##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-05 r89546)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-13 04:12:46 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... 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       38.179  0.581  38.837
corr_plot     35.483  0.320  35.831
FSmethod      33.863  0.619  34.487
pred_ensembel 12.923  0.103  11.713
enrichfindP    0.567  0.038   8.997
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 106.092929 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.299554 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.108987 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.420789 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.103527 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.321184 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.577853 
iter  10 value 94.040200
iter  20 value 94.018678
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.792911 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.069035 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.387355 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.289006 
iter  10 value 93.935550
iter  20 value 93.934349
final  value 93.934347 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.673121 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.575734 
iter  10 value 93.030173
iter  20 value 88.603150
iter  30 value 88.591889
final  value 88.591840 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.097424 
iter  10 value 93.659915
final  value 93.656595 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.533370 
iter  10 value 93.884871
iter  20 value 86.341291
iter  30 value 86.256827
iter  40 value 86.255122
iter  40 value 86.255121
iter  40 value 86.255121
final  value 86.255121 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.850343 
iter  10 value 93.990861
iter  20 value 88.651867
iter  30 value 87.928080
iter  40 value 86.757987
iter  50 value 86.518236
iter  60 value 86.459175
iter  70 value 86.412484
iter  80 value 86.282174
iter  90 value 86.175873
final  value 86.175869 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.189490 
iter  10 value 94.054862
iter  10 value 94.054862
iter  20 value 94.014744
iter  30 value 93.432719
iter  40 value 92.903584
iter  50 value 92.837267
iter  60 value 91.763131
iter  70 value 91.253105
iter  80 value 91.230143
iter  90 value 91.190597
final  value 91.186686 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.143159 
iter  10 value 94.317258
iter  20 value 94.054727
iter  30 value 92.843858
iter  40 value 89.848786
iter  50 value 89.452108
iter  60 value 88.923158
iter  70 value 86.677976
iter  80 value 86.408653
iter  90 value 86.389410
iter 100 value 86.384037
final  value 86.384037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.643232 
iter  10 value 94.031794
iter  20 value 90.402803
iter  30 value 88.985478
iter  40 value 87.373563
iter  50 value 86.699965
iter  60 value 86.629858
iter  70 value 86.586600
iter  80 value 86.466727
iter  90 value 86.391994
iter 100 value 86.381004
final  value 86.381004 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.251031 
iter  10 value 94.038007
iter  20 value 91.073426
iter  30 value 90.208771
iter  40 value 88.351463
iter  50 value 87.234514
iter  60 value 86.391984
iter  70 value 86.381006
final  value 86.381004 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.871903 
iter  10 value 94.891376
iter  20 value 93.744481
iter  30 value 93.709495
iter  40 value 92.910699
iter  50 value 89.126902
iter  60 value 86.467903
iter  70 value 86.245522
iter  80 value 86.084325
iter  90 value 84.911828
iter 100 value 84.737067
final  value 84.737067 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.211463 
iter  10 value 94.036290
iter  20 value 92.283698
iter  30 value 89.491011
iter  40 value 88.153117
iter  50 value 85.107402
iter  60 value 84.551805
iter  70 value 84.079606
iter  80 value 83.407368
iter  90 value 82.983385
iter 100 value 82.921563
final  value 82.921563 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.437997 
iter  10 value 94.002925
iter  20 value 92.382074
iter  30 value 91.471608
iter  40 value 91.386903
iter  50 value 90.626467
iter  60 value 88.307649
iter  70 value 86.401719
iter  80 value 85.551313
iter  90 value 85.086491
iter 100 value 83.590712
final  value 83.590712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.747735 
iter  10 value 91.536532
iter  20 value 86.077168
iter  30 value 85.423029
iter  40 value 85.107080
iter  50 value 84.685331
iter  60 value 84.425570
