##############################################################################
##############################################################################
###
### 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_1.17.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-10-21 r88958)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* 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 ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
  Code: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 FALSE, filename = "plots.pdf")
  Docs: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 TRUE, filename = "plots.pdf")
  Mismatches in argument default values:
    Name: 'plots' Code: FALSE Docs: TRUE

* 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
FSmethod      36.870  1.816  40.911
corr_plot     35.517  1.756  37.681
var_imp       35.089  1.792  37.390
pred_ensembel 13.979  0.465  12.536
enrichfindP    0.529  0.081   9.469
* 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: 1 WARNING, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.23-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/4.6-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.1’
** 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 Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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 97.052493 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.298375 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.399243 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.286264 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.579454 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.269645 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.278455 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.449142 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.638558 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.788863 
final  value 93.900000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.227798 
iter  10 value 94.008707
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.490885 
iter  10 value 94.000000
iter  10 value 94.000000
iter  10 value 94.000000
final  value 94.000000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.487416 
iter  10 value 93.942966
iter  20 value 93.937253
final  value 93.937249 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.524369 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.012882 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.127398 
iter  10 value 94.053903
iter  20 value 94.024062
iter  30 value 93.883418
iter  40 value 91.683335
iter  50 value 90.788040
iter  60 value 84.839662
iter  70 value 83.185422
iter  80 value 82.899318
iter  90 value 82.281355
iter 100 value 82.196021
final  value 82.196021 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.934789 
iter  10 value 94.056119
iter  20 value 89.411601
iter  30 value 83.682413
iter  40 value 83.192498
iter  50 value 82.744282
iter  60 value 82.580485
iter  70 value 82.546432
iter  80 value 82.002498
iter  90 value 81.665804
iter 100 value 80.797665
final  value 80.797665 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.438187 
iter  10 value 94.064547
iter  20 value 94.049266
iter  30 value 91.371703
iter  40 value 86.749959
iter  50 value 85.653103
iter  60 value 85.620169
iter  70 value 84.857193
iter  80 value 84.641924
final  value 84.640447 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.997975 
iter  10 value 94.057221
iter  10 value 94.057220
iter  20 value 94.001699
iter  30 value 88.612264
iter  40 value 86.011999
iter  50 value 84.915819
iter  60 value 84.659559
iter  70 value 84.640448
iter  70 value 84.640447
iter  70 value 84.640447
final  value 84.640447 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.946374 
iter  10 value 93.956382
iter  20 value 92.310838
iter  30 value 87.310502
iter  40 value 85.616346
iter  50 value 84.376879
iter  60 value 83.798739
iter  70 value 83.467391
iter  80 value 83.435641
final  value 83.435637 
converged
Fitting Repeat 1 

# weights:  305
initial  value 144.026789 
iter  10 value 94.386086
iter  20 value 94.071710
iter  30 value 93.795448
iter  40 value 87.246018
iter  50 value 86.198016
iter  60 value 85.754574
iter  70 value 84.328694
iter  80 value 82.006970
iter  90 value 80.905797
iter 100 value 80.477246
final  value 80.477246 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.724716 
iter  10 value 92.732989
iter  20 value 85.785780
iter  30 value 83.235943
iter  40 value 82.619271
iter  50 value 81.283007
iter  60 value 80.476529
iter  70 value 80.373527
iter  80 value 80.268248
iter  90 value 79.829176
iter 100 value 79.698943
final  value 79.698943 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.965572 
iter  10 value 94.140987
iter  20 value 87.916079
iter  30 value 87.400254
iter  40 value 87.099330
iter  50 value 85.674590
iter  60 value 83.076170
iter  70 value 81.992859
iter  80 value 81.566192
iter  90 value 81.121851
iter 100 value 81.064898
final  value 81.064898 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.628451 
iter  10 value 94.089145
iter  20 value 93.818349
iter  30 value 93.131672
iter  40 value 87.989165
iter  50 value 86.788411
iter  60 value 85.924507
iter  70 value 85.433948
iter  80 value 84.314590
iter  90 value 83.105359
iter 100 value 80.629569
final  value 80.629569 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.229045 
iter  10 value 95.358005
iter  20 value 94.601251
iter  30 value 85.935382
iter  40 value 84.343065
iter  50 value 83.712150
iter  60 value 83.047267
iter  70 value 82.689891
iter  80 value 82.561505
iter  90 value 82.300050
iter 100 value 80.713785
final  value 80.713785 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.548976 
iter  10 value 94.186472
iter  20 value 87.174762
iter  30 value 85.735191
iter  40 value 85.067118
iter  50 value 84.491837
iter  60 value 83.055534
iter  70 value 82.758782
iter  80 value 82.528516
iter  90 value 81.579596
iter 100 value 80.865218
final  value 80.865218 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.492614 
iter  10 value 94.167915
iter  20 value 93.700846
