##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-20 r89666)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-03-21 03:22:36 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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 ... 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       18.354  0.306  19.493
FSmethod      18.063  0.274  19.217
corr_plot     17.944  0.279  18.991
pred_ensembel  7.103  0.313   6.784
enrichfindP    0.299  0.075   8.367
* 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: 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/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** 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) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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 94.748800 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.951044 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.516119 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.679860 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.573678 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 93.976661 
iter  10 value 85.844516
iter  20 value 85.787372
iter  30 value 85.288804
final  value 85.274205 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.737774 
iter  10 value 93.547776
iter  20 value 93.540600
final  value 93.540563 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.478867 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.709358 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.205171 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.417296 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.266783 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 127.937198 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.635307 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.170134 
iter  10 value 92.822295
iter  20 value 92.011357
final  value 92.011232 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.283705 
iter  10 value 93.364993
iter  20 value 84.827512
iter  30 value 82.865642
iter  40 value 82.612995
iter  50 value 82.253444
iter  60 value 82.008245
iter  70 value 81.924639
iter  80 value 81.774326
iter  90 value 81.500467
iter 100 value 81.361148
final  value 81.361148 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.150195 
iter  10 value 94.054862
iter  10 value 94.054861
iter  20 value 93.016751
iter  30 value 88.681528
iter  40 value 87.046741
iter  50 value 86.717129
iter  60 value 86.526033
iter  70 value 86.314697
iter  80 value 85.825613
iter  90 value 85.628376
final  value 85.622108 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.548676 
iter  10 value 93.669559
iter  20 value 92.238856
iter  30 value 86.793617
iter  40 value 85.531222
iter  50 value 85.286244
iter  60 value 85.229345
iter  70 value 84.803050
iter  80 value 83.614574
iter  90 value 82.625285
iter 100 value 82.166514
final  value 82.166514 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.972806 
iter  10 value 93.201050
iter  20 value 90.594952
iter  30 value 90.060319
iter  40 value 87.068640
iter  50 value 85.532900
iter  60 value 85.408280
iter  70 value 83.776298
iter  80 value 83.525858
final  value 83.524310 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.754488 
iter  10 value 94.055273
iter  20 value 93.835001
iter  30 value 88.037626
iter  40 value 86.307905
iter  50 value 84.868088
iter  60 value 83.511031
iter  70 value 83.375814
final  value 83.375604 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.895588 
iter  10 value 94.060561
iter  20 value 89.245418
iter  30 value 85.162880
iter  40 value 82.908418
iter  50 value 82.064716
iter  60 value 81.719990
iter  70 value 81.572130
iter  80 value 81.129181
iter  90 value 80.761777
iter 100 value 80.334311
final  value 80.334311 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.791160 
iter  10 value 94.090618
iter  20 value 93.617043
iter  30 value 90.846818
iter  40 value 85.961227
iter  50 value 85.705249
iter  60 value 85.449587
iter  70 value 85.295314
iter  80 value 84.533429
iter  90 value 81.145783
iter 100 value 80.268261
final  value 80.268261 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.505901 
iter  10 value 94.071364
iter  20 value 90.056089
iter  30 value 89.419623
iter  40 value 88.831256
iter  50 value 86.998737
iter  60 value 83.365637
iter  70 value 82.823650
iter  80 value 81.521939
iter  90 value 80.544257
iter 100 value 80.180412
final  value 80.180412 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 128.350703 
iter  10 value 94.268405
iter  20 value 92.098604
iter  30 value 85.279335
iter  40 value 84.695897
iter  50 value 84.457516
iter  60 value 83.848713
iter  70 value 82.032151
iter  80 value 80.990400
iter  90 value 80.694857
iter 100 value 80.446828
final  value 80.446828 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.015572 
iter  10 value 93.965271
iter  20 value 91.183583
iter  30 value 85.350324
iter  40 value 84.019154
iter  50 value 82.430518
iter  60 value 81.327413
iter  70 value 81.134516
iter  80 value 80.673682
iter  90 value 80.229422
iter 100 value 80.064557
final  value 80.064557 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.218565 
iter  10 value 94.072364
iter  20 value 94.012485
iter  30 value 92.121683
iter  40 value 88.831441
iter  50 value 86.830223
iter  60 value 86.143401
iter  70 value 83.193648
iter  80 value 81.609515
iter  90 value 81.267878
iter 100 value 80.737022
final  value 80.737022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.755271 
iter  10 value 89.612771
iter  20 value 86.952938
iter  30 value 86.095109
iter  40 value 82.962274
iter  50 value 81.526013
iter  60 value 80.812194
iter  70 value 80.696150
iter  80 value 80.424189
iter  90 value 80.346249
iter 100 value 80.167876
final  value 80.167876 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.499702 
iter  10 value 93.936031
iter  20 value 88.738997
iter  30 value 83.570804
iter  40 value 82.348483
iter  50 value 81.439815
