ( 29.14 s, 12.5 h) <br> iter 452 lrate = 0.0312500000 LL = -0.9391297090 nd = 0.0048786310, D = 0.42687E+01 0.42687E+01 ( 20.96 s, 9.0 h) <br> iter 453 lrate = 0.0312500000 LL = -0.9391255004 nd = 0.0048816057, D = 0.42684E+01 0.42684E+01 ( 21.07 s, 9.1 h) <br> iter 454 lrate = 0.0312500000 LL = -0.9391213086 nd = 0.0048844046, D = 0.42680E+01 0.42680E+01 ( 20.85 s, 9.0 h) <br> iter 455 lrate = 0.0312500000 LL = -0.9391171283 nd = 0.0048872701, D = 0.42677E+01 0.42677E+01 ( 20.95 s, 9.0 h) <br> iter 456 lrate = 0.0312500000 LL = -0.9391129516 nd = 0.0048903609, D = 0.42674E+01 0.42674E+01 ( 21.06 s, 9.0 h) <br> iter 457 lrate = 0.0312500000 LL = -0.9391087736 nd = 0.0048937519, D = 0.42671E+01 0.42671E+01 ( 20.94 s, 9.0 h) <br> iter 458 lrate = 0.0312500000 LL = -0.9391045916 nd = 0.0048972867, D = 0.42668E+01 0.42668E+01 ( 21.06 s, 9.0 h) <br> iter 459 lrate = 0.0312500000 LL = -0.9391004179 nd = 0.0049008466, D = 0.42664E+01 0.42664E+01 ( 21.07 s, 9.0 h) <br> iter 460 lrate = 0.0312500000 LL = -0.9390962476 nd = 0.0049042859, D = 0.42661E+01 0.42661E+01 ( 20.81 s, 8.9 h) <br> iter 461 lrate = 0.0312500000 LL = -0.9390920883 nd = 0.0049075339, D = 0.42658E+01 0.42658E+01 ( 29.32 s, 12.5 h) <br> iter 462 lrate = 0.0312500000 LL = -0.9390879428 nd = 0.0049105917, D = 0.42655E+01 0.42655E+01 ( 20.64 s, 8.8 h) <br> iter 463 lrate = 0.0312500000 LL = -0.9390838112 nd = 0.0049134973, D = 0.42652E+01 0.42652E+01 ( 20.40 s, 8.7 h) <br> iter 464 lrate = 0.0312500000 LL = -0.9390797122 nd = 0.0049164002, D = 0.42649E+01 0.42649E+01 ( 20.77 s, 8.9 h) <br> iter 465 lrate = 0.0312500000 LL = -0.9390756049 nd = 0.0049193356, D = 0.42645E+01 0.42645E+01 ( 20.98 s, 8.9 h) <br> iter 466 lrate = 0.0312500000 LL = -0.9390715046 nd = 0.0049223937, D = 0.42642E+01 0.42642E+01 ( 20.81 s, 8.9 h) <br> iter 467 lrate = 0.0312500000 LL = -0.9390674032 nd = 0.0049255262, D = 0.42639E+01 0.42639E+01 ( 20.84 s, 8.9 h) <br> iter 468 lrate = 0.0312500000 LL = -0.9390633096 nd = 0.0049288993, D = 0.42636E+01 0.42636E+01 ( 21.10 s, 9.0 h) <br> iter 469 lrate = 0.0312500000 LL = -0.9390592008 nd = 0.0049325187, D = 0.42633E+01 0.42633E+01 ( 20.96 s, 8.9 h) <br> iter 470 lrate = 0.0312500000 LL = -0.9390550846 nd = 0.0049363288, D = 0.42630E+01 0.42630E+01 ( 21.01 s, 8.9 h) <br> iter 471 lrate = 0.0312500000 LL = -0.9390509725 nd = 0.0049400380, D = 0.42626E+01 0.42626E+01 ( 29.14 s, 12.4 h) <br> iter 472 lrate = 0.0312500000 LL = -0.9390468563 nd = 0.0049435249, D = 0.42623E+01 0.42623E+01 ( 20.94 s, 8.9 h) <br> iter 473 lrate = 0.0312500000 LL = -0.9390427455 nd = 0.0049467773, D = 0.42620E+01 0.42620E+01 ( 21.01 s, 8.9 h) <br> iter 474 lrate = 0.0312500000 LL = -0.9390386549 nd = 0.0049499523, D = 0.42617E+01 0.42617E+01 ( 21.14 s, 9.0 h) <br> iter 475 lrate = 0.0312500000 LL = -0.9390345584 nd = 0.0049531202, D = 0.42614E+01 0.42614E+01 ( 20.95 s, 8.9 h) <br> iter 476 lrate = 0.0312500000 LL = -0.9390304702 nd = 0.0049563085, D = 0.42611E+01 0.42611E+01 ( 21.17 s, 9.0 h) <br> iter 477 lrate = 0.0312500000 LL = -0.9390263940 nd = 0.0049596403, D = 0.42607E+01 0.42607E+01 ( 20.74 s, 8.8 h) <br> iter 478 lrate = 0.0312500000 LL = -0.9390223278 nd = 0.0049632624, D = 0.42604E+01 0.42604E+01 ( 21.06 s, 8.9 h) <br> iter 479 lrate = 0.0312500000 LL = -0.9390182388 nd = 0.0049671992, D = 0.42601E+01 0.42601E+01 ( 20.63 s, 8.7 h) <br> iter 480 lrate = 0.0312500000 LL = -0.9390141457 nd = 0.0049713253, D = 0.42598E+01 0.42598E+01 ( 20.84 s, 8.8 h) <br> iter 481 lrate = 0.0312500000 LL = -0.9390100590 nd = 0.0049754453, D = 0.42595E+01 0.42595E+01 ( 29.13 s, 12.3 h) <br> iter 482 lrate = 0.0312500000 LL = -0.9390059765 nd = 0.0049794126, D = 0.42592E+01 0.42592E+01 ( 21.04 s, 8.9 h) <br> iter 483 lrate = 0.0312500000 LL = -0.9390019016 nd = 0.0049832059, D = 0.42588E+01 0.42588E+01 ( 20.97 s, 8.8 h) <br> iter 484 lrate = 0.0312500000 LL = -0.9389978451 nd = 0.0049868247, D = 0.42585E+01 0.42585E+01 ( 20.62 s, 8.7 h) <br> iter 485 lrate = 0.0312500000 LL = -0.9389937992 nd = 0.0049903336, D = 0.42582E+01 0.42582E+01 ( 20.84 s, 8.8 h) <br> iter 486 lrate = 0.0312500000 LL = -0.9389897677 nd = 0.0049937374, D = 0.42579E+01 0.42579E+01 ( 20.83 s, 8.8 h) <br> iter 487 lrate = 0.0312500000 LL = -0.9389857500 nd = 0.0049970366, D = 0.42576E+01 0.42576E+01 ( 21.00 s, 8.8 h) <br> iter 488 lrate = 0.0312500000 LL = -0.9389817380 nd = 0.0050001926, D = 0.42573E+01 0.42573E+01 ( 20.80 s, 8.7 h) <br> iter 489 lrate = 0.0312500000 LL = -0.9389777432 nd = 0.0050031662, D = 0.42570E+01 0.42570E+01 ( 20.96 s, 8.8 h) <br> iter 490 lrate = 0.0312500000 LL = -0.9389737615 nd = 0.0050059911, D = 0.42566E+01 0.42566E+01 ( 21.11 s, 8.9 h) <br> iter 491 lrate = 0.0312500000 LL = -0.9389697931 nd = 0.0050087189, D = 0.42563E+01 0.42563E+01 ( 29.56 s, 12.4 h) <br> iter 492 lrate = 0.0312500000 LL = -0.9389658359 nd = 0.0050113722, D = 0.42560E+01 0.42560E+01 ( 21.04 s, 8.8 h) <br> iter 493 lrate = 0.0312500000 LL = -0.9389618854 nd = 0.0050139326, D = 0.42557E+01 0.42557E+01 ( 21.09 s, 8.8 h) <br> iter 494 lrate = 0.0312500000 LL = -0.9389579421 nd = 0.0050164807, D = 0.42554E+01 0.42554E+01 ( 20.88 s, 8.7 h) <br> iter 495 lrate = 0.0312500000 LL = -0.9389540080 nd = 0.0050190216, D = 0.42551E+01 0.42551E+01 ( 20.90 s, 8.7 h) <br> iter 496 lrate = 0.0312500000 LL = -0.9389500773 nd = 0.0050215605, D = 0.42548E+01 0.42548E+01 ( 20.91 s, 8.7 h) <br> iter 497 lrate = 0.0312500000 LL = -0.9389461541 nd = 0.0050240798, D = 0.42544E+01 0.42544E+01 ( 20.99 s, 8.8 h) <br> iter 498 lrate = 0.0312500000 LL = -0.9389422374 nd = 0.0050265590, D = 0.42541E+01 0.42541E+01 ( 20.67 s, 8.6 h) <br> iter 499 lrate = 0.0312500000 LL = -0.9389383309 nd = 0.0050289954, D = 0.42538E+01 0.42538E+01 ( 21.10 s, 8.8 h) <br> iter 500 lrate = 0.0312500000 LL = -0.9389344278 nd = 0.0050314070, D = 0.42535E+01 0.42535E+01 ( 20.96 s, 8.7 h) <br> iter 501 lrate = 0.0312500000 LL = -0.9391203305 nd = 0.0052606850, D = 0.42535E+01 0.42535E+01 ( 29.19 s, 12.2 h) <br> Likelihood decreasing! <br> iter 502 lrate = 0.0156250000 LL = -0.9391200022 nd = 0.0052627438, D = 0.42535E+01 0.42535E+01 ( 20.92 s, 8.7 h) <br> iter 503 lrate = 0.0156250000 LL = -0.9391197284 nd = 0.0052634020, D = 0.42535E+01 0.42535E+01 ( 20.95 s, 8.7 h) <br> iter 504 lrate = 0.0156250000 LL = -0.9391194628 nd = 0.0052634255, D = 0.42535E+01 0.42535E+01 ( 20.85 s, 8.7 h) <br> iter 505 lrate = 0.0156250000 LL = -0.9391192058 nd = 0.0052631335, D = 0.42535E+01 0.42535E+01 ( 20.89 s, 8.7 h) <br> iter 506 lrate = 0.0156250000 LL = -0.9391189620 nd = 0.0052627288, D = 0.42535E+01 0.42535E+01 ( 20.93 s, 8.7 h) <br> iter 507 lrate = 0.0312500000 LL = -0.9389206300 nd = 0.0050232004, D = 0.42532E+01 0.42532E+01 ( 20.88 s, 8.7 h) <br> iter 508 lrate = 0.0312500000 LL = -0.9389254863 nd = 0.0050357916, D = 0.42529E+01 0.42529E+01 ( 20.93 s, 8.7 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 509 lrate = 0.0156250000 LL = -0.9390158589 nd = 0.0051520976, D = 