iter  30 value 91.147107
iter  40 value 86.611588
iter  50 value 85.343990
iter  60 value 82.761942
iter  70 value 80.907327
iter  80 value 80.623421
iter  90 value 80.406832
iter 100 value 80.394268
final  value 80.394268 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.584708 
iter  10 value 94.094493
iter  20 value 93.895140
iter  30 value 86.735391
iter  40 value 85.612671
iter  50 value 84.604933
iter  60 value 83.167052
iter  70 value 81.175396
iter  80 value 80.416434
iter  90 value 79.367794
iter 100 value 78.984687
final  value 78.984687 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.443565 
iter  10 value 94.494110
iter  20 value 88.938565
iter  30 value 86.666463
iter  40 value 84.323300
iter  50 value 82.619924
iter  60 value 81.998071
iter  70 value 81.534221
iter  80 value 79.941150
iter  90 value 79.341946
iter 100 value 79.189261
final  value 79.189261 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.915849 
iter  10 value 94.087905
iter  20 value 94.014152
iter  30 value 86.970784
iter  40 value 84.637173
iter  50 value 84.315113
iter  60 value 83.441374
iter  70 value 81.201579
iter  80 value 80.260622
iter  90 value 80.183159
iter 100 value 79.957286
final  value 79.957286 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.667649 
final  value 94.054451 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.637153 
final  value 94.054517 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.544541 
iter  10 value 94.012991
final  value 94.012086 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.055760 
final  value 94.054502 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.869153 
iter  10 value 92.709801
iter  20 value 87.763995
iter  30 value 84.226198
iter  40 value 83.674423
iter  50 value 83.554406
iter  60 value 83.506566
final  value 83.506414 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.043875 
iter  10 value 93.668784
iter  20 value 93.653837
iter  30 value 93.651838
iter  40 value 93.651260
iter  50 value 93.567996
iter  60 value 93.539235
iter  70 value 90.460594
iter  80 value 88.526351
iter  90 value 88.436263
iter 100 value 87.543064
final  value 87.543064 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.345013 
iter  10 value 94.016825
iter  20 value 94.012252
final  value 94.011781 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.721498 
iter  10 value 94.057045
iter  20 value 87.068007
iter  30 value 86.889834
final  value 86.889501 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.555891 
iter  10 value 94.058011
iter  20 value 93.691391
iter  30 value 87.072021
iter  40 value 85.679185
iter  50 value 83.526772
iter  60 value 83.519718
iter  70 value 83.238036
iter  80 value 81.302180
iter  90 value 80.600237
iter 100 value 79.442537
final  value 79.442537 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.843010 
iter  10 value 93.974589
iter  20 value 93.969800
iter  30 value 93.969291
iter  40 value 93.878577
iter  50 value 86.906730
iter  60 value 86.278523
iter  70 value 85.724871
iter  80 value 84.803493
iter  90 value 84.762838
iter 100 value 84.761336
final  value 84.761336 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.159159 
iter  10 value 94.060953
iter  20 value 94.045319
iter  30 value 90.292085
iter  40 value 83.948522
iter  50 value 81.130040
iter  60 value 79.752652
iter  70 value 79.733124
iter  80 value 79.730377
iter  90 value 79.727160
iter 100 value 79.522275
final  value 79.522275 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.549755 
iter  10 value 94.061032
iter  20 value 94.042240
iter  30 value 88.130102
final  value 86.796574 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.083688 
iter  10 value 93.527513
iter  20 value 92.602205
iter  30 value 92.600212
iter  40 value 92.599159
iter  50 value 92.596164
iter  60 value 92.595301
iter  70 value 92.594475
iter  80 value 92.564496
iter  90 value 91.746103
iter 100 value 83.950704
final  value 83.950704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.083491 
iter  10 value 94.016648
iter  20 value 94.008078
iter  30 value 92.622772
iter  40 value 92.502680
final  value 92.498519 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.098475 
iter  10 value 93.856844
iter  20 value 93.803314
iter  30 value 93.800089
iter  40 value 92.568376
iter  50 value 92.435393
iter  60 value 92.434314
final  value 92.434069 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.814977 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.128086 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.710057 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.758982 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.340864 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.298707 
final  value 91.651099 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.517406 
iter  10 value 94.147191
final  value 94.147184 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.000701 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.177965 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.558898 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.814397 
iter  10 value 91.651293
final  value 91.651099 
converged
Fitting Repeat 2 

# weights:  507
initial  value 126.543880 
iter  10 value 93.830744
final  value 93.818219 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.091202 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.436207 
iter  10 value 94.147732
final  value 94.144480 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.040571 
iter  10 value 94.016464
iter  20 value 93.653396
iter  30 value 93.652152
final  value 93.652150 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.290920 
iter  10 value 94.486490
iter  20 value 93.749645
iter  30 value 93.727955
iter  40 value 93.723129
iter  50 value 93.722303
iter  60 value 93.721933
iter  70 value 93.721319
iter  80 value 93.333743
iter  90 value 87.905608
iter 100 value 87.643212
final  value 87.643212 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.915201 
iter  10 value 94.488545
iter  20 value 93.729236
iter  30 value 93.600887
iter  40 value 89.927994
iter  50 value 89.420133
iter  60 value 88.115041
