##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       54.267  1.969  56.272
corr_plot     52.664  1.950  54.685
FSmethod      52.177  1.886  54.172
pred_ensembel 16.154  0.353  13.716
enrichfindP    0.501  0.076   9.592
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 101.074099 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.448800 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.863726 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.051691 
iter  10 value 90.582049
iter  20 value 85.812728
iter  30 value 85.287405
iter  40 value 85.278291
final  value 85.278094 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.081295 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.229538 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.168726 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.136376 
iter  10 value 93.992007
final  value 93.976471 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.092918 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.797758 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.412767 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.012404 
iter  10 value 85.374435
iter  20 value 85.224592
final  value 85.220334 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.310606 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.866809 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.296518 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.298829 
iter  10 value 94.054874
iter  20 value 93.545846
iter  30 value 93.489785
iter  40 value 92.660620
iter  50 value 90.398687
iter  60 value 90.189871
iter  70 value 88.874147
iter  80 value 86.542545
iter  90 value 84.834861
iter 100 value 84.358522
final  value 84.358522 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.015616 
iter  10 value 94.056787
iter  20 value 93.223007
iter  30 value 93.065054
iter  40 value 90.051619
iter  50 value 88.727944
iter  60 value 86.878612
iter  70 value 86.301361
iter  80 value 86.151310
iter  90 value 86.098022
iter 100 value 86.066287
final  value 86.066287 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.441249 
iter  10 value 94.055449
iter  20 value 91.549609
iter  30 value 88.606918
iter  40 value 86.695616
iter  50 value 86.097213
iter  60 value 86.061936
iter  70 value 86.049437
final  value 86.049422 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.471218 
iter  10 value 94.109020
iter  20 value 94.055125
iter  30 value 94.023731
iter  40 value 92.472256
iter  50 value 88.786061
iter  60 value 88.317476
iter  70 value 86.612655
iter  80 value 84.035621
iter  90 value 83.766099
iter 100 value 83.559894
final  value 83.559894 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.314409 
iter  10 value 94.094223
iter  20 value 94.054847
iter  30 value 93.601856
iter  40 value 92.197088
iter  50 value 88.593380
iter  60 value 84.607373
iter  70 value 83.291154
iter  80 value 83.102644
iter  90 value 82.839528
iter 100 value 82.802823
final  value 82.802823 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.041722 
iter  10 value 91.811120
iter  20 value 85.590641
iter  30 value 84.341625
iter  40 value 83.864214
iter  50 value 83.586727
iter  60 value 83.242598
iter  70 value 82.945497
iter  80 value 82.250834
iter  90 value 81.294616
iter 100 value 81.210239
final  value 81.210239 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.850542 
iter  10 value 94.289903
iter  20 value 91.019988
iter  30 value 89.270740
iter  40 value 86.674309
iter  50 value 85.930305
iter  60 value 84.027566
iter  70 value 83.311855
iter  80 value 82.834117
iter  90 value 82.120111
iter 100 value 81.941838
final  value 81.941838 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.592885 
iter  10 value 93.773600
iter  20 value 93.544116
iter  30 value 90.865301
iter  40 value 84.839562
iter  50 value 84.451052
iter  60 value 84.180392
iter  70 value 83.385025
iter  80 value 82.677427
iter  90 value 82.303998
iter 100 value 82.232531
final  value 82.232531 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.333428 
iter  10 value 94.057284
iter  20 value 93.988539
iter  30 value 86.329736
iter  40 value 85.916038
iter  50 value 85.269373
iter  60 value 84.839197
iter  70 value 84.572339
iter  80 value 84.227587
iter  90 value 83.392316
iter 100 value 82.400995
final  value 82.400995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.945769 
iter  10 value 94.012340
iter  20 value 90.209308
iter  30 value 87.826556
iter  40 value 85.972176
iter  50 value 83.213639
iter  60 value 82.931455
iter  70 value 82.510757
iter  80 value 81.557262
iter  90 value 81.301144
iter 100 value 81.116798
final  value 81.116798 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.922388 
iter  10 value 94.219144
iter  20 value 92.794489
iter  30 value 87.376633
iter  40 value 85.410255
iter  50 value 83.914243
iter  60 value 82.554587
iter  70 value 81.851091
iter  80 value 81.120289
iter  90 value 80.992548
iter 100 value 80.957268
final  value 80.957268 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.539978 
iter  10 value 93.580729
iter  20 value 93.485176
iter  30 value 92.704461
iter  40 value 90.839480
iter  50 value 86.618278
iter  60 value 84.415222
iter  70 value 83.260829
iter  80 value 82.272172
iter  90 value 81.934019
iter 100 value 81.796353
final  value 81.796353 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.412968 
iter  10 value 93.891315
iter  20 value 88.573757
iter  30 value 86.810882
iter  40 value 86.436877
iter  50 value 86.041020
iter  60 value 85.627284
iter  70 value 85.188455
iter  80 value 84.551129
iter  90 value 83.623100
iter 100 value 83.182157
final  value 83.182157 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.441744 
iter  10 value 97.071220
iter  20 value 96.814923
iter  30 value 93.992460
iter  40 value 91.103010
iter  50 value 87.930484
iter  60 value 85.215798
iter  70 value 84.165775
iter  80 value 83.106144
iter  90 value 82.618142
iter 100 value 82.266132
final  value 82.266132 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.217327 