iter  70 value 84.250860
iter  80 value 83.957743
iter  90 value 83.884264
iter 100 value 83.846171
final  value 83.846171 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.580917 
iter  10 value 95.762111
iter  20 value 93.862473
iter  30 value 93.217940
iter  40 value 92.936223
iter  50 value 85.844929
iter  60 value 85.524160
iter  70 value 85.399892
iter  80 value 85.181944
iter  90 value 84.776045
iter 100 value 84.613632
final  value 84.613632 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.477273 
iter  10 value 94.409760
iter  20 value 94.069552
iter  30 value 93.887642
iter  40 value 87.547999
iter  50 value 87.244953
iter  60 value 85.842607
iter  70 value 84.862566
iter  80 value 83.378549
iter  90 value 82.717353
iter 100 value 82.506355
final  value 82.506355 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.797174 
iter  10 value 96.730655
iter  20 value 94.083447
iter  30 value 94.053662
iter  40 value 89.204999
iter  50 value 86.591422
iter  60 value 86.214290
iter  70 value 85.681014
iter  80 value 84.710357
iter  90 value 83.812840
iter 100 value 83.493503
final  value 83.493503 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.435391 
iter  10 value 94.492356
iter  20 value 94.268885
iter  30 value 88.046469
iter  40 value 87.608014
iter  50 value 87.026282
iter  60 value 86.064579
iter  70 value 85.804289
iter  80 value 85.733891
iter  90 value 85.450975
iter 100 value 84.875356
final  value 84.875356 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.808706 
iter  10 value 94.512942
iter  20 value 93.900675
iter  30 value 92.242097
iter  40 value 91.462256
iter  50 value 91.259433
iter  60 value 85.676777
iter  70 value 84.016141
iter  80 value 83.720561
iter  90 value 83.044534
iter 100 value 82.654775
final  value 82.654775 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.950457 
iter  10 value 94.195264
iter  20 value 93.958841
iter  30 value 89.980425
iter  40 value 88.026541
iter  50 value 86.525836
iter  60 value 85.295467
iter  70 value 84.597219
iter  80 value 83.881312
iter  90 value 83.647487
iter 100 value 83.622065
final  value 83.622065 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.500754 
final  value 94.040170 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.891937 
final  value 94.054632 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.292880 
final  value 94.054456 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.390656 
iter  10 value 94.054475
final  value 94.052921 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.178077 
iter  10 value 94.054335
iter  20 value 94.052914
iter  20 value 94.052914
iter  20 value 94.052914
final  value 94.052914 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.250666 
iter  10 value 94.057608
iter  20 value 94.053081
iter  30 value 93.396947
iter  40 value 91.776955
iter  50 value 91.670809
iter  60 value 89.270589
iter  70 value 89.206198
iter  80 value 89.187225
iter  90 value 89.183499
iter 100 value 89.182803
final  value 89.182803 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.916045 
iter  10 value 94.042353
final  value 94.040196 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.333987 
iter  10 value 94.058247
iter  20 value 94.049970
iter  30 value 92.159086
iter  40 value 86.159610
iter  50 value 82.885761
iter  60 value 82.358084
iter  70 value 81.594388
iter  80 value 81.477574
iter  90 value 81.176468
iter 100 value 81.125438
final  value 81.125438 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.670747 
iter  10 value 94.057826
iter  20 value 94.047338
iter  30 value 94.038488
final  value 94.038472 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.766865 
iter  10 value 94.057432
iter  20 value 94.041092
iter  30 value 94.039496
iter  40 value 93.794516
iter  50 value 92.186726
iter  60 value 90.572498
iter  70 value 90.365882
iter  80 value 90.352116
final  value 90.352021 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.452268 
iter  10 value 94.061206
iter  20 value 92.741822
iter  30 value 91.735888
iter  40 value 91.735717
final  value 91.735715 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.782973 
iter  10 value 89.421859
iter  20 value 87.665016
iter  30 value 87.609498
iter  40 value 87.591920
iter  50 value 85.836546
iter  60 value 85.788354
iter  70 value 85.597118
iter  80 value 84.849688
iter  90 value 82.865369
iter 100 value 82.522591
final  value 82.522591 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.379578 
iter  10 value 93.658252
iter  20 value 93.655505
iter  30 value 93.654581
iter  40 value 93.650123