iter  70 value 87.825585
iter  80 value 82.134730
iter  90 value 81.299969
iter 100 value 79.547951
final  value 79.547951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.905582 
iter  10 value 94.490550
iter  20 value 94.403840
iter  30 value 94.382572
iter  40 value 94.370895
iter  50 value 94.041183
iter  60 value 93.835103
iter  70 value 93.727597
iter  80 value 86.945328
iter  90 value 85.425978
iter 100 value 84.217295
final  value 84.217295 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.793142 
iter  10 value 92.623235
iter  20 value 83.660708
iter  30 value 82.221728
iter  40 value 82.079871
iter  50 value 80.959484
iter  60 value 80.448968
iter  70 value 79.683555
iter  80 value 79.454331
final  value 79.454292 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.524192 
iter  10 value 89.090315
iter  20 value 84.629155
iter  30 value 84.210450
iter  40 value 83.589100
iter  50 value 83.171734
iter  60 value 83.162745
final  value 83.162356 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.338583 
iter  10 value 89.119981
iter  20 value 87.278260
iter  30 value 86.724344
iter  40 value 82.786888
iter  50 value 81.275969
iter  60 value 80.187751
iter  70 value 79.370942
iter  80 value 78.874015
iter  90 value 78.804879
iter 100 value 78.427355
final  value 78.427355 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.911808 
iter  10 value 94.763572
iter  20 value 94.524188
iter  30 value 92.706875
iter  40 value 88.264925
iter  50 value 84.031783
iter  60 value 81.692257
iter  70 value 80.112627
iter  80 value 79.530187
iter  90 value 79.225684
iter 100 value 79.073821
final  value 79.073821 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.125502 
iter  10 value 89.511161
iter  20 value 86.709349
iter  30 value 84.626347
iter  40 value 82.861989
iter  50 value 82.705485
iter  60 value 81.592980
iter  70 value 81.299881
iter  80 value 80.405239
iter  90 value 79.857452
iter 100 value 79.738289
final  value 79.738289 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.097948 
iter  10 value 94.480633
iter  20 value 88.509074
iter  30 value 84.316687
iter  40 value 84.090727
iter  50 value 83.382391
iter  60 value 80.896771
iter  70 value 79.805395
iter  80 value 79.569907
iter  90 value 79.276939
iter 100 value 79.264358
final  value 79.264358 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.260081 
iter  10 value 94.420023
iter  20 value 85.498471
iter  30 value 82.230902
iter  40 value 81.274267
iter  50 value 80.764237
iter  60 value 79.827089
iter  70 value 79.564202
iter  80 value 79.223161
iter  90 value 78.457820
iter 100 value 77.968347
final  value 77.968347 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.872133 
iter  10 value 94.286675
iter  20 value 85.216556
iter  30 value 82.461945
iter  40 value 80.513917
iter  50 value 80.169410
iter  60 value 79.910919
iter  70 value 78.518108
iter  80 value 78.190385
iter  90 value 78.157980
iter 100 value 78.080731
final  value 78.080731 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.377825 
iter  10 value 96.353538
iter  20 value 90.206976
iter  30 value 83.526481
iter  40 value 81.470854
iter  50 value 79.567634
iter  60 value 79.104717
iter  70 value 78.849062
iter  80 value 78.734720
iter  90 value 78.633214
iter 100 value 78.579379
final  value 78.579379 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.860801 
iter  10 value 94.477377
iter  20 value 93.745262
iter  30 value 91.539100
iter  40 value 85.947047
iter  50 value 82.068352
iter  60 value 81.317761
iter  70 value 80.862228
iter  80 value 79.887378
iter  90 value 79.357688
iter 100 value 79.112701
final  value 79.112701 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.093318 
iter  10 value 94.739065
iter  20 value 93.194578
iter  30 value 88.519579
iter  40 value 87.645624
iter  50 value 87.414106
iter  60 value 82.371707
iter  70 value 81.844171
iter  80 value 81.574781
iter  90 value 80.581967
iter 100 value 79.215257
final  value 79.215257 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.324335 
iter  10 value 94.304890
iter  20 value 90.081385
iter  30 value 87.986917
iter  40 value 84.630756
iter  50 value 83.489885
iter  60 value 83.056980
iter  70 value 82.659354
iter  80 value 82.354656
iter  90 value 80.237358
iter 100 value 79.883054
final  value 79.883054 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.009324 
final  value 94.486084 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.961574 
iter  10 value 94.485984
final  value 94.484406 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.475507 
final  value 94.485938 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.981824 
final  value 94.485897 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.303918 
iter  10 value 94.485914
iter  20 value 94.484227
iter  30 value 91.665053
iter  40 value 91.655467
iter  50 value 91.652912
iter  60 value 82.528034
iter  70 value 82.354286
iter  80 value 82.338415
iter  90 value 82.331561
final  value 82.331526 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.266682 
iter  10 value 94.489464
iter  20 value 94.455475
iter  30 value 92.300750
iter  40 value 84.744629
iter  50 value 81.287406
final  value 81.227555 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.181398 
iter  10 value 94.487496
iter  20 value 94.359883
iter  30 value 92.430235
iter  40 value 85.955063
final  value 85.955017 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.172883 
iter  10 value 94.152174
iter  20 value 93.342867
iter  30 value 91.654865
iter  40 value 86.041331
iter  50 value 81.828508
iter  60 value 81.767124
iter  70 value 81.755377
iter  80 value 81.754821
final  value 81.753832 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.485950 
iter  10 value 85.821315
iter  20 value 85.368486
iter  30 value 84.861637
iter  40 value 84.821975
iter  50 value 84.754926
iter  60 value 84.752814
iter  70 value 84.750801
iter  80 value 83.312787
iter  90 value 83.310973
iter 100 value 82.983234
final  value 82.983234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.749590 
iter  10 value 94.490424
iter  20 value 94.485229
iter  20 value 94.485229