iter  10 value 94.147160
iter  20 value 91.215378
iter  30 value 86.594531
iter  40 value 85.208947
iter  50 value 84.769409
iter  60 value 84.678196
iter  70 value 83.374929
iter  80 value 82.247503
iter  90 value 81.549625
iter 100 value 81.414100
final  value 81.414100 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.135472 
final  value 94.054486 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.922436 
iter  10 value 94.054671
iter  20 value 93.869730
iter  30 value 89.801951
final  value 89.801035 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.796899 
final  value 94.054633 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.419525 
iter  10 value 94.054458
iter  20 value 94.052954
iter  30 value 87.882893
iter  40 value 87.364247
iter  50 value 86.798426
iter  60 value 86.689880
iter  70 value 86.687336
final  value 86.687331 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.112662 
final  value 94.010322 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.891601 
iter  10 value 92.622406
iter  20 value 92.568498
iter  30 value 92.567273
iter  40 value 89.170422
iter  50 value 86.210731
iter  60 value 86.062263
iter  70 value 85.508452
iter  80 value 85.272774
iter  90 value 85.272471
iter 100 value 85.271917
final  value 85.271917 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.299565 
iter  10 value 94.013435
iter  20 value 94.009250
iter  30 value 90.646200
iter  40 value 86.121713
iter  50 value 83.832817
iter  60 value 82.614413
iter  70 value 81.681379
iter  80 value 81.040482
iter  90 value 81.039367
iter 100 value 80.996306
final  value 80.996306 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.600821 
iter  10 value 93.996436
iter  20 value 93.935106
iter  30 value 93.192637
iter  40 value 85.794821
iter  50 value 83.357425
iter  60 value 82.303506
final  value 82.267420 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.786983 
iter  10 value 94.013851
iter  20 value 93.478825
iter  30 value 93.476231
iter  40 value 93.342285
iter  50 value 89.043543
iter  60 value 89.010821
iter  70 value 89.010709
iter  80 value 89.010486
iter  90 value 89.010385
iter 100 value 89.010274
final  value 89.010274 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.209670 
iter  10 value 93.947490
iter  20 value 93.944675
iter  30 value 93.702943
iter  40 value 92.972425
final  value 92.971242 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.072580 
iter  10 value 93.297517
iter  20 value 92.175546
iter  30 value 85.388707
iter  40 value 85.367262
iter  50 value 85.366279
iter  60 value 85.332289
iter  70 value 85.229435
iter  80 value 85.210818
final  value 85.210775 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.966821 
iter  10 value 94.061096
iter  20 value 94.008400
iter  30 value 93.522241
iter  40 value 93.366002
iter  50 value 93.353442
final  value 93.353425 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.314690 
iter  10 value 94.061822
iter  20 value 94.053701
iter  30 value 93.615628
iter  40 value 93.536828
iter  50 value 93.519048
iter  50 value 93.519048
iter  50 value 93.519048
final  value 93.519048 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.275410 
iter  10 value 93.952655
iter  20 value 93.564553
iter  30 value 93.387758
final  value 93.387729 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.502321 
iter  10 value 94.061079
iter  20 value 94.053179
iter  30 value 93.390893
iter  40 value 90.119632
iter  50 value 85.437370
iter  60 value 85.365163
iter  70 value 85.308921
final  value 85.226069 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.554641 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.927454 
iter  10 value 88.454941
iter  20 value 86.449982
iter  30 value 86.446450
final  value 86.446402 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.259548 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.444851 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.744749 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.411971 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.744885 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.683805 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.742140 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.732708 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.379288 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.221152 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.585438 
iter  10 value 94.022599
iter  10 value 94.022599
iter  10 value 94.022599
final  value 94.022599 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.180397 
iter  10 value 93.280127
final  value 93.264439 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.062933 
iter  10 value 91.554445
iter  20 value 91.183289
iter  30 value 91.182375
iter  40 value 90.460304
iter  50 value 90.122794
final  value 90.062323 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.974765 
iter  10 value 90.363335
iter  20 value 85.840884
iter  30 value 85.320457
iter  40 value 85.232815
iter  50 value 84.728782
iter  60 value 84.609287
iter  70 value 84.605030
final  value 84.603601 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.237950 
iter  10 value 94.030814
iter  20 value 93.859388
iter  30 value 91.974235
iter  40 value 91.568973
iter  50 value 91.124814
iter  60 value 91.043744
iter  70 value 91.023405
iter  80 value 90.755921
iter  90 value 88.965114
iter 100 value 85.218410
final  value 85.218410 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.232714 
iter  10 value 94.048450
iter  20 value 89.883619
iter  30 value 87.296766
iter  40 value 84.619570
iter  50 value 83.990923
iter  60 value 83.572897
iter  70 value 83.405803
iter  80 value 83.309859
iter  90 value 83.272191
iter 100 value 83.198330
final  value 83.198330 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.340856 
iter  10 value 90.605773
iter  20 value 86.044031
iter  30 value 83.770212
iter  40 value 83.694596
iter  50 value 83.593313
iter  60 value 83.307016
iter  70 value 83.280538
iter  80 value 83.218096
