##############################################################################
##############################################################################
###
### 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_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.0 Patched (2025-04-21 r88169)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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       33.989  1.609  35.872
FSmethod      33.328  1.649  35.213
corr_plot     33.010  1.521  34.736
pred_ensembel 13.298  0.429  11.868
enrichfindP    0.459  0.057   7.822
* 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-3.22-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/4.5-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 95.420095 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.351298 
iter  10 value 94.014455
iter  20 value 94.005860
final  value 94.005849 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.450374 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.813538 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.057564 
iter  10 value 93.582430
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.515013 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.884351 
iter  10 value 91.315051
iter  20 value 84.926178
iter  30 value 83.843407
iter  40 value 83.730358
final  value 83.729943 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.798696 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.436784 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.646174 
iter  10 value 94.011429
iter  10 value 94.011429
iter  10 value 94.011429
final  value 94.011429 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.870130 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.781863 
iter  10 value 93.874413
iter  20 value 91.950239
iter  30 value 90.813245
iter  40 value 90.801712
final  value 90.515286 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.888340 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.844663 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.727646 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.058982 
iter  10 value 94.056969
iter  20 value 93.819526
iter  30 value 89.497193
iter  40 value 85.359674
iter  50 value 84.675113
iter  60 value 84.090168
iter  70 value 83.388064
iter  80 value 82.692548
iter  90 value 82.567526
final  value 82.563309 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.302111 
iter  10 value 94.057505
iter  20 value 93.793137
iter  30 value 86.216599
iter  40 value 85.204644
iter  50 value 84.992930
iter  60 value 84.877803
iter  70 value 84.797027
final  value 84.796536 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.144874 
iter  10 value 93.554279
iter  20 value 93.153213
iter  30 value 88.743171
iter  40 value 88.424814
iter  50 value 85.683925
iter  60 value 84.905704
iter  70 value 84.808947
iter  80 value 84.798884
iter  90 value 84.796545
final  value 84.796536 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.665226 
iter  10 value 94.056916
iter  20 value 93.792614
iter  30 value 93.011733
iter  40 value 88.006964
iter  50 value 87.831044
iter  60 value 86.863315
iter  70 value 85.359717
iter  80 value 85.316850
iter  90 value 85.290859
iter 100 value 85.280478
final  value 85.280478 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.333809 
iter  10 value 94.001928
iter  20 value 92.194834
iter  30 value 90.695199
iter  40 value 90.101660
iter  50 value 87.036474
iter  60 value 86.228433
iter  70 value 83.231992
iter  80 value 82.897247
iter  90 value 82.734352
final  value 82.733817 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.225932 
iter  10 value 93.847381
iter  20 value 90.339529
iter  30 value 88.178879
iter  40 value 87.906696
iter  50 value 87.605966
iter  60 value 85.537637
iter  70 value 84.951552
iter  80 value 84.463131
iter  90 value 84.021675
iter 100 value 83.223675
final  value 83.223675 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.373230 
iter  10 value 94.105594
iter  20 value 93.268201
iter  30 value 86.533344
iter  40 value 83.154257
iter  50 value 81.968264
iter  60 value 81.623041
iter  70 value 81.580949
iter  80 value 81.483287
iter  90 value 81.205855
iter 100 value 81.107580
final  value 81.107580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.871978 
iter  10 value 93.966716
iter  20 value 89.033535
iter  30 value 87.078360
iter  40 value 85.903642
iter  50 value 83.214696
iter  60 value 81.896693
iter  70 value 81.383682
iter  80 value 81.280530
iter  90 value 81.186906
iter 100 value 81.025228
final  value 81.025228 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.717801 
iter  10 value 94.106291
iter  20 value 89.608737
iter  30 value 88.277223
iter  40 value 86.285418
iter  50 value 84.795858
iter  60 value 84.738168
iter  70 value 84.283520
iter  80 value 82.553199
iter  90 value 81.948912
iter 100 value 81.098323
final  value 81.098323 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.872679 
iter  10 value 95.231329
iter  20 value 86.964365
iter  30 value 85.042861
iter  40 value 83.180748
iter  50 value 82.591178
iter  60 value 82.199745
iter  70 value 82.056812
iter  80 value 81.951729
iter  90 value 81.936296
iter 100 value 81.818627
final  value 81.818627 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.047610 
iter  10 value 96.064410
iter  20 value 93.608798
iter  30 value 86.168809
iter  40 value 84.827508
iter  50 value 84.736082
iter  60 value 84.562455
iter  70 value 83.744208
iter  80 value 83.340352
iter  90 value 82.265733
iter 100 value 82.018843
final  value 82.018843 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.794179 
iter  10 value 92.168920
iter  20 value 86.008862
iter  30 value 84.799040
iter  40 value 84.657998
iter  50 value 82.915042
iter  60 value 82.225778
iter  70 value 81.970354
iter  80 value 81.534594
iter  90 value 81.468399
iter 100 value 81.275430
final  value 81.275430 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.487914 
iter  10 value 93.989940
iter  20 value 88.825954
iter  30 value 87.743094
iter  40 value 84.758779
iter  50 value 82.252396