iter  20 value 94.485229
final  value 94.485229 
converged
Fitting Repeat 1 

# weights:  507
initial  value 135.707477 
iter  10 value 94.492533
iter  20 value 94.456871
iter  30 value 86.149060
iter  40 value 85.960384
iter  50 value 85.959489
iter  60 value 82.363548
iter  70 value 82.360712
iter  80 value 82.323042
iter  90 value 79.851727
iter 100 value 78.193471
final  value 78.193471 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.231624 
iter  10 value 94.492205
iter  20 value 94.482641
iter  30 value 85.786154
iter  40 value 81.757597
iter  50 value 81.738315
iter  60 value 81.737429
iter  70 value 81.556996
iter  80 value 80.932592
iter  90 value 80.881510
iter 100 value 80.878536
final  value 80.878536 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.713733 
iter  10 value 93.667838
iter  20 value 93.653611
iter  30 value 93.652346
final  value 93.652078 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.133471 
iter  10 value 93.361044
iter  20 value 91.268534
iter  30 value 91.074148
iter  40 value 90.907373
iter  50 value 90.905644
iter  60 value 85.003349
iter  70 value 81.831495
iter  80 value 81.830625
iter  90 value 81.762418
iter 100 value 81.762127
final  value 81.762127 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.987565 
iter  10 value 84.592356
iter  20 value 82.359129
iter  30 value 82.334907
iter  40 value 80.964761
iter  50 value 80.282169
iter  60 value 80.012117
iter  70 value 80.010609
iter  80 value 80.004689
iter  90 value 79.939474
iter 100 value 79.939100
final  value 79.939100 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.374636 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.942628 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.256425 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.973368 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.697915 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.702934 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.551776 
iter  10 value 93.729814
iter  10 value 93.729814
iter  10 value 93.729814
final  value 93.729814 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.618326 
final  value 94.008695 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.980852 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.488614 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.269968 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.273629 
final  value 93.962011 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.500508 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.579054 
final  value 93.288889 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.231326 
final  value 93.271094 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.823741 
iter  10 value 94.057133
iter  20 value 94.030395
iter  30 value 92.537930
iter  40 value 85.924847
iter  50 value 83.668382
iter  60 value 83.048096
iter  70 value 82.423750
iter  80 value 82.215055
iter  90 value 82.093227
iter 100 value 82.059526
final  value 82.059526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.339179 
iter  10 value 94.026893
iter  20 value 93.586031
iter  30 value 84.305201
iter  40 value 83.354832
iter  50 value 82.303615
iter  60 value 82.098941
iter  70 value 81.865264
final  value 81.847485 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.409726 
iter  10 value 93.997442
iter  20 value 83.513632
iter  30 value 82.181132
iter  40 value 82.074668
iter  50 value 81.332831
iter  60 value 81.090294
iter  70 value 81.035316
final  value 81.021488 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.715733 
iter  10 value 94.016662
iter  20 value 92.253908
iter  30 value 83.763816
iter  40 value 82.445785
iter  50 value 82.149000
iter  60 value 81.882120
iter  70 value 81.847517
final  value 81.847485 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.239375 
iter  10 value 89.352032
iter  20 value 86.848820
iter  30 value 83.041987
iter  40 value 82.456868
iter  50 value 81.356468
iter  60 value 81.272322
iter  70 value 81.182906
iter  80 value 81.075857
iter  90 value 81.008607
final  value 81.008600 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.324455 
iter  10 value 94.065446
iter  20 value 93.878256
iter  30 value 84.731509
iter  40 value 82.427282
iter  50 value 82.251370
iter  60 value 82.085240
iter  70 value 81.323798
iter  80 value 80.879316
iter  90 value 79.306007
iter 100 value 79.102329
final  value 79.102329 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.928024 
iter  10 value 94.027817
iter  20 value 93.650624
iter  30 value 86.224909
iter  40 value 83.266686
iter  50 value 80.466625
iter  60 value 79.931236
iter  70 value 79.798189
iter  80 value 79.507669
iter  90 value 79.213312
iter 100 value 78.977391
final  value 78.977391 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.411990 
iter  10 value 94.338926
iter  20 value 94.128073
iter  30 value 93.696979
iter  40 value 82.575132
iter  50 value 82.241529
iter  60 value 82.097943
iter  70 value 81.506351
iter  80 value 80.776827
iter  90 value 79.501541
iter 100 value 79.444961
final  value 79.444961 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.812121 
iter  10 value 94.071485
iter  20 value 87.547095
iter  30 value 84.602825
iter  40 value 83.475246
iter  50 value 80.704114
iter  60 value 79.201434
iter  70 value 79.025936
iter  80 value 78.493119
iter  90 value 78.012446
iter 100 value 77.505192
final  value 77.505192 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.765504 
iter  10 value 94.056567
iter  20 value 93.223821
iter  30 value 86.205623
iter  40 value 85.769487
iter  50 value 81.321939
iter  60 value 80.865025
iter  70 value 80.076664
iter  80 value 79.502322
iter  90 value 79.017693
iter 100 value 78.884058
final  value 78.884058 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.065248 
iter  10 value 93.490633
iter  20 value 88.659657
iter  30 value 87.073846
iter  40 value 86.444485
iter  50 value 83.225242
iter  60 value 81.940849
iter  70 value 81.393451
iter  80 value 81.115007
iter  90 value 80.619610
iter 100 value 79.523929
final  value 79.523929 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.544338 