iter  90 value 83.185075
final  value 83.184910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.195571 
iter  10 value 94.056796
iter  20 value 93.585204
iter  30 value 88.469495
iter  40 value 86.768367
iter  50 value 84.687878
iter  60 value 84.258656
iter  70 value 84.226668
final  value 84.226623 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.521166 
iter  10 value 94.157259
iter  20 value 93.892329
iter  30 value 93.696370
iter  40 value 93.362398
iter  50 value 89.924282
iter  60 value 87.251556
iter  70 value 86.838392
iter  80 value 85.739654
iter  90 value 83.367713
iter 100 value 82.923502
final  value 82.923502 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.236417 
iter  10 value 93.724433
iter  20 value 86.140436
iter  30 value 85.282366
iter  40 value 84.682356
iter  50 value 84.297639
iter  60 value 84.225502
iter  70 value 84.108098
iter  80 value 82.191220
iter  90 value 82.049360
iter 100 value 81.961702
final  value 81.961702 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.805183 
iter  10 value 94.066655
iter  20 value 94.018340
iter  30 value 92.964193
iter  40 value 87.422442
iter  50 value 86.270988
iter  60 value 83.868071
iter  70 value 83.029200
iter  80 value 82.024526
iter  90 value 81.695671
iter 100 value 81.443779
final  value 81.443779 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.625968 
iter  10 value 93.888178
iter  20 value 87.766657
iter  30 value 83.370037
iter  40 value 82.487441
iter  50 value 81.943384
iter  60 value 81.458036
iter  70 value 80.946239
iter  80 value 80.858633
iter  90 value 80.800439
iter 100 value 80.669836
final  value 80.669836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.599589 
iter  10 value 93.968221
iter  20 value 91.861932
iter  30 value 90.557046
iter  40 value 89.107182
iter  50 value 88.892473
iter  60 value 88.806319
iter  70 value 88.720131
iter  80 value 86.329025
iter  90 value 83.275740
iter 100 value 82.216165
final  value 82.216165 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.254558 
iter  10 value 93.811188
iter  20 value 89.880186
iter  30 value 86.994463
iter  40 value 86.376052
iter  50 value 85.971620
iter  60 value 85.532383
iter  70 value 84.308383
iter  80 value 83.585468
iter  90 value 82.673007
iter 100 value 82.034717
final  value 82.034717 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.370222 
iter  10 value 94.183997
iter  20 value 92.859796
iter  30 value 89.586131
iter  40 value 88.915250
iter  50 value 86.687562
iter  60 value 83.424444
iter  70 value 82.770749
iter  80 value 82.525866
iter  90 value 81.952259
iter 100 value 81.901026
final  value 81.901026 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.347927 
iter  10 value 93.921364
iter  20 value 90.775982
iter  30 value 88.651789
iter  40 value 87.980892
iter  50 value 86.252765
iter  60 value 85.759909
iter  70 value 84.962627
iter  80 value 83.687913
iter  90 value 81.522762
iter 100 value 81.056970
final  value 81.056970 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.290283 
iter  10 value 94.369176
iter  20 value 85.651219
iter  30 value 84.940673
iter  40 value 83.549271
iter  50 value 82.186158
iter  60 value 81.102527
iter  70 value 80.767750
iter  80 value 80.459478
iter  90 value 80.437258
iter 100 value 80.404503
final  value 80.404503 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.860769 
iter  10 value 94.134116
iter  20 value 87.079273
iter  30 value 84.690426
iter  40 value 84.377912
iter  50 value 83.661551
iter  60 value 83.348853
iter  70 value 83.247842
iter  80 value 82.810502
iter  90 value 81.970397
iter 100 value 81.263843
final  value 81.263843 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.566016 
iter  10 value 94.054911
iter  20 value 94.042088
iter  30 value 89.660909
iter  40 value 86.292482
iter  50 value 86.203674
iter  60 value 84.139108
iter  70 value 84.076219
iter  80 value 83.541609
iter  90 value 82.829414
iter 100 value 82.820995
final  value 82.820995 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.056902 
iter  10 value 94.059722
iter  20 value 94.057199
iter  30 value 94.050983
iter  40 value 87.534338
iter  50 value 87.399603
iter  60 value 87.399198
iter  70 value 86.657002
iter  80 value 86.315390
final  value 86.315388 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.858869 
final  value 94.054574 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.798374 
final  value 94.054653 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.428540 
final  value 94.054721 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.815796 
iter  10 value 94.056168
iter  20 value 93.926278
iter  30 value 93.697135
iter  40 value 87.943332
iter  50 value 87.942278
iter  60 value 87.938497
iter  70 value 86.438679
iter  80 value 86.338509
iter  90 value 83.778391
iter 100 value 81.641781
final  value 81.641781 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.870026 
iter  10 value 93.919961
iter  20 value 93.783551
iter  30 value 88.058419
final  value 88.058340 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.047537 
iter  10 value 93.701705
iter  20 value 93.698311
iter  30 value 93.697335
iter  40 value 89.581039
iter  50 value 86.583759
iter  60 value 85.669461
iter  70 value 84.020405
iter  80 value 83.738632
iter  90 value 83.517384
iter 100 value 83.329603
final  value 83.329603 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.465804 
iter  10 value 94.057951
iter  20 value 93.840752
iter  30 value 85.818959
iter  40 value 85.133560
iter  50 value 85.133170
iter  60 value 84.475262
iter  70 value 84.088661
iter  80 value 83.757087
iter  90 value 83.736489
iter 100 value 83.735068
final  value 83.735068 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.142603 
iter  10 value 92.322856
iter  20 value 92.310830
iter  30 value 92.308565
iter  40 value 92.287966
iter  50 value 92.256307
iter  60 value 92.252655
iter  70 value 92.178932
final  value 92.173720 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.324559 
iter  10 value 93.924399
iter  20 value 93.918353