iter  60 value 81.130022
iter  70 value 80.506916
iter  80 value 80.367248
iter  90 value 80.266441
iter 100 value 80.204199
final  value 80.204199 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.674344 
iter  10 value 96.768183
iter  20 value 96.343888
iter  30 value 85.038384
iter  40 value 83.228273
iter  50 value 82.951355
iter  60 value 82.510882
iter  70 value 81.712213
iter  80 value 80.732548
iter  90 value 80.538451
iter 100 value 80.287591
final  value 80.287591 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.063155 
iter  10 value 93.925183
iter  20 value 93.044829
iter  30 value 89.550477
iter  40 value 84.942328
iter  50 value 82.344787
iter  60 value 81.894707
iter  70 value 81.615604
iter  80 value 81.519849
iter  90 value 80.712727
iter 100 value 80.063157
final  value 80.063157 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.984345 
final  value 94.054506 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.217285 
iter  10 value 94.039776
iter  20 value 94.038397
final  value 94.038263 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.932600 
final  value 94.054497 
converged
Fitting Repeat 4 

# weights:  103
initial  value 117.381142 
iter  10 value 94.054470
iter  20 value 90.621663
iter  30 value 88.106965
iter  40 value 88.104559
iter  50 value 88.104094
iter  60 value 88.102686
iter  70 value 87.758557
iter  80 value 87.244702
iter  90 value 87.237830
final  value 87.237822 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.309540 
final  value 93.606512 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.316004 
iter  10 value 94.058171
iter  20 value 94.053110
final  value 94.053098 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.673663 
iter  10 value 94.043053
iter  20 value 94.032420
iter  30 value 93.831776
iter  40 value 93.477988
iter  50 value 93.477287
final  value 93.476985 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.307750 
iter  10 value 94.057403
iter  20 value 94.052841
iter  30 value 93.604774
iter  40 value 84.801862
iter  50 value 84.621415
iter  60 value 84.110689
iter  70 value 83.541780
iter  80 value 83.138189
iter  90 value 83.136691
iter 100 value 83.136143
final  value 83.136143 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.121307 
iter  10 value 94.057450
iter  20 value 94.017420
iter  30 value 93.429065
iter  40 value 83.359613
iter  50 value 82.451264
iter  60 value 79.296447
iter  70 value 78.577274
iter  80 value 78.532751
iter  90 value 78.529523
iter 100 value 78.526735
final  value 78.526735 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.571922 
iter  10 value 94.043286
iter  20 value 94.038294
final  value 94.038270 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.646662 
iter  10 value 94.059757
iter  20 value 94.052745
iter  30 value 94.050554
iter  40 value 94.046838
iter  50 value 93.971585
iter  60 value 93.557870
iter  70 value 93.529383
iter  80 value 93.528558
iter  90 value 93.527982
iter 100 value 93.526258
final  value 93.526258 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.883312 
iter  10 value 94.046216
iter  20 value 93.989435
iter  30 value 93.578961
final  value 93.578828 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.608773 
iter  10 value 93.545416
iter  20 value 93.520728
iter  30 value 93.499760
iter  40 value 84.403848
iter  50 value 83.348765
iter  60 value 83.344215
iter  70 value 83.342786
iter  80 value 83.307161
iter  90 value 83.305903
iter 100 value 83.196662
final  value 83.196662 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.095568 
iter  10 value 94.047003
iter  20 value 90.183812
iter  30 value 83.442124
iter  40 value 83.313611
iter  50 value 83.288303
iter  60 value 83.283144
iter  70 value 83.166583
iter  80 value 83.102008
iter  90 value 83.100311
iter 100 value 83.099034
final  value 83.099034 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.892890 
iter  10 value 94.017055
iter  20 value 93.999537
iter  30 value 93.995739
final  value 93.995737 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.079866 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.134428 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.463952 
final  value 94.214007 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.545362 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.741691 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.067049 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.029002 
iter  10 value 94.300637
final  value 94.289860 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.703280 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.123929 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.982866 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.032862 
final  value 94.443245 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.325718 
iter  10 value 94.225944
iter  20 value 93.874355
iter  30 value 92.899689
final  value 92.890121 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.191828 
final  value 94.213041 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.352597 
final  value 94.264859 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.685253 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.932336 
iter  10 value 94.486408
iter  20 value 93.886659
iter  30 value 86.766615
iter  40 value 83.242308
iter  50 value 82.910162
iter  60 value 82.827822
iter  70 value 82.695869
iter  80 value 82.654778
iter  80 value 82.654778
final  value 82.654778 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.873987 
iter  10 value 94.336280
iter  20 value 92.880476
iter  30 value 90.991928
iter  40 value 83.219788
iter  50 value 82.404897
iter  60 value 82.061020
iter  70 value 81.876051
iter  80 value 81.620167
final  value 81.611575 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.949610 
iter  10 value 94.472707
iter  20 value 92.787617
iter  30 value 86.243288
iter  40 value 85.739964
iter  50 value 85.502786
iter  60 value 85.283447
iter  70 value 84.345755
