##############################################################################
##############################################################################
###
### 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) (2025-11-04 r88984)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    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
corr_plot     19.048  1.016  21.964
FSmethod      19.057  0.932  21.207
var_imp       18.534  0.963  21.099
pred_ensembel  6.691  0.108   6.598
enrichfindP    0.194  0.039  12.094
getFASTA       0.038  0.007   5.790
* 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-arm64/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) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 102.946652 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.686207 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.588228 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.569432 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 93.656250 
iter  10 value 90.475234
iter  20 value 88.532856
iter  30 value 87.629828
iter  40 value 87.366866
iter  50 value 87.270678
final  value 87.270480 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.316560 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.227217 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.794037 
final  value 93.890110 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.441172 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.860871 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.095007 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.850611 
iter  10 value 93.701380
iter  20 value 93.538180
iter  30 value 93.535690
final  value 93.535679 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.025844 
iter  10 value 93.627491
final  value 93.627345 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.679814 
iter  10 value 92.339619
iter  20 value 91.493218
iter  30 value 91.442859
final  value 91.439287 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.036835 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.352748 
iter  10 value 94.056983
iter  20 value 91.851535
iter  30 value 86.437552
iter  40 value 86.298787
iter  50 value 84.761499
iter  60 value 84.247544
iter  70 value 83.273028
iter  80 value 83.166363
iter  90 value 83.078987
final  value 83.071722 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.379104 
iter  10 value 93.967523
iter  20 value 88.174669
iter  30 value 87.505182
iter  40 value 87.336438
iter  50 value 86.886967
iter  60 value 86.701083
iter  70 value 84.814587
iter  80 value 84.596216
iter  90 value 84.595199
iter  90 value 84.595199
iter  90 value 84.595199
final  value 84.595199 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.938709 
iter  10 value 94.056749
iter  20 value 89.816259
iter  30 value 88.320196
iter  40 value 85.476471
iter  50 value 85.200694
iter  60 value 84.739396
iter  70 value 84.640077
iter  80 value 84.595446
final  value 84.595199 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.726715 
iter  10 value 94.056665
iter  20 value 93.895840
iter  30 value 93.891252
iter  40 value 93.889875
iter  50 value 93.468849
iter  60 value 90.465767
iter  70 value 89.936226
iter  80 value 88.291388
iter  90 value 85.964390
iter 100 value 84.937836
final  value 84.937836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.023286 
iter  10 value 94.057809
iter  20 value 93.932687
iter  30 value 92.052026
iter  40 value 89.465469
iter  50 value 87.332877
iter  60 value 87.218573
iter  70 value 87.037202
iter  80 value 84.840935
iter  90 value 84.598103
final  value 84.595199 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.170637 
iter  10 value 93.162870
iter  20 value 88.090481
iter  30 value 85.567264
iter  40 value 84.705057
iter  50 value 84.345927
iter  60 value 83.372381
iter  70 value 83.074330
iter  80 value 82.519645
iter  90 value 81.895666
iter 100 value 81.696074
final  value 81.696074 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.148366 
iter  10 value 94.015602
iter  20 value 87.797264
iter  30 value 86.923743
iter  40 value 86.107337
iter  50 value 84.240403
iter  60 value 82.404592
iter  70 value 82.049275
iter  80 value 81.753611
iter  90 value 81.681943
iter 100 value 81.612377
final  value 81.612377 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.280726 
iter  10 value 94.057554
iter  20 value 88.131964
iter  30 value 86.104631
iter  40 value 83.336614
iter  50 value 82.255598
iter  60 value 81.883678
iter  70 value 81.709459
iter  80 value 81.624001
iter  90 value 81.597410
iter 100 value 81.481609
final  value 81.481609 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.701267 
iter  10 value 94.050291
iter  20 value 92.316603
iter  30 value 87.500128
iter  40 value 85.959906
iter  50 value 84.884024
iter  60 value 84.337508
iter  70 value 83.559449
iter  80 value 83.371338
iter  90 value 83.068740
iter 100 value 82.872905
final  value 82.872905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.467570 
iter  10 value 93.980061
iter  20 value 93.910841
iter  30 value 87.579522
iter  40 value 85.286777
iter  50 value 84.634475
iter  60 value 84.219336
iter  70 value 82.745510
iter  80 value 81.970630
iter  90 value 81.925122
iter 100 value 81.823192
final  value 81.823192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.041760 
iter  10 value 98.638569
iter  20 value 89.060588
iter  30 value 83.978026
iter  40 value 83.305261
iter  50 value 82.785383
iter  60 value 82.029846
iter  70 value 81.829641
iter  80 value 81.666649
iter  90 value 81.487770
iter 100 value 81.432508
final  value 81.432508 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.213591 
iter  10 value 91.368006
iter  20 value 88.239424
iter  30 value 85.021155
iter  40 value 84.645475
iter  50 value 84.409788
iter  60 value 84.315007
iter  70 value 84.283419
iter  80 value 84.266814
iter  90 value 84.178305
iter 100 value 83.231664
final  value 83.231664 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.649952 
iter  10 value 94.192720
iter  20 value 90.571393
iter  30 value 90.009918
iter  40 value 84.308346
iter  50 value 83.907837
iter  60 value 83.786979
iter  70 value 82.431348
iter  80 value 81.737964
iter  90 value 81.655064
iter 100 value 81.601852
final  value 81.601852 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.995303 