iter  30 value 93.915899
iter  40 value 93.810812
iter  50 value 89.513282
iter  60 value 87.930272
iter  70 value 82.774286
iter  80 value 80.929807
iter  90 value 80.750689
iter 100 value 80.718899
final  value 80.718899 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.166221 
iter  10 value 93.805839
final  value 92.831529 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.680220 
iter  10 value 88.642137
iter  20 value 88.622972
iter  30 value 87.706802
iter  40 value 87.567979
iter  50 value 87.564765
final  value 87.564654 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.860615 
iter  10 value 93.924082
iter  20 value 93.916705
iter  30 value 93.697518
final  value 93.697478 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.135309 
iter  10 value 93.900455
iter  20 value 93.895890
iter  30 value 88.602293
iter  40 value 86.102004
iter  50 value 85.943981
final  value 85.943831 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.888625 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.959467 
iter  10 value 86.092617
iter  20 value 82.148107
final  value 82.147604 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.745718 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.166803 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.720918 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.755846 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.183493 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.029410 
iter  10 value 94.148355
iter  20 value 94.147192
final  value 94.147188 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.119101 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.271674 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.005125 
final  value 93.109890 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.924584 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.518029 
final  value 94.423530 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.228239 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.511505 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.517532 
iter  10 value 90.225657
iter  20 value 84.079807
iter  30 value 82.683961
iter  40 value 82.254159
iter  50 value 82.141222
iter  60 value 82.022651
iter  70 value 81.531368
iter  80 value 81.131535
iter  90 value 81.055776
final  value 81.055751 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.039630 
iter  10 value 94.489228
iter  20 value 85.281911
iter  30 value 84.211702
iter  40 value 82.201439
iter  50 value 82.060677
iter  60 value 81.905414
iter  70 value 81.532695
iter  80 value 81.336927
iter  90 value 81.188900
final  value 81.188882 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.880105 
iter  10 value 94.488594
iter  20 value 94.125720
iter  30 value 91.337625
iter  40 value 91.040663
iter  50 value 90.824084
iter  60 value 82.939584
iter  70 value 81.313739
iter  80 value 80.858012
iter  90 value 80.775165
final  value 80.774654 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.740568 
iter  10 value 94.455342
iter  20 value 92.563305
iter  30 value 92.450378
iter  40 value 92.003505
iter  50 value 84.271291
iter  60 value 82.326263
iter  70 value 82.123033
iter  80 value 81.585784
iter  90 value 81.173930
iter 100 value 81.055755
final  value 81.055755 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.731504 
iter  10 value 94.330539
iter  20 value 86.122879
iter  30 value 82.786443
iter  40 value 82.479323
iter  50 value 82.240511
iter  60 value 81.789397
iter  70 value 81.268136
iter  80 value 81.210520
final  value 81.198068 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.624430 
iter  10 value 94.414246
iter  20 value 91.961797
iter  30 value 84.259167
iter  40 value 82.107839
iter  50 value 80.347858
iter  60 value 79.402427
iter  70 value 79.101252
iter  80 value 79.073843
iter  90 value 79.034768
iter 100 value 78.343136
final  value 78.343136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.584174 
iter  10 value 94.489970
iter  20 value 92.297428
iter  30 value 88.643926
iter  40 value 88.300805
iter  50 value 85.313332
iter  60 value 83.865783
iter  70 value 83.164831
iter  80 value 79.681495
iter  90 value 78.105221
iter 100 value 77.502850
final  value 77.502850 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.854095 
iter  10 value 92.122144
iter  20 value 86.017623
iter  30 value 85.696466
iter  40 value 85.559264
iter  50 value 83.237994
iter  60 value 81.492739
iter  70 value 81.034627
iter  80 value 80.938784
iter  90 value 80.912010
iter 100 value 80.879005
final  value 80.879005 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.205231 
iter  10 value 94.495802
iter  20 value 90.681919
iter  30 value 85.928448
iter  40 value 83.743070
iter  50 value 83.148734
iter  60 value 82.506407
iter  70 value 81.722124
iter  80 value 81.448827
iter  90 value 81.160310
iter 100 value 80.967022
final  value 80.967022 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.201159 
iter  10 value 91.801133
iter  20 value 83.895427
iter  30 value 79.863444
iter  40 value 78.892066
iter  50 value 78.295313
iter  60 value 78.041792
iter  70 value 77.870523
iter  80 value 77.827481
iter  90 value 77.819910
final  value 77.819637 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.557060 
iter  10 value 94.553465
iter  20 value 84.826465
iter  30 value 83.101036
iter  40 value 81.707374
iter  50 value 80.986289
iter  60 value 80.863437
iter  70 value 80.823109
iter  80 value 80.702164
iter  90 value 80.184280
iter 100 value 79.292614
final  value 79.292614 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.076183 
iter  10 value 94.410758
iter  20 value 86.717262
iter  30 value 82.795451
iter  40 value 78.944948
iter  50 value 78.272168
iter  60 value 78.097094
iter  70 value 77.602234
iter  80 value 77.226907
iter  90 value 77.026884
iter 100 value 76.863194
final  value 76.863194 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 143.027060 
iter  10 value 94.322313
iter  20 value 88.432270
iter  30 value 86.324789
iter  40 value 81.104297
iter  50 value 79.658691