0.42527E+01 0.42527E+01 ( 20.96 s, 8.7 h) <br> Likelihood decreasing! <br> iter 510 lrate = 0.0156250000 LL = -0.9390117450 nd = 0.0051510036, D = 0.42526E+01 0.42526E+01 ( 21.01 s, 8.7 h) <br> iter 511 lrate = 0.0156250000 LL = -0.9390097845 nd = 0.0051524999, D = 0.42524E+01 0.42524E+01 ( 29.36 s, 12.1 h) <br> iter 512 lrate = 0.0156250000 LL = -0.9390077808 nd = 0.0051537602, D = 0.42522E+01 0.42522E+01 ( 21.26 s, 8.8 h) <br> iter 513 lrate = 0.0156250000 LL = -0.9390057826 nd = 0.0051549090, D = 0.42521E+01 0.42521E+01 ( 21.06 s, 8.7 h) <br> iter 514 lrate = 0.0156250000 LL = -0.9390037957 nd = 0.0051560006, D = 0.42519E+01 0.42519E+01 ( 20.74 s, 8.6 h) <br> iter 515 lrate = 0.0156250000 LL = -0.9390018092 nd = 0.0051570312, D = 0.42518E+01 0.42518E+01 ( 20.90 s, 8.6 h) <br> iter 516 lrate = 0.0156250000 LL = -0.9389998267 nd = 0.0051580135, D = 0.42516E+01 0.42516E+01 ( 20.56 s, 8.5 h) <br> iter 517 lrate = 0.0156250000 LL = -0.9389978521 nd = 0.0051589556, D = 0.42515E+01 0.42515E+01 ( 20.89 s, 8.6 h) <br> iter 518 lrate = 0.0156250000 LL = -0.9389958747 nd = 0.0051598635, D = 0.42513E+01 0.42513E+01 ( 20.74 s, 8.5 h) <br> iter 519 lrate = 0.0156250000 LL = -0.9389939028 nd = 0.0051607294, D = 0.42512E+01 0.42512E+01 ( 21.07 s, 8.7 h) <br> iter 520 lrate = 0.0156250000 LL = -0.9389919378 nd = 0.0051615640, D = 0.42510E+01 0.42510E+01 ( 20.66 s, 8.5 h) <br> iter 521 lrate = 0.0156250000 LL = -0.9389899684 nd = 0.0051623722, D = 0.42509E+01 0.42509E+01 ( 29.23 s, 12.0 h) <br> iter 522 lrate = 0.0156250000 LL = -0.9389880037 nd = 0.0051631498, D = 0.42507E+01 0.42507E+01 ( 20.86 s, 8.6 h) <br> iter 523 lrate = 0.0156250000 LL = -0.9389860405 nd = 0.0051639112, D = 0.42505E+01 0.42505E+01 ( 20.68 s, 8.5 h) <br> iter 524 lrate = 0.0156250000 LL = -0.9389840824 nd = 0.0051646354, D = 0.42504E+01 0.42504E+01 ( 21.20 s, 8.7 h) <br> iter 525 lrate = 0.0156250000 LL = -0.9389821231 nd = 0.0051653533, D = 0.42502E+01 0.42502E+01 ( 21.18 s, 8.7 h) <br> iter 526 lrate = 0.0156250000 LL = -0.9389801739 nd = 0.0051660622, D = 0.42501E+01 0.42501E+01 ( 21.01 s, 8.6 h) <br> iter 527 lrate = 0.0156250000 LL = -0.9389782155 nd = 0.0051667977, D = 0.42499E+01 0.42499E+01 ( 20.99 s, 8.6 h) <br> iter 528 lrate = 0.0156250000 LL = -0.9389762647 nd = 0.0051675631, D = 0.42498E+01 0.42498E+01 ( 20.97 s, 8.6 h) <br> iter 529 lrate = 0.0156250000 LL = -0.9389743098 nd = 0.0051683491, D = 0.42496E+01 0.42496E+01 ( 21.00 s, 8.6 h) <br> iter 530 lrate = 0.0156250000 LL = -0.9389723612 nd = 0.0051691785, D = 0.42495E+01 0.42495E+01 ( 20.95 s, 8.6 h) <br> iter 531 lrate = 0.0156250000 LL = -0.9389704091 nd = 0.0051700392, D = 0.42493E+01 0.42493E+01 ( 29.25 s, 11.9 h) <br> iter 532 lrate = 0.0156250000 LL = -0.9389684687 nd = 0.0051709357, D = 0.42491E+01 0.42491E+01 ( 21.19 s, 8.6 h) <br> iter 533 lrate = 0.0156250000 LL = -0.9389665194 nd = 0.0051718708, D = 0.42490E+01 0.42490E+01 ( 21.11 s, 8.6 h) <br> iter 534 lrate = 0.0156250000 LL = -0.9389645688 nd = 0.0051728369, D = 0.42488E+01 0.42488E+01 ( 20.76 s, 8.5 h) <br> iter 535 lrate = 0.0156250000 LL = -0.9389626199 nd = 0.0051738246, D = 0.42487E+01 0.42487E+01 ( 20.85 s, 8.5 h) <br> iter 536 lrate = 0.0156250000 LL = -0.9389606720 nd = 0.0051748145, D = 0.42485E+01 0.42485E+01 ( 20.83 s, 8.5 h) <br> iter 537 lrate = 0.0156250000 LL = -0.9389587237 nd = 0.0051758294, D = 0.42484E+01 0.42484E+01 ( 20.72 s, 8.4 h) <br> iter 538 lrate = 0.0156250000 LL = -0.9389567760 nd = 0.0051768332, D = 0.42482E+01 0.42482E+01 ( 20.90 s, 8.5 h) <br> iter 539 lrate = 0.0156250000 LL = -0.9389548322 nd = 0.0051778243, D = 0.42481E+01 0.42481E+01 ( 20.95 s, 8.5 h) <br> iter 540 lrate = 0.0156250000 LL = -0.9389528884 nd = 0.0051788257, D = 0.42479E+01 0.42479E+01 ( 21.09 s, 8.6 h) <br> iter 541 lrate = 0.0156250000 LL = -0.9389509447 nd = 0.0051798174, D = 0.42478E+01 0.42478E+01 ( 29.05 s, 11.8 h) <br> iter 542 lrate = 0.0156250000 LL = -0.9389490064 nd = 0.0051808045, D = 0.42476E+01 0.42476E+01 ( 20.82 s, 8.4 h) <br> iter 543 lrate = 0.0156250000 LL = -0.9389470712 nd = 0.0051817652, D = 0.42474E+01 0.42474E+01 ( 20.96 s, 8.5 h) <br> iter 544 lrate = 0.0156250000 LL = -0.9389451400 nd = 0.0051826922, D = 0.42473E+01 0.42473E+01 ( 21.13 s, 8.5 h) <br> iter 545 lrate = 0.0156250000 LL = -0.9389432141 nd = 0.0051836258, D = 0.42471E+01 0.42471E+01 ( 20.92 s, 8.5 h) <br> iter 546 lrate = 0.0156250000 LL = -0.9389412909 nd = 0.0051845482, D = 0.42470E+01 0.42470E+01 ( 20.91 s, 8.4 h) <br> iter 547 lrate = 0.0156250000 LL = -0.9389393615 nd = 0.0051854994, D = 0.42468E+01 0.42468E+01 ( 21.20 s, 8.6 h) <br> iter 548 lrate = 0.0156250000 LL = -0.9389374272 nd = 0.0051864205, D = 0.42467E+01 0.42467E+01 ( 20.99 s, 8.5 h) <br> iter 549 lrate = 0.0156250000 LL = -0.9389354938 nd = 0.0051873666, D = 0.42465E+01 0.42465E+01 ( 20.99 s, 8.5 h) <br> iter 550 lrate = 0.0156250000 LL = -0.9389335632 nd = 0.0051883096, D = 0.42464E+01 0.42464E+01 ( 20.92 s, 8.4 h) <br> iter 551 lrate = 0.0156250000 LL = -0.9389316318 nd = 0.0051892554, D = 0.42462E+01 0.42462E+01 ( 29.10 s, 11.7 h) <br> iter 552 lrate = 0.0156250000 LL = -0.9389297059 nd = 0.0051902016, D = 0.42461E+01 0.42461E+01 ( 21.09 s, 8.5 h) <br> iter 553 lrate = 0.0156250000 LL = -0.9389277820 nd = 0.0051911541, D = 0.42459E+01 0.42459E+01 ( 21.03 s, 8.5 h) <br> iter 554 lrate = 0.0156250000 LL = -0.9389258602 nd = 0.0051920863, D = 0.42458E+01 0.42458E+01 ( 21.14 s, 8.5 h) <br> iter 555 lrate = 0.0156250000 LL = -0.9389239350 nd = 0.0051930028, D = 0.42456E+01 0.42456E+01 ( 20.93 s, 8.4 h) <br> iter 556 lrate = 0.0156250000 LL = -0.9389220087 nd = 0.0051939006, D = 0.42454E+01 0.42454E+01 ( 20.83 s, 8.4 h) <br> iter 557 lrate = 0.0156250000 LL = -0.9389200835 nd = 0.0051947711, D = 0.42453E+01 0.42453E+01 ( 21.16 s, 8.5 h) <br> iter 558 lrate = 0.0156250000 LL = -0.9389181689 nd = 0.0051956345, D = 0.42451E+01 0.42451E+01 ( 21.04 s, 8.4 h) <br> iter 559 lrate = 0.0156250000 LL = -0.9389162464 nd = 0.0051964496, D = 0.42450E+01 0.42450E+01 ( 20.60 s, 8.2 h) <br> iter 560 lrate = 0.0156250000 LL = -0.9389143274 nd = 0.0051972440, D = 0.42448E+01 0.42448E+01 ( 20.88 s, 8.4 h) <br> iter 561 lrate = 0.0156250000 LL = -0.9389124126 nd = 0.0051979837, D = 0.42447E+01 0.42447E+01 ( 29.42 s, 11.8 h) <br> iter 562 lrate = 0.0156250000 LL = -0.9389104961 nd = 0.0051986994, D = 0.42445E+01 0.42445E+01 ( 20.92 s, 8.4 h) <br> iter 563 lrate = 0.0156250000 LL = -0.9389085873 nd = 0.0051993690, D = 0.42444E+01 0.42444E+01 ( 21.24 s, 8.5 h) <br> iter 564 lrate = 0.0156250000 LL = -0.9389066806 nd = 0.0052000166, D = 0.42442E+01 0.42442E+01 ( 21.15 s, 8.4 h) <br> iter 565 lrate = 0.0156250000 LL = -0.9389047674 nd = 0.0052006452, D = 0.42441E+01 0.42441E+01 ( 21.03 s, 8.4 h) <br> iter 566 lrate = 0.0156250000 LL = -0.9389028597 nd = 0.0052012430, D = 0.42439E+01 0.42439E+01 ( 20.96 s, 8.3 h) <br> iter 567 lrate = 0.0156250000 LL = -0.9389009605 nd = 0.0052018275, D = 0.42438E+01 0.42438E+01 ( 21.05 s, 8.4 h) <br> iter 568 lrate = 0.0156250000 LL = -0.9388990554 nd = 0.0052024160, D = 0.42436E+01 0.42436E+01 ( 21.04 s, 8.4 h) <br> iter 569 lrate = 0.0156250000 LL = -0.9388971502 nd = 0.0052030155, D = 0.42434E+01 0.42434E+01 ( 20.73 s, 8.2 h) <br> iter 570 lrate = 0.0156250000 LL = -0.9388952464 nd = 0.0052036343, D = 0.42433E+01 0.42433E+01 ( 20.73 s, 8.2 h) <br> iter 571 lrate = 0.0156250000 LL = -0.9388933439 nd = 0.0052042744, D = 0.42431E+01 0.42431E+01 ( 29.25 s, 11.6 h) <br> iter 572 lrate = 0.0156250000 LL = -0.9388914425 nd = 0.0052049522, D = 0.42430E+01 0.42430E+01 ( 20.97 s, 8.3 h) <br> iter 573 lrate = 0.0156250000 LL = -0.9388895416 nd = 0.0052056461, D = 0.42428E+01 0.42428E+01 ( 21.05 s, 8.3 h) <br> iter 574 lrate = 0.0156250000 LL = -0.9388876352 nd = 0.0052063594, D = 0.42427E+01 0.42427E+01 ( 20.95 s, 8.3 h) <br> iter 575 lrate = 0.0156250000 LL = -0.9388857319 nd = 0.0052071002, D = 0.42425E+01 0.42425E+01 ( 21.05 s, 8.3 h) <br> iter 576 lrate = 0.0156250000 LL = -0.9388838280 nd = 0.0052078642, D = 0.42424E+01 0.42424E+01 ( 21.26 s, 8.4 h) <br> iter 577 lrate = 0.0156250000 LL = -0.9388819247 nd = 0.0052086164, D = 0.42422E+01 0.42422E+01 ( 20.75 s, 8.2 h) <br> iter 578 lrate = 0.0156250000 LL = -0.9388800235 nd = 0.0052093929, D = 0.42421E+01 0.42421E+01 ( 20.71 s, 8.2 h) <br> iter 579 lrate = 0.0156250000 LL = -0.9388781174 nd = 0.0052101933, D = 0.42419E+01 0.42419E+01 ( 21.25 s, 8.4 h) <br> iter 580 lrate = 0.0156250000 LL = -0.9388762156 nd = 0.0052109803, D = 0.42418E+01 0.42418E+01 ( 21.10 s, 8.3 h) <br> iter 581 lrate = 0.0156250000 LL = -0.9388743154 nd = 0.0052117311, D = 0.42416E+01 0.42416E+01 ( 29.34 s, 11.6 h) <br> iter 582 lrate = 0.0156250000 LL = -0.9388724205 nd = 0.0052124779, D = 0.42415E+01 0.42415E+01 ( 21.02 s, 8.3 h) <br> iter 583 lrate = 0.0156250000 LL = -0.9388705220 nd = 0.0052132290, D = 0.42413E+01 0.42413E+01 ( 21.02 s, 8.3 h) <br> iter 584 lrate = 0.0156250000 LL = -0.9388686313 nd = 0.0052139419, D = 0.42412E+01 0.42412E+01 ( 21.04 s, 8.3 h) <br> iter 585 lrate = 0.0156250000 LL = -0.9388667311 nd = 0.0052146352, D = 0.42410E+01 0.42410E+01 ( 21.18 s, 8.3 h) <br> iter 586 lrate = 0.0156250000 LL = -0.9388648356 nd = 0.0052153205, D = 0.42409E+01 0.42409E+01 ( 21.07 s, 8.3 h) <br> iter 587 lrate = 0.0156250000 LL = -0.9388629477 nd = 0.0052159513, D = 0.42407E+01 0.42407E+01 ( 20.97 s, 8.2 h) <br> iter 588 lrate = 0.0156250000 LL = -0.9388610570 nd = 0.0052165725, D = 0.42405E+01 0.42405E+01 ( 20.79 s, 8.2 h) <br> iter 589 lrate = 0.0156250000 LL = -0.9388591671 nd = 0.0052171648, D = 0.42404E+01 0.42404E+01 ( 20.83 s, 8.2 h) <br> iter 590 lrate = 0.0156250000 LL = -0.9388572817 nd = 0.0052177358, D = 0.42402E+01 0.42402E+01 ( 21.06 s, 8.2 h) <br> iter 591 lrate = 0.0156250000 LL = -0.9388554057 nd = 0.0052182872, D = 0.42401E+01 0.42401E+01 ( 29.43 s, 11.5 h) <br> iter 592 lrate = 0.0156250000 LL = -0.9388535271 nd = 0.0052188173, D = 0.42399E+01 0.42399E+01 ( 21.17 s, 8.3 h) <br> iter 593 lrate = 0.0156250000 LL = -0.9388516449 nd = 0.0052193322, D = 0.42398E+01 0.42398E+01 ( 21.00 s, 8.2 h) <br> iter 594 lrate = 0.0156250000 LL = -0.9388497666 nd = 0.0052198488, D = 0.42396E+01 0.42396E+01 ( 20.80 s, 8.1 h) <br> iter 595 lrate = 0.0156250000 LL = -0.9388478884 nd = 0.0052203420, D = 0.42395E+01 0.42395E+01 ( 20.99 s, 8.2 h) <br> iter 596 lrate = 0.0156250000 LL = -0.9388460094 nd = 0.0052208312, D = 0.42393E+01 0.42393E+01 ( 21.00 s, 8.2 h) <br> iter 597 lrate = 0.0156250000 LL = -0.9388441276 nd = 0.0052212941, D = 0.42392E+01 0.42392E+01 ( 21.08 s, 8.2 h) <br> iter 598 lrate = 0.0156250000 LL = -0.9388422509 nd = 0.0052217552, D = 0.42390E+01 0.42390E+01 ( 20.95 s, 8.2 h) <br> iter 599 lrate = 0.0156250000 LL = -0.9388403778 nd = 0.0052222191, D = 0.42389E+01 0.42389E+01 ( 20.69 s, 8.1 h) <br> iter 600 lrate = 0.0156250000 LL = -0.9388385040 nd = 0.0052226755, D = 0.42387E+01 0.42387E+01 ( 20.89 s, 8.1 h) <br> iter 601 lrate = 0.0156250000 LL = -0.9389353089 nd = 0.0053385079, D = 0.42387E+01 0.42387E+01 ( 29.10 s, 11.3 h) <br> Likelihood decreasing! <br> iter 602 lrate = 0.0078125000 LL = -0.9389351211 nd = 0.0053396370, D = 0.42387E+01 0.42387E+01 ( 20.59 s, 8.0 h) <br> iter 603 lrate = 0.0078125000 LL = -0.9389349319 nd = 0.0053400339, D = 0.42387E+01 0.42387E+01 ( 20.81 s, 8.1 h) <br> iter 604 lrate = 0.0078125000 LL = -0.9389347433 nd = 0.0053400957, D = 0.42387E+01 0.42387E+01 ( 20.81 s, 8.1 h) <br> iter 605 lrate = 0.0078125000 LL = -0.9389345590 nd = 0.0053399754, D = 0.42387E+01 0.42387E+01 ( 21.10 s, 8.2 h) <br> iter 606 lrate = 0.0078125000 LL = -0.9389343809 nd = 0.0053397915, D = 0.42387E+01 0.42387E+01 ( 20.63 s, 8.0 h) <br> iter 607 lrate = 0.0156250000 LL = -0.9388333923 nd = 0.0052212687, D = 0.42386E+01 0.42386E+01 ( 20.99 s, 8.1 h) <br> iter 608 lrate = 0.0156250000 LL = -0.9388336961 nd = 0.0052233359, D = 0.42384E+01 0.42384E+01 ( 21.02 s, 8.1 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 609 lrate = 0.0078125000 LL = -0.9388810632 nd = 0.0052812839, D = 0.42383E+01 0.42383E+01 ( 20.87 s, 8.1 h) <br> Likelihood decreasing! <br> iter 610 lrate = 0.0078125000 LL = -0.9388795217 nd = 0.0052811130, D = 0.42383E+01 0.42383E+01 ( 21.02 s, 8.1 h) <br> iter 611 lrate = 0.0078125000 LL = -0.9388785198 nd = 0.0052814722, D = 0.42382E+01 0.42382E+01 ( 29.38 s, 11.3 h) <br> iter 612 lrate = 0.0078125000 LL = -0.9388775163 nd = 0.0052817391, D = 0.42381E+01 0.42381E+01 ( 20.98 s, 8.1 h) <br> iter 613 lrate = 0.0078125000 LL = -0.9388765152 nd = 0.0052819618, D = 0.42380E+01 0.42380E+01 ( 20.77 s, 8.0 h) <br> iter 614 lrate = 0.0078125000 LL = -0.9388755124 nd = 0.0052821709, D = 0.42380E+01 0.42380E+01 ( 21.03 s, 8.1 h) <br> iter 615 lrate = 0.0078125000 LL = -0.9388745163 nd = 0.0052823732, D = 0.42379E+01 0.42379E+01 ( 21.14 s, 8.1 h) <br> iter 616 lrate = 0.0078125000 LL = -0.9388735116 nd = 0.0052825701, D = 0.42378E+01 0.42378E+01 ( 21.15 s, 8.1 h) <br> iter 617 lrate = 0.0078125000 LL = -0.9388725086 nd = 0.0052827782, D = 0.42377E+01 0.42377E+01 ( 21.08 s, 8.1 h) <br> iter 618 lrate = 0.0078125000 LL = -0.9388715089 nd = 0.0052829902, D = 0.42377E+01 0.42377E+01 ( 21.23 s, 8.1 h) <br> iter 619 lrate = 0.0078125000 LL = -0.9388705039 nd = 0.0052832022, D = 0.42376E+01 0.42376E+01 ( 20.79 s, 8.0 h) <br> iter 620 lrate = 0.0078125000 LL = -0.9388695021 nd = 0.0052834156, D = 0.42375E+01 0.42375E+01 ( 20.94 s, 8.0 h) <br> iter 621 lrate = 0.0078125000 LL = -0.9388685015 nd = 0.0052836382, D = 0.42374E+01 0.42374E+01 ( 28.97 s, 11.1 h) <br> iter 622 lrate = 0.0078125000 LL = -0.9388675047 nd = 0.0052838633, D = 0.42374E+01 0.42374E+01 ( 20.69 s, 7.9 h) <br> iter 623 lrate = 0.0078125000 LL = -0.9388665085 nd = 0.0052840989, D = 0.42373E+01 0.42373E+01 ( 20.92 s, 8.0 h) <br> iter 624 lrate = 0.0078125000 LL = -0.9388655069 nd = 0.0052843404, D = 0.42372E+01 0.42372E+01 ( 21.08 s, 8.1 h) <br> iter 625 lrate = 0.0078125000 LL = -0.9388645034 