iter  60 value 81.381913
iter  70 value 81.026853
iter  80 value 80.789320
iter  90 value 80.661296
iter 100 value 80.625896
final  value 80.625896 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.708813 
iter  10 value 92.925931
iter  20 value 84.966472
iter  30 value 84.839608
iter  40 value 84.148572
iter  50 value 83.534898
iter  60 value 83.068655
iter  70 value 82.824062
iter  80 value 82.687729
iter  90 value 82.480674
iter 100 value 81.836891
final  value 81.836891 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 135.801307 
iter  10 value 94.311253
iter  20 value 92.510594
iter  30 value 91.210172
iter  40 value 85.338163
iter  50 value 84.505622
iter  60 value 83.971526
iter  70 value 83.687847
iter  80 value 83.236594
iter  90 value 82.432328
iter 100 value 82.113604
final  value 82.113604 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.311202 
final  value 94.054525 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.017845 
final  value 94.054567 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.494231 
final  value 94.054526 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.095056 
final  value 94.054548 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.268284 
final  value 94.054316 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.888691 
iter  10 value 94.057683
iter  20 value 94.005731
iter  30 value 88.234202
iter  40 value 86.969290
iter  50 value 84.028936
iter  60 value 83.986306
iter  70 value 83.977208
iter  80 value 83.976728
iter  90 value 83.962983
iter 100 value 83.962758
final  value 83.962758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.921174 
iter  10 value 94.058583
iter  20 value 94.004120
iter  30 value 91.600339
iter  40 value 89.821992
iter  50 value 86.639127
iter  60 value 85.476652
iter  70 value 84.807915
iter  80 value 84.577312
iter  90 value 84.426412
final  value 84.425972 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.010699 
iter  10 value 94.057796
iter  20 value 94.051577
iter  30 value 93.351538
iter  40 value 84.292964
iter  50 value 84.063596
iter  60 value 84.059895
iter  70 value 84.057264
iter  80 value 84.038350
iter  90 value 83.864034
iter 100 value 82.044323
final  value 82.044323 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.836823 
iter  10 value 94.057450
iter  20 value 93.384976
iter  30 value 88.464112
iter  40 value 86.821137
iter  50 value 85.628776
iter  60 value 85.240399
iter  60 value 85.240398
final  value 85.240398 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.545736 
iter  10 value 94.058176
iter  20 value 94.050260
iter  30 value 93.716880
iter  40 value 93.712597
iter  50 value 93.076032
iter  60 value 90.178962
iter  70 value 85.604890
iter  80 value 81.603447
iter  90 value 81.004835
iter 100 value 81.000567
final  value 81.000567 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 146.811706 
iter  10 value 94.018770
iter  20 value 94.014002
iter  30 value 93.858586
iter  40 value 93.482585
iter  50 value 93.338099
iter  60 value 93.271714
final  value 93.270079 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.752033 
iter  10 value 93.093969
iter  20 value 92.851000
iter  30 value 92.848156
iter  40 value 92.823507
iter  50 value 92.528965
iter  60 value 91.215560
iter  70 value 89.079817
iter  80 value 86.808676
iter  90 value 86.772668
final  value 86.772600 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.718730 
iter  10 value 93.590517
iter  20 value 93.519186
final  value 93.116649 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.087489 
iter  10 value 91.816278
iter  20 value 91.041341
iter  30 value 90.862807
iter  40 value 90.816804
iter  50 value 90.255253
iter  60 value 89.940913
iter  70 value 89.800589
iter  80 value 89.247895
iter  90 value 85.538916
iter 100 value 81.843962
final  value 81.843962 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.967548 
iter  10 value 93.795704
iter  20 value 93.792973
iter  30 value 93.128601
iter  40 value 93.073346
iter  50 value 93.032265
final  value 92.996900 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.825559 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.678131 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.909382 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.557962 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.226180 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.126948 
iter  10 value 92.728764
iter  20 value 92.725588
iter  30 value 92.470857
iter  40 value 92.470268
final  value 92.470267 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.331580 
iter  10 value 92.141982
iter  20 value 91.267683
iter  30 value 83.612623
iter  40 value 82.433733
iter  50 value 82.344287
final  value 82.343399 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.651416 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.866035 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.578035 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.422067 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.245550 
iter  10 value 90.835769
iter  20 value 89.248864
iter  30 value 89.228531
final  value 89.228363 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.361002 
final  value 94.325945 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.416461 
iter  10 value 92.631702
iter  20 value 92.630982
iter  30 value 92.550731
final  value 92.550725 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.394723 
iter  10 value 87.783382
iter  20 value 87.220744
final  value 87.220513 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.797161 
iter  10 value 94.487329
iter  20 value 91.208620
iter  30 value 82.797487
iter  40 value 82.308012
iter  50 value 82.011548
iter  60 value 81.791145
iter  70 value 81.339611
iter  80 value 81.153098
iter  90 value 80.532534
iter 100 value 80.506103
final  value 80.506103 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.865947 
iter  10 value 88.758885
iter  20 value 86.969579
iter  30 value 85.038600
iter  40 value 84.616745
iter  50 value 84.612714
final  value 84.612712 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.490129 