iter  80 value 82.451495
iter  90 value 82.334745
iter 100 value 82.333584
final  value 82.333584 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.164044 
iter  10 value 94.151764
iter  20 value 84.404648
iter  30 value 84.222769
iter  40 value 82.813798
iter  50 value 82.690109
iter  60 value 82.604403
iter  70 value 82.599726
iter  70 value 82.599725
iter  70 value 82.599725
final  value 82.599725 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.168256 
iter  10 value 94.472405
iter  20 value 94.237024
iter  30 value 93.332124
iter  40 value 91.013034
iter  50 value 90.889319
iter  60 value 90.882418
iter  70 value 84.162348
iter  80 value 82.510408
iter  90 value 82.223191
iter 100 value 81.963656
final  value 81.963656 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.857952 
iter  10 value 94.369747
iter  20 value 91.234723
iter  30 value 86.253591
iter  40 value 84.072534
iter  50 value 82.106958
iter  60 value 81.961243
iter  70 value 81.873175
iter  80 value 81.014329
iter  90 value 80.306492
iter 100 value 80.221587
final  value 80.221587 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.538416 
iter  10 value 94.462849
iter  20 value 93.465672
iter  30 value 89.301642
iter  40 value 88.264809
iter  50 value 86.495884
iter  60 value 85.426488
iter  70 value 85.048172
iter  80 value 85.019935
iter  90 value 84.987004
iter 100 value 83.757537
final  value 83.757537 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.410154 
iter  10 value 87.705223
iter  20 value 84.313490
iter  30 value 84.070515
iter  40 value 82.839602
iter  50 value 81.656289
iter  60 value 80.968230
iter  70 value 80.792194
iter  80 value 80.605845
iter  90 value 80.399742
iter 100 value 80.370846
final  value 80.370846 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.851784 
iter  10 value 94.616131
iter  20 value 88.278817
iter  30 value 84.062559
iter  40 value 83.342520
iter  50 value 82.778041
iter  60 value 82.642759
iter  70 value 82.500038
iter  80 value 82.263993
iter  90 value 81.608567
iter 100 value 80.497587
final  value 80.497587 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.467717 
iter  10 value 86.937040
iter  20 value 85.318464
iter  30 value 83.981445
iter  40 value 83.736395
iter  50 value 83.649569
iter  60 value 82.683024
iter  70 value 82.083351
iter  80 value 81.948593
iter  90 value 81.571319
iter 100 value 80.990938
final  value 80.990938 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.197025 
iter  10 value 94.423222
iter  20 value 91.997190
iter  30 value 87.475626
iter  40 value 84.437879
iter  50 value 82.969408
iter  60 value 82.801631
iter  70 value 82.176892
iter  80 value 81.733607
iter  90 value 81.328548
iter 100 value 80.955433
final  value 80.955433 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.390358 
iter  10 value 90.007704
iter  20 value 83.988631
iter  30 value 83.475224
iter  40 value 83.315960
iter  50 value 82.875518
iter  60 value 82.615088
iter  70 value 82.480498
iter  80 value 82.224086
iter  90 value 81.690756
iter 100 value 81.281645
final  value 81.281645 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.951951 
iter  10 value 91.615205
iter  20 value 85.800721
iter  30 value 84.695423
iter  40 value 81.735440
iter  50 value 80.940074
iter  60 value 80.540442
iter  70 value 80.455485
iter  80 value 80.346641
iter  90 value 80.241356
iter 100 value 80.119780
final  value 80.119780 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.689109 
iter  10 value 94.503470
iter  20 value 85.968353
iter  30 value 83.827637
iter  40 value 81.953747
iter  50 value 81.193502
iter  60 value 80.784511
iter  70 value 80.530071
iter  80 value 80.348698
iter  90 value 80.066641
iter 100 value 79.825888
final  value 79.825888 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.110161 
iter  10 value 95.410244
iter  20 value 93.245874
iter  30 value 83.802830
iter  40 value 83.394277
iter  50 value 81.373279
iter  60 value 80.789855
iter  70 value 80.578780
iter  80 value 80.481654
iter  90 value 80.258055
iter 100 value 80.098098
final  value 80.098098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.800658 
final  value 94.485878 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.135830 
final  value 94.485860 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.629596 
iter  10 value 94.445096
iter  20 value 94.404373
iter  30 value 92.617025
iter  30 value 92.617025
iter  30 value 92.617025
final  value 92.617025 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.993422 
final  value 94.485846 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.298774 
final  value 94.485820 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.596657 
iter  10 value 94.489123
iter  20 value 94.464786
iter  30 value 93.974166
iter  40 value 93.906696
iter  50 value 93.899467
iter  60 value 93.895581
final  value 93.895491 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.094908 
iter  10 value 94.448099
iter  20 value 94.444893
final  value 94.444658 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.172629 
iter  10 value 94.448405
iter  20 value 94.443506
iter  30 value 88.560419
iter  40 value 87.710663
iter  50 value 84.239366
iter  60 value 81.111620
iter  70 value 81.104215
final  value 81.104212 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.203788 
iter  10 value 94.489197
iter  20 value 94.484258
iter  30 value 94.460912
iter  40 value 93.954041
iter  50 value 93.942583
final  value 93.942466 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.174656 
iter  10 value 94.448364
iter  20 value 94.300548
iter  30 value 86.340033
iter  40 value 86.332330
final  value 86.332327 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.197770 
iter  10 value 93.860391
iter  20 value 84.453610
iter  30 value 84.094244
iter  40 value 84.093187
iter  50 value 84.069327
iter  60 value 83.813885
iter  70 value 83.794416
iter  80 value 83.792833
iter  90 value 83.792141