nd = 0.0052845837, D = 0.42371E+01 0.42371E+01 ( 20.99 s, 8.0 h) <br> iter 626 lrate = 0.0078125000 LL = -0.9388635164 nd = 0.0052848255, D = 0.42371E+01 0.42371E+01 ( 21.16 s, 8.1 h) <br> iter 627 lrate = 0.0078125000 LL = -0.9388625164 nd = 0.0052850771, D = 0.42370E+01 0.42370E+01 ( 20.88 s, 8.0 h) <br> iter 628 lrate = 0.0078125000 LL = -0.9388615182 nd = 0.0052853378, D = 0.42369E+01 0.42369E+01 ( 20.84 s, 7.9 h) <br> iter 629 lrate = 0.0078125000 LL = -0.9388605192 nd = 0.0052855969, D = 0.42368E+01 0.42368E+01 ( 20.88 s, 8.0 h) <br> iter 630 lrate = 0.0078125000 LL = -0.9388595198 nd = 0.0052858594, D = 0.42368E+01 0.42368E+01 ( 21.17 s, 8.1 h) <br> iter 631 lrate = 0.0078125000 LL = -0.9388585260 nd = 0.0052861248, D = 0.42367E+01 0.42367E+01 ( 29.41 s, 11.2 h) <br> iter 632 lrate = 0.0078125000 LL = -0.9388575236 nd = 0.0052863894, D = 0.42366E+01 0.42366E+01 ( 20.74 s, 7.9 h) <br> iter 633 lrate = 0.0078125000 LL = -0.9388565295 nd = 0.0052866605, D = 0.42365E+01 0.42365E+01 ( 21.01 s, 8.0 h) <br> iter 634 lrate = 0.0078125000 LL = -0.9388555316 nd = 0.0052869299, D = 0.42365E+01 0.42365E+01 ( 20.71 s, 7.9 h) <br> iter 635 lrate = 0.0078125000 LL = -0.9388545372 nd = 0.0052872045, D = 0.42364E+01 0.42364E+01 ( 20.89 s, 7.9 h) <br> iter 636 lrate = 0.0078125000 LL = -0.9388535382 nd = 0.0052874798, D = 0.42363E+01 0.42363E+01 ( 21.06 s, 8.0 h) <br> iter 637 lrate = 0.0078125000 LL = -0.9388525413 nd = 0.0052877549, D = 0.42362E+01 0.42362E+01 ( 20.99 s, 7.9 h) <br> iter 638 lrate = 0.0078125000 LL = -0.9388515438 nd = 0.0052880336, D = 0.42362E+01 0.42362E+01 ( 20.86 s, 7.9 h) <br> iter 639 lrate = 0.0078125000 LL = -0.9388505518 nd = 0.0052883143, D = 0.42361E+01 0.42361E+01 ( 21.17 s, 8.0 h) <br> iter 640 lrate = 0.0078125000 LL = -0.9388495626 nd = 0.0052885981, D = 0.42360E+01 0.42360E+01 ( 21.05 s, 8.0 h) <br> iter 641 lrate = 0.0078125000 LL = -0.9388485663 nd = 0.0052888758, D = 0.42359E+01 0.42359E+01 ( 29.17 s, 11.0 h) <br> iter 642 lrate = 0.0078125000 LL = -0.9388475734 nd = 0.0052891553, D = 0.42359E+01 0.42359E+01 ( 21.12 s, 8.0 h) <br> iter 643 lrate = 0.0078125000 LL = -0.9388465784 nd = 0.0052894445, D = 0.42358E+01 0.42358E+01 ( 21.10 s, 8.0 h) <br> iter 644 lrate = 0.0078125000 LL = -0.9388455907 nd = 0.0052897231, D = 0.42357E+01 0.42357E+01 ( 21.24 s, 8.0 h) <br> iter 645 lrate = 0.0078125000 LL = -0.9388446082 nd = 0.0052900003, D = 0.42356E+01 0.42356E+01 ( 21.22 s, 8.0 h) <br> iter 646 lrate = 0.0078125000 LL = -0.9388436148 nd = 0.0052902805, D = 0.42356E+01 0.42356E+01 ( 20.72 s, 7.8 h) <br> iter 647 lrate = 0.0078125000 LL = -0.9388426270 nd = 0.0052905696, D = 0.42355E+01 0.42355E+01 ( 20.96 s, 7.9 h) <br> iter 648 lrate = 0.0078125000 LL = -0.9388416328 nd = 0.0052908437, D = 0.42354E+01 0.42354E+01 ( 21.13 s, 7.9 h) <br> iter 649 lrate = 0.0078125000 LL = -0.9388406578 nd = 0.0052911201, D = 0.42353E+01 0.42353E+01 ( 21.00 s, 7.9 h) <br> iter 650 lrate = 0.0078125000 LL = -0.9388396656 nd = 0.0052913945, D = 0.42353E+01 0.42353E+01 ( 21.17 s, 7.9 h) <br> iter 651 lrate = 0.0078125000 LL = -0.9388386761 nd = 0.0052916699, D = 0.42352E+01 0.42352E+01 ( 28.90 s, 10.8 h) <br> iter 652 lrate = 0.0078125000 LL = -0.9388376870 nd = 0.0052919427, D = 0.42351E+01 0.42351E+01 ( 20.90 s, 7.8 h) <br> iter 653 lrate = 0.0078125000 LL = -0.9388366991 nd = 0.0052922229, D = 0.42351E+01 0.42351E+01 ( 20.73 s, 7.8 h) <br> iter 654 lrate = 0.0078125000 LL = -0.9388357121 nd = 0.0052924919, D = 0.42350E+01 0.42350E+01 ( 21.39 s, 8.0 h) <br> iter 655 lrate = 0.0078125000 LL = -0.9388347201 nd = 0.0052927562, D = 0.42349E+01 0.42349E+01 ( 20.87 s, 7.8 h) <br> iter 656 lrate = 0.0078125000 LL = -0.9388337315 nd = 0.0052930227, D = 0.42348E+01 0.42348E+01 ( 21.23 s, 7.9 h) <br> iter 657 lrate = 0.0078125000 LL = -0.9388327401 nd = 0.0052932817, D = 0.42348E+01 0.42348E+01 ( 20.86 s, 7.8 h) <br> iter 658 lrate = 0.0078125000 LL = -0.9388317526 nd = 0.0052935411, D = 0.42347E+01 0.42347E+01 ( 21.11 s, 7.9 h) <br> iter 659 lrate = 0.0078125000 LL = -0.9388307620 nd = 0.0052937985, D = 0.42346E+01 0.42346E+01 ( 20.90 s, 7.8 h) <br> iter 660 lrate = 0.0078125000 LL = -0.9388297712 nd = 0.0052940607, D = 0.42345E+01 0.42345E+01 ( 21.32 s, 7.9 h) <br> iter 661 lrate = 0.0078125000 LL = -0.9388287817 nd = 0.0052943128, D = 0.42345E+01 0.42345E+01 ( 29.01 s, 10.8 h) <br> iter 662 lrate = 0.0078125000 LL = -0.9388277935 nd = 0.0052945742, D = 0.42344E+01 0.42344E+01 ( 21.08 s, 7.8 h) <br> iter 663 lrate = 0.0078125000 LL = -0.9388268069 nd = 0.0052948237, D = 0.42343E+01 0.42343E+01 ( 20.90 s, 7.8 h) <br> iter 664 lrate = 0.0078125000 LL = -0.9388258175 nd = 0.0052950672, D = 0.42342E+01 0.42342E+01 ( 20.96 s, 7.8 h) <br> iter 665 lrate = 0.0078125000 LL = -0.9388248344 nd = 0.0052953074, D = 0.42342E+01 0.42342E+01 ( 21.14 s, 7.8 h) <br> iter 666 lrate = 0.0078125000 LL = -0.9388238491 nd = 0.0052955533, D = 0.42341E+01 0.42341E+01 ( 20.96 s, 7.8 h) <br> iter 667 lrate = 0.0078125000 LL = -0.9388228634 nd = 0.0052957946, D = 0.42340E+01 0.42340E+01 ( 21.12 s, 7.8 h) <br> iter 668 lrate = 0.0078125000 LL = -0.9388218791 nd = 0.0052960292, D = 0.42339E+01 0.42339E+01 ( 20.98 s, 7.8 h) <br> iter 669 lrate = 0.0078125000 LL = -0.9388208929 nd = 0.0052962612, D = 0.42339E+01 0.42339E+01 ( 20.82 s, 7.7 h) <br> iter 670 lrate = 0.0078125000 LL = -0.9388199079 nd = 0.0052965029, D = 0.42338E+01 0.42338E+01 ( 21.03 s, 7.8 h) <br> iter 671 lrate = 0.0078125000 LL = -0.9388189204 nd = 0.0052967285, D = 0.42337E+01 0.42337E+01 ( 28.98 s, 10.7 h) <br> iter 672 lrate = 0.0078125000 LL = -0.9388179484 nd = 0.0052969556, D = 0.42336E+01 0.42336E+01 ( 20.77 s, 7.7 h) <br> iter 673 lrate = 0.0078125000 LL = -0.9388169672 nd = 0.0052971788, D = 0.42336E+01 0.42336E+01 ( 21.07 s, 7.8 h) <br> iter 674 lrate = 0.0078125000 LL = -0.9388159883 nd = 0.0052974013, D = 0.42335E+01 0.42335E+01 ( 21.07 s, 7.8 h) <br> iter 675 lrate = 0.0078125000 LL = -0.9388150055 nd = 0.0052976187, D = 0.42334E+01 0.42334E+01 ( 20.91 s, 7.7 h) <br> iter 676 lrate = 0.0078125000 LL = -0.9388140322 nd = 0.0052978361, D = 0.42333E+01 0.42333E+01 ( 20.74 s, 7.6 h) <br> iter 677 lrate = 0.0078125000 LL = -0.9388130540 nd = 0.0052980517, D = 0.42333E+01 0.42333E+01 ( 21.05 s, 7.7 h) <br> iter 678 lrate = 0.0078125000 LL = -0.9388120713 nd = 0.0052982729, D = 0.42332E+01 0.42332E+01 ( 20.69 s, 7.6 h) <br> iter 679 lrate = 0.0078125000 LL = -0.9388110888 nd = 0.0052984785, D = 0.42331E+01 0.42331E+01 ( 20.77 s, 7.6 h) <br> iter 680 lrate = 0.0078125000 LL = -0.9388101139 nd = 0.0052986902, D = 0.42331E+01 0.42331E+01 ( 20.99 s, 7.7 h) <br> iter 681 lrate = 0.0078125000 LL = -0.9388091391 nd = 0.0052988966, D = 0.42330E+01 0.42330E+01 ( 29.41 s, 10.8 h) <br> iter 682 lrate = 0.0078125000 LL = -0.9388081676 nd = 0.0052991110, D = 0.42329E+01 0.42329E+01 ( 20.93 s, 7.7 h) <br> iter 683 lrate = 0.0078125000 LL = -0.9388071877 nd = 0.0052993084, D = 0.42328E+01 0.42328E+01 ( 21.04 s, 7.7 h) <br> iter 684 lrate = 0.0078125000 LL = -0.9388062078 nd = 0.0052995092, D = 0.42328E+01 0.42328E+01 ( 21.00 s, 7.7 h) <br> iter 685 lrate = 0.0078125000 LL = -0.9388052256 nd = 0.0052997087, D = 0.42327E+01 0.42327E+01 ( 21.03 s, 7.7 h) <br> iter 686 lrate = 0.0078125000 LL = -0.9388042529 nd = 0.0052999061, D = 0.42326E+01 0.42326E+01 ( 20.80 s, 7.6 h) <br> iter 687 lrate = 0.0078125000 LL = -0.9388032748 nd = 0.0053001123, D = 0.42325E+01 0.42325E+01 ( 21.05 s, 7.7 h) <br> iter 688 lrate = 0.0078125000 LL = -0.9388022945 nd = 0.0053003083, D = 0.42325E+01 0.42325E+01 ( 20.60 s, 7.5 h) <br> iter 689 lrate = 0.0078125000 LL = -0.9388013158 nd = 0.0053005142, D = 0.42324E+01 0.42324E+01 ( 20.89 s, 7.6 h) <br> iter 690 lrate = 0.0078125000 LL = -0.9388003462 nd = 0.0053007065, D = 0.42323E+01 0.42323E+01 ( 20.75 s, 7.6 h) <br> iter 691 lrate = 0.0078125000 LL = -0.9387993673 nd = 0.0053008964, D = 0.42322E+01 0.42322E+01 ( 28.98 s, 10.5 h) <br> iter 692 lrate = 0.0078125000 LL = -0.9387983926 nd = 0.0053010805, D = 0.42322E+01 0.42322E+01 ( 21.02 s, 7.6 h) <br> iter 693 lrate = 0.0078125000 LL = -0.9387974183 nd = 0.0053012669, D = 0.42321E+01 0.42321E+01 ( 21.29 s, 7.7 h) <br> iter 694 lrate = 0.0078125000 LL = -0.9387964439 nd = 0.0053014507, D = 0.42320E+01 0.42320E+01 ( 20.98 s, 7.6 h) <br> iter 695 lrate = 0.0078125000 LL = -0.9387954756 nd = 0.0053016409, D = 0.42319E+01 0.42319E+01 ( 20.99 s, 7.6 h) <br> iter 696 lrate = 0.0078125000 LL = -0.9387945040 nd = 0.0053018262, D = 0.42319E+01 0.42319E+01 ( 21.02 s, 7.6 h) <br> iter 697 lrate = 0.0078125000 LL = -0.9387935313 nd = 0.0053020153, D = 0.42318E+01 0.42318E+01 ( 21.21 s, 7.7 h) <br> iter 698 lrate = 0.0078125000 LL = -0.9387925642 nd = 0.0053021989, D = 0.42317E+01 0.42317E+01 ( 20.68 s, 7.5 h) <br> iter 699 lrate = 0.0078125000 LL = -0.9387915953 nd = 0.0053023879, D = 0.42317E+01 0.42317E+01 ( 21.17 s, 7.7 h) <br> iter 700 lrate = 0.0078125000 LL = -0.9387906219 nd = 0.0053025774, D = 0.42316E+01 0.42316E+01 ( 21.00 s, 7.6 h) <br> iter 701 lrate = 0.0078125000 LL = -0.9388397918 nd = 0.0053606321, D = 0.42316E+01 0.42316E+01 ( 29.24 s, 10.6 h) <br> Likelihood decreasing! <br> iter 702 lrate = 0.0039062500 LL = -0.9388396367 nd = 0.0053611965, D = 0.42316E+01 0.42316E+01 ( 20.94 s, 7.5 h) <br> iter 703 lrate = 0.0039062500 LL = -0.9388394816 nd = 0.0053614037, D = 0.42316E+01 0.42316E+01 ( 20.90 s, 7.5 h) <br> iter 704 lrate = 0.0039062500 LL = -0.9388393260 nd = 0.0053614429, D = 0.42316E+01 0.42316E+01 ( 20.97 s, 7.5 h) <br> iter 705 lrate = 0.0039062500 LL = -0.9388391770 nd = 0.0053613929, D = 0.42316E+01 0.42316E+01 ( 21.04 s, 7.6 h) <br> iter 706 lrate = 0.0039062500 LL = -0.9388390267 nd = 0.0053612977, D = 0.42316E+01 0.42316E+01 ( 21.16 s, 7.6 h) <br> iter 707 lrate = 0.0078125000 LL = -0.9387881836 nd = 0.0053025911, D = 0.42315E+01 0.42315E+01 ( 20.83 s, 7.5 h) <br> iter 708 lrate = 0.0078125000 LL = -0.9387877560 nd = 0.0053028066, D = 0.42314E+01 0.42314E+01 ( 20.88 s, 7.5 h) <br> iter 709 lrate = 0.0078125000 LL = -0.9387867920 nd = 0.0053026776, D = 0.42314E+01 0.42314E+01 ( 20.96 s, 7.5 h) <br> iter 710 lrate = 0.0078125000 LL = -0.9387858256 nd = 0.0053027353, D = 0.42313E+01 0.42313E+01 ( 20.83 s, 7.5 h) <br> iter 711 lrate = 0.0078125000 LL = -0.9387848589 nd = 0.0053028853, D = 0.42312E+01 0.42312E+01 ( 29.76 s, 10.7 h) <br> iter 712 lrate = 0.0078125000 LL = -0.9387838890 nd = 0.0053030779, D = 0.42311E+01 0.42311E+01 ( 21.03 s, 7.5 h) <br> iter 713 lrate = 0.0078125000 LL = -0.9387829196 nd = 0.0053032910, D = 0.42311E+01 0.42311E+01 ( 20.99 s, 7.5 h) <br> iter 714 lrate = 0.0078125000 LL = -0.9387819511 nd = 0.0053035120, D = 0.42310E+01 0.42310E+01 ( 20.93 s, 7.5 h) <br> iter 715 lrate = 0.0078125000 LL = -0.9387809792 nd = 0.0053037350, D = 0.42309E+01 0.42309E+01 ( 20.83 s, 7.4 h) <br> iter 716 lrate = 0.0078125000 LL = -0.9387800185 nd = 0.0053039590, D = 0.42308E+01 0.42308E+01 ( 20.85 s, 7.4 h) <br> iter 717 lrate = 0.0078125000 LL = -0.9387790512 nd = 0.0053041787, D = 0.42308E+01 0.42308E+01 ( 20.98 s, 7.5 h) <br> iter 718 lrate = 0.0078125000 LL = -0.9387780892 nd = 0.0053044070, D = 0.42307E+01 0.42307E+01 ( 20.66 s, 7.4 h) <br> iter 719 lrate = 0.0078125000 LL = -0.9387771291 nd = 0.0053046172, D = 0.42306E+01 0.42306E+01 ( 20.92 s, 7.4 h) <br> iter 720 lrate = 0.0078125000 LL = -0.9387761597 nd = 0.0053048317, D = 0.42306E+01 0.42306E+01 ( 20.88 s, 7.4 h) <br> iter 721 lrate = 0.0078125000 LL = -0.9387751916 nd = 0.0053050314, D = 0.42305E+01 0.42305E+01 ( 29.25 s, 10.4 h) <br> iter 722 lrate = 0.0078125000 LL = -0.9387742300 nd = 0.0053052297, D = 0.42304E+01 0.42304E+01 ( 21.34 s, 7.6 h) <br> iter 723 lrate = 0.0078125000 LL = -0.9387732637 nd = 0.0053054324, D = 0.42303E+01 0.42303E+01 ( 21.07 s, 7.5 h) <br> iter 724 lrate = 0.0078125000 LL = -0.9387722998 nd = 0.0053056277, D = 0.42303E+01 0.42303E+01 ( 21.00 s, 7.4 h) <br> iter 725 lrate = 0.0078125000 LL = -0.9387713363 nd = 0.0053058316, D = 0.42302E+01 0.42302E+01 ( 20.73 s, 7.3 h) <br> iter 726 lrate = 0.0078125000 LL = -0.9387703722 nd = 0.0053060231, D = 0.42301E+01 0.42301E+01 ( 21.09 s, 7.5 h) <br> iter 727 lrate = 0.0078125000 LL = -0.9387694056 nd = 0.0053062082, D = 0.42300E+01 0.42300E+01 ( 21.13 s, 7.5 h) <br> iter 728 lrate = 0.0078125000 LL = -0.9387684409 nd = 0.0053063942, D = 0.42300E+01 0.42300E+01 ( 20.98 s, 7.4 h) <br> iter 729 lrate = 0.0078125000 LL = -0.9387674763 nd = 0.0053065933, D = 0.42299E+01 0.42299E+01 ( 21.22 s, 7.5 h) <br> iter 730 lrate = 0.0078125000 LL = -0.9387665123 nd = 0.0053067727, D = 0.42298E+01 0.42298E+01 ( 20.89 s, 7.4 h) <br> iter 731 lrate = 0.0078125000 LL = -0.9387655577 nd = 0.0053069518, D = 0.42298E+01 0.42298E+01 ( 29.41 s, 10.4 h) <br> iter 732 lrate = 0.0078125000 LL = -0.9387645942 nd = 0.0053071340, D = 0.42297E+01 0.42297E+01 ( 20.97 s, 7.4 h) <br> iter 733 lrate = 0.0078125000 LL = -0.9387636324 nd = 0.0053073093, D = 0.42296E+01 0.42296E+01 ( 20.96 s, 7.4 h) <br> iter 734 lrate = 0.0078125000 LL = -0.9387626690 nd = 0.0053074872, D = 0.42295E+01 0.42295E+01 ( 20.71 s, 7.3 h) <br> iter 735 lrate = 0.0078125000 LL = -0.9387617083 nd = 0.0053076617, D = 0.42295E+01 0.42295E+01 ( 20.94 s, 7.4 h) <br> iter 736 lrate = 0.0078125000 LL = -0.9387607557 nd = 0.0053078351, D = 0.42294E+01 0.42294E+01 ( 20.92 s, 7.3 h) <br> iter 737 lrate = 0.0078125000 LL = -0.9387597933 nd = 0.0053080079, D = 0.42293E+01 0.42293E+01 ( 20.66 s, 7.2 h) <br> iter 738 lrate = 0.0078125000 LL = -0.9387588308 nd = 0.0053081802, D = 0.42292E+01 0.42292E+01 ( 20.83 s, 7.3 h) <br> iter 739 lrate = 0.0078125000 LL = -0.9387578773 nd = 0.0053083489, D = 0.42292E+01 0.42292E+01 ( 20.79 s, 7.3 h) <br> iter 740 lrate = 0.0078125000 LL = -0.9387569166 nd = 0.0053085167, D = 0.42291E+01 0.42291E+01 ( 21.25 s, 7.4 h) <br> iter 741 lrate = 0.0078125000 LL = -0.9387559598 nd = 0.0053086844, D = 0.42290E+01 0.42290E+01 ( 29.26 s, 10.2 