iter  10 value 94.917964
iter  20 value 94.417100
iter  30 value 84.581543
iter  40 value 83.562598
iter  50 value 83.262328
iter  60 value 82.080706
iter  70 value 81.714346
iter  80 value 81.609938
iter  90 value 81.200615
iter 100 value 80.712231
final  value 80.712231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.944446 
iter  10 value 94.481165
iter  20 value 88.212661
iter  30 value 86.331531
iter  40 value 85.956436
iter  50 value 85.548779
iter  60 value 85.109272
iter  70 value 85.028379
iter  80 value 80.131855
iter  90 value 79.720600
iter 100 value 79.198525
final  value 79.198525 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.085994 
iter  10 value 94.488691
iter  20 value 91.787809
iter  30 value 90.605822
iter  40 value 87.468911
iter  50 value 82.260003
iter  60 value 81.503069
iter  70 value 81.203288
iter  80 value 80.848644
iter  90 value 80.542687
final  value 80.504829 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.749103 
iter  10 value 94.399016
iter  20 value 91.935658
iter  30 value 87.651871
iter  40 value 86.159276
iter  50 value 85.863087
iter  60 value 85.687260
iter  70 value 83.434991
iter  80 value 80.284365
iter  90 value 79.620510
iter 100 value 78.871222
final  value 78.871222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.425354 
iter  10 value 94.339533
iter  20 value 82.123154
iter  30 value 80.264376
iter  40 value 79.598882
iter  50 value 79.357444
iter  60 value 79.041644
iter  70 value 78.835143
iter  80 value 78.090747
iter  90 value 77.687946
iter 100 value 77.615602
final  value 77.615602 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.047535 
iter  10 value 93.919306
iter  20 value 87.218826
iter  30 value 86.328216
iter  40 value 86.112697
iter  50 value 85.976669
iter  60 value 84.573888
iter  70 value 82.811846
iter  80 value 82.230081
iter  90 value 81.444168
iter 100 value 79.225690
final  value 79.225690 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.805840 
iter  10 value 94.239119
iter  20 value 86.479668
iter  30 value 84.362982
iter  40 value 81.537904
iter  50 value 80.410151
iter  60 value 78.608577
iter  70 value 78.061460
iter  80 value 77.642904
iter  90 value 77.232782
iter 100 value 77.202002
final  value 77.202002 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.395020 
iter  10 value 94.495043
iter  20 value 88.437613
iter  30 value 85.332771
iter  40 value 82.368411
iter  50 value 81.880981
iter  60 value 80.856352
iter  70 value 79.640813
iter  80 value 78.489476
iter  90 value 78.148385
iter 100 value 78.000275
final  value 78.000275 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.837278 
iter  10 value 94.552910
iter  20 value 92.008631
iter  30 value 91.631120
iter  40 value 88.585746
iter  50 value 84.726107
iter  60 value 81.856215
iter  70 value 80.966681
iter  80 value 80.469717
iter  90 value 80.055958
iter 100 value 79.454309
final  value 79.454309 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.142043 
iter  10 value 93.707580
iter  20 value 92.385278
iter  30 value 87.248641
iter  40 value 84.139283
iter  50 value 82.914120
iter  60 value 81.300115
iter  70 value 80.668406
iter  80 value 80.539124
iter  90 value 79.583964
iter 100 value 78.347041
final  value 78.347041 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.174642 
iter  10 value 94.471609
iter  20 value 91.095679
iter  30 value 85.456451
iter  40 value 83.063452
iter  50 value 82.029659
iter  60 value 81.521563
iter  70 value 80.474420
iter  80 value 80.095306
iter  90 value 79.922453
iter 100 value 79.532601
final  value 79.532601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.981185 
iter  10 value 94.559758
iter  20 value 92.684164
iter  30 value 88.780858
iter  40 value 83.176095
iter  50 value 81.282201
iter  60 value 79.928396
iter  70 value 79.544695
iter  80 value 78.849153
iter  90 value 78.619658
iter 100 value 78.541402
final  value 78.541402 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.841181 
iter  10 value 94.714359
iter  20 value 93.612134
iter  30 value 87.788856
iter  40 value 86.277830
iter  50 value 85.472984
iter  60 value 83.706821
iter  70 value 80.944841
iter  80 value 79.923497
iter  90 value 78.214661
iter 100 value 77.805765
final  value 77.805765 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.498450 
iter  10 value 94.485810
iter  20 value 91.619308
iter  30 value 91.314882
final  value 91.314869 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.411119 
iter  10 value 91.891078
iter  20 value 91.889808
iter  30 value 86.353759
iter  40 value 86.212080
iter  50 value 86.204006
iter  60 value 85.373842
iter  70 value 84.962896
final  value 84.907686 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.606938 
final  value 94.485900 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.009093 
final  value 94.485928 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.224231 
final  value 94.486021 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.288680 
iter  10 value 94.488634
iter  20 value 94.061620
iter  30 value 86.765077
iter  40 value 86.764576
iter  50 value 86.585022
final  value 86.585021 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.243968 
iter  10 value 94.488506
iter  20 value 94.327403
iter  30 value 85.702112
final  value 85.509574 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.038994 
iter  10 value 94.488786
iter  20 value 93.947798
iter  30 value 87.710062
iter  40 value 87.702678
iter  50 value 87.089281
iter  60 value 85.751263
iter  70 value 85.748520
iter  80 value 85.713317
iter  90 value 85.707583
iter 100 value 85.337338
final  value 85.337338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.382808 
iter  10 value 87.100611
iter  20 value 86.119458
iter  30 value 84.684602
iter  40 value 84.683461
iter  50 value 84.652069
iter  60 value 84.567870
iter  70 value 84.567581
iter  80 value 83.741384
iter  90 value 83.640370
iter 100 value 83.068098
final  value 83.068098 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.430061 
iter  10 value 94.488051
iter  20 value 94.361554
iter  30 value 91.436385