final  value 93.649849 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.196623 
iter  10 value 94.060654
iter  20 value 94.048134
iter  30 value 94.043015
iter  40 value 93.369038
iter  50 value 86.385392
iter  60 value 86.357446
iter  70 value 86.298720
iter  80 value 86.258065
iter  90 value 84.797823
iter 100 value 84.674309
final  value 84.674309 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.225178 
iter  10 value 94.059968
iter  20 value 93.370051
iter  30 value 92.045716
iter  40 value 91.368289
iter  50 value 91.190140
iter  60 value 91.186639
final  value 91.186542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.554650 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.036881 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.383930 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.366929 
iter  10 value 88.580961
final  value 88.555221 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.986394 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.933780 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.773294 
iter  10 value 94.071857
final  value 94.071545 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.954330 
iter  10 value 91.854309
iter  20 value 90.342985
iter  30 value 90.341030
iter  30 value 90.341030
final  value 90.341024 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.589882 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.096908 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.184069 
iter  10 value 88.965747
iter  20 value 86.086455
iter  30 value 86.036894
final  value 86.036816 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.202541 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.445431 
iter  10 value 91.709551
iter  20 value 90.226712
iter  30 value 90.225439
iter  30 value 90.225438
iter  30 value 90.225438
final  value 90.225438 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.411477 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.351391 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.331345 
iter  10 value 93.246185
iter  20 value 91.073589
iter  30 value 89.415329
iter  40 value 85.878854
iter  50 value 84.994040
iter  60 value 83.718983
iter  70 value 83.256012
iter  80 value 83.177652
iter  90 value 83.092948
iter 100 value 83.050249
final  value 83.050249 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.559384 
iter  10 value 94.341531
iter  20 value 94.327301
iter  30 value 93.812936
iter  40 value 91.389881
iter  50 value 89.141080
iter  60 value 87.897976
iter  70 value 87.702861
iter  80 value 82.236028
iter  90 value 81.688370
iter 100 value 81.560528
final  value 81.560528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.842413 
iter  10 value 94.508345
iter  20 value 94.406508
iter  30 value 93.661682
iter  40 value 87.727271
iter  50 value 87.630349
iter  60 value 87.532997
iter  70 value 87.507100
iter  80 value 83.344813
iter  90 value 83.128499
iter 100 value 82.779988
final  value 82.779988 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.108566 
iter  10 value 94.488564
iter  20 value 94.480614
iter  30 value 94.313004
iter  40 value 90.702233
iter  50 value 87.987079
iter  60 value 86.337116
iter  70 value 83.823878
iter  80 value 83.042361
iter  90 value 82.836032
iter 100 value 81.932951
final  value 81.932951 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.907882 
iter  10 value 94.341761
iter  20 value 89.287558
iter  30 value 88.439851
iter  40 value 83.398133
iter  50 value 82.042325
iter  60 value 81.604477
iter  70 value 81.228675
iter  80 value 81.092478
final  value 81.092453 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.803943 
iter  10 value 94.111863
iter  20 value 86.879802
iter  30 value 82.846776
iter  40 value 82.466365
iter  50 value 81.407907
iter  60 value 80.325741
iter  70 value 79.389832
iter  80 value 79.003001
iter  90 value 78.896430
iter 100 value 78.838089
final  value 78.838089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.676875 
iter  10 value 94.407098
iter  20 value 89.730897
iter  30 value 86.326361
iter  40 value 85.277954
iter  50 value 83.740191
iter  60 value 82.833977
iter  70 value 82.057320
iter  80 value 81.478269
iter  90 value 81.155523
iter 100 value 81.097605
final  value 81.097605 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.503375 
iter  10 value 94.400342
iter  20 value 86.241746
iter  30 value 85.193678
iter  40 value 84.776489
iter  50 value 83.793427
iter  60 value 81.250151
iter  70 value 80.897915
iter  80 value 80.579907
iter  90 value 80.207262
iter 100 value 80.008768