iter  10 value 93.937912
iter  20 value 90.610599
iter  30 value 85.318792
iter  40 value 83.755973
iter  50 value 82.395159
iter  60 value 82.065016
iter  70 value 81.954063
iter  80 value 81.905999
iter  90 value 81.820501
iter 100 value 81.786089
final  value 81.786089 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.615472 
iter  10 value 95.201022
iter  20 value 90.140527
iter  30 value 84.164140
iter  40 value 82.351313
iter  50 value 82.105791
iter  60 value 82.024857
iter  70 value 81.996270
iter  80 value 81.909566
iter  90 value 81.752145
iter 100 value 81.609957
final  value 81.609957 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.295957 
final  value 94.054533 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.168348 
iter  10 value 93.837502
iter  20 value 93.837159
iter  30 value 93.836550
final  value 93.836157 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.604844 
final  value 93.837623 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.521642 
final  value 93.837659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.909155 
final  value 94.054299 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.950766 
iter  10 value 93.887825
iter  20 value 93.071245
iter  30 value 91.889074
iter  40 value 86.163870
iter  50 value 86.136096
iter  60 value 85.688150
iter  70 value 85.687026
iter  80 value 85.686697
iter  90 value 85.686139
iter 100 value 85.666920
final  value 85.666920 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.195671 
iter  10 value 94.056509
iter  20 value 93.930253
iter  30 value 86.860068
iter  40 value 84.660058
iter  50 value 84.092482
iter  60 value 82.144501
iter  70 value 82.075985
iter  80 value 82.070707
iter  90 value 82.069904
iter 100 value 82.066588
final  value 82.066588 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.757551 
iter  10 value 94.057315
iter  20 value 94.033606
iter  30 value 93.536746
iter  40 value 89.902428
iter  50 value 88.485398
iter  60 value 87.497859
iter  70 value 85.174766
iter  80 value 83.506246
iter  90 value 81.813081
iter 100 value 81.653919
final  value 81.653919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.787774 
iter  10 value 90.486731
iter  20 value 89.777839
iter  30 value 89.541587
iter  40 value 87.420298
iter  50 value 84.620546
iter  60 value 84.050849
iter  70 value 82.945884
iter  80 value 82.302941
iter  90 value 82.287476
final  value 82.287474 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.647999 
iter  10 value 93.943507
iter  20 value 93.875422
iter  30 value 93.873161
iter  40 value 93.310760
iter  50 value 93.033326
iter  60 value 93.030653
iter  70 value 91.747726
iter  80 value 85.579026
iter  90 value 85.559206
iter 100 value 85.558091
final  value 85.558091 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.993946 
iter  10 value 94.060811
iter  20 value 94.052562
iter  30 value 93.836955
iter  40 value 88.746527
iter  50 value 85.291132
iter  60 value 85.289992
iter  70 value 85.164058
iter  80 value 85.149925
final  value 85.149862 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.191729 
iter  10 value 94.061038
iter  20 value 94.042045
iter  30 value 86.342533
iter  40 value 83.729799
iter  50 value 83.727881
iter  60 value 83.718375
iter  70 value 83.717643
iter  80 value 83.716186
iter  90 value 83.174448
iter 100 value 83.157718
final  value 83.157718 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.455049 
iter  10 value 94.060612
iter  20 value 88.900159
iter  30 value 85.881878
iter  40 value 85.879884
iter  50 value 84.138489
iter  60 value 81.206514
iter  70 value 80.925674
final  value 80.925576 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.670455 
iter  10 value 94.060889
iter  20 value 93.943203
iter  30 value 86.762158
iter  40 value 86.338943
iter  50 value 86.291717
final  value 86.291055 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.292591 
iter  10 value 88.801781
iter  20 value 85.668312
iter  30 value 85.395854
iter  40 value 85.391098
iter  40 value 85.391098
final  value 85.391098 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.242755 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.820257 
final  value 94.144481 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.776406 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.065938 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.078792 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.236371 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 121.676305 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.235950 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.643639 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.546000 
iter  10 value 94.484215
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.788719 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.894679 
iter  10 value 93.676934
iter  20 value 93.641069
final  value 93.640744 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.271852 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.066574 
iter  10 value 93.424564
iter  20 value 93.330997
iter  20 value 93.330997
iter  20 value 93.330997
final  value 93.330997 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.016343 
iter  10 value 90.021266
iter  20 value 86.766926
iter  30 value 86.433422
iter  40 value 85.293482
iter  50 value 84.735829
iter  60 value 84.726526
iter  70 value 84.726135
final  value 84.726131 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.818022 
iter  10 value 94.486700
iter  20 value 93.932146
iter  30 value 93.695501
iter  40 value 93.681796
iter  50 value 92.812046
iter  60 value 89.822253
iter  70 value 88.998055
iter  80 value 85.835893
iter  90 value 85.297667
iter 100 value 84.743812
final  value 84.743812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.050095 
iter  10 value 95.477900
iter  20 value 94.487880
iter  30 value 93.775543
iter  40 value 93.722075
iter  50 value 93.321989
iter  60 value 87.312764
iter  70 value 85.485491
iter  80 value 84.786954
iter  90 value 84.614820
iter 100 value 84.481260
final  value 84.481260 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.873764 
iter  10 value 94.489513
iter  20 value 94.474797
iter  30 value 94.234546
iter  40 value 94.215971
iter  50 value 93.310125
iter  60 value 90.043484