iter  40 value 89.790506
iter  50 value 89.722460
final  value 89.721297 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.851504 
iter  10 value 88.581131
iter  20 value 85.446397
final  value 85.438844 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.237311 
iter  10 value 94.096729
iter  20 value 81.181708
iter  30 value 80.458557
iter  40 value 80.414092
final  value 80.408117 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.120179 
iter  10 value 94.491897
iter  20 value 93.445887
iter  30 value 80.176778
iter  40 value 78.510596
iter  50 value 78.333959
iter  60 value 78.316871
iter  70 value 78.310293
iter  80 value 78.055342
iter  90 value 77.980736
iter 100 value 77.968356
final  value 77.968356 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.539445 
iter  10 value 94.431404
iter  20 value 94.429563
iter  30 value 91.076318
iter  40 value 85.019576
iter  50 value 81.689423
iter  60 value 81.476231
iter  70 value 81.427623
iter  80 value 81.342107
iter  90 value 81.244662
iter 100 value 81.208239
final  value 81.208239 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.355065 
iter  10 value 94.485091
iter  20 value 91.322892
iter  30 value 83.435982
iter  40 value 83.401085
iter  50 value 83.351559
final  value 83.351535 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.699503 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.778474 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.310969 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.837150 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.486276 
iter  10 value 93.714687
iter  20 value 93.714320
iter  20 value 93.714319
iter  20 value 93.714318
final  value 93.714318 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.142197 
iter  10 value 93.650498
final  value 93.649425 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.018580 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.536762 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.850005 
iter  10 value 93.923075
iter  20 value 93.918078
iter  30 value 93.916956
final  value 93.916876 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.725662 
final  value 94.088888 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.246497 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.849897 
iter  10 value 94.539232
iter  20 value 94.401202
iter  30 value 94.144892
final  value 94.144482 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.151136 
iter  10 value 90.390732
iter  20 value 90.014334
final  value 90.014268 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.628198 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.939385 
iter  10 value 94.467420
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.771768 
iter  10 value 94.407353
iter  20 value 92.256464
iter  30 value 91.954423
iter  40 value 85.288264
iter  50 value 83.532116
iter  60 value 83.005741
iter  70 value 82.582684
iter  80 value 82.190552
iter  90 value 82.085092
iter 100 value 82.022102
final  value 82.022102 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.548994 
iter  10 value 92.929388
iter  20 value 86.386948
iter  30 value 85.332755
iter  40 value 84.616333
iter  50 value 83.974863
final  value 83.930142 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.446140 
iter  10 value 94.405779
iter  20 value 89.656071
iter  30 value 85.883509
iter  40 value 84.977200
iter  50 value 84.562748
iter  60 value 83.953952
final  value 83.930142 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.297116 
iter  10 value 92.253584
iter  20 value 87.254478
iter  30 value 86.939827
iter  40 value 86.480738
iter  50 value 86.187342
iter  60 value 86.001373
final  value 86.001310 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.538708 
iter  10 value 94.403227
iter  20 value 86.804785
iter  30 value 84.849581
iter  40 value 84.087510
iter  50 value 83.546481
iter  60 value 83.522168
final  value 83.522131 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.149894 
iter  10 value 94.550782
iter  20 value 94.287651
iter  30 value 86.052273
iter  40 value 85.403116
iter  50 value 85.041349
iter  60 value 84.595571
iter  70 value 83.896597
iter  80 value 81.655601
iter  90 value 81.472398
iter 100 value 81.389077
final  value 81.389077 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.767681 
iter  10 value 94.396587
iter  20 value 92.090654
iter  30 value 90.534788
iter  40 value 89.380677
iter  50 value 87.950041
iter  60 value 86.512449
iter  70 value 83.652078
iter  80 value 83.207121
iter  90 value 82.494839
iter 100 value 81.611788
final  value 81.611788 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.369882 
iter  10 value 95.051196
iter  20 value 94.466783
iter  30 value 86.725273
iter  40 value 85.292265
iter  50 value 84.097922
iter  60 value 82.584394
iter  70 value 82.394748
iter  80 value 82.216337
iter  90 value 81.860891
iter 100 value 81.840561
final  value 81.840561 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.661205 
iter  10 value 94.316526
iter  20 value 89.546623
iter  30 value 84.874615
iter  40 value 81.824001
iter  50 value 81.305012
iter  60 value 80.930124
iter  70 value 80.714958
iter  80 value 80.564752
iter  90 value 80.539801
iter 100 value 80.535130
final  value 80.535130 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.021824 
iter  10 value 91.639645
iter  20 value 87.388555
iter  30 value 83.447913
iter  40 value 81.316303
iter  50 value 81.077013
iter  60 value 80.910863
iter  70 value 80.857952
iter  80 value 80.843394
iter  90 value 80.829540
iter 100 value 80.820890
final  value 80.820890 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.970600 
iter  10 value 94.459607
iter  20 value 88.824776
iter  30 value 85.907594
iter  40 value 82.218652
iter  50 value 81.440497
iter  60 value 81.236913
iter  70 value 81.067068
iter  80 value 80.990203
iter  90 value 80.980192
iter 100 value 80.966287
final  value 80.966287 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.899358 
iter  10 value 94.726537
iter  20 value 88.995771
iter  30 value 87.097292
iter  40 value 86.839428
iter  50 value 86.601680