iter  10 value 94.337061
iter  20 value 88.881895
iter  30 value 85.996485
iter  40 value 84.885938
iter  50 value 83.426031
iter  60 value 80.270733
iter  70 value 79.928914
iter  80 value 79.542143
iter  90 value 79.290846
iter 100 value 79.007264
final  value 79.007264 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.634298 
iter  10 value 93.547417
iter  20 value 85.017481
iter  30 value 82.169482
iter  40 value 79.462446
iter  50 value 78.961079
iter  60 value 78.934176
iter  70 value 78.739164
iter  80 value 78.540175
iter  90 value 78.401163
iter 100 value 78.350178
final  value 78.350178 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.095535 
iter  10 value 95.211480
iter  20 value 94.056677
iter  30 value 93.863010
iter  40 value 85.198807
iter  50 value 82.412540
iter  60 value 81.136226
iter  70 value 80.849252
iter  80 value 79.759797
iter  90 value 79.623736
iter 100 value 78.369745
final  value 78.369745 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.047913 
iter  10 value 95.666848
iter  20 value 85.776864
iter  30 value 84.035317
iter  40 value 82.768281
iter  50 value 81.440004
iter  60 value 80.161271
iter  70 value 78.887406
iter  80 value 78.394508
iter  90 value 77.886765
iter 100 value 77.406665
final  value 77.406665 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.596118 
final  value 94.054326 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.737072 
final  value 94.054414 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.854964 
iter  10 value 91.832271
iter  20 value 91.831925
final  value 91.831922 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.184719 
iter  10 value 87.239483
iter  20 value 86.550493
iter  30 value 86.521179
iter  40 value 86.520300
iter  50 value 85.888488
iter  60 value 85.667790
final  value 85.667778 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.492047 
final  value 94.054404 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.293992 
iter  10 value 94.014119
iter  20 value 94.010238
iter  30 value 94.008803
iter  30 value 94.008803
iter  30 value 94.008803
final  value 94.008803 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.328646 
iter  10 value 94.057979
iter  20 value 94.052787
iter  30 value 93.836464
iter  40 value 84.842694
iter  50 value 84.832057
iter  50 value 84.832057
iter  50 value 84.832057
final  value 84.832057 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.443955 
iter  10 value 94.013576
iter  20 value 94.009261
final  value 94.008820 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.832255 
iter  10 value 94.013948
iter  20 value 93.922782
iter  30 value 85.473313
iter  40 value 84.123536
iter  50 value 84.093652
final  value 84.093430 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.061028 
iter  10 value 94.057026
iter  20 value 94.004326
iter  30 value 89.266096
iter  40 value 89.114442
iter  50 value 89.112604
iter  60 value 84.720260
iter  70 value 84.392961
iter  80 value 84.386974
iter  90 value 83.252175
iter 100 value 82.627088
final  value 82.627088 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.760575 
iter  10 value 93.945550
iter  20 value 92.706478
iter  30 value 92.275781
iter  40 value 92.271553
iter  50 value 92.270070
iter  60 value 92.102291
iter  70 value 92.096908
iter  80 value 90.394867
iter  90 value 90.362417
iter 100 value 90.362248
final  value 90.362248 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.336479 
iter  10 value 94.061258
iter  20 value 94.046725
iter  30 value 89.172690
iter  40 value 84.843520
final  value 84.843404 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.089140 
iter  10 value 86.479641
iter  20 value 85.052518
iter  30 value 84.869962
iter  40 value 83.194528
iter  50 value 82.033517
iter  60 value 81.810347
iter  70 value 81.793254
iter  80 value 81.783667
final  value 81.783665 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.581488 
iter  10 value 93.950176
iter  20 value 93.291831
iter  30 value 91.516374
iter  40 value 91.464570
iter  50 value 90.363112
iter  60 value 85.123674
iter  70 value 80.761629
iter  80 value 78.387817
iter  90 value 78.013799
iter 100 value 78.013090
final  value 78.013090 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.557591 
iter  10 value 92.657856
iter  20 value 91.839490
iter  30 value 91.783916
iter  40 value 91.586804
iter  50 value 90.884277
iter  60 value 90.710087
iter  70 value 90.699367
iter  80 value 90.696538
iter  90 value 88.016953
iter 100 value 81.762985
final  value 81.762985 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.580385 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.402782 
iter  10 value 94.275363
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.162729 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.960761 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.734184 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.407738 
final  value 94.477594 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.625929 
iter  10 value 94.059604
iter  20 value 92.959774
iter  30 value 90.733066
iter  40 value 90.724292
iter  50 value 89.138355
iter  60 value 88.215583
iter  70 value 88.136174
iter  80 value 88.135437
final  value 88.135435 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.001138 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.359053 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.720216 
final  value 93.637385 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.205943 
iter  10 value 93.660267
final  value 93.558233 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.396027 
iter  10 value 84.858174
iter  20 value 84.425460
iter  30 value 84.424647
iter  40 value 84.028183
final  value 84.027007 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.003089 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.333203 
iter  10 value 92.725857
iter  20 value 88.799584
iter  30 value 88.744636
iter  40 value 88.728690
final  value 88.728592 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.388066 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.199703 
iter  10 value 94.488587
iter  20 value 92.745944
iter  30 value 88.699687