iter  60 value 79.407958
iter  70 value 79.036767
iter  80 value 78.315277
iter  90 value 77.986277
iter 100 value 77.395852
final  value 77.395852 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.359212 
iter  10 value 89.197638
iter  20 value 84.375040
iter  30 value 82.535223
iter  40 value 81.963647
iter  50 value 78.839204
iter  60 value 77.926054
iter  70 value 77.542171
iter  80 value 77.296999
iter  90 value 77.105211
iter 100 value 77.021556
final  value 77.021556 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.744568 
iter  10 value 97.550028
iter  20 value 94.471737
iter  30 value 86.472714
iter  40 value 84.308402
iter  50 value 82.413114
iter  60 value 82.171086
iter  70 value 82.068939
iter  80 value 81.068219
iter  90 value 79.884304
iter 100 value 79.516581
final  value 79.516581 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.244212 
final  value 94.485930 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.976352 
final  value 94.486037 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.038378 
final  value 94.485868 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.424046 
final  value 94.485926 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.129616 
final  value 94.485836 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.784578 
iter  10 value 94.668154
iter  20 value 94.487043
iter  30 value 94.403506
iter  40 value 93.121322
iter  50 value 93.114615
iter  60 value 89.396185
iter  70 value 85.016960
iter  80 value 82.858596
iter  90 value 81.801991
iter 100 value 81.650245
final  value 81.650245 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.008659 
iter  10 value 94.489044
iter  20 value 94.466547
iter  30 value 82.338835
iter  40 value 81.074523
final  value 81.058879 
converged
Fitting Repeat 3 

# weights:  305
initial  value 92.976760 
iter  10 value 91.077165
iter  20 value 91.016779
iter  30 value 89.468354
iter  40 value 80.368706
iter  50 value 80.214275
final  value 80.213425 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.552162 
iter  10 value 94.489340
iter  20 value 94.465407
iter  30 value 91.019050
iter  40 value 82.876709
iter  50 value 82.674544
iter  60 value 82.673218
iter  70 value 82.672661
iter  80 value 81.471557
iter  90 value 81.449196
final  value 81.449107 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.581781 
iter  10 value 94.472412
iter  20 value 94.434796
iter  30 value 82.795077
iter  40 value 79.710054
iter  50 value 79.373993
iter  60 value 78.492762
iter  70 value 78.301384
iter  80 value 78.299911
iter  90 value 78.298555
iter 100 value 78.298268
final  value 78.298268 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.675534 
iter  10 value 94.492619
iter  20 value 94.481683
final  value 94.467464 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.780146 
iter  10 value 94.492713
iter  20 value 94.279296
iter  30 value 82.276830
iter  40 value 80.709447
iter  50 value 80.154889
iter  60 value 80.086672
iter  70 value 79.918240
iter  80 value 79.686167
iter  90 value 79.644501
final  value 79.644455 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.858257 
iter  10 value 94.492274
iter  20 value 90.646670
iter  30 value 83.439361
iter  40 value 83.404647
iter  50 value 83.400626
iter  60 value 83.400330
iter  70 value 83.230333
iter  80 value 82.095704
iter  90 value 81.779542
iter 100 value 81.768967
final  value 81.768967 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.382869 
iter  10 value 94.492565
iter  20 value 92.626702
iter  30 value 82.104551
iter  40 value 80.911644
iter  50 value 77.116486
iter  60 value 76.474204
iter  70 value 76.431559
iter  80 value 76.400764
iter  90 value 76.201389
iter 100 value 76.166492
final  value 76.166492 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.538755 
iter  10 value 94.436314
iter  20 value 94.435612
iter  30 value 94.428362
iter  40 value 84.311961
iter  50 value 81.999204
iter  60 value 81.949180
iter  70 value 81.879582
iter  80 value 81.719000
iter  90 value 81.663130
iter 100 value 81.550260
final  value 81.550260 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.593879 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.269958 
iter  10 value 93.693786
iter  20 value 93.669297
final  value 93.663124 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.931130 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.611888 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.558991 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.729208 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.454075 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.499049 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.835854 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.918169 
iter  10 value 94.381476
final  value 94.381462 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.539259 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.363581 
iter  10 value 94.318030
final  value 94.315791 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.834942 
iter  10 value 91.545444
iter  20 value 89.793017
iter  30 value 82.280578
iter  40 value 82.042577
final  value 82.042213 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.093998 
final  value 94.214007 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.978309 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.558583 
iter  10 value 94.510590
iter  20 value 88.375791
iter  30 value 86.514861
iter  40 value 82.892803
iter  50 value 82.153246
iter  60 value 82.083172
iter  70 value 82.024817
iter  80 value 82.016318
iter  80 value 82.016317
iter  80 value 82.016317
final  value 82.016317 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.213115 
iter  10 value 94.495459
iter  20 value 90.083313
iter  30 value 88.635226
iter  40 value 87.134267
iter  50 value 86.452683
iter  60 value 85.850595
iter  70 value 83.424201
iter  80 value 82.831759
iter  90 value 82.726837
iter 100 value 82.253141
final  value 82.253141 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.848363 
iter  10 value 92.331533