final  value 83.791654 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.226596 
iter  10 value 91.550995
iter  20 value 88.297045
iter  30 value 87.239909
iter  40 value 84.464279
iter  50 value 84.278579
iter  60 value 84.275517
iter  70 value 82.210496
iter  80 value 81.591731
final  value 81.591322 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.664214 
iter  10 value 94.461478
iter  20 value 94.122424
iter  30 value 94.083576
iter  40 value 93.679751
iter  50 value 93.678290
iter  60 value 93.674435
iter  70 value 93.643227
iter  80 value 85.282474
iter  90 value 83.987047
iter 100 value 83.914659
final  value 83.914659 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.775137 
iter  10 value 92.609882
iter  20 value 92.297695
iter  30 value 92.243675
iter  40 value 84.457240
iter  50 value 84.418394
iter  60 value 84.418125
iter  70 value 82.667499
iter  80 value 80.890517
iter  90 value 79.913148
iter 100 value 79.896450
final  value 79.896450 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.224462 
iter  10 value 94.451744
iter  20 value 94.444819
iter  30 value 94.443406
iter  30 value 94.443406
iter  30 value 94.443406
final  value 94.443406 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.197754 
final  value 93.897214 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.664706 
iter  10 value 85.598264
iter  20 value 82.319592
final  value 82.319398 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.084910 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.323781 
iter  10 value 90.473409
final  value 90.467799 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.953947 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.136090 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.217053 
final  value 93.897214 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.553716 
iter  10 value 94.052948
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.624532 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.883175 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.480110 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.245455 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.979207 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.413274 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.025609 
iter  10 value 94.036058
final  value 94.032972 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.536996 
iter  10 value 93.904437
iter  20 value 91.062703
iter  30 value 90.328705
iter  40 value 89.321987
iter  50 value 83.199646
iter  60 value 81.940801
iter  70 value 81.815571
iter  80 value 80.968064
iter  90 value 79.518704
iter 100 value 79.426469
final  value 79.426469 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.919600 
iter  10 value 94.046282
iter  20 value 83.241430
iter  30 value 81.382340
iter  40 value 80.589893
iter  50 value 79.983752
iter  60 value 79.525600
iter  70 value 79.187514
iter  80 value 79.180481
final  value 79.180477 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.519841 
iter  10 value 94.056843
iter  20 value 94.023879
iter  30 value 83.509280
iter  40 value 81.020316
iter  50 value 79.860911
iter  60 value 79.595507
iter  70 value 79.269249
iter  80 value 79.174302
final  value 79.174006 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.715176 
iter  10 value 94.056315
iter  20 value 91.965948
iter  30 value 85.546705
iter  40 value 84.190822
iter  50 value 83.574530
iter  60 value 82.537680
iter  70 value 82.452923
final  value 82.452920 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.744826 
iter  10 value 94.056764
iter  20 value 94.054974
iter  30 value 93.956573
iter  40 value 89.366407
iter  50 value 89.126355
iter  60 value 88.887168
iter  70 value 88.845135
final  value 88.844818 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.818651 
iter  10 value 94.039313
iter  20 value 90.672078
iter  30 value 88.401116
iter  40 value 80.775118
iter  50 value 79.917893
iter  60 value 79.591967
iter  70 value 78.654152
iter  80 value 77.904433
iter  90 value 77.301337
iter 100 value 77.128970
final  value 77.128970 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.922126 
iter  10 value 94.063245
iter  20 value 89.633169
iter  30 value 83.315691
iter  40 value 81.141694
iter  50 value 80.064404
iter  60 value 78.070535
iter  70 value 77.542791
iter  80 value 77.359381
iter  90 value 76.965111
iter 100 value 76.706344
final  value 76.706344 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.015029 
iter  10 value 94.119981
iter  20 value 82.066298
iter  30 value 81.473531
iter  40 value 81.291479
iter  50 value 80.910170
iter  60 value 80.574983
iter  70 value 79.741287
iter  80 value 78.571252
iter  90 value 77.685990
iter 100 value 77.461313
final  value 77.461313 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.690964 
iter  10 value 94.178103
iter  20 value 90.817228
iter  30 value 82.700277
iter  40 value 80.728084
iter  50 value 78.115947
iter  60 value 77.411196
iter  70 value 77.322290
iter  80 value 77.293868
iter  90 value 77.035514
iter 100 value 76.733537
final  value 76.733537 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.971191 
iter  10 value 93.974815
iter  20 value 86.197664
iter  30 value 84.453268
iter  40 value 82.390570
iter  50 value 81.973672
iter  60 value 81.324705
iter  70 value 81.059306
iter  80 value 80.641843
iter  90 value 79.676659
iter 100 value 78.260511
final  value 78.260511 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.789682 
iter  10 value 93.967870
iter  20 value 91.834917
iter  30 value 84.739363
iter  40 value 81.263868
iter  50 value 79.897086
iter  60 value 79.142550
iter  70 value 77.974966
iter  80 value 77.147670
iter  90 value 77.081461
iter 100 value 76.952068
final  value 76.952068 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.071709 
iter  10 value 93.811579
iter  20 value 83.635223
iter  30 value 82.132679
iter  40 value 79.487112
iter  50 value 78.202202
iter  60 value 77.730672
iter  70 value 77.617256
iter  80 value 77.481288