iter  40 value 87.963573
iter  50 value 87.008781
iter  60 value 86.567001
iter  70 value 86.265752
iter  80 value 86.099009
iter  90 value 84.147541
iter 100 value 83.349045
final  value 83.349045 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.138008 
iter  10 value 94.416864
iter  20 value 91.378788
iter  30 value 88.575190
iter  40 value 87.967642
iter  50 value 85.948929
iter  60 value 85.686461
iter  70 value 85.607794
iter  80 value 85.593605
final  value 85.592439 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.657496 
iter  10 value 94.765782
iter  20 value 94.488541
iter  30 value 88.996485
iter  40 value 85.067958
iter  50 value 84.438199
iter  60 value 84.409362
iter  70 value 84.373680
iter  80 value 84.354593
final  value 84.354589 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.163969 
iter  10 value 93.826799
iter  20 value 93.627918
iter  30 value 93.585155
iter  40 value 93.522361
iter  50 value 92.205214
iter  60 value 87.601158
iter  70 value 85.044087
iter  80 value 84.041806
iter  90 value 83.945716
iter 100 value 83.889314
final  value 83.889314 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.929918 
iter  10 value 94.470660
iter  20 value 93.726412
iter  30 value 93.551506
iter  40 value 91.385092
iter  50 value 88.163342
iter  60 value 84.623911
iter  70 value 84.089129
iter  80 value 83.432246
iter  90 value 83.201464
iter 100 value 83.143786
final  value 83.143786 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.575489 
iter  10 value 91.271188
iter  20 value 87.442848
iter  30 value 86.945269
iter  40 value 86.794962
iter  50 value 86.410449
iter  60 value 86.015333
iter  70 value 83.910071
iter  80 value 83.894082
iter  90 value 83.836647
iter 100 value 83.570780
final  value 83.570780 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 126.535510 
iter  10 value 94.356928
iter  20 value 87.732317
iter  30 value 86.883340
iter  40 value 84.846186
iter  50 value 83.744619
iter  60 value 83.136269
iter  70 value 82.814187
iter  80 value 82.118048
iter  90 value 81.758384
iter 100 value 81.675080
final  value 81.675080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.006455 
iter  10 value 94.503661
iter  20 value 91.881962
iter  30 value 86.862930
iter  40 value 85.921423
iter  50 value 85.312339
iter  60 value 84.936138
iter  70 value 83.786389
iter  80 value 83.165083
iter  90 value 82.092427
iter 100 value 81.738249
final  value 81.738249 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.921474 
iter  10 value 94.460312
iter  20 value 93.672527
iter  30 value 92.249937
iter  40 value 87.646302
iter  50 value 83.645531
iter  60 value 83.209823
iter  70 value 82.244083
iter  80 value 81.613788
iter  90 value 81.437122
iter 100 value 81.228183
final  value 81.228183 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.410983 
iter  10 value 94.558278
iter  20 value 90.655073
iter  30 value 89.096605
iter  40 value 86.572091
iter  50 value 85.353811
iter  60 value 82.950048
iter  70 value 82.461968
iter  80 value 81.899987
iter  90 value 81.640296
iter 100 value 81.471982
final  value 81.471982 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.788091 
iter  10 value 94.015270
iter  20 value 91.687747
iter  30 value 87.992409
iter  40 value 84.846724
iter  50 value 82.792194
iter  60 value 81.957404
iter  70 value 81.724627
iter  80 value 81.589518
iter  90 value 81.312559
iter 100 value 81.184761
final  value 81.184761 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.518173 
iter  10 value 91.888103
iter  20 value 87.911517
iter  30 value 85.109267
iter  40 value 84.354133
iter  50 value 83.271778
iter  60 value 82.423487
iter  70 value 81.857872
iter  80 value 81.560399
iter  90 value 81.313544
iter 100 value 81.179818
final  value 81.179818 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.118265 
iter  10 value 95.182512
iter  20 value 91.868292
iter  30 value 88.205897
iter  40 value 85.864570
iter  50 value 83.542760
iter  60 value 83.268433
iter  70 value 82.709076
iter  80 value 81.576589
iter  90 value 81.139837
iter 100 value 80.911304
final  value 80.911304 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.793646 
iter  10 value 94.752626
iter  20 value 87.467153
iter  30 value 85.249386
iter  40 value 84.573272
iter  50 value 84.390304
iter  60 value 84.059629
iter  70 value 83.300469
iter  80 value 82.477393
iter  90 value 81.789469
iter 100 value 81.666315
final  value 81.666315 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.214104 
iter  10 value 94.538970
iter  20 value 90.194637
iter  30 value 88.477008
iter  40 value 85.692674
iter  50 value 84.957873
iter  60 value 84.599648
iter  70 value 83.623169
iter  80 value 83.090472
iter  90 value 82.839932
iter 100 value 82.784143
final  value 82.784143 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.011711 
final  value 94.485882 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.261405 
final  value 94.485937 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.783958 
final  value 94.485987 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.113550 
final  value 94.485828 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.744251 
final  value 94.485727 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.985509 
iter  10 value 94.287484
iter  20 value 93.642414
iter  30 value 93.392007
iter  40 value 86.674574
iter  50 value 85.226589
iter  60 value 84.591614
iter  70 value 84.508114
iter  80 value 84.500711
final  value 84.500597 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.951458 
iter  10 value 94.280404
iter  20 value 94.087348
final  value 94.083851 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.304493 
iter  10 value 94.489083
iter  20 value 94.484502
iter  30 value 93.917581
iter  40 value 93.559094
final  value 93.558973 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.470243 
iter  10 value 94.488542
iter  20 value 92.404934
iter  30 value 89.652406
iter  40 value 89.625154
iter  50 value 89.609297
final  value 89.606282 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.283351 
iter  10 value 94.488419
iter  20 value 94.484231