iter  70 value 87.023393
iter  80 value 86.250387
iter  90 value 83.894309
iter 100 value 83.818428
final  value 83.818428 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.467331 
iter  10 value 94.482586
iter  20 value 93.803620
iter  30 value 93.686928
iter  40 value 93.685816
iter  50 value 93.613868
iter  60 value 86.046905
iter  70 value 84.492952
iter  80 value 84.360428
final  value 84.360399 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.889057 
iter  10 value 88.272385
iter  20 value 84.450299
iter  30 value 83.964727
iter  40 value 83.179918
iter  50 value 82.891181
iter  60 value 82.762323
iter  70 value 82.698293
final  value 82.698002 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.911338 
iter  10 value 94.201328
iter  20 value 94.122726
iter  30 value 88.703926
iter  40 value 86.100878
iter  50 value 83.633583
iter  60 value 82.856990
iter  70 value 82.744068
iter  80 value 82.508125
iter  90 value 82.260576
iter 100 value 82.060516
final  value 82.060516 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.013140 
iter  10 value 94.270931
iter  20 value 86.168013
iter  30 value 85.022519
iter  40 value 84.766964
iter  50 value 84.042972
iter  60 value 83.406803
iter  70 value 82.856623
iter  80 value 82.452976
iter  90 value 82.384171
iter 100 value 82.355189
final  value 82.355189 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.950937 
iter  10 value 94.509102
iter  20 value 93.700400
iter  30 value 85.192103
iter  40 value 84.919081
iter  50 value 84.357178
iter  60 value 83.801285
iter  70 value 83.374639
iter  80 value 83.192010
iter  90 value 82.683553
iter 100 value 82.379844
final  value 82.379844 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.387747 
iter  10 value 94.462532
iter  20 value 87.617367
iter  30 value 85.902688
iter  40 value 84.234288
iter  50 value 83.289546
iter  60 value 82.316515
iter  70 value 81.944185
iter  80 value 81.874930
iter  90 value 81.700591
iter 100 value 81.616034
final  value 81.616034 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.394969 
iter  10 value 94.935052
iter  20 value 91.405219
iter  30 value 86.554404
iter  40 value 86.119826
iter  50 value 85.732330
iter  60 value 85.584828
iter  70 value 84.948545
iter  80 value 84.552480
iter  90 value 83.547215
iter 100 value 83.322084
final  value 83.322084 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.977453 
iter  10 value 93.664304
iter  20 value 85.616299
iter  30 value 84.822509
iter  40 value 83.155375
iter  50 value 82.508638
iter  60 value 82.283424
iter  70 value 82.080483
iter  80 value 81.846583
iter  90 value 81.777745
iter 100 value 81.654964
final  value 81.654964 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.006478 
iter  10 value 94.613333
iter  20 value 94.074392
iter  30 value 85.891921
iter  40 value 85.203426
iter  50 value 84.961612
iter  60 value 83.763138
iter  70 value 82.517419
iter  80 value 81.834599
iter  90 value 81.597185
iter 100 value 81.553618
final  value 81.553618 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.376759 
iter  10 value 94.900860
iter  20 value 92.937381
iter  30 value 84.313236
iter  40 value 83.449603
iter  50 value 82.809635
iter  60 value 82.637499
iter  70 value 82.428603
iter  80 value 81.819095
iter  90 value 81.668264
iter 100 value 81.553109
final  value 81.553109 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.536982 
iter  10 value 94.510015
iter  20 value 93.790254
iter  30 value 93.713511
iter  40 value 91.742968
iter  50 value 83.979354
iter  60 value 83.053875
iter  70 value 82.623165
iter  80 value 82.551743
iter  90 value 82.321748
iter 100 value 82.061334
final  value 82.061334 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.686670 
iter  10 value 94.526202
iter  20 value 94.331540
iter  30 value 93.724849
iter  40 value 87.735462
iter  50 value 86.587295
iter  60 value 85.784754
iter  70 value 83.537867
iter  80 value 82.437161
iter  90 value 81.927652
iter 100 value 81.552330
final  value 81.552330 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.443870 
iter  10 value 94.485974
iter  20 value 94.103830
final  value 94.027717 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.889171 
final  value 94.485734 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.142018 
final  value 94.485836 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.155111 
final  value 94.485852 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.671936 
final  value 94.485836 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.288785 
iter  10 value 94.031870
iter  20 value 94.027087
iter  30 value 93.660196
iter  40 value 93.647894
iter  50 value 92.399148
iter  60 value 85.697161
iter  70 value 83.563299
iter  80 value 82.992282
iter  90 value 82.837563
iter 100 value 82.684634
final  value 82.684634 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.941732 
iter  10 value 94.499208
iter  20 value 94.340715
iter  30 value 94.036796
iter  40 value 93.916939
iter  50 value 93.556161
iter  60 value 93.549998
iter  70 value 93.486784
iter  80 value 93.476606
iter  90 value 84.757828
iter 100 value 82.900908
final  value 82.900908 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.873266 
iter  10 value 93.645849
iter  20 value 93.641259
iter  30 value 93.570488
iter  40 value 85.007692
iter  50 value 83.681952
iter  60 value 83.679436
iter  70 value 83.524126
iter  80 value 82.931830
iter  90 value 80.677411
iter 100 value 80.167806
final  value 80.167806 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.310761 
iter  10 value 94.488736
iter  20 value 94.484331
iter  30 value 86.528405
final  value 86.334653 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.257221 
iter  10 value 94.488504
iter  20 value 92.382495
iter  30 value 86.985516
iter  40 value 85.047286
iter  50 value 84.125987
iter  60 value 84.113428
iter  70 value 84.112238
iter  80 value 84.010613
iter  90 value 82.450862
iter 100 value 82.397729
final  value 82.397729 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.229127 
iter  10 value 94.485810
iter  20 value 93.467213
iter  30 value 86.174039
iter  40 value 85.660498
iter  50 value 84.243586
iter  60 value 84.203786
iter  70 value 84.101254
iter  80 value 83.939497
iter  80 value 83.939496
final  value 83.939496 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.338877 