iter  90 value 77.425010
iter 100 value 77.229699
final  value 77.229699 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.260198 
iter  10 value 94.496942
iter  20 value 90.102834
iter  30 value 84.257694
iter  40 value 80.549475
iter  50 value 80.154255
iter  60 value 79.353447
iter  70 value 79.206026
iter  80 value 79.154230
iter  90 value 78.972092
iter 100 value 78.058244
final  value 78.058244 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.846557 
iter  10 value 96.006527
iter  20 value 94.046662
iter  30 value 92.267338
iter  40 value 89.016459
iter  50 value 85.473344
iter  60 value 80.901167
iter  70 value 79.015093
iter  80 value 77.909222
iter  90 value 77.503818
iter 100 value 76.992784
final  value 76.992784 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.020664 
iter  10 value 94.024997
iter  20 value 90.548991
iter  30 value 83.039735
iter  40 value 80.881606
iter  50 value 80.423175
iter  60 value 80.178819
iter  70 value 79.242306
iter  80 value 78.661624
iter  90 value 78.413093
iter 100 value 77.621727
final  value 77.621727 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.259402 
iter  10 value 94.054746
iter  20 value 94.052919
iter  20 value 94.052919
iter  20 value 94.052919
final  value 94.052919 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.842710 
final  value 94.034710 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.111655 
final  value 94.054531 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.362903 
final  value 94.054379 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.869285 
iter  10 value 94.054734
final  value 94.053143 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.347648 
iter  10 value 94.057651
iter  20 value 94.053230
iter  30 value 93.965342
iter  40 value 93.024356
iter  50 value 92.768794
iter  60 value 87.469612
iter  70 value 83.188538
iter  80 value 82.333163
iter  90 value 82.332252
final  value 82.329359 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.225042 
iter  10 value 90.849834
iter  20 value 88.582981
iter  30 value 88.205443
iter  40 value 88.093583
iter  50 value 88.093248
iter  60 value 83.472078
iter  70 value 80.255844
iter  80 value 79.879648
iter  90 value 79.877855
iter 100 value 79.875183
final  value 79.875183 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.493618 
iter  10 value 93.902111
iter  20 value 93.702943
iter  30 value 86.639038
iter  40 value 80.872405
iter  50 value 80.552442
iter  60 value 80.544359
iter  70 value 80.543119
iter  80 value 80.540911
final  value 80.540693 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.236287 
iter  10 value 94.057769
iter  20 value 93.210737
iter  30 value 86.927570
final  value 86.926889 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.251214 
iter  10 value 94.057732
iter  20 value 94.053126
iter  30 value 94.000395
iter  40 value 89.110707
iter  50 value 86.871322
iter  60 value 84.087931
iter  70 value 82.496668
iter  80 value 82.433362
iter  90 value 82.431307
iter 100 value 82.360209
final  value 82.360209 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.136772 
iter  10 value 94.041591
iter  20 value 94.035437
iter  30 value 83.693636
iter  40 value 81.824171
final  value 81.820665 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.529065 
iter  10 value 94.046439
iter  20 value 94.024103
iter  30 value 88.723630
iter  40 value 87.618061
iter  50 value 87.613489
iter  60 value 83.286042
iter  70 value 80.850115
iter  80 value 80.424588
iter  90 value 80.412045
iter 100 value 80.091981
final  value 80.091981 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.250513 
iter  10 value 93.693514
iter  20 value 93.590200
iter  30 value 93.108683
iter  40 value 92.925259
iter  50 value 92.925061
iter  60 value 92.924217
iter  70 value 92.594274
iter  80 value 82.801977
iter  90 value 81.376415
iter 100 value 79.248211
final  value 79.248211 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.783148 
iter  10 value 87.980223
iter  20 value 86.197954
iter  30 value 86.188681
iter  40 value 86.137279
iter  50 value 86.134718
iter  60 value 86.128710
iter  70 value 81.996625
final  value 81.996339 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.468441 
iter  10 value 93.288141
iter  20 value 93.283377
iter  30 value 93.251514
iter  40 value 91.060622
iter  50 value 81.441350
iter  60 value 80.098921
iter  70 value 79.405285
iter  80 value 79.154042
iter  90 value 78.438620
iter 100 value 78.438333
final  value 78.438333 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.772166 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.813201 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.269871 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.063694 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.373196 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.261352 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.860800 
final  value 94.477594 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.993892 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.906262 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.700298 
iter  10 value 94.057659
final  value 94.049334 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.227975 
iter  10 value 87.902965
iter  20 value 87.591261
iter  30 value 87.590738
iter  30 value 87.590738
final  value 87.590733 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.114896 
iter  10 value 94.026573
final  value 94.026547 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.174664 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.464874 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.445358 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.394112 
iter  10 value 94.449741
iter  20 value 90.475231
iter  30 value 87.380202
iter  40 value 87.135752
iter  50 value 86.713303
iter  60 value 83.958583
iter  70 value 83.731664
iter  80 value 83.132053
iter  90 value 83.007369
iter 100 value 82.989565