final  value 80.008768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.187049 
iter  10 value 94.316124
iter  20 value 91.616374
iter  30 value 83.448101
iter  40 value 81.036061
iter  50 value 80.421474
iter  60 value 79.929733
iter  70 value 79.521817
iter  80 value 79.458745
iter  90 value 79.374643
iter 100 value 79.207128
final  value 79.207128 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.242021 
iter  10 value 94.291246
iter  20 value 92.814277
iter  30 value 90.015409
iter  40 value 86.966029
iter  50 value 83.654488
iter  60 value 81.071535
iter  70 value 80.045917
iter  80 value 79.850946
iter  90 value 79.572928
iter 100 value 79.135464
final  value 79.135464 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.608862 
iter  10 value 94.001481
iter  20 value 91.773016
iter  30 value 86.088879
iter  40 value 84.326440
iter  50 value 83.443860
iter  60 value 83.290647
iter  70 value 83.202420
iter  80 value 83.121735
iter  90 value 81.373892
iter 100 value 80.885457
final  value 80.885457 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.745616 
iter  10 value 94.616703
iter  20 value 94.293901
iter  30 value 94.074987
iter  40 value 91.043230
iter  50 value 87.098278
iter  60 value 84.303217
iter  70 value 82.204896
iter  80 value 81.169222
iter  90 value 80.599340
iter 100 value 79.767376
final  value 79.767376 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.256650 
iter  10 value 95.100111
iter  20 value 90.021312
iter  30 value 85.693871
iter  40 value 85.142022
iter  50 value 84.641590
iter  60 value 83.305566
iter  70 value 82.350212
iter  80 value 81.831658
iter  90 value 81.430523
iter 100 value 80.531775
final  value 80.531775 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.898089 
iter  10 value 94.685689
iter  20 value 90.125529
iter  30 value 84.720422
iter  40 value 81.882268
iter  50 value 81.689930
iter  60 value 80.768659
iter  70 value 79.928265
iter  80 value 79.844373
iter  90 value 79.545071
iter 100 value 79.350595
final  value 79.350595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.955575 
iter  10 value 97.542166
iter  20 value 91.011478
iter  30 value 85.797560
iter  40 value 84.374164
iter  50 value 81.896848
iter  60 value 80.667210
iter  70 value 80.336390
iter  80 value 79.956261
iter  90 value 79.624911
iter 100 value 79.467751
final  value 79.467751 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.871336 
final  value 94.486368 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.250373 
iter  10 value 94.485868
iter  20 value 94.483918
iter  30 value 88.702785
iter  40 value 87.607753
iter  50 value 87.601593
iter  60 value 86.009666
iter  70 value 85.880765
final  value 85.868164 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.803255 
final  value 94.486022 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.099401 
final  value 94.485806 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.927763 
final  value 94.485766 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.322170 
iter  10 value 94.484730
final  value 94.484728 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.113936 
iter  10 value 94.489003
iter  20 value 94.478295
iter  30 value 90.768604
iter  40 value 85.956428
iter  50 value 85.941862
iter  60 value 84.748183
iter  70 value 83.937387
iter  80 value 83.929158
final  value 83.928677 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.455577 
iter  10 value 94.063372
iter  20 value 94.061457
iter  30 value 94.033048
iter  40 value 94.030121
iter  50 value 94.028144
iter  60 value 94.028012
final  value 94.027963 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.182435 
iter  10 value 94.487438
iter  20 value 91.886985
iter  30 value 90.322315
iter  40 value 90.316149
iter  50 value 90.309686
iter  60 value 90.307483
iter  70 value 90.059347
iter  80 value 89.332594
iter  90 value 84.998252
iter 100 value 83.927460
final  value 83.927460 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.806116 
iter  10 value 94.489286
iter  20 value 94.484280
final  value 94.484224 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.223032 
iter  10 value 94.283897
iter  20 value 94.279152
iter  30 value 94.275481
iter  40 value 88.441717
iter  50 value 86.256587
iter  60 value 86.095216
iter  70 value 85.474212
iter  80 value 84.785502
iter  90 value 84.714459
iter 100 value 84.544745
final  value 84.544745 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.331916 
iter  10 value 94.488839
iter  20 value 94.269813
iter  30 value 85.012026
iter  40 value 83.965921