iter  10 value 94.035796
iter  20 value 93.876702
iter  30 value 93.550529
iter  40 value 93.550083
final  value 93.550046 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.540465 
iter  10 value 94.034922
iter  20 value 93.678451
iter  30 value 93.575945
iter  40 value 91.879567
iter  50 value 85.211675
final  value 83.893904 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.368427 
iter  10 value 94.452197
iter  20 value 94.451321
iter  30 value 86.794718
iter  40 value 84.403501
iter  50 value 84.402885
iter  60 value 84.396710
iter  70 value 84.312811
iter  80 value 84.095834
iter  90 value 84.094167
iter 100 value 84.093840
final  value 84.093840 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.030536 
iter  10 value 93.649918
iter  20 value 93.642246
iter  30 value 93.122658
iter  40 value 85.857170
iter  50 value 84.493941
iter  60 value 83.582675
iter  70 value 82.547812
iter  80 value 82.337167
iter  90 value 82.237887
iter 100 value 82.095546
final  value 82.095546 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.367016 
iter  10 value 94.275362
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.127121 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.802192 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.290960 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.234296 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.912495 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.481885 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.859455 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.068686 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.310158 
final  value 94.443182 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.051048 
iter  10 value 93.659629
final  value 93.659477 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.102063 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.411017 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.319132 
iter  10 value 93.776473
iter  20 value 93.659570
final  value 93.659475 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.094143 
iter  10 value 93.009293
iter  20 value 92.419016
iter  30 value 92.307155
iter  40 value 92.305864
iter  40 value 92.305863
iter  40 value 92.305863
final  value 92.305863 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.467445 
iter  10 value 94.424717
iter  20 value 88.598786
iter  30 value 85.261217
iter  40 value 84.927334
iter  50 value 84.675751
iter  60 value 84.674875
final  value 84.674868 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.422527 
iter  10 value 94.490299
iter  20 value 94.248168
iter  30 value 93.681695
iter  40 value 92.883462
iter  50 value 90.476205
iter  60 value 86.173862
iter  70 value 85.265969
iter  80 value 84.811330
final  value 84.790174 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.176828 
iter  10 value 94.142705
iter  20 value 91.434023
iter  30 value 87.194836
iter  40 value 85.789039
iter  50 value 83.954287
iter  60 value 83.195452
iter  70 value 82.942152
iter  80 value 82.439403
iter  90 value 81.954138
final  value 81.947133 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.927370 
iter  10 value 94.486222
iter  20 value 94.332029
iter  30 value 93.698883
iter  40 value 93.673546
iter  50 value 92.749880
iter  60 value 88.421168
iter  70 value 88.397309
iter  80 value 88.304755
iter  90 value 87.538994
iter 100 value 84.576807
final  value 84.576807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.170046 
iter  10 value 94.488701
iter  20 value 93.927412
iter  30 value 93.864163
iter  40 value 93.726287
iter  50 value 89.618201
iter  60 value 88.589168
iter  70 value 88.517719
iter  80 value 88.404793
iter  90 value 85.037226
iter 100 value 84.865663
final  value 84.865663 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.629241 
iter  10 value 94.832780
iter  20 value 94.495440
iter  30 value 93.669798
iter  40 value 93.440459
iter  50 value 93.393684
iter  60 value 90.611933
iter  70 value 85.139365
iter  80 value 82.312775
iter  90 value 81.398813
iter 100 value 80.597753
final  value 80.597753 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.192362 
iter  10 value 94.748340
iter  20 value 94.156465
iter  30 value 94.096895
iter  40 value 89.035095
iter  50 value 85.487969
iter  60 value 82.370879
iter  70 value 81.504283
iter  80 value 81.397867
iter  90 value 81.362297
iter 100 value 81.281401
final  value 81.281401 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.431179 
iter  10 value 93.610391
iter  20 value 87.738491
iter  30 value 84.484850
iter  40 value 83.126122
iter  50 value 82.100662
iter  60 value 81.901638
iter  70 value 81.824191
iter  80 value 81.775312
iter  90 value 81.583266
iter 100 value 80.362186
final  value 80.362186 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.864201 
iter  10 value 94.332457
iter  20 value 86.963900
iter  30 value 81.825302
iter  40 value 81.491952
iter  50 value 81.259464
iter  60 value 81.129078
iter  70 value 80.906466
iter  80 value 80.872958
iter  90 value 80.644341
iter 100 value 80.542275
final  value 80.542275 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.757402 
iter  10 value 94.597786
iter  20 value 88.178022
iter  30 value 85.888652
iter  40 value 84.145983
iter  50 value 82.484728
iter  60 value 80.996125
iter  70 value 80.833138
iter  80 value 80.594105
iter  90 value 80.475211
iter 100 value 80.438291
final  value 80.438291 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.486763 
iter  10 value 94.382142
iter  20 value 87.110438
iter  30 value 85.404149
iter  40 value 84.286557
iter  50 value 83.077642
iter  60 value 82.930369
iter  70 value 82.759923
iter  80 value 82.669389
iter  90 value 82.521455
iter 100 value 82.184316
final  value 82.184316 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.212798 
iter  10 value 94.487288
iter  20 value 89.123170
iter  30 value 84.582775
iter  40 value 82.687720
iter  50 value 81.680746
iter  60 value 81.524848
iter  70 value 81.100305
iter  80 value 80.759787
iter  90 value 80.553096
iter 100 value 80.478043
final  value 80.478043 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.428599 
iter  10 value 93.831349
iter  20 value 86.587813
iter  30 value 85.204048
iter  40 value 84.408916
iter  50 value 82.730644
iter  60 value 80.910081