h) <br> iter 742 lrate = 0.0078125000 LL = -0.9387550063 nd = 0.0053088475, D = 0.42289E+01 0.42289E+01 ( 20.73 s, 7.2 h) <br> iter 743 lrate = 0.0078125000 LL = -0.9387540475 nd = 0.0053090111, D = 0.42289E+01 0.42289E+01 ( 20.66 s, 7.2 h) <br> iter 744 lrate = 0.0078125000 LL = -0.9387530894 nd = 0.0053091728, D = 0.42288E+01 0.42288E+01 ( 21.09 s, 7.4 h) <br> iter 745 lrate = 0.0078125000 LL = -0.9387521298 nd = 0.0053093331, D = 0.42287E+01 0.42287E+01 ( 20.97 s, 7.3 h) <br> iter 746 lrate = 0.0078125000 LL = -0.9387511726 nd = 0.0053094913, D = 0.42287E+01 0.42287E+01 ( 21.05 s, 7.3 h) <br> iter 747 lrate = 0.0078125000 LL = -0.9387502203 nd = 0.0053096487, D = 0.42286E+01 0.42286E+01 ( 20.91 s, 7.3 h) <br> iter 748 lrate = 0.0078125000 LL = -0.9387492617 nd = 0.0053098062, D = 0.42285E+01 0.42285E+01 ( 21.01 s, 7.3 h) <br> iter 749 lrate = 0.0078125000 LL = -0.9387483077 nd = 0.0053099617, D = 0.42284E+01 0.42284E+01 ( 20.76 s, 7.2 h) <br> iter 750 lrate = 0.0078125000 LL = -0.9387473501 nd = 0.0053101149, D = 0.42284E+01 0.42284E+01 ( 20.96 s, 7.3 h) <br> iter 751 lrate = 0.0078125000 LL = -0.9387463945 nd = 0.0053102664, D = 0.42283E+01 0.42283E+01 ( 29.25 s, 10.1 h) <br> iter 752 lrate = 0.0078125000 LL = -0.9387454396 nd = 0.0053104184, D = 0.42282E+01 0.42282E+01 ( 20.95 s, 7.3 h) <br> iter 753 lrate = 0.0078125000 LL = -0.9387444829 nd = 0.0053105697, D = 0.42281E+01 0.42281E+01 ( 21.00 s, 7.3 h) <br> iter 754 lrate = 0.0078125000 LL = -0.9387435300 nd = 0.0053107211, D = 0.42281E+01 0.42281E+01 ( 21.05 s, 7.3 h) <br> iter 755 lrate = 0.0078125000 LL = -0.9387425809 nd = 0.0053108681, D = 0.42280E+01 0.42280E+01 ( 20.97 s, 7.3 h) <br> iter 756 lrate = 0.0078125000 LL = -0.9387416276 nd = 0.0053110135, D = 0.42279E+01 0.42279E+01 ( 20.89 s, 7.2 h) <br> iter 757 lrate = 0.0078125000 LL = -0.9387406727 nd = 0.0053111595, D = 0.42279E+01 0.42279E+01 ( 21.30 s, 7.4 h) <br> iter 758 lrate = 0.0078125000 LL = -0.9387397170 nd = 0.0053113069, D = 0.42278E+01 0.42278E+01 ( 20.81 s, 7.2 h) <br> iter 759 lrate = 0.0078125000 LL = -0.9387387641 nd = 0.0053114458, D = 0.42277E+01 0.42277E+01 ( 20.65 s, 7.1 h) <br> iter 760 lrate = 0.0078125000 LL = -0.9387378081 nd = 0.0053115861, D = 0.42276E+01 0.42276E+01 ( 21.10 s, 7.3 h) <br> iter 761 lrate = 0.0078125000 LL = -0.9387368544 nd = 0.0053117265, D = 0.42276E+01 0.42276E+01 ( 29.39 s, 10.1 h) <br> iter 762 lrate = 0.0078125000 LL = -0.9387359011 nd = 0.0053118652, D = 0.42275E+01 0.42275E+01 ( 21.10 s, 7.3 h) <br> iter 763 lrate = 0.0078125000 LL = -0.9387349475 nd = 0.0053120027, D = 0.42274E+01 0.42274E+01 ( 20.97 s, 7.2 h) <br> iter 764 lrate = 0.0078125000 LL = -0.9387339960 nd = 0.0053121372, D = 0.42273E+01 0.42273E+01 ( 20.70 s, 7.1 h) <br> iter 765 lrate = 0.0078125000 LL = -0.9387330489 nd = 0.0053122727, D = 0.42273E+01 0.42273E+01 ( 20.75 s, 7.1 h) <br> iter 766 lrate = 0.0078125000 LL = -0.9387320950 nd = 0.0053124067, D = 0.42272E+01 0.42272E+01 ( 21.25 s, 7.3 h) <br> iter 767 lrate = 0.0078125000 LL = -0.9387311434 nd = 0.0053125403, D = 0.42271E+01 0.42271E+01 ( 21.02 s, 7.2 h) <br> iter 768 lrate = 0.0078125000 LL = -0.9387301944 nd = 0.0053126697, D = 0.42271E+01 0.42271E+01 ( 20.86 s, 7.1 h) <br> iter 769 lrate = 0.0078125000 LL = -0.9387292433 nd = 0.0053128012, D = 0.42270E+01 0.42270E+01 ( 20.97 s, 7.2 h) <br> iter 770 lrate = 0.0078125000 LL = -0.9387282924 nd = 0.0053129273, D = 0.42269E+01 0.42269E+01 ( 20.89 s, 7.1 h) <br> iter 771 lrate = 0.0078125000 LL = -0.9387273410 nd = 0.0053130539, D = 0.42268E+01 0.42268E+01 ( 29.03 s, 9.9 h) <br> iter 772 lrate = 0.0078125000 LL = -0.9387263885 nd = 0.0053131767, D = 0.42268E+01 0.42268E+01 ( 20.64 s, 7.0 h) <br> iter 773 lrate = 0.0078125000 LL = -0.9387254357 nd = 0.0053132983, D = 0.42267E+01 0.42267E+01 ( 20.68 s, 7.0 h) <br> iter 774 lrate = 0.0078125000 LL = -0.9387244884 nd = 0.0053134125, D = 0.42266E+01 0.42266E+01 ( 21.03 s, 7.2 h) <br> iter 775 lrate = 0.0078125000 LL = -0.9387235344 nd = 0.0053135297, D = 0.42265E+01 0.42265E+01 ( 20.60 s, 7.0 h) <br> iter 776 lrate = 0.0078125000 LL = -0.9387225830 nd = 0.0053136436, D = 0.42265E+01 0.42265E+01 ( 20.96 s, 7.1 h) <br> iter 777 lrate = 0.0078125000 LL = -0.9387216346 nd = 0.0053137602, D = 0.42264E+01 0.42264E+01 ( 21.10 s, 7.2 h) <br> iter 778 lrate = 0.0078125000 LL = -0.9387206839 nd = 0.0053138679, D = 0.42263E+01 0.42263E+01 ( 20.99 s, 7.1 h) <br> iter 779 lrate = 0.0078125000 LL = -0.9387197364 nd = 0.0053139783, D = 0.42263E+01 0.42263E+01 ( 21.11 s, 7.2 h) <br> iter 780 lrate = 0.0078125000 LL = -0.9387187861 nd = 0.0053140821, D = 0.42262E+01 0.42262E+01 ( 20.91 s, 7.1 h) <br> iter 781 lrate = 0.0078125000 LL = -0.9387178405 nd = 0.0053141882, D = 0.42261E+01 0.42261E+01 ( 28.72 s, 9.7 h) <br> iter 782 lrate = 0.0078125000 LL = -0.9387168929 nd = 0.0053142873, D = 0.42260E+01 0.42260E+01 ( 20.65 s, 7.0 h) <br> iter 783 lrate = 0.0078125000 LL = -0.9387159453 nd = 0.0053143870, D = 0.42260E+01 0.42260E+01 ( 20.93 s, 7.1 h) <br> iter 784 lrate = 0.0078125000 LL = -0.9387149978 nd = 0.0053144743, D = 0.42259E+01 0.42259E+01 ( 21.08 s, 7.1 h) <br> iter 785 lrate = 0.0078125000 LL = -0.9387140507 nd = 0.0053145678, D = 0.42258E+01 0.42258E+01 ( 21.12 s, 7.1 h) <br> iter 786 lrate = 0.0078125000 LL = -0.9387131045 nd = 0.0053146582, D = 0.42258E+01 0.42258E+01 ( 20.80 s, 7.0 h) <br> iter 787 lrate = 0.0078125000 LL = -0.9387121587 nd = 0.0053147375, D = 0.42257E+01 0.42257E+01 ( 21.26 s, 7.2 h) <br> iter 788 lrate = 0.0078125000 LL = -0.9387112127 nd = 0.0053148184, D = 0.42256E+01 0.42256E+01 ( 21.17 s, 7.1 h) <br> iter 789 lrate = 0.0078125000 LL = -0.9387102709 nd = 0.0053148987, D = 0.42255E+01 0.42255E+01 ( 20.94 s, 7.0 h) <br> iter 790 lrate = 0.0078125000 LL = -0.9387093279 nd = 0.0053149736, D = 0.42255E+01 0.42255E+01 ( 21.07 s, 7.1 h) <br> iter 791 lrate = 0.0078125000 LL = -0.9387083838 nd = 0.0053150615, D = 0.42254E+01 0.42254E+01 ( 29.30 s, 9.8 h) <br> iter 792 lrate = 0.0078125000 LL = -0.9387074401 nd = 0.0053151262, D = 0.42253E+01 0.42253E+01 ( 21.14 s, 7.1 h) <br> iter 793 lrate = 0.0078125000 LL = -0.9387064971 nd = 0.0053152049, D = 0.42252E+01 0.42252E+01 ( 20.98 s, 7.0 h) <br> iter 794 lrate = 0.0078125000 LL = -0.9387055540 nd = 0.0053152714, D = 0.42252E+01 0.42252E+01 ( 21.06 s, 7.1 h) <br> iter 795 lrate = 0.0078125000 LL = -0.9387046111 nd = 0.0053153424, D = 0.42251E+01 0.42251E+01 ( 20.78 s, 7.0 h) <br> iter 796 lrate = 0.0078125000 LL = -0.9387036688 nd = 0.0053154180, D = 0.42250E+01 0.42250E+01 ( 20.64 s, 6.9 h) <br> iter 797 lrate = 0.0078125000 LL = -0.9387027265 nd = 0.0053154938, D = 0.42250E+01 0.42250E+01 ( 20.65 s, 6.9 h) <br> iter 798 lrate = 0.0078125000 LL = -0.9387017830 nd = 0.0053155712, D = 0.42249E+01 0.42249E+01 ( 21.02 s, 7.0 h) <br> iter 799 lrate = 0.0078125000 LL = -0.9387008420 nd = 0.0053156524, D = 0.42248E+01 0.42248E+01 ( 21.05 s, 7.0 h) <br> iter 800 lrate = 0.0078125000 LL = -0.9386998988 