iter  60 value 85.973586
iter  70 value 84.734659
iter  80 value 81.002751
iter  90 value 80.417023
iter 100 value 80.339845
final  value 80.339845 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.055211 
iter  10 value 96.146698
iter  20 value 94.534929
iter  30 value 86.118824
iter  40 value 85.736726
iter  50 value 83.549568
iter  60 value 81.879284
iter  70 value 81.742248
iter  80 value 81.599460
iter  90 value 81.196427
iter 100 value 81.008816
final  value 81.008816 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.879063 
iter  10 value 98.606204
iter  20 value 94.288840
iter  30 value 89.405939
iter  40 value 87.132779
iter  50 value 85.197654
iter  60 value 82.440953
iter  70 value 81.719751
iter  80 value 81.416962
iter  90 value 81.138502
iter 100 value 80.866775
final  value 80.866775 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.623398 
iter  10 value 94.928490
iter  20 value 94.510208
iter  30 value 94.444423
iter  40 value 93.816532
iter  50 value 88.184682
iter  60 value 87.161366
iter  70 value 84.969319
iter  80 value 84.256216
iter  90 value 83.905964
iter 100 value 82.420143
final  value 82.420143 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.838895 
final  value 94.485789 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.026337 
final  value 94.485500 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.119619 
iter  10 value 94.484692
final  value 94.484678 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.331729 
final  value 94.486188 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.251599 
final  value 94.485797 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.992582 
iter  10 value 94.318968
iter  20 value 87.670935
iter  30 value 86.973754
iter  40 value 86.951776
final  value 86.946437 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.484597 
iter  10 value 94.489031
iter  20 value 94.346931
iter  30 value 87.858351
iter  40 value 87.671228
iter  50 value 87.228692
iter  60 value 86.116876
iter  70 value 83.528558
iter  80 value 83.437646
iter  90 value 83.432023
iter 100 value 83.417288
final  value 83.417288 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.537589 
iter  10 value 94.489213
iter  20 value 94.050452
iter  30 value 88.277690
iter  40 value 87.097169
iter  50 value 87.089763
iter  50 value 87.089762
final  value 87.089762 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.869094 
iter  10 value 94.187324
iter  20 value 94.184631
iter  30 value 94.181413
final  value 94.181405 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.486653 
iter  10 value 94.489452
iter  20 value 94.484405
final  value 94.484324 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.543144 
iter  10 value 94.484804
iter  20 value 94.476000
iter  30 value 94.469975
iter  40 value 92.150265
iter  50 value 85.513078
iter  60 value 85.403282
iter  70 value 84.236699
iter  80 value 82.832711
iter  90 value 82.459896
iter 100 value 82.329416
final  value 82.329416 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.242901 
iter  10 value 94.108063
iter  20 value 93.949592
iter  30 value 84.736121
iter  40 value 84.581641
iter  50 value 84.580700
iter  60 value 84.580216
iter  70 value 84.056806
iter  80 value 83.347757
iter  90 value 83.324255
iter 100 value 83.324029
final  value 83.324029 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.078091 
iter  10 value 94.492127
iter  20 value 94.394102
iter  30 value 94.052746
final  value 94.052715 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.057498 
iter  10 value 94.256563
iter  20 value 93.956023
iter  30 value 89.434876
iter  40 value 88.341943
iter  50 value 88.334813
iter  60 value 88.283780
iter  70 value 87.335568
iter  80 value 87.298539
final  value 87.282517 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.879169 
iter  10 value 94.272410
iter  20 value 94.265236
iter  30 value 94.020632
iter  40 value 87.017207
iter  50 value 84.156138
final  value 84.155969 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.966850 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.853161 
final  value 94.251193 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.863545 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.897152 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.209328 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.534616 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.949202 
iter  10 value 91.473969
iter  20 value 91.266221
final  value 91.266196 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.506206 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.837220 
iter  10 value 94.112915
final  value 94.112903 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.463454 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.535314 
iter  10 value 94.146215
iter  20 value 94.065867
final  value 94.065746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.667646 
iter  10 value 94.333267
final  value 94.325945 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.036723 
final  value 94.165746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.876796 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.804245 
iter  10 value 87.352007
iter  20 value 86.347896
iter  30 value 86.239048
iter  40 value 86.238379
final  value 86.238376 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.731237 
iter  10 value 94.498019
iter  20 value 85.574363
iter  30 value 85.000870
iter  40 value 84.528997
iter  50 value 84.441192
iter  60 value 84.412623
iter  70 value 83.848782
iter  80 value 83.731138
iter  90 value 83.721537
final  value 83.721529 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.210198 
iter  10 value 91.527271
iter  20 value 88.879316
iter  30 value 86.560213
iter  40 value 86.432512
iter  50 value 85.330017
iter  60 value 84.805838
iter  70 value 84.303197
iter  80 value 84.079141
iter  90 value 84.070826
iter  90 value 84.070825
iter  90 value 84.070825
final  value 84.070825 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.415712 
iter  10 value 94.343783
iter  20 value 86.824806
iter  30 value 85.965974