iter  70 value 80.301950
iter  80 value 80.239177
iter  90 value 80.185303
iter 100 value 80.176354
final  value 80.176354 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.486433 
iter  10 value 94.472760
iter  20 value 93.280770
iter  30 value 90.822484
iter  40 value 87.553368
iter  50 value 84.613353
iter  60 value 81.634652
iter  70 value 81.188447
iter  80 value 80.848682
iter  90 value 80.735314
iter 100 value 80.674181
final  value 80.674181 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.500843 
iter  10 value 94.486782
iter  20 value 93.153703
iter  30 value 90.162738
iter  40 value 85.114047
iter  50 value 84.179346
iter  60 value 83.521368
iter  70 value 82.650525
iter  80 value 82.206894
iter  90 value 82.087756
iter 100 value 81.283818
final  value 81.283818 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.525621 
final  value 94.485880 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.198565 
final  value 94.485868 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.293639 
final  value 94.485993 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.915782 
final  value 94.485834 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.740524 
final  value 94.485745 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.627692 
iter  10 value 94.488879
iter  20 value 89.458512
iter  30 value 87.499523
iter  40 value 87.499276
iter  50 value 85.104583
iter  60 value 84.668773
iter  70 value 84.668252
iter  80 value 84.646599
iter  90 value 84.630846
iter  90 value 84.630846
iter  90 value 84.630846
final  value 84.630846 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.260504 
iter  10 value 94.280457
iter  20 value 91.019566
final  value 88.815175 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.108564 
iter  10 value 94.489844
iter  20 value 94.474926
iter  30 value 93.663396
iter  40 value 93.637834
final  value 93.637766 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.671897 
iter  10 value 94.280524
iter  20 value 94.226665
iter  30 value 93.517233
iter  40 value 93.455033
final  value 93.454741 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.210043 
iter  10 value 94.488580
iter  20 value 94.279483
iter  30 value 94.277093
iter  40 value 94.220474
iter  50 value 91.109247
iter  60 value 88.875534
final  value 88.873080 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.590352 
iter  10 value 93.012493
iter  20 value 91.907138
iter  30 value 91.337553
iter  40 value 84.715903
iter  50 value 84.710439
iter  60 value 84.330717
iter  70 value 83.022838
iter  80 value 80.717869
iter  90 value 80.154452
iter 100 value 80.150629
final  value 80.150629 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.029779 
iter  10 value 94.363393
iter  20 value 94.360918
iter  30 value 93.694477
iter  40 value 87.244211
iter  50 value 84.714076
iter  60 value 83.990786
iter  70 value 82.539968
iter  80 value 80.386423
iter  90 value 79.154837
iter 100 value 79.092125
final  value 79.092125 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.992060 
iter  10 value 94.493085
iter  20 value 93.991938
iter  30 value 93.455171
final  value 93.454710 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.451844 
iter  10 value 94.283581
iter  20 value 94.034630
iter  30 value 86.134702
final  value 85.985221 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.333177 
iter  10 value 91.266816
iter  20 value 90.591038
iter  30 value 88.431784
iter  40 value 86.085010
iter  50 value 84.713706
iter  60 value 83.432110
iter  70 value 83.212314
iter  80 value 83.210605
iter  90 value 83.204593
iter 100 value 81.896622
final  value 81.896622 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.651079 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.481493 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.467580 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.905274 
iter  10 value 93.870449
iter  20 value 83.963652
iter  30 value 83.926767
iter  40 value 83.917963
iter  50 value 83.916941
iter  60 value 80.819317
iter  70 value 80.788402
final  value 80.780000 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.719493 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.726641 
iter  10 value 91.749430
iter  20 value 91.662487
iter  30 value 90.505453
iter  40 value 88.993594
iter  50 value 88.982655
final  value 88.982418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.056226 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.560694 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.814141 
iter  10 value 93.124191
iter  20 value 90.579615
final  value 90.577303 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.080055 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.694125 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.594158 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 130.248633 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.353024 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  507
initial  value 131.430007 
iter  10 value 93.641989
iter  20 value 93.305104
final  value 93.299758 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.597237 
iter  10 value 93.980691
iter  20 value 88.646353
iter  30 value 85.135846
iter  40 value 84.752623
iter  50 value 82.231533
iter  60 value 81.968746
iter  70 value 81.891523
iter  80 value 81.839250
iter  90 value 81.820473
final  value 81.820470 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.430649 
iter  10 value 93.871359
iter  20 value 87.381137
iter  30 value 82.206244
iter  40 value 82.036867
iter  50 value 79.809292
iter  60 value 79.065959
final  value 79.043730 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.943204 
iter  10 value 94.032282
iter  20 value 92.705574
iter  30 value 87.058875
iter  40 value 84.855341
iter  50 value 82.766174
iter  60 value 82.181589
iter  70 value 82.083434
iter  80 value 82.064628
iter  90 value 82.000110
iter 100 value 81.864489
final  value 81.864489 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.913754 
iter  10 value 93.735776
iter  20 value 89.997709
iter  30 value 88.622114
iter  40 value 79.515400
iter  50 value 77.597066
iter  60 value 77.261574
iter  70 value 77.014964
iter  80 value 76.952040
iter  90 value 76.949216
final  value 76.947948 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.021200 