final  value 94.484212 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.445764 
iter  10 value 93.566745
iter  20 value 93.487271
iter  30 value 93.410100
final  value 93.410085 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.528041 
iter  10 value 94.283918
iter  20 value 93.453576
iter  30 value 84.557973
iter  40 value 83.464858
iter  50 value 83.456389
iter  60 value 83.452957
iter  70 value 83.451659
iter  80 value 83.446536
iter  90 value 83.429374
iter 100 value 83.306837
final  value 83.306837 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.654405 
iter  10 value 94.491794
iter  20 value 92.359959
iter  30 value 85.262492
iter  40 value 84.662688
iter  50 value 83.559674
iter  60 value 83.344908
iter  70 value 82.771346
iter  80 value 81.689534
iter  90 value 80.202160
iter 100 value 79.832074
final  value 79.832074 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.502951 
iter  10 value 94.283847
iter  20 value 94.279107
iter  30 value 93.696543
iter  40 value 93.531973
iter  50 value 93.312914
final  value 93.312911 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.999508 
iter  10 value 94.493038
iter  20 value 90.643586
iter  30 value 86.014095
iter  40 value 85.998396
iter  50 value 85.971033
iter  60 value 85.958601
iter  70 value 85.956034
iter  80 value 85.939971
final  value 85.939862 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.468890 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.626491 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.503876 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.626152 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  103
initial  value 125.156509 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.197343 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.332993 
iter  10 value 88.195545
iter  20 value 86.191992
iter  30 value 85.644478
final  value 85.611688 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.375213 
final  value 94.354395 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.118104 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.526848 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.765899 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.299452 
final  value 94.484212 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.723783 
iter  10 value 93.584739
iter  20 value 93.454643
iter  30 value 93.413611
final  value 93.413550 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.928686 
iter  10 value 94.206208
final  value 94.206005 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.133977 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.381208 
iter  10 value 94.455448
iter  20 value 89.612273
iter  30 value 88.927446
iter  40 value 88.183403
iter  50 value 86.954228
iter  60 value 86.703432
iter  70 value 86.681461
final  value 86.681457 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.331892 
iter  10 value 94.456435
iter  20 value 94.153021
iter  30 value 94.143353
iter  40 value 94.142239
iter  50 value 94.141496
iter  60 value 88.353874
iter  70 value 87.441061
iter  80 value 86.430817
iter  90 value 85.908634
iter 100 value 85.861987
final  value 85.861987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.461464 
iter  10 value 94.195022
iter  20 value 89.093385
iter  30 value 87.306077
iter  40 value 86.251387
iter  50 value 85.739001
iter  60 value 85.639248
iter  70 value 85.098596
iter  80 value 85.011040
final  value 85.010973 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.153665 
iter  10 value 94.482535
iter  20 value 93.336895
iter  30 value 89.477532
iter  40 value 88.331984
iter  50 value 86.855625
iter  60 value 85.593564
iter  70 value 84.719420
iter  80 value 83.902771
iter  90 value 83.800209
iter 100 value 83.786379
final  value 83.786379 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.181270 
iter  10 value 94.466213
iter  20 value 90.907715
iter  30 value 89.320255
iter  40 value 89.175411
iter  50 value 89.119380
iter  60 value 89.075010
iter  70 value 86.245228
iter  80 value 85.286185
iter  90 value 85.012136
iter 100 value 84.398046
final  value 84.398046 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.717926 
iter  10 value 93.298192
iter  20 value 87.535073
iter  30 value 85.798778
iter  40 value 85.051346
iter  50 value 83.757655
iter  60 value 83.323085
iter  70 value 83.141615
iter  80 value 82.913739
iter  90 value 82.778039
iter 100 value 82.717875
final  value 82.717875 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.838749 
iter  10 value 91.984093
iter  20 value 86.572734
iter  30 value 84.257859
iter  40 value 83.644935
iter  50 value 83.442850
iter  60 value 83.252339
iter  70 value 83.181820
iter  80 value 82.857474
iter  90 value 82.551277
iter 100 value 82.492943
final  value 82.492943 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.101559 
iter  10 value 94.422181
iter  20 value 90.276769
iter  30 value 88.317829
iter  40 value 86.205629
iter  50 value 84.920673
iter  60 value 84.450593
iter  70 value 84.153513
iter  80 value 84.105011
iter  90 value 84.092770
iter 100 value 84.074344
final  value 84.074344 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.129653 
iter  10 value 94.453039
iter  20 value 90.150906
iter  30 value 86.698710
iter  40 value 85.766232
iter  50 value 84.989242
iter  60 value 83.676674
iter  70 value 83.179641
iter  80 value 82.885171
iter  90 value 82.803834
iter 100 value 82.789240
final  value 82.789240 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.318201 
iter  10 value 94.783398
iter  20 value 94.454402
iter  30 value 93.925397
iter  40 value 93.319224
iter  50 value 92.883936
iter  60 value 90.548131
iter  70 value 89.551598
iter  80 value 87.501660
iter  90 value 84.059766
iter 100 value 83.595578
final  value 83.595578 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.945437 
iter  10 value 94.385019
iter  20 value 88.655667
iter  30 value 86.509016
iter  40 value 84.744347
iter  50 value 83.841963
iter  60 value 83.068230
iter  70 value 82.885823
iter  80 value 82.824874
iter  90 value 82.671110
iter 100 value 82.526874
final  value 82.526874 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.779098 