final  value 82.989565 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 120.130009 
iter  10 value 94.290453
iter  20 value 87.010774
iter  30 value 86.698221
iter  40 value 85.961439
iter  50 value 85.019302
iter  60 value 84.867768
iter  70 value 84.853949
iter  80 value 84.805809
final  value 84.786763 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.410057 
iter  10 value 94.274740
iter  20 value 94.122840
iter  30 value 94.088074
iter  40 value 90.488696
iter  50 value 90.297872
iter  60 value 88.027398
iter  70 value 86.305921
iter  80 value 84.982151
iter  90 value 84.966572
iter 100 value 84.966445
final  value 84.966445 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.867315 
iter  10 value 94.486454
iter  20 value 94.278631
iter  30 value 94.108271
iter  40 value 87.237565
iter  50 value 85.886021
iter  60 value 85.730438
iter  70 value 85.036267
iter  80 value 84.516656
iter  90 value 83.075647
iter 100 value 82.995583
final  value 82.995583 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.376282 
iter  10 value 91.768765
iter  20 value 89.179064
iter  30 value 87.693448
iter  40 value 87.377417
iter  50 value 86.042792
iter  60 value 85.323911
iter  70 value 83.889785
iter  80 value 83.045458
iter  90 value 82.787495
final  value 82.785869 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.570004 
iter  10 value 94.130843
iter  20 value 92.477334
iter  30 value 86.704543
iter  40 value 85.118146
iter  50 value 83.984042
iter  60 value 83.605128
iter  70 value 82.840158
iter  80 value 82.465136
iter  90 value 82.297899
iter 100 value 82.150398
final  value 82.150398 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.945017 
iter  10 value 94.192689
iter  20 value 92.596704
iter  30 value 87.791022
iter  40 value 86.576485
iter  50 value 85.891134
iter  60 value 83.750741
iter  70 value 82.783339
iter  80 value 82.097770
iter  90 value 81.938154
iter 100 value 81.912843
final  value 81.912843 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.368389 
iter  10 value 94.517870
iter  20 value 94.501780
iter  30 value 94.071343
iter  40 value 86.859554
iter  50 value 86.644783
iter  60 value 85.437478
iter  70 value 83.592503
iter  80 value 81.879935
iter  90 value 81.526044
iter 100 value 81.327234
final  value 81.327234 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.573474 
iter  10 value 94.464209
iter  20 value 92.681544
iter  30 value 86.260197
iter  40 value 85.623138
iter  50 value 85.372632
iter  60 value 85.012621
iter  70 value 84.189600
iter  80 value 82.552328
iter  90 value 82.117450
iter 100 value 81.741611
final  value 81.741611 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.397180 
iter  10 value 94.411937
iter  20 value 88.719084
iter  30 value 86.083079
iter  40 value 83.654723
iter  50 value 83.122664
iter  60 value 82.483477
iter  70 value 82.410981
iter  80 value 82.148833
iter  90 value 81.770248
iter 100 value 81.357384
final  value 81.357384 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.415803 
iter  10 value 95.037413
iter  20 value 94.247550
iter  30 value 87.907868
iter  40 value 87.083546
iter  50 value 85.758611
iter  60 value 83.537877
iter  70 value 82.501534
iter  80 value 82.153226
iter  90 value 82.036948
iter 100 value 81.686425
final  value 81.686425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.542109 
iter  10 value 94.631358
iter  20 value 94.201339
iter  30 value 87.223008
iter  40 value 86.579372
iter  50 value 84.333766
iter  60 value 84.114783
iter  70 value 83.647035
iter  80 value 83.375465
iter  90 value 82.460811
iter 100 value 82.224573
final  value 82.224573 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.256736 
iter  10 value 94.426455
iter  20 value 92.868749
iter  30 value 86.696632
iter  40 value 86.007014
iter  50 value 85.501250
iter  60 value 85.233465
iter  70 value 85.001026
iter  80 value 84.615915
iter  90 value 84.048404
iter 100 value 83.863005
final  value 83.863005 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.254882 
iter  10 value 94.481364
iter  20 value 89.333383
iter  30 value 84.978846
iter  40 value 84.270415
iter  50 value 82.738150
iter  60 value 82.340514
iter  70 value 82.251825
iter  80 value 82.106930
iter  90 value 81.764279
iter 100 value 81.669220
final  value 81.669220 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.999521 
iter  10 value 94.602789
iter  20 value 91.869663
iter  30 value 87.110772
iter  40 value 84.927330
iter  50 value 83.625260
iter  60 value 83.152964
iter  70 value 82.475334
iter  80 value 81.666777
iter  90 value 81.292789
iter 100 value 81.192965
final  value 81.192965 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.686157 
final  value 94.485935 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.181392 
iter  10 value 94.485708
iter  20 value 94.484224
final  value 94.484222 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.910918 
final  value 94.485739 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.473773 
iter  10 value 94.106764
iter  10 value 94.106763
iter  10 value 94.106763
final  value 94.106763 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.709342 
final  value 94.486045 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.887259 
iter  10 value 94.488480
iter  20 value 93.975726
iter  30 value 91.943742
iter  40 value 91.590038
iter  50 value 91.586295
final  value 91.586214 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.431176 
iter  10 value 94.488542
iter  20 value 94.018798
iter  30 value 87.871825
iter  40 value 87.822188
iter  50 value 87.821927
iter  60 value 87.810664
iter  70 value 87.809638
iter  80 value 87.809291
iter  90 value 86.919473
final  value 86.861756 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.552932 
iter  10 value 94.488619
iter  20 value 93.996267
iter  30 value 87.260337
iter  40 value 85.050572
iter  50 value 85.047172
iter  60 value 84.960681
iter  70 value 84.959303
final  value 84.959056 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.708048 