iter  10 value 92.635003
iter  20 value 82.884217
iter  30 value 82.125280
iter  40 value 81.919650
iter  50 value 81.877766
iter  60 value 81.828126
iter  70 value 81.820482
final  value 81.820471 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.816913 
iter  10 value 93.297548
iter  20 value 81.808214
iter  30 value 80.421621
iter  40 value 78.288777
iter  50 value 77.545881
iter  60 value 76.501207
iter  70 value 76.261611
iter  80 value 76.078785
iter  90 value 76.073123
final  value 76.073103 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.668031 
iter  10 value 93.986145
iter  20 value 92.657256
iter  30 value 89.475192
iter  40 value 83.286546
iter  50 value 80.508471
iter  60 value 79.846827
iter  70 value 78.691769
iter  80 value 77.751997
iter  90 value 76.748643
iter 100 value 76.578733
final  value 76.578733 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.713723 
iter  10 value 93.991464
iter  20 value 93.565584
iter  30 value 86.042257
iter  40 value 82.757446
iter  50 value 82.442447
iter  60 value 82.241257
iter  70 value 81.975312
iter  80 value 81.826912
iter  90 value 81.409338
iter 100 value 79.398244
final  value 79.398244 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.675005 
iter  10 value 94.083056
iter  20 value 93.784732
iter  30 value 82.530384
iter  40 value 82.117824
iter  50 value 81.767569
iter  60 value 80.863480
iter  70 value 78.608262
iter  80 value 77.410763
iter  90 value 76.210829
iter 100 value 75.611079
final  value 75.611079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.937966 
iter  10 value 88.922477
iter  20 value 82.851919
iter  30 value 81.899613
iter  40 value 80.249507
iter  50 value 79.235082
iter  60 value 78.593814
iter  70 value 78.440956
iter  80 value 77.963682
iter  90 value 77.490844
iter 100 value 77.381332
final  value 77.381332 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.039834 
iter  10 value 93.892125
iter  20 value 86.736134
iter  30 value 83.177688
iter  40 value 77.336046
iter  50 value 76.567214
iter  60 value 76.322870
iter  70 value 75.951589
iter  80 value 75.813375
iter  90 value 75.599450
iter 100 value 75.425425
final  value 75.425425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.000719 
iter  10 value 92.744624
iter  20 value 82.745462
iter  30 value 81.061783
iter  40 value 78.900569
iter  50 value 78.692285
iter  60 value 78.221851
iter  70 value 76.923615
iter  80 value 76.328656
iter  90 value 76.225424
iter 100 value 76.161154
final  value 76.161154 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.159872 
iter  10 value 93.780111
iter  20 value 89.295002
iter  30 value 85.453534
iter  40 value 82.816737
iter  50 value 82.565778
iter  60 value 82.070961
iter  70 value 78.287735
iter  80 value 77.721382
iter  90 value 77.369727
iter 100 value 77.238031
final  value 77.238031 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.079848 
iter  10 value 96.353718
iter  20 value 94.202577
iter  30 value 93.810784
iter  40 value 92.913054
iter  50 value 86.946157
iter  60 value 85.024515
iter  70 value 83.263032
iter  80 value 81.946237
iter  90 value 79.272843
iter 100 value 78.636785
final  value 78.636785 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.171372 
iter  10 value 93.994750
iter  20 value 84.566011
iter  30 value 82.297878
iter  40 value 82.008605
iter  50 value 80.584940
iter  60 value 78.982521
iter  70 value 77.306562
iter  80 value 76.747237
iter  90 value 76.172029
iter 100 value 76.089203
final  value 76.089203 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.743719 
final  value 94.054572 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.462176 
iter  10 value 93.606380
iter  20 value 93.596237
iter  30 value 93.539644
iter  40 value 93.078735
iter  50 value 83.461145
iter  60 value 83.453941
final  value 83.453892 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.654663 
final  value 94.054564 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.158654 
iter  10 value 89.871921
iter  20 value 84.833002
iter  30 value 84.780787
final  value 84.780557 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.109870 
final  value 94.054665 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.131119 
iter  10 value 93.362947
iter  20 value 89.063538
iter  30 value 89.056882
iter  40 value 89.039846
iter  50 value 89.039399
iter  60 value 89.037181
iter  70 value 89.033656
iter  80 value 89.033341
iter  90 value 89.033236
final  value 89.032675 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.898734 
iter  10 value 94.057321
iter  20 value 93.940397
iter  30 value 92.153837
iter  40 value 91.390717
iter  50 value 91.114136
iter  60 value 91.109170
iter  70 value 89.620103
iter  80 value 89.619523
final  value 89.619336 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.449699 
iter  10 value 94.057143
iter  20 value 93.655919
iter  30 value 93.650468
final  value 93.650410 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.563449 
iter  10 value 85.850961
iter  20 value 83.387522
iter  30 value 83.386743
iter  40 value 83.196917
iter  50 value 83.140038
iter  60 value 83.138833
iter  70 value 83.137926
iter  80 value 83.135912
iter  90 value 79.496054
iter 100 value 78.494508
final  value 78.494508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.156171 
iter  10 value 93.306112
iter  20 value 93.305024
iter  30 value 93.298549
iter  40 value 88.511519
iter  50 value 83.313225
iter  60 value 83.252083
iter  70 value 83.251286
iter  80 value 83.250033
iter  90 value 83.140198
iter 100 value 81.254463
final  value 81.254463 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.680082 
iter  10 value 94.062037
iter  20 value 94.053284
iter  30 value 93.711602
iter  40 value 93.705642
iter  50 value 93.705402
iter  60 value 93.705272
iter  70 value 93.610903
iter  80 value 93.536485
final  value 93.536483 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.456656 
iter  10 value 85.836673
iter  20 value 81.804981
iter  30 value 81.653636
iter  40 value 81.649344
iter  50 value 81.645906
iter  60 value 81.644629
iter  70 value 81.250548
iter  80 value 80.984750
iter  90 value 79.896030
iter 100 value 79.666058
final  value 79.666058 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.372795 
iter  10 value 94.058564
iter  20 value 94.023610
iter  30 value 86.297400