iter  40 value 84.552435
iter  50 value 84.044717
iter  60 value 83.862919
iter  70 value 83.762303
iter  80 value 83.735538
iter  90 value 83.721584
final  value 83.721529 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.653152 
iter  10 value 94.486508
iter  20 value 94.212570
iter  30 value 94.190325
final  value 94.188780 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.834244 
iter  10 value 94.486617
iter  20 value 94.484434
iter  30 value 93.206141
iter  40 value 91.353887
iter  50 value 91.150217
final  value 91.147653 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.814193 
iter  10 value 92.313234
iter  20 value 87.904752
iter  30 value 85.206704
iter  40 value 84.592593
iter  50 value 83.920091
iter  60 value 83.762751
iter  70 value 83.712969
iter  80 value 83.357388
iter  90 value 83.238116
iter 100 value 83.019114
final  value 83.019114 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.362230 
iter  10 value 94.456262
iter  20 value 88.909172
iter  30 value 85.598880
iter  40 value 85.097426
iter  50 value 84.726872
iter  60 value 84.055695
iter  70 value 83.803093
iter  80 value 83.575640
iter  90 value 83.343341
iter 100 value 83.163614
final  value 83.163614 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.062088 
iter  10 value 94.489456
iter  20 value 90.205820
iter  30 value 85.699832
iter  40 value 85.179005
iter  50 value 84.555651
iter  60 value 84.417007
iter  70 value 83.870196
iter  80 value 83.238555
iter  90 value 82.842477
iter 100 value 82.767459
final  value 82.767459 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.611431 
iter  10 value 94.622941
iter  20 value 94.497114
iter  30 value 94.373171
iter  40 value 91.003275
iter  50 value 90.575181
iter  60 value 85.722750
iter  70 value 84.670357
iter  80 value 84.559522
iter  90 value 84.353292
iter 100 value 83.266404
final  value 83.266404 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.958024 
iter  10 value 94.930291
iter  20 value 94.079363
iter  30 value 88.401793
iter  40 value 85.904519
iter  50 value 84.523558
iter  60 value 83.920233
iter  70 value 83.306214
iter  80 value 83.126065
iter  90 value 82.915780
iter 100 value 82.777034
final  value 82.777034 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.574644 
iter  10 value 94.883657
iter  20 value 93.284905
iter  30 value 91.834032
iter  40 value 87.858340
iter  50 value 84.616339
iter  60 value 83.477006
iter  70 value 83.316483
iter  80 value 82.960837
iter  90 value 82.932967
iter 100 value 82.694779
final  value 82.694779 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.560572 
iter  10 value 96.209121
iter  20 value 90.295397
iter  30 value 84.873860
iter  40 value 83.895175
iter  50 value 83.570807
iter  60 value 82.549886
iter  70 value 82.173465
iter  80 value 82.001295
iter  90 value 81.960341
iter 100 value 81.930005
final  value 81.930005 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.485875 
iter  10 value 94.425329
iter  20 value 92.054660
iter  30 value 91.554746
iter  40 value 90.865118
iter  50 value 86.985036
iter  60 value 84.174607
iter  70 value 83.708484
iter  80 value 82.720505
iter  90 value 81.948408
iter 100 value 81.555380
final  value 81.555380 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.191905 
iter  10 value 95.723694
iter  20 value 86.439531
iter  30 value 85.554190
iter  40 value 83.579017
iter  50 value 82.685952
iter  60 value 82.200383
iter  70 value 82.048389
iter  80 value 81.951285
iter  90 value 81.902802
iter 100 value 81.748680
final  value 81.748680 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.375532 
iter  10 value 94.194024
iter  20 value 90.244823
iter  30 value 86.320453
iter  40 value 84.793547
iter  50 value 83.930580
iter  60 value 83.522239
iter  70 value 83.226949
iter  80 value 82.790322
iter  90 value 82.751043
iter 100 value 82.574962
final  value 82.574962 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.071164 
final  value 94.485945 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.605014 
final  value 94.485824 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.922053 
iter  10 value 94.116409
iter  20 value 88.998580
iter  30 value 84.421123
iter  40 value 84.418856
iter  50 value 83.974401
final  value 83.770582 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.780627 
final  value 94.485882 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.738153 
final  value 94.485918 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.898301 
iter  10 value 88.630909
iter  20 value 88.526689
iter  30 value 88.518625
iter  40 value 85.890305
iter  50 value 85.486483
iter  60 value 85.029129
iter  70 value 84.900795
iter  80 value 84.900209
iter  90 value 83.011488
iter 100 value 83.010329
final  value 83.010329 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.939407 
iter  10 value 94.485887
iter  20 value 88.545312
iter  30 value 86.539898
iter  40 value 86.519948
iter  50 value 85.794185
final  value 85.794179 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.261074 
iter  10 value 94.162858
iter  20 value 94.161286
iter  30 value 94.109698
iter  40 value 94.079380
iter  50 value 90.439679
iter  60 value 86.977155
iter  70 value 85.989707
iter  80 value 85.900178
iter  90 value 85.871453
iter 100 value 85.832210
final  value 85.832210 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.873137 
iter  10 value 94.488738
iter  20 value 94.484545
final  value 94.484428 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.341254 
iter  10 value 94.483721
iter  20 value 93.988327
iter  30 value 87.099881
iter  40 value 87.099578
iter  50 value 86.605477
final  value 86.603650 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.231913 
iter  10 value 94.121038
iter  20 value 94.118656
iter  30 value 94.075460
iter  40 value 94.066906
iter  50 value 94.066491
final  value 94.066468 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.493727 
iter  10 value 94.456486
iter  20 value 93.830892
iter  30 value 93.787172
iter  40 value 93.785730
iter  50 value 92.697728
iter  60 value 85.623662
iter  70 value 85.130966
iter  80 value 84.966560