iter  10 value 95.012550
iter  20 value 94.499374
iter  30 value 94.254366
iter  40 value 87.584465
iter  50 value 86.546878
iter  60 value 86.151462
iter  70 value 85.788951
iter  80 value 85.120602
iter  90 value 83.795897
iter 100 value 83.047585
final  value 83.047585 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.762603 
iter  10 value 94.534336
iter  20 value 92.420265
iter  30 value 88.342614
iter  40 value 86.741440
iter  50 value 86.424987
iter  60 value 85.220316
iter  70 value 83.788346
iter  80 value 83.663172
iter  90 value 83.472337
iter 100 value 83.091223
final  value 83.091223 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.289113 
iter  10 value 91.705869
iter  20 value 87.251867
iter  30 value 86.831776
iter  40 value 86.201594
iter  50 value 85.797348
iter  60 value 85.326016
iter  70 value 84.988598
iter  80 value 84.955932
iter  90 value 83.910002
iter 100 value 83.513140
final  value 83.513140 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.277041 
iter  10 value 94.480091
iter  20 value 91.859266
iter  30 value 88.790104
iter  40 value 85.425971
iter  50 value 84.349479
iter  60 value 83.438408
iter  70 value 83.294802
iter  80 value 83.096172
iter  90 value 82.785233
iter 100 value 82.594640
final  value 82.594640 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.143466 
iter  10 value 94.485998
iter  20 value 94.484196
iter  30 value 94.144876
final  value 94.144862 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.066938 
final  value 94.485993 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.889786 
final  value 94.485800 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.496174 
final  value 94.485911 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.989463 
final  value 94.485809 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.744544 
iter  10 value 94.489358
iter  20 value 94.310829
iter  30 value 93.512578
iter  40 value 93.485229
iter  50 value 93.483193
final  value 93.483187 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.600486 
iter  10 value 94.489488
iter  20 value 94.484507
iter  30 value 90.275101
iter  40 value 88.520161
iter  50 value 86.795482
iter  60 value 86.637080
iter  70 value 86.607340
iter  80 value 86.466291
iter  90 value 83.102269
iter 100 value 82.702820
final  value 82.702820 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.896148 
iter  10 value 94.359245
iter  20 value 94.208689
iter  30 value 88.142602
final  value 88.090129 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.062421 
iter  10 value 94.331305
iter  20 value 93.911608
iter  30 value 87.891689
iter  40 value 87.860703
iter  50 value 87.859990
iter  60 value 87.858747
final  value 87.858740 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.780566 
iter  10 value 94.484440
iter  20 value 92.921015
iter  30 value 92.896234
iter  40 value 92.895381
final  value 92.895342 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.911503 
iter  10 value 94.331549
iter  20 value 94.324706
final  value 94.323323 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.003036 
iter  10 value 94.492257
iter  20 value 94.358099
iter  30 value 87.860517
iter  40 value 87.574663
iter  50 value 85.657016
iter  60 value 84.544131
iter  70 value 82.333515
iter  80 value 82.089572
iter  90 value 82.049382
iter 100 value 82.033331
final  value 82.033331 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.680023 
iter  10 value 94.219063
iter  20 value 91.634246
iter  30 value 87.599302
iter  40 value 86.429322
iter  50 value 85.802358
iter  60 value 85.802139
iter  70 value 85.801258
iter  80 value 85.799900
final  value 85.799449 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.928136 
iter  10 value 94.221325
iter  20 value 94.214058
iter  30 value 93.723707
iter  40 value 93.381182
final  value 93.281460 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.127007 
iter  10 value 94.492241
iter  20 value 92.546129
iter  30 value 88.626435
iter  40 value 88.193654
iter  50 value 88.186531
iter  60 value 88.165345
iter  70 value 88.163265
iter  80 value 88.161447
iter  90 value 88.136895
iter 100 value 88.135370
final  value 88.135370 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 123.067415 
iter  10 value 118.020515
iter  20 value 114.852512
iter  30 value 109.717073
iter  40 value 107.095349
iter  50 value 106.888848
iter  60 value 103.524953
iter  70 value 103.145911
iter  80 value 102.889059
iter  90 value 102.382084
iter 100 value 101.922955
final  value 101.922955 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.604107 
iter  10 value 117.574546
iter  20 value 108.284772
iter  30 value 106.815933
iter  40 value 105.808168
iter  50 value 105.562066
iter  60 value 105.524234
iter  70 value 105.477500
iter  80 value 105.332891
iter  90 value 105.282990
iter 100 value 104.351066
final  value 104.351066 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 135.453277 
iter  10 value 117.570370
iter  20 value 114.642661
iter  30 value 105.386782
iter  40 value 102.348299
iter  50 value 101.568756
iter  60 value 101.358518
iter  70 value 100.972830
iter  80 value 100.882381
iter  90 value 100.797949
iter 100 value 100.623999
final  value 100.623999 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 131.136635 
iter  10 value 118.429495
iter  20 value 113.026740
iter  30 value 107.518160
iter  40 value 106.219855
iter  50 value 103.609568
iter  60 value 102.503551
iter  70 value 101.968326
iter  80 value 101.723277
iter  90 value 101.629337
iter 100 value 101.615125
final  value 101.615125 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.281597 
iter  10 value 117.899698
iter  20 value 111.851389
iter  30 value 108.906746
iter  40 value 108.381208
iter  50 value 106.942765
iter  60 value 106.235699
iter  70 value 103.101265
iter  80 value 102.617793
iter  90 value 101.633458
iter 100 value 101.220192
final  value 101.220192 
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 -- Fri Nov 28 02:20:25 2025 
*********************************************** 
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 
 44.711   1.834  81.211