iter  40 value 84.587085
iter  50 value 83.872713
iter  60 value 83.540277
iter  70 value 78.771401
iter  80 value 78.008281
iter  90 value 78.007746
iter 100 value 77.792159
final  value 77.792159 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.150617 
iter  10 value 94.057352
iter  20 value 94.013576
iter  30 value 93.604713
final  value 93.595324 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.786112 
iter  10 value 94.060720
iter  20 value 93.737232
iter  30 value 84.171827
iter  40 value 84.126277
iter  50 value 84.125365
iter  60 value 80.886569
iter  70 value 80.884672
iter  80 value 80.794332
iter  90 value 80.793496
final  value 80.793415 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.662009 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.862897 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.311645 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.817677 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.527767 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.800095 
iter  10 value 88.541476
iter  20 value 88.377540
iter  30 value 87.154059
iter  40 value 87.153033
final  value 87.153030 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.532625 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.371928 
iter  10 value 92.253808
iter  20 value 83.907360
iter  30 value 83.716570
iter  40 value 83.658502
iter  50 value 83.621143
final  value 83.621133 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.915241 
iter  10 value 92.265773
iter  20 value 92.207108
final  value 92.206737 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.614448 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.512253 
iter  10 value 87.199229
iter  20 value 87.175413
final  value 87.175325 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.263987 
iter  10 value 90.435742
iter  20 value 90.323391
iter  30 value 90.321534
final  value 90.321457 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.507799 
iter  10 value 94.414817
final  value 94.414729 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.403020 
iter  10 value 90.339987
iter  20 value 85.978764
iter  30 value 85.931267
iter  40 value 85.931101
final  value 85.931098 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.540025 
iter  10 value 94.467380
iter  20 value 94.071194
final  value 94.064368 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.365888 
iter  10 value 94.488562
iter  20 value 94.472741
iter  30 value 91.076244
iter  40 value 88.436786
iter  50 value 87.721875
iter  60 value 86.527993
iter  70 value 85.602523
iter  80 value 82.206715
iter  90 value 81.352685
iter 100 value 81.181670
final  value 81.181670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.455985 
iter  10 value 94.134618
iter  20 value 92.421519
iter  30 value 91.756086
iter  40 value 85.185983
iter  50 value 82.648977
iter  60 value 81.269263
iter  70 value 81.211714
iter  80 value 81.181240
final  value 81.181238 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.787066 
iter  10 value 94.488551
iter  20 value 94.382583
iter  30 value 87.511871
iter  40 value 86.535177
iter  50 value 84.746333
iter  60 value 84.217888
iter  70 value 84.172969
iter  80 value 83.463298
iter  90 value 83.424587
iter 100 value 83.422202
final  value 83.422202 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.559510 
iter  10 value 94.488626
iter  20 value 94.386397
iter  30 value 89.732599
iter  40 value 85.934102
iter  50 value 85.077832
iter  60 value 84.860559
iter  70 value 84.669180
iter  80 value 84.304740
iter  90 value 84.083304
final  value 84.082229 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.697445 
iter  10 value 94.502737
iter  20 value 94.480812
iter  30 value 92.566236
iter  40 value 88.536184
iter  50 value 88.278760
iter  60 value 88.037298
iter  70 value 83.549773
iter  80 value 83.374932
iter  90 value 83.001991
iter 100 value 82.349005
final  value 82.349005 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.511383 
iter  10 value 94.466339
iter  20 value 88.798163
iter  30 value 85.368177
iter  40 value 84.708975
iter  50 value 84.489350
iter  60 value 83.987721
iter  70 value 83.221546
iter  80 value 83.126867
iter  90 value 83.113461
iter 100 value 82.984421
final  value 82.984421 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.747891 
iter  10 value 94.462391
iter  20 value 90.448629
iter  30 value 85.590682
iter  40 value 84.868923
iter  50 value 84.569088
iter  60 value 84.306182
iter  70 value 84.028039
iter  80 value 83.727585
iter  90 value 81.828347
iter 100 value 80.574133
final  value 80.574133 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.645228 
iter  10 value 94.339178
iter  20 value 93.507358
iter  30 value 90.631183
iter  40 value 84.193849
iter  50 value 82.348994
iter  60 value 81.835593
iter  70 value 81.031702
iter  80 value 80.539340
iter  90 value 79.977211
iter 100 value 79.788162
final  value 79.788162 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.118732 
iter  10 value 94.474180
iter  20 value 93.951854
iter  30 value 90.786334
iter  40 value 88.389005
iter  50 value 83.301131
iter  60 value 81.152295
iter  70 value 80.780430
iter  80 value 80.549341
iter  90 value 80.510830
iter 100 value 80.396271
final  value 80.396271 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.355641 
iter  10 value 94.710431
iter  20 value 94.227854
iter  30 value 87.009789
iter  40 value 83.478488
iter  50 value 81.125285
iter  60 value 80.706840
iter  70 value 80.422346
iter  80 value 80.144187
iter  90 value 80.111861
iter 100 value 80.063601
final  value 80.063601 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.871154 
iter  10 value 94.535163
iter  20 value 86.303407
iter  30 value 85.026436
iter  40 value 83.998126
iter  50 value 82.662781
iter  60 value 82.041363
iter  70 value 81.772929
iter  80 value 81.616576
iter  90 value 81.485372
iter 100 value 81.032076
final  value 81.032076 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.987684 
iter  10 value 94.499860
iter  20 value 94.324952
iter  30 value 88.336088
iter  40 value 86.727057
iter  50 value 86.208795
iter  60 value 83.768686
iter  70 value 83.369919
iter  80 value 83.161083
iter  90 value 83.057120
iter 100 value 82.664663
final  value 82.664663 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.565309 