iter  20 value 83.090370
iter  30 value 82.214767
iter  40 value 82.083881
final  value 82.083079 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.260775 
iter  10 value 94.485100
iter  20 value 93.674687
iter  30 value 89.485921
iter  40 value 85.199181
iter  50 value 84.382147
iter  60 value 81.200216
iter  70 value 80.431771
iter  80 value 80.256749
final  value 80.255540 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.599159 
iter  10 value 94.508714
iter  20 value 94.487374
iter  30 value 94.240843
iter  40 value 93.781865
iter  50 value 85.756819
iter  60 value 83.218499
iter  70 value 82.819041
iter  80 value 82.589208
iter  90 value 82.512084
final  value 82.512071 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.130838 
iter  10 value 93.347415
iter  20 value 85.291176
iter  30 value 83.149279
iter  40 value 82.444503
iter  50 value 82.292037
iter  60 value 82.213234
iter  70 value 82.082774
iter  80 value 82.060228
iter  90 value 82.046156
iter 100 value 81.959409
final  value 81.959409 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 129.273554 
iter  10 value 94.049885
iter  20 value 84.239220
iter  30 value 82.761296
iter  40 value 82.212418
iter  50 value 81.219790
iter  60 value 80.471497
iter  70 value 79.984341
iter  80 value 79.772659
iter  90 value 79.639076
iter 100 value 79.492134
final  value 79.492134 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.375649 
iter  10 value 94.476991
iter  20 value 85.923417
iter  30 value 84.711548
iter  40 value 82.948511
iter  50 value 82.119593
iter  60 value 81.171654
iter  70 value 80.838933
iter  80 value 80.764734
iter  90 value 80.579963
iter 100 value 80.488076
final  value 80.488076 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.419472 
iter  10 value 94.147737
iter  20 value 84.669748
iter  30 value 83.964992
iter  40 value 82.667974
iter  50 value 82.127466
iter  60 value 81.964275
iter  70 value 81.533280
iter  80 value 80.325427
iter  90 value 79.771057
iter 100 value 79.737685
final  value 79.737685 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.637382 
iter  10 value 94.433628
iter  20 value 93.277312
iter  30 value 85.510161
iter  40 value 83.413823
iter  50 value 82.525889
iter  60 value 81.426844
iter  70 value 80.649446
iter  80 value 79.926563
iter  90 value 79.645891
iter 100 value 79.606551
final  value 79.606551 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.728360 
iter  10 value 94.721709
iter  20 value 93.074593
iter  30 value 86.520247
iter  40 value 81.512997
iter  50 value 80.806631
iter  60 value 80.322960
iter  70 value 79.238810
iter  80 value 79.035958
iter  90 value 78.812080
iter 100 value 78.739043
final  value 78.739043 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.548442 
iter  10 value 94.473917
iter  20 value 85.237210
iter  30 value 84.942931
iter  40 value 84.293649
iter  50 value 81.111646
iter  60 value 80.216071
iter  70 value 80.013785
iter  80 value 79.524989
iter  90 value 79.435993
iter 100 value 79.323097
final  value 79.323097 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.451780 
iter  10 value 93.040691
iter  20 value 91.194124
iter  30 value 89.903077
iter  40 value 85.657548
iter  50 value 82.114187
iter  60 value 80.723272
iter  70 value 80.469668
iter  80 value 80.360120
iter  90 value 80.063485
iter 100 value 79.957396
final  value 79.957396 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 146.929924 
iter  10 value 100.395046
iter  20 value 92.362548
iter  30 value 89.917846
iter  40 value 84.942390
iter  50 value 84.101705
iter  60 value 82.248007
iter  70 value 80.246989
iter  80 value 79.705779
iter  90 value 79.398820
iter 100 value 79.168465
final  value 79.168465 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.391443 
iter  10 value 95.178372
iter  20 value 94.489858
iter  30 value 84.837061
iter  40 value 83.388749
iter  50 value 82.469968
iter  60 value 80.825007
iter  70 value 80.348850
iter  80 value 80.095939
iter  90 value 79.871725
iter 100 value 79.682137
final  value 79.682137 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.267327 
iter  10 value 94.485738
iter  20 value 94.463027
iter  30 value 85.515906
iter  40 value 85.193676
iter  50 value 85.024662
iter  60 value 84.379733
iter  70 value 84.366220
iter  80 value 84.353596
iter  90 value 84.264973
iter 100 value 84.261735
final  value 84.261735 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.480111 
final  value 94.485937 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.617510 
iter  10 value 94.277021
iter  20 value 94.275618
iter  30 value 94.206616
iter  40 value 84.876372
iter  50 value 84.870976
iter  60 value 84.793476
iter  70 value 84.769816
final  value 84.769565 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.363665 
iter  10 value 94.486054
iter  20 value 94.481315
iter  30 value 92.101756
iter  40 value 89.003446
iter  50 value 88.839040
iter  60 value 88.830585
iter  70 value 88.788331
iter  80 value 88.753243
iter  90 value 88.334203
iter 100 value 88.211458
final  value 88.211458 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.208137 
final  value 94.485691 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.052674 
iter  10 value 94.280483
iter  20 value 94.275556
iter  30 value 93.804102
iter  40 value 87.687845
iter  50 value 86.784792
iter  60 value 83.695408
iter  70 value 81.963232
iter  80 value 81.917968
iter  90 value 81.910437
iter 100 value 81.903231
final  value 81.903231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.132155 
iter  10 value 94.488624
iter  20 value 91.086511
iter  30 value 91.010428
iter  40 value 90.994457
iter  50 value 90.458901
iter  60 value 90.215323
final  value 90.214852 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.637433 
iter  10 value 94.486645
iter  20 value 94.051402
iter  20 value 94.051402
final  value 94.051402 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.791195 
iter  10 value 94.280499
iter  20 value 94.276851
iter  30 value 83.805508
iter  40 value 81.541812