iter  90 value 84.960784
iter 100 value 84.959246
final  value 84.959246 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.703708 
iter  10 value 94.122290
iter  20 value 94.120115
iter  30 value 94.114294
iter  40 value 93.678797
iter  50 value 92.779246
iter  60 value 83.889325
iter  70 value 81.155002
iter  80 value 80.723762
iter  90 value 80.529822
iter 100 value 80.372026
final  value 80.372026 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.576187 
iter  10 value 93.982786
iter  20 value 93.981404
iter  30 value 93.974046
iter  40 value 86.588392
final  value 86.566492 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.679966 
iter  10 value 94.121043
iter  20 value 94.114704
iter  30 value 94.106557
iter  40 value 93.823449
iter  50 value 88.501051
iter  60 value 88.221683
iter  70 value 86.450598
iter  80 value 83.264651
iter  90 value 81.724470
iter 100 value 80.815626
final  value 80.815626 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.757274 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.736853 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.593605 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.234198 
iter  10 value 94.053194
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.206949 
iter  10 value 93.455092
final  value 93.455029 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.556198 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.033207 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.649656 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.018092 
iter  10 value 94.013518
iter  20 value 87.217029
iter  30 value 87.138446
iter  40 value 86.793456
iter  50 value 86.567097
iter  60 value 86.279092
final  value 85.976098 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.896485 
final  value 93.414528 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.502431 
iter  10 value 82.596460
iter  20 value 82.541713
final  value 82.541667 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.059803 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.131619 
iter  10 value 93.455036
final  value 93.455030 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.665900 
iter  10 value 93.733275
iter  20 value 93.725675
final  value 93.725223 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.151046 
iter  10 value 93.455039
final  value 93.455030 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.742540 
iter  10 value 94.028800
iter  20 value 93.265399
iter  30 value 93.249353
iter  40 value 93.240866
iter  50 value 82.439262
iter  60 value 79.691222
iter  70 value 78.998345
iter  80 value 78.540826
final  value 78.524034 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.103442 
iter  10 value 94.723523
iter  20 value 93.263524
iter  30 value 93.179444
iter  40 value 88.168877
iter  50 value 82.774617
iter  60 value 80.861520
iter  70 value 80.033706
iter  80 value 79.743946
iter  90 value 79.423832
iter 100 value 79.131088
final  value 79.131088 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.543064 
iter  10 value 93.894635
iter  20 value 84.706302
iter  30 value 81.830400
iter  40 value 79.966324
iter  50 value 79.309672
iter  60 value 79.097698
final  value 79.064063 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.370330 
iter  10 value 94.021622
iter  20 value 92.058813
iter  30 value 85.621554
iter  40 value 82.920867
iter  50 value 81.505905
iter  60 value 81.468415
iter  70 value 81.446562
final  value 81.438153 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.917512 
iter  10 value 93.768434
iter  20 value 90.496743
iter  30 value 86.569817
iter  40 value 85.999201
iter  50 value 85.881123
iter  60 value 85.869545
iter  70 value 85.826008
iter  80 value 85.824336
final  value 85.819632 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.183446 
iter  10 value 94.086277
iter  20 value 93.987764
iter  30 value 84.077678
iter  40 value 82.247402
iter  50 value 81.824245
iter  60 value 80.165850
iter  70 value 78.753942
iter  80 value 78.037526
iter  90 value 77.515264
iter 100 value 77.292526
final  value 77.292526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.201021 
iter  10 value 94.471975
iter  20 value 93.871477
iter  30 value 91.351223
iter  40 value 91.097746
iter  50 value 83.794305
iter  60 value 82.347428
iter  70 value 81.856704
iter  80 value 81.644429
iter  90 value 80.822976
iter 100 value 79.729778
final  value 79.729778 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.887455 
iter  10 value 93.584087
iter  20 value 93.257043
iter  30 value 92.046879
iter  40 value 90.596161
iter  50 value 89.531826
iter  60 value 82.011583
iter  70 value 81.399074
iter  80 value 80.271183
iter  90 value 79.983391
iter 100 value 78.161371
final  value 78.161371 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.062314 
iter  10 value 94.255471
iter  20 value 93.237102
iter  30 value 90.563020
iter  40 value 82.438236
iter  50 value 80.622166
iter  60 value 78.885166
iter  70 value 78.526035
iter  80 value 78.303141
iter  90 value 78.160385
iter 100 value 78.061079
final  value 78.061079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.525886 
iter  10 value 93.830520
iter  20 value 84.079543
iter  30 value 83.600362
iter  40 value 81.893400
iter  50 value 80.509322
iter  60 value 79.611432
iter  70 value 79.384444
iter  80 value 78.628373
iter  90 value 78.464081
iter 100 value 78.228667
final  value 78.228667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.482257 
iter  10 value 93.834326
iter  20 value 85.269774
iter  30 value 83.200856
iter  40 value 82.380698
iter  50 value 80.698437
iter  60 value 79.820836
iter  70 value 79.477744
iter  80 value 79.216330
iter  90 value 79.059682
iter 100 value 78.901843
final  value 78.901843 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.603221 
iter  10 value 93.978538
iter  20 value 91.794045
iter  30 value 85.373787
iter  40 value 79.731366
iter  50 value 78.904698
iter  60 value 77.914932
iter  70 value 77.125237
iter  80 value 76.848455
iter  90 value 76.769010
iter 100 value 76.731792
final  value 76.731792 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.519321 