iter  10 value 94.361458
iter  20 value 93.102543
iter  30 value 90.149497
iter  40 value 85.042764
iter  50 value 83.987458
iter  60 value 82.461111
iter  70 value 81.222355
iter  80 value 80.799722
iter  90 value 80.450642
iter 100 value 80.074046
final  value 80.074046 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.573005 
iter  10 value 93.403173
iter  20 value 90.670243
iter  30 value 84.734127
iter  40 value 83.181464
iter  50 value 81.544579
iter  60 value 80.826151
iter  70 value 80.184868
iter  80 value 79.665895
iter  90 value 79.474908
iter 100 value 79.402584
final  value 79.402584 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.086831 
iter  10 value 96.430598
iter  20 value 94.105748
iter  30 value 92.736480
iter  40 value 92.447785
iter  50 value 87.097742
iter  60 value 83.811203
iter  70 value 81.598633
iter  80 value 81.230255
iter  90 value 81.012301
iter 100 value 80.377538
final  value 80.377538 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.567407 
final  value 94.485658 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.365464 
iter  10 value 94.485860
iter  20 value 94.220150
iter  30 value 89.482227
iter  40 value 89.197177
iter  50 value 89.193061
final  value 89.192993 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.560432 
final  value 94.485840 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.863127 
iter  10 value 94.485985
iter  20 value 94.484042
iter  30 value 89.273289
iter  40 value 84.197595
iter  50 value 84.193487
iter  60 value 83.463077
iter  60 value 83.463077
iter  60 value 83.463077
final  value 83.463077 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.657221 
final  value 94.485751 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.770137 
iter  10 value 94.472248
iter  20 value 94.470582
iter  30 value 94.469436
iter  40 value 91.856241
iter  50 value 84.453722
iter  60 value 82.404586
iter  70 value 80.227961
iter  80 value 80.219095
iter  90 value 79.728363
iter 100 value 79.481778
final  value 79.481778 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.687515 
iter  10 value 94.488996
iter  20 value 94.484590
iter  30 value 85.207954
iter  40 value 84.455074
iter  50 value 83.767744
iter  60 value 81.837808
iter  70 value 80.791041
iter  80 value 80.788832
iter  90 value 80.786665
iter 100 value 80.782175
final  value 80.782175 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.827839 
iter  10 value 94.378434
iter  20 value 94.373151
iter  30 value 94.287561
iter  40 value 93.811903
iter  50 value 93.782935
iter  60 value 93.781276
iter  70 value 93.760289
iter  80 value 93.527765
iter  90 value 90.166551
iter 100 value 81.987413
final  value 81.987413 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.871005 
iter  10 value 94.489719
iter  20 value 94.048618
iter  30 value 84.270363
iter  40 value 84.065263
iter  50 value 84.064281
iter  60 value 84.008613
final  value 84.008448 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.996752 
iter  10 value 94.461605
iter  20 value 94.446928
iter  30 value 94.446702
iter  40 value 84.654912
iter  50 value 82.872765
iter  60 value 82.468502
iter  70 value 82.141150
final  value 82.131569 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.326427 
iter  10 value 94.437138
iter  20 value 94.429753
final  value 94.429589 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.814602 
iter  10 value 94.491995
iter  20 value 94.476180
iter  30 value 88.345322
iter  40 value 88.184691
iter  50 value 88.167183
iter  60 value 86.910013
iter  70 value 86.881263
iter  80 value 86.878476
iter  90 value 86.877155
iter 100 value 86.876251
final  value 86.876251 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.711426 
iter  10 value 94.097477
iter  20 value 94.058075
iter  30 value 94.027481
iter  40 value 84.437436
iter  50 value 81.660490
iter  60 value 81.528440
iter  70 value 81.526531
iter  80 value 81.521959
final  value 81.521864 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.054355 
iter  10 value 93.037465
iter  20 value 92.296183
iter  30 value 92.289528
iter  40 value 92.287929
iter  50 value 92.174896
iter  60 value 91.741355
final  value 91.741352 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.488417 
iter  10 value 94.476934
iter  20 value 94.474286
iter  30 value 94.473077
iter  40 value 94.406858
iter  50 value 86.221674
iter  60 value 84.001127
final  value 83.935139 
converged
Fitting Repeat 1 

# weights:  305
initial  value 133.121696 
iter  10 value 118.429807
iter  20 value 112.828292
iter  30 value 111.577326
iter  40 value 105.058661
iter  50 value 103.268423
iter  60 value 102.975517
iter  70 value 102.256771
iter  80 value 102.039964
iter  90 value 101.964794
iter 100 value 101.941199
final  value 101.941199 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 126.223273 
iter  10 value 120.040964
iter  20 value 114.814023
iter  30 value 105.793830
iter  40 value 104.419076
iter  50 value 101.713160
iter  60 value 101.249304
iter  70 value 101.108997
iter  80 value 101.000495
iter  90 value 100.873879
iter 100 value 100.865742
final  value 100.865742 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.120860 
iter  10 value 117.771792
iter  20 value 113.294137
iter  30 value 108.843489
iter  40 value 108.605926
iter  50 value 108.303505
iter  60 value 108.131320
iter  70 value 105.459078
iter  80 value 103.452017
iter  90 value 102.197363
iter 100 value 101.617309
final  value 101.617309 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 157.436332 
iter  10 value 120.058299
iter  20 value 119.125909
iter  30 value 117.774193
iter  40 value 117.559223
iter  50 value 110.714560
iter  60 value 106.658467
iter  70 value 103.148994
iter  80 value 102.662234
iter  90 value 102.393244
iter 100 value 102.137127
final  value 102.137127 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.658562 
iter  10 value 116.553100
iter  20 value 108.963906
iter  30 value 107.052104
iter  40 value 105.892251
iter  50 value 105.501238
iter  60 value 104.988792
iter  70 value 104.409370
iter  80 value 104.291804
iter  90 value 103.481207
iter 100 value 103.218661
final  value 103.218661 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Thu Nov 27 20:36:37 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 
 21.396   0.492  75.075