iter  50 value 80.785849
iter  60 value 80.785209
iter  70 value 80.717054
iter  80 value 80.701695
final  value 80.701683 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.091180 
iter  10 value 94.280256
iter  20 value 94.125498
iter  30 value 84.871112
iter  40 value 84.870449
iter  50 value 84.771968
iter  60 value 83.541698
final  value 83.541399 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.853128 
iter  10 value 93.993062
iter  20 value 93.939733
iter  30 value 93.933094
iter  40 value 93.725683
iter  50 value 93.628182
iter  60 value 85.220107
iter  70 value 80.812187
iter  80 value 80.701127
iter  90 value 80.700888
iter 100 value 80.700758
final  value 80.700758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.609384 
iter  10 value 94.321245
iter  20 value 94.281640
iter  30 value 94.269305
iter  40 value 82.400266
iter  50 value 81.903455
iter  60 value 81.823372
iter  70 value 81.819007
final  value 81.818984 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.076633 
iter  10 value 94.492360
iter  20 value 94.399965
iter  30 value 92.305972
final  value 92.305852 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.583707 
iter  10 value 94.314103
iter  20 value 94.237700
iter  30 value 94.204597
iter  40 value 84.255207
iter  50 value 84.106877
iter  60 value 84.101703
final  value 84.101686 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.205259 
iter  10 value 94.283517
iter  20 value 94.276220
final  value 94.275966 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.062683 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.567068 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.261445 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.267446 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.995399 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.145066 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.978110 
iter  10 value 86.518625
iter  20 value 86.440814
final  value 86.440679 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.575206 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.383757 
final  value 93.976244 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.661831 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.926609 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.632362 
iter  10 value 93.012417
iter  20 value 88.748698
iter  30 value 87.088161
iter  40 value 85.439931
iter  50 value 85.132198
iter  60 value 85.128815
iter  70 value 84.928321
iter  80 value 84.541180
final  value 84.541148 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.164357 
iter  10 value 88.816006
iter  20 value 88.754271
iter  30 value 88.674124
iter  40 value 88.672432
final  value 88.672429 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.106681 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.169065 
final  value 94.484212 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.980190 
iter  10 value 94.488485
iter  20 value 91.513235
iter  30 value 87.518826
iter  40 value 86.938945
iter  50 value 86.479569
iter  60 value 86.131545
iter  70 value 85.173096
iter  80 value 84.189676
iter  90 value 83.689616
iter 100 value 83.136252
final  value 83.136252 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.752643 
iter  10 value 94.431919
iter  20 value 92.626014
iter  30 value 92.353402
iter  40 value 92.256725
final  value 92.256679 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.818974 
iter  10 value 94.477232
iter  20 value 94.187864
iter  30 value 94.015046
iter  40 value 92.522190
iter  50 value 87.026023
iter  60 value 85.594994
iter  70 value 85.213447
iter  80 value 84.641558
iter  90 value 84.098054
iter 100 value 83.633456
final  value 83.633456 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.934816 
iter  10 value 94.486518
iter  20 value 94.259978
iter  30 value 94.021135
iter  40 value 93.282657
iter  50 value 88.209282
iter  60 value 87.748643
iter  70 value 86.549080
iter  80 value 85.727505
iter  90 value 85.699955
final  value 85.699952 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.399380 
iter  10 value 92.496043
iter  20 value 86.285346
iter  30 value 86.095817
iter  40 value 85.454976
iter  50 value 85.233830
iter  60 value 85.116779
iter  70 value 85.041687
final  value 85.040381 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.801325 
iter  10 value 94.750517
iter  20 value 93.051836
iter  30 value 92.672088
iter  40 value 92.247860
iter  50 value 85.966434
iter  60 value 82.969519
iter  70 value 82.022560
iter  80 value 81.743148
iter  90 value 81.702023
iter 100 value 81.643905
final  value 81.643905 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.323413 
iter  10 value 94.488083
iter  20 value 93.967580
iter  30 value 91.588948
iter  40 value 89.665133
iter  50 value 89.515756
iter  60 value 86.446637
iter  70 value 84.441315
iter  80 value 82.558922
iter  90 value 82.168210
iter 100 value 81.764692
final  value 81.764692 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.002910 
iter  10 value 94.554672
iter  20 value 94.383895
iter  30 value 93.883652
iter  40 value 90.062932
iter  50 value 87.057688
iter  60 value 86.452406
iter  70 value 86.176743
iter  80 value 85.918433
iter  90 value 85.313927
iter 100 value 82.929076
final  value 82.929076 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.356400 
iter  10 value 94.542968
iter  20 value 93.341802
iter  30 value 93.038068
iter  40 value 90.684892
iter  50 value 88.226259
iter  60 value 84.923308
iter  70 value 82.783455
iter  80 value 82.251744
iter  90 value 81.969928
iter 100 value 81.854898
final  value 81.854898 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.878594 
iter  10 value 94.545027
iter  20 value 90.419150
iter  30 value 88.796059
iter  40 value 86.371360
iter  50 value 85.953871
iter  60 value 84.391311
iter  70 value 82.955363
iter  80 value 82.359576
iter  90 value 82.192975
iter 100 value 82.132220
final  value 82.132220 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.014392 
iter  10 value 93.421266
iter  20 value 88.875101