nd = 0.0053157354, D = 0.42247E+01 0.42247E+01 ( 20.98 s, 7.0 h) <br> iter 801 lrate = 0.0078125000 LL = -0.9387492223 nd = 0.0053739101, D = 0.42247E+01 0.42247E+01 ( 28.95 s, 9.6 h) <br> Likelihood decreasing! <br> Reducing maximum Newton lrate <br> iter 802 lrate = 0.0039062500 LL = -0.9387490765 nd = 0.0053744844, D = 0.42247E+01 0.42247E+01 ( 20.95 s, 7.0 h) <br> iter 803 lrate = 0.0039062500 LL = -0.9387489256 nd = 0.0053747038, D = 0.42247E+01 0.42247E+01 ( 20.73 s, 6.9 h) <br> iter 804 lrate = 0.0039062500 LL = -0.9387487781 nd = 0.0053747377, D = 0.42247E+01 0.42247E+01 ( 20.72 s, 6.9 h) <br> iter 805 lrate = 0.0039062500 LL = -0.9387486372 nd = 0.0053746822, D = 0.42247E+01 0.42247E+01 ( 20.83 s, 6.9 h) <br> iter 806 lrate = 0.0039062500 LL = -0.9387484903 nd = 0.0053745887, D = 0.42247E+01 0.42247E+01 ( 21.03 s, 7.0 h) <br> iter 807 lrate = 0.0039062500 LL = -0.9387229261 nd = 0.0053452118, D = 0.42247E+01 0.42247E+01 ( 21.06 s, 7.0 h) <br> iter 808 lrate = 0.0039062500 LL = -0.9387225278 nd = 0.0053450389, D = 0.42247E+01 0.42247E+01 ( 21.25 s, 7.0 h) <br> iter 809 lrate = 0.0039062500 LL = -0.9387219997 nd = 0.0053448767, D = 0.42246E+01 0.42246E+01 ( 21.16 s, 7.0 h) <br> iter 810 lrate = 0.0039062500 LL = -0.9387214667 nd = 0.0053448111, D = 0.42246E+01 0.42246E+01 ( 20.95 s, 6.9 h) <br> iter 811 lrate = 0.0039062500 LL = -0.9387209358 nd = 0.0053447982, D = 0.42246E+01 0.42246E+01 ( 29.21 s, 9.6 h) <br> iter 812 lrate = 0.0039062500 LL = -0.9387204104 nd = 0.0053448169, D = 0.42245E+01 0.42245E+01 ( 20.76 s, 6.9 h) <br> iter 813 lrate = 0.0039062500 LL = -0.9387198771 nd = 0.0053448507, D = 0.42245E+01 0.42245E+01 ( 21.20 s, 7.0 h) <br> iter 814 lrate = 0.0039062500 LL = -0.9387193429 nd = 0.0053448934, D = 0.42245E+01 0.42245E+01 ( 21.09 s, 6.9 h) <br> iter 815 lrate = 0.0039062500 LL = -0.9387188160 nd = 0.0053449427, D = 0.42244E+01 0.42244E+01 ( 21.04 s, 6.9 h) <br> iter 816 lrate = 0.0039062500 LL = -0.9387182842 nd = 0.0053449970, D = 0.42244E+01 0.42244E+01 ( 21.15 s, 7.0 h) <br> iter 817 lrate = 0.0039062500 LL = -0.9387177549 nd = 0.0053450516, D = 0.42243E+01 0.42243E+01 ( 20.95 s, 6.9 h) <br> iter 818 lrate = 0.0039062500 LL = -0.9387172212 nd = 0.0053451097, D = 0.42243E+01 0.42243E+01 ( 21.26 s, 7.0 h) <br> iter 819 lrate = 0.0039062500 LL = -0.9387166870 nd = 0.0053451689, D = 0.42243E+01 0.42243E+01 ( 21.08 s, 6.9 h) <br> iter 820 lrate = 0.0039062500 LL = -0.9387161525 nd = 0.0053452320, D = 0.42242E+01 0.42242E+01 ( 21.08 s, 6.9 h) <br> iter 821 lrate = 0.0039062500 LL = -0.9387156197 nd = 0.0053452958, D = 0.42242E+01 0.42242E+01 ( 29.15 s, 9.5 h) <br> iter 822 lrate = 0.0039062500 LL = -0.9387150841 nd = 0.0053453618, D = 0.42242E+01 0.42242E+01 ( 20.87 s, 6.8 h) <br> iter 823 lrate = 0.0039062500 LL = -0.9387145442 nd = 0.0053454305, D = 0.42241E+01 0.42241E+01 ( 21.01 s, 6.9 h) <br> iter 824 lrate = 0.0039062500 LL = -0.9387140008 nd = 0.0053455015, D = 0.42241E+01 0.42241E+01 ( 21.09 s, 6.9 h) <br> iter 825 lrate = 0.0039062500 LL = -0.9387134610 nd = 0.0053455740, D = 0.42241E+01 0.42241E+01 ( 21.05 s, 6.9 h) <br> iter 826 lrate = 0.0039062500 LL = -0.9387129124 nd = 0.0053456455, D = 0.42240E+01 0.42240E+01 ( 20.99 s, 6.8 h) <br> iter 827 lrate = 0.0039062500 LL = -0.9387123567 nd = 0.0053457185, D = 0.42240E+01 0.42240E+01 ( 20.90 s, 6.8 h) <br> iter 828 lrate = 0.0039062500 LL = -0.9387118159 nd = 0.0053457953, D = 0.42239E+01 0.42239E+01 ( 20.94 s, 6.8 h) <br> iter 829 lrate = 0.0039062500 LL = -0.9387112602 nd = 0.0053458715, D = 0.42239E+01 0.42239E+01 ( 20.76 s, 6.8 h) <br> iter 830 lrate = 0.0039062500 LL = -0.9387106920 nd = 0.0053459491, D = 0.42239E+01 0.42239E+01 ( 21.07 s, 6.8 h) <br> iter 831 lrate = 0.0039062500 LL = -0.9387101084 nd = 0.0053460314, D = 0.42238E+01 0.42238E+01 ( 29.23 s, 9.5 h) <br> iter 832 lrate = 0.0039062500 LL = -0.9387095198 nd = 0.0053461073, D = 0.42238E+01 0.42238E+01 ( 20.86 s, 6.8 h) <br> iter 833 lrate = 0.0039062500 LL = -0.9387089103 nd = 0.0053461850, D = 0.42238E+01 0.42238E+01 ( 20.93 s, 6.8 h) <br> iter 834 lrate = 0.0039062500 LL = -0.9387083138 nd = 0.0053462657, D = 0.42237E+01 0.42237E+01 ( 20.93 s, 6.8 h) <br> iter 835 lrate = 0.0039062500 LL = -0.9387077058 nd = 0.0053463421, D = 0.42237E+01 0.42237E+01 ( 20.91 s, 6.8 h) <br> iter 836 lrate = 0.0039062500 LL = -0.9387071422 nd = 0.0053464267, D = 0.42237E+01 0.42237E+01 ( 21.12 s, 6.8 h) <br> iter 837 lrate = 0.0039062500 LL = -0.9387065760 nd = 0.0053465113, D = 0.42236E+01 0.42236E+01 ( 21.13 s, 6.8 h) <br> iter 838 lrate = 0.0039062500 LL = -0.9387060128 nd = 0.0053465993, D = 0.42236E+01 0.42236E+01 ( 21.11 s, 6.8 h) <br> iter 839 lrate = 0.0039062500 LL = -0.9387054365 nd = 0.0053466823, D = 0.42235E+01 0.42235E+01 ( 20.97 s, 6.8 h) <br> iter 840 lrate = 0.0039062500 LL = -0.9387048898 nd = 0.0053467729, D = 0.42235E+01 0.42235E+01 ( 20.74 s, 6.7 h) <br> iter 841 lrate = 0.0039062500 LL = -0.9387043317 nd = 0.0053468608, D = 0.42235E+01 0.42235E+01 ( 29.23 s, 9.4 h) <br> iter 842 lrate = 0.0039062500 LL = -0.9387037622 nd = 0.0053469480, D = 0.42234E+01 0.42234E+01 ( 20.95 s, 6.7 h) <br> iter 843 lrate = 0.0039062500 LL = -0.9387031852 nd = 0.0053470388, D = 0.42234E+01 0.42234E+01 ( 20.97 s, 6.7 h) <br> iter 844 lrate = 0.0039062500 LL = -0.9387026463 nd = 0.0053471327, D = 0.42234E+01 0.42234E+01 ( 21.04 s, 6.8 h) <br> iter 845 lrate = 0.0039062500 LL = -0.9387020973 nd = 0.0053472195, D = 0.42233E+01 0.42233E+01 ( 20.87 s, 6.7 h) <br> iter 846 lrate = 0.0039062500 LL = -0.9387015260 nd = 0.0053473083, D = 0.42233E+01 0.42233E+01 ( 20.85 s, 6.7 h) <br> iter 847 lrate = 0.0039062500 LL = -0.9387009546 nd = 0.0053474007, D = 0.42233E+01 0.42233E+01 ( 21.09 s, 6.8 h) <br> iter 848 lrate = 0.0039062500 LL = -0.9387003695 nd = 0.0053474928, D = 0.42232E+01 0.42232E+01 ( 20.93 s, 6.7 h) <br> iter 849 lrate = 0.0039062500 LL = -0.9386997862 nd = 0.0053475859, D = 0.42232E+01 0.42232E+01 ( 20.91 s, 6.7 h) <br> iter 850 lrate = 0.0039062500 LL = -0.9386992058 nd = 0.0053476819, D = 0.42232E+01 0.42232E+01 ( 21.12 s, 6.7 h) <br> iter 851 lrate = 0.0039062500 LL = -0.9386986291 nd = 0.0053477787, D = 0.42231E+01 0.42231E+01 ( 29.19 s, 9.3 h) <br> iter 852 lrate = 0.0039062500 LL = -0.9386980395 nd = 0.0053478747, D = 0.42231E+01 0.42231E+01 ( 20.90 s, 6.7 h) <br> iter 853 lrate = 0.0039062500 LL = -0.9386974507 nd = 0.0053479724, D = 0.42230E+01 0.42230E+01 ( 21.05 s, 6.7 h) <br> iter 854 lrate = 0.0039062500 LL = -0.9386968566 nd = 0.0053480705, D = 0.42230E+01 0.42230E+01 ( 20.89 s, 6.7 h) <br> iter 855 lrate = 0.0039062500 LL = -0.9386962646 nd = 0.0053481666, D = 0.42230E+01 0.42230E+01 ( 20.80 s, 6.6 h) <br> iter 856 lrate = 0.0039062500 LL = -0.9386956899 nd = 0.0053482634, D = 0.42229E+01 0.42229E+01 ( 20.98 s, 6.7 h) <br> iter 857 lrate = 0.0039062500 LL = -0.9386950973 nd = 0.0053483661, D = 0.42229E+01 0.42229E+01 ( 21.07 s, 6.7 h) <br> iter 858 lrate = 0.0039062500 LL = -0.9386945073 nd = 0.0053484625, D = 0.42229E+01 0.42229E+01 ( 20.86 s, 6.6 h) <br> iter 859 lrate = 0.0039062500 LL = -0.9386939216 nd = 0.0053485666, D = 0.42228E+01 0.42228E+01 ( 20.69 s, 6.6 h) <br> iter 860 lrate = 0.0039062500 LL = -0.9386933252 nd = 0.0053486610, D = 0.42228E+01 0.42228E+01 ( 20.86 s, 6.6 h) <br> iter 861 lrate = 0.0039062500 LL = -0.9386927398 nd = 0.0053487584, D = 0.42228E+01 0.42228E+01 ( 28.98 s, 9.2 h) <br> iter 862 lrate = 0.0039062500 LL = -0.9386921856 nd = 0.0053488617, D = 0.42227E+01 0.42227E+01 ( 21.05 s, 6.7 h) <br> iter 863 lrate = 0.0039062500 LL = -0.9386916113 nd = 0.0053489549, D = 0.42227E+01 0.42227E+01 ( 20.87 s, 6.6 h) <br> iter 864 lrate = 0.0039062500 LL = -0.9386910440 nd = 0.0053490519, D = 0.42226E+01 0.42226E+01 ( 20.91 s, 6.6 h) <br> iter 865 lrate = 0.0039062500 LL = -0.9386904933 nd = 0.0053491550, D = 0.42226E+01 0.42226E+01 ( 20.90 s, 6.6 h) <br> iter 866 lrate = 0.0039062500 LL = -0.9386899434 nd = 0.0053492494, D = 0.42226E+01 0.42226E+01 ( 21.03 s, 6.6 h) <br> iter 867 lrate = 0.0039062500 LL = -0.9386894061 nd = 0.0053493486, D = 0.42225E+01 0.42225E+01 ( 20.69 s, 6.5 h) <br> iter 868 lrate = 0.0039062500 LL = -0.9386888574 nd = 0.0053494465, D = 0.42225E+01 0.42225E+01 ( 20.97 s, 6.6 h) <br> iter 869 lrate = 0.0039062500 LL = -0.9386883119 nd = 0.0053495482, D = 0.42225E+01 0.42225E+01 ( 21.20 s, 6.7 h) <br> iter 870 lrate = 0.0039062500 LL = -0.9386877793 nd = 0.0053496443, D = 0.42224E+01 0.42224E+01 ( 21.02 s, 6.6 h) <br> iter 871 lrate = 0.0039062500 LL = -0.9386872454 nd = 0.0053497482, D = 0.42224E+01 0.42224E+01 ( 29.10 s, 9.1 h) <br> iter 872 lrate = 0.0039062500 LL = -0.9386867170 nd = 0.0053498458, D = 0.42224E+01 0.42224E+01 ( 21.00 s, 6.6 h) <br> iter 873 lrate = 0.0039062500 LL = -0.9386861830 nd = 0.0053499453, D = 0.42223E+01 0.42223E+01 ( 20.84 s, 6.5 h) <br> iter 874 lrate = 0.0039062500 LL = -0.9386856534 nd = 0.0053500475, D = 0.42223E+01 0.42223E+01 ( 20.93 s, 6.5 h) <br> iter 875 lrate = 0.0039062500 LL = -0.9386851267 nd = 0.0053501457, D = 0.42223E+01 0.42223E+01 ( 21.06 s, 6.6 h) <br> iter 876 lrate = 0.0039062500 LL = -0.9386846013 nd = 0.0053502489, D = 0.42222E+01 0.42222E+01 ( 20.70 s, 6.5 h) <br> iter 877 lrate = 0.0039062500 LL = -0.9386840797 nd = 0.0053503483, D = 0.42222E+01 0.42222E+01 ( 20.84 s, 6.5 h) <br> iter 878 lrate = 0.0039062500 LL = -0.9386835590 nd = 0.0053504510, D = 0.42221E+01 0.42221E+01 ( 21.07 s, 6.6 h) <br> iter 879 lrate = 0.0039062500 LL = -0.9386830376 nd = 0.0053505502, D = 0.42221E+01 0.42221E+01 ( 20.61 s, 6.4 h) <br> iter 880 lrate = 0.0039062500 LL = -0.9386825220 nd = 0.0053506520, D = 0.42221E+01 0.42221E+01 ( 21.15 s, 6.6 h) <br> iter 881 lrate = 0.0039062500 LL = -0.9386820059 nd = 0.0053507507, D = 0.42220E+01 0.42220E+01 ( 29.46 s, 9.2 h) <br> iter 882 lrate = 0.0039062500 LL = -0.9386814917 nd = 0.0053508510, D = 0.42220E+01 0.42220E+01 ( 21.08 s, 6.5 h) <br> iter 883 lrate = 0.0039062500 LL = -0.9386809787 nd = 0.0053509510, D = 0.42220E+01 0.42220E+01 ( 20.92 s, 6.5 h) <br> iter 884 lrate = 0.0039062500 LL = -0.9386804674 nd = 0.0053510585, D = 0.42219E+01 0.42219E+01 ( 20.96 s, 6.5 h) <br> iter 885 lrate = 0.0039062500 LL = -0.9386799580 nd = 0.0053511587, D = 0.42219E+01 0.42219E+01 ( 21.10 s, 6.5 h) <br> iter 886 lrate = 0.0039062500 LL = -0.9386794483 nd = 0.0053512591, D = 0.42219E+01 0.42219E+01 ( 21.17 s, 6.6 h) <br> iter 887 lrate = 0.0039062500 LL = -0.9386789434 nd = 0.0053513573, D = 0.42218E+01 0.42218E+01 ( 20.84 s, 6.4 h) <br> iter 888 lrate = 0.0039062500 LL = -0.9386784404 nd = 0.0053514578, D = 0.42218E+01 0.42218E+01 ( 21.11 s, 6.5 h) <br> iter 889 lrate = 0.0039062500 LL = -0.9386779370 nd = 0.0053515622, D = 0.42217E+01 0.42217E+01 ( 21.19 s, 6.5 h) <br> iter 890 lrate = 0.0039062500 LL = -0.9386774357 nd = 0.0053516619, D = 0.42217E+01 0.42217E+01 ( 21.00 s, 6.5 h) <br> iter 891 lrate = 0.0039062500 LL = -0.9386769358 nd = 0.0053517643, D = 0.42217E+01 0.42217E+01 ( 29.25 s, 9.0 h) <br> iter 892 lrate = 0.0039062500 LL = -0.9386764365 nd = 0.0053518648, D = 0.42216E+01 0.42216E+01 ( 20.95 s, 6.4 h) <br> iter 893 lrate = 0.0039062500 LL = -0.9386759421 nd = 0.0053519679, D = 0.42216E+01 0.42216E+01 ( 21.12 s, 6.5 h) <br> iter 894 lrate = 0.0039062500 LL = -0.9386754473 nd = 0.0053520698, D = 0.42216E+01 0.42216E+01 ( 20.71 s, 6.4 h) <br> iter 895 lrate = 0.0039062500 LL = -0.9386749508 nd = 0.0053521735, D = 0.42215E+01 0.42215E+01 ( 20.67 s, 6.3 h) <br> iter 896 lrate = 0.0039062500 LL = -0.9386744581 nd = 0.0053522734, D = 0.42215E+01 0.42215E+01 ( 21.09 s, 6.5 h) <br> iter 897 lrate = 0.0039062500 LL = -0.9386739643 nd = 0.0053523755, D = 0.42215E+01 0.42215E+01 ( 21.12 s, 6.5 h) <br> iter 898 lrate = 0.0039062500 LL = -0.9386734723 nd = 0.0053524775, D = 0.42214E+01 0.42214E+01 ( 20.91 s, 6.4 h) <br> iter 899 lrate = 0.0039062500 LL = -0.9386729828 nd = 0.0053525798, D = 0.42214E+01 0.42214E+01 ( 21.08 s, 6.4 h) <br> iter 900 lrate = 0.0039062500 LL = -0.9386724929 nd = 0.0053526828, D = 0.42213E+01 0.42213E+01 ( 21.13 s, 6.5 h) <br> iter 901 lrate = 0.0039062500 LL = -0.9386973255 nd = 0.0053817201, D = 0.42213E+01 0.42213E+01 ( 29.24 s, 8.9 h) <br> Likelihood decreasing! <br> iter 902 lrate = 0.0019531250 LL = -0.9386972308 nd = 0.0053820066, D = 0.42213E+01 0.42213E+01 ( 20.80 s, 6.3 h) <br> iter 903 lrate = 0.0019531250 LL = -0.9386971379 nd = 0.0053821167, D = 0.42213E+01 0.42213E+01 ( 21.14 s, 6.4 h) <br> iter 904 lrate = 0.0019531250 LL = -0.9386970454 nd = 0.0053821356, D = 0.42213E+01 0.42213E+01 ( 20.77 s, 6.3 h) <br> iter 905 lrate = 0.0019531250 LL = -0.9386969549 nd = 0.0053821094, D = 0.42213E+01 0.42213E+01 ( 20.83 s, 6.3 h) <br> iter 906 lrate = 0.0019531250 LL = -0.9386968656 nd = 0.0053820647, D = 0.42213E+01 0.42213E+01 ( 20.86 s, 6.3 h) <br> Exiting because likelihood increasing by less than 1.000000011686097E-007 <br> for more than 5 iterations ... <br>... done. Execution time: 5.47 h <br> output directory = C:\tom\MotParEEG\code\amicaouttmp\ <br>>> EEG = eeg_checkset(EEG);<br>eeg_checkset: recomputing the ICA activation matrix ...<br>>> eeglab redraw<br>Warning: for some reason, the backup dataset in EEGLAB memory does not<br> match the current dataset. The dataset in memory has been overwritten<o:p></o:p></span></p></div><div><div id=ecxSkyDrivePlaceholder><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Calibri","sans-serif"'> </span><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><o:p></o:p></span></p></div></div></div></div></div></div></div><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'><br>_______________________________________________ Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html To unsubscribe, send an empty email to eeglablist-unsubscribe@sccn.ucsd.edu For digest mode, send an email with the subject "set digest mime" to eeglablist-request@sccn.ucsd.edu<o:p></o:p></span></p></div></div></div></body></html>