iter  50 value 82.674831
iter  60 value 77.750156
iter  70 value 77.579517
iter  80 value 77.569974
iter  90 value 77.564522
iter 100 value 77.562611
final  value 77.562611 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.579008 
iter  10 value 94.491516
iter  20 value 94.117220
iter  30 value 93.045646
final  value 93.045637 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.088334 
iter  10 value 87.271494
iter  20 value 87.182706
iter  30 value 86.552500
iter  40 value 86.471639
iter  50 value 86.242869
iter  60 value 86.229533
iter  70 value 86.227888
iter  80 value 86.227538
final  value 86.227365 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.279871 
iter  10 value 94.283406
iter  20 value 94.238663
iter  30 value 94.205125
final  value 94.204731 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.025851 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.299572 
final  value 92.701658 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.989171 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.568663 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.687129 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.874946 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.186408 
final  value 93.904720 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.359629 
iter  10 value 93.836171
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.044471 
iter  10 value 93.543416
iter  20 value 93.543204
iter  20 value 93.543203
final  value 93.543203 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.331739 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.283387 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.118506 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.439103 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.308943 
final  value 93.904720 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.307210 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.998825 
iter  10 value 93.682892
iter  20 value 85.730722
iter  30 value 84.641005
iter  40 value 84.115094
iter  50 value 82.148616
iter  60 value 81.719127
iter  70 value 81.561487
iter  80 value 81.415298
iter  90 value 81.355035
final  value 81.346661 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.886043 
iter  10 value 94.299546
iter  20 value 93.944825
iter  30 value 87.009071
iter  40 value 86.493281
iter  50 value 80.879011
iter  60 value 80.274981
iter  70 value 78.709843
iter  80 value 78.034095
iter  90 value 77.896560
iter 100 value 77.808700
final  value 77.808700 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.940597 
iter  10 value 94.051574
iter  20 value 88.439684
iter  30 value 84.728756
iter  40 value 82.166366
iter  50 value 81.433065
iter  60 value 81.349493
iter  70 value 81.346664
final  value 81.346661 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.680716 
iter  10 value 94.056273
iter  20 value 83.469182
iter  30 value 82.819543
iter  40 value 81.573165
iter  50 value 81.262320
iter  60 value 79.914296
iter  70 value 79.382428
iter  80 value 77.894817
iter  90 value 77.858908
iter 100 value 77.839864
final  value 77.839864 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.111687 
iter  10 value 94.057500
iter  20 value 91.577551
iter  30 value 85.283688
iter  40 value 82.653894
iter  50 value 82.256959
iter  60 value 82.097905
iter  70 value 81.989258
iter  80 value 81.376548
final  value 81.346661 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.331568 
iter  10 value 94.239254
iter  20 value 93.756936
iter  30 value 93.548652
iter  40 value 87.962515
iter  50 value 86.979765
iter  60 value 86.336396
iter  70 value 82.950809
iter  80 value 82.335659
iter  90 value 81.744994
iter 100 value 81.265089
final  value 81.265089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.165246 
iter  10 value 90.468439
iter  20 value 82.887287
iter  30 value 80.794341
iter  40 value 79.639917
iter  50 value 79.291650
iter  60 value 78.178806
iter  70 value 77.854387
iter  80 value 77.668733
iter  90 value 77.285171
iter 100 value 76.733454
final  value 76.733454 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.154879 
iter  10 value 93.874143
iter  20 value 86.704924
iter  30 value 85.611788
iter  40 value 81.805836
iter  50 value 78.547725
iter  60 value 77.712640
iter  70 value 77.082444
iter  80 value 76.942540
iter  90 value 76.914102
iter 100 value 76.882016
final  value 76.882016 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.952617 
iter  10 value 93.522974
iter  20 value 83.260771
iter  30 value 79.470068
iter  40 value 79.019784