iter  30 value 87.620182
iter  40 value 86.116152
iter  50 value 83.585386
iter  60 value 83.303690
iter  70 value 82.432674
iter  80 value 81.642500
iter  90 value 81.587247
iter 100 value 81.419355
final  value 81.419355 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.113355 
iter  10 value 92.934241
iter  20 value 87.754341
iter  30 value 84.916347
iter  40 value 83.379438
iter  50 value 81.978346
iter  60 value 81.642367
iter  70 value 81.446880
iter  80 value 81.335850
iter  90 value 81.324870
iter 100 value 81.321658
final  value 81.321658 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.444503 
iter  10 value 94.582860
iter  20 value 94.424459
iter  30 value 93.914341
iter  40 value 90.207580
iter  50 value 86.518543
iter  60 value 86.184592
iter  70 value 85.736084
iter  80 value 85.305155
iter  90 value 85.074141
iter 100 value 84.197818
final  value 84.197818 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.970472 
iter  10 value 94.303294
iter  20 value 87.737055
iter  30 value 87.416953
iter  40 value 86.453346
iter  50 value 82.204107
iter  60 value 81.745513
iter  70 value 81.570970
iter  80 value 81.331996
iter  90 value 81.235850
iter 100 value 81.215559
final  value 81.215559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.943796 
iter  10 value 98.351014
iter  20 value 96.320277
iter  30 value 96.191077
iter  40 value 93.698149
iter  50 value 90.499256
iter  60 value 85.035391
iter  70 value 84.070150
iter  80 value 83.779140
iter  90 value 82.746448
iter 100 value 82.047075
final  value 82.047075 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.491679 
iter  10 value 94.485520
final  value 94.484318 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.317955 
iter  10 value 94.486119
iter  20 value 94.483682
final  value 94.027230 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.149367 
final  value 94.485689 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.383216 
final  value 94.485699 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.668250 
final  value 94.485720 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.120840 
iter  10 value 93.374334
iter  20 value 93.330507
final  value 93.330090 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.694133 
iter  10 value 94.489768
iter  20 value 94.484623
iter  30 value 94.460514
iter  40 value 93.852936
iter  50 value 93.851969
final  value 93.851959 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.901548 
iter  10 value 94.310916
iter  20 value 94.193565
final  value 94.026802 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.912232 
iter  10 value 94.484941
iter  20 value 94.484398
iter  20 value 94.484397
iter  20 value 94.484397
final  value 94.484397 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.469042 
iter  10 value 94.488602
iter  20 value 94.484254
final  value 94.484212 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.866251 
iter  10 value 94.034954
iter  20 value 93.995088
iter  30 value 93.763155
iter  40 value 93.763034
iter  50 value 93.758781
iter  60 value 93.505380
iter  70 value 92.112561
iter  80 value 90.872317
iter  90 value 84.792145
iter 100 value 83.854579
final  value 83.854579 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.957817 
iter  10 value 94.491474
iter  20 value 93.721858
iter  30 value 88.244006
iter  40 value 88.243345
iter  50 value 88.129295
iter  60 value 88.128883
iter  70 value 87.835029
iter  80 value 87.242368
iter  90 value 87.149332
final  value 87.147690 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.595093 
iter  10 value 94.060797
iter  20 value 93.889124
iter  30 value 93.873195
final  value 93.851709 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.731330 
iter  10 value 94.320463
iter  20 value 94.311241
iter  30 value 93.859424
final  value 93.822517 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.601377 
iter  10 value 88.585853
iter  20 value 86.227690
iter  30 value 83.928737
iter  40 value 83.586524
iter  50 value 83.460537
iter  60 value 83.202445
iter  70 value 83.158955
iter  80 value 83.121915
iter  90 value 83.116776
iter  90 value 83.116775
final  value 83.116775 
converged
Fitting Repeat 1 

# weights:  305
initial  value 133.996068 
iter  10 value 117.921426
iter  20 value 108.371252
iter  30 value 105.424588
iter  40 value 102.919766
iter  50 value 101.787010
iter  60 value 101.369690
iter  70 value 101.199135
iter  80 value 101.091214
iter  90 value 101.076402
iter 100 value 100.952559
final  value 100.952559 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.795330 
iter  10 value 118.065401
iter  20 value 105.293078
iter  30 value 103.152953
iter  40 value 102.614862
iter  50 value 101.853357
iter  60 value 101.229391
iter  70 value 100.986616
iter  80 value 100.944425
iter  90 value 100.499515
iter 100 value 100.333842
final  value 100.333842 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 127.091161 
iter  10 value 118.378413
iter  20 value 117.424540
iter  30 value 113.083976
iter  40 value 112.228460
iter  50 value 109.391440
iter  60 value 106.761120
iter  70 value 105.802912
iter  80 value 102.961480
iter  90 value 101.339054
iter 100 value 101.102537
final  value 101.102537 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 143.727698 
iter  10 value 117.869384
iter  20 value 113.972565
iter  30 value 107.105610
iter  40 value 105.360428
iter  50 value 104.416021
iter  60 value 102.170959
iter  70 value 101.254562
iter  80 value 100.915039
iter  90 value 100.866553
iter 100 value 100.810479
final  value 100.810479 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 158.760649 
iter  10 value 117.916160
iter  20 value 115.914819
iter  30 value 108.921288
iter  40 value 106.362667
iter  50 value 105.115617
iter  60 value 104.358112
iter  70 value 102.170302
iter  80 value 101.221585
iter  90 value 100.938269
iter 100 value 100.696558
final  value 100.696558 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Thu Jul 11 22:40:36 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 45.287   1.168  50.637