iter  10 value 94.488823
iter  20 value 94.478468
iter  30 value 92.826929
iter  40 value 89.813929
iter  50 value 89.737597
iter  60 value 89.706311
iter  60 value 89.706311
iter  60 value 89.706311
final  value 89.706311 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.594075 
iter  10 value 94.488733
iter  20 value 94.484349
iter  30 value 93.595525
iter  40 value 92.351680
iter  50 value 92.349655
final  value 92.349647 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.153352 
iter  10 value 93.984178
iter  20 value 93.976391
iter  30 value 91.970651
iter  40 value 86.641983
iter  50 value 85.569228
iter  60 value 85.559343
iter  70 value 85.558270
iter  80 value 85.557912
iter  90 value 85.278690
iter 100 value 83.543553
final  value 83.543553 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.453255 
iter  10 value 94.492714
iter  20 value 94.153163
iter  30 value 88.672075
final  value 88.672071 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.826782 
iter  10 value 94.493304
iter  20 value 94.301709
iter  30 value 87.662635
final  value 87.538169 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.486645 
iter  10 value 94.328723
iter  20 value 93.202347
iter  30 value 91.500744
iter  40 value 91.500154
iter  50 value 85.773688
iter  60 value 85.257709
iter  70 value 85.086815
iter  80 value 84.288355
iter  90 value 84.153718
iter 100 value 84.094769
final  value 84.094769 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.432020 
iter  10 value 92.918778
iter  20 value 92.913712
iter  30 value 88.758332
iter  40 value 82.575499
iter  50 value 82.159814
iter  60 value 81.834457
iter  70 value 81.833674
final  value 81.833546 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.817254 
final  value 94.448052 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.736079 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.433267 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.814631 
iter  10 value 92.684741
final  value 92.613874 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.894462 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.151124 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.469586 
iter  10 value 94.142825
iter  20 value 93.826162
final  value 93.824259 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.087282 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.479851 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.689180 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.535846 
iter  10 value 91.136822
iter  20 value 90.070388
iter  30 value 89.987955
iter  40 value 89.984013
final  value 89.983981 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.992840 
iter  10 value 89.455715
iter  20 value 88.272946
iter  30 value 88.257303
iter  40 value 85.882716
iter  50 value 85.463048
iter  60 value 84.693513
iter  70 value 84.568689
iter  80 value 84.566807
final  value 84.566799 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.794765 
iter  10 value 94.015849
iter  20 value 93.745298
iter  20 value 93.745298
iter  20 value 93.745298
final  value 93.745298 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.278562 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.668892 
iter  10 value 94.425404
iter  20 value 88.948736
iter  30 value 87.872878
iter  40 value 87.855442
final  value 87.855346 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.447672 
iter  10 value 94.418983
iter  20 value 87.443810
iter  30 value 85.352183
iter  40 value 85.049359
iter  50 value 84.528499
iter  60 value 84.156223
iter  70 value 84.113702
final  value 84.106207 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.337295 
iter  10 value 94.488497
iter  20 value 94.486701
iter  30 value 94.140408
iter  40 value 94.126258
iter  50 value 93.949253
iter  60 value 88.247047
iter  70 value 86.577776
iter  80 value 86.255874
iter  90 value 85.080779
iter 100 value 82.548476
final  value 82.548476 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.607175 
iter  10 value 94.488445
iter  20 value 87.520970
iter  30 value 85.890806
iter  40 value 85.171181
iter  50 value 84.914704
iter  60 value 84.902213
iter  70 value 84.902151
iter  70 value 84.902151
iter  70 value 84.902151
final  value 84.902151 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.511252 
iter  10 value 93.946198
iter  20 value 84.436161
iter  30 value 83.529789
iter  40 value 83.133306
iter  50 value 82.411237
iter  60 value 81.498194
iter  70 value 81.413627
iter  80 value 81.408673
final  value 81.408367 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.517651 
iter  10 value 94.481628
iter  20 value 91.105184
iter  30 value 89.987088
iter  40 value 86.093349
iter  50 value 84.523555
iter  60 value 84.067345
iter  70 value 83.975137
final  value 83.975110 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.558519 
iter  10 value 94.404290
iter  20 value 86.791469
iter  30 value 86.003531
iter  40 value 84.592992
iter  50 value 83.580563
iter  60 value 83.399560
iter  70 value 82.855762
iter  80 value 82.111006
iter  90 value 81.153996
iter 100 value 80.092160
final  value 80.092160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.621892 
iter  10 value 93.463593
iter  20 value 86.810192
iter  30 value 86.326557
iter  40 value 85.634634
iter  50 value 83.687705
iter  60 value 83.005428
iter  70 value 82.085150
iter  80 value 80.888941
iter  90 value 80.192628
iter 100 value 80.051682
final  value 80.051682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.511028 
iter  10 value 93.655937
iter  20 value 84.340895
iter  30 value 83.064088
iter  40 value 82.652357
iter  50 value 82.586951
iter  60 value 81.837118
iter  70 value 81.548650
iter  80 value 81.530271
iter  90 value 81.471687
iter 100 value 81.094766
final  value 81.094766 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.780520 
iter  10 value 94.497047
iter  20 value 93.217242
iter  30 value 86.666624
iter  40 value 85.315494
iter  50 value 82.697913