iter  10 value 93.853852
iter  20 value 91.501711
iter  30 value 87.017928
iter  40 value 83.252743
iter  50 value 82.582115
iter  60 value 80.919962
iter  70 value 79.041346
iter  80 value 77.881413
iter  90 value 77.618315
iter 100 value 77.363122
final  value 77.363122 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.843714 
iter  10 value 94.184480
iter  20 value 88.652324
iter  30 value 87.386924
iter  40 value 82.004663
iter  50 value 81.181459
iter  60 value 80.711353
iter  70 value 79.143980
iter  80 value 78.329878
iter  90 value 77.352352
iter 100 value 76.868104
final  value 76.868104 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.285554 
iter  10 value 93.320840
iter  20 value 87.177892
iter  30 value 82.448911
iter  40 value 81.275557
iter  50 value 80.831744
iter  60 value 80.756660
iter  70 value 80.561666
iter  80 value 79.839271
iter  90 value 78.262426
iter 100 value 77.909498
final  value 77.909498 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.237954 
final  value 94.054507 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.462496 
iter  10 value 94.054703
iter  20 value 94.052040
iter  30 value 93.092321
final  value 93.092183 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.438711 
iter  10 value 94.054581
iter  20 value 93.963663
iter  30 value 84.385751
iter  40 value 83.657852
iter  50 value 83.644474
iter  60 value 83.086753
iter  70 value 82.903221
iter  80 value 82.826757
iter  90 value 80.703270
iter 100 value 80.107161
final  value 80.107161 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.509181 
final  value 94.054829 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.804349 
iter  10 value 93.917324
iter  20 value 93.915817
iter  30 value 89.237463
iter  40 value 89.218240
iter  50 value 87.113229
iter  60 value 85.262365
iter  70 value 83.786533
iter  80 value 83.722369
iter  90 value 83.703305
iter 100 value 83.540745
final  value 83.540745 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 119.365690 
iter  10 value 93.920754
iter  20 value 93.107316
iter  30 value 91.882854
iter  40 value 84.563628
iter  50 value 83.933654
iter  60 value 83.524915
iter  70 value 83.512153
iter  80 value 82.991874
final  value 82.991780 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.568856 
iter  10 value 93.769286
iter  20 value 93.766832
iter  30 value 93.675604
iter  40 value 93.349579
iter  50 value 93.314789
final  value 93.314777 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.705980 
iter  10 value 94.057175
iter  20 value 94.048618
iter  30 value 93.091258
iter  30 value 93.091258
iter  30 value 93.091258
final  value 93.091258 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.023289 
iter  10 value 94.057447
final  value 94.052920 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.550698 
iter  10 value 92.528135
iter  20 value 90.712927
iter  30 value 90.704222
iter  40 value 90.133149
iter  50 value 89.037730
iter  60 value 89.036688
iter  70 value 89.036151
iter  80 value 89.035859
iter  80 value 89.035859
final  value 89.035859 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.920118 
iter  10 value 90.675927
iter  20 value 90.674002
iter  30 value 89.728991
iter  40 value 89.173363
iter  50 value 89.155641
iter  60 value 89.155329
iter  70 value 89.155023
final  value 89.154842 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.488923 
iter  10 value 93.600221
iter  20 value 93.015296
iter  30 value 92.311716
iter  40 value 92.309817
iter  50 value 92.306758
iter  60 value 92.306633
iter  70 value 92.306454
iter  80 value 90.693762
iter  90 value 90.336376
iter 100 value 89.604542
final  value 89.604542 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.009001 
iter  10 value 93.612765
iter  20 value 84.319799
iter  30 value 83.795714
iter  40 value 82.890320
iter  50 value 82.517547
iter  60 value 82.512082
iter  70 value 81.960409
iter  80 value 80.839114
iter  90 value 80.646311
iter 100 value 80.493318
final  value 80.493318 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.525745 
iter  10 value 87.718868
iter  20 value 84.754178
iter  30 value 84.753650
iter  40 value 84.545436
iter  50 value 84.544380
final  value 84.540584 
converged
Fitting Repeat 5 

# weights:  507
initial  value 132.597778 
iter  10 value 94.060604
iter  20 value 92.014776
iter  30 value 85.902478
iter  40 value 84.594685
iter  50 value 84.576660
iter  50 value 84.576660
iter  50 value 84.576660
final  value 84.576660 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.868310 
iter  10 value 117.895113
iter  20 value 117.612200
iter  30 value 113.897281
iter  40 value 111.499208
iter  50 value 111.409440
iter  60 value 111.402473
iter  70 value 107.633234
iter  80 value 105.182588
iter  90 value 104.625621
iter 100 value 104.600580
final  value 104.600580 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.790910 
iter  10 value 117.764121
iter  20 value 117.763283
final  value 117.759684 
converged
Fitting Repeat 3 

# weights:  305
initial  value 154.466118 
iter  10 value 117.895426
iter  20 value 117.823461
iter  30 value 116.912930
iter  40 value 109.400209
iter  50 value 106.395989
iter  60 value 105.329221
iter  70 value 104.704669
iter  80 value 104.593303
iter  90 value 104.313120
iter 100 value 104.312639
final  value 104.312639 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.399472 
iter  10 value 117.894341
iter  20 value 112.998679
iter  30 value 107.036900
iter  40 value 107.016074
iter  50 value 106.953348
iter  60 value 106.908368
iter  70 value 106.659469
final  value 106.657798 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.816734 
iter  10 value 114.187333
iter  20 value 109.153329
iter  30 value 107.931049
iter  40 value 107.897984
iter  50 value 107.893698
iter  60 value 106.827654
iter  70 value 105.889761
iter  80 value 105.369095
iter  90 value 105.218560
iter 100 value 105.216987
final  value 105.216987 
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 Jun 12 21:25:19 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 
 41.527   1.633 122.473