iter  60 value 81.660954
iter  70 value 81.143223
iter  80 value 80.732237
iter  90 value 80.536892
iter 100 value 80.485829
final  value 80.485829 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.292408 
iter  10 value 94.412889
iter  20 value 90.006124
iter  30 value 85.804974
iter  40 value 82.663456
iter  50 value 82.090260
iter  60 value 81.654321
iter  70 value 81.096417
iter  80 value 80.357128
iter  90 value 80.238510
iter 100 value 80.185038
final  value 80.185038 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.013004 
iter  10 value 92.659168
iter  20 value 87.109955
iter  30 value 86.655301
iter  40 value 85.999493
iter  50 value 83.166390
iter  60 value 82.809668
iter  70 value 82.308132
iter  80 value 82.230747
iter  90 value 81.115442
iter 100 value 80.878713
final  value 80.878713 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.043615 
iter  10 value 94.408332
iter  20 value 87.168529
iter  30 value 83.806843
iter  40 value 82.242132
iter  50 value 80.843035
iter  60 value 80.154572
iter  70 value 79.850842
iter  80 value 79.762270
iter  90 value 79.667633
iter 100 value 79.630063
final  value 79.630063 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.639899 
iter  10 value 94.597126
iter  20 value 93.983095
iter  30 value 89.106733
iter  40 value 85.629448
iter  50 value 85.332634
iter  60 value 84.343634
iter  70 value 82.797282
iter  80 value 82.409600
iter  90 value 81.187977
iter 100 value 80.079295
final  value 80.079295 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.606811 
iter  10 value 92.662536
iter  20 value 84.769902
iter  30 value 83.291003
iter  40 value 83.022017
iter  50 value 81.150193
iter  60 value 80.753461
iter  70 value 80.526999
iter  80 value 80.482477
iter  90 value 80.467992
iter 100 value 80.458811
final  value 80.458811 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.881484 
iter  10 value 94.263850
iter  20 value 87.686224
iter  30 value 86.204123
iter  40 value 84.769542
iter  50 value 83.764953
iter  60 value 82.950521
iter  70 value 81.723345
iter  80 value 80.532888
iter  90 value 80.395572
iter 100 value 80.341909
final  value 80.341909 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.141516 
final  value 94.485910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.118533 
iter  10 value 94.259863
iter  20 value 86.592446
iter  30 value 86.271969
iter  40 value 85.695786
final  value 85.695224 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.706299 
iter  10 value 89.324146
iter  20 value 86.030032
iter  30 value 85.853306
iter  40 value 85.841437
iter  50 value 85.838795
iter  60 value 85.506630
iter  70 value 84.640796
iter  80 value 83.705960
final  value 83.705947 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.998019 
final  value 94.483860 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.856321 
final  value 94.485833 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.527991 
iter  10 value 94.487699
iter  20 value 94.471457
final  value 93.931179 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.369763 
iter  10 value 94.489489
iter  20 value 94.484496
final  value 94.484226 
converged
Fitting Repeat 3 

# weights:  305
initial  value 122.298771 
iter  10 value 94.093870
iter  20 value 94.089629
iter  30 value 93.789213
iter  40 value 90.248773
iter  50 value 85.184109
iter  60 value 85.152936
iter  70 value 85.149694
iter  80 value 85.146577
iter  90 value 81.957579
iter 100 value 81.673574
final  value 81.673574 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.207784 
iter  10 value 93.813693
iter  20 value 93.810926
iter  30 value 93.795891
final  value 93.731067 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.009961 
iter  10 value 94.490872
iter  20 value 94.486103
iter  30 value 92.731845
iter  40 value 87.955229
iter  50 value 87.588146
iter  60 value 83.592076
iter  70 value 83.585848
final  value 83.585673 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.569017 
iter  10 value 94.034628
iter  20 value 94.028069
final  value 94.027197 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.403505 
iter  10 value 94.426162
iter  20 value 94.417524
iter  30 value 92.879154
iter  40 value 92.859633
iter  50 value 92.855929
iter  60 value 92.475153
iter  70 value 84.733377
iter  80 value 81.578065
iter  90 value 80.771731
iter 100 value 80.743769
final  value 80.743769 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.740361 
iter  10 value 94.491748
iter  20 value 94.480917
iter  30 value 92.429459
iter  40 value 90.640905
iter  50 value 90.516076
iter  60 value 90.511755
iter  70 value 90.277397
iter  80 value 90.222889
iter  90 value 90.222586
final  value 90.222093 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.291403 
iter  10 value 94.491996
iter  20 value 94.465834
iter  30 value 90.155294
iter  40 value 84.875215
iter  50 value 83.639583
iter  60 value 83.508476
iter  70 value 83.409487
iter  80 value 81.586775
iter  90 value 80.859492
iter 100 value 80.838530
final  value 80.838530 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.763915 
iter  10 value 94.492358
iter  20 value 94.460161
iter  30 value 84.263080
iter  40 value 82.902096
iter  50 value 81.226971
iter  60 value 80.656178
final  value 80.653115 
converged
Fitting Repeat 1 

# weights:  507
initial  value 153.988622 
final  value 117.890295 
converged
Fitting Repeat 2 

# weights:  507
initial  value 143.000851 
final  value 117.890295 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.263917 
final  value 117.890295 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.760159 
iter  10 value 105.366329
iter  20 value 105.270085
final  value 105.262380 
converged
Fitting Repeat 5 

# weights:  507
initial  value 139.609698 
final  value 117.890295 
converged
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 Mar 20 23:25:59 2026 
*********************************************** 
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 
 21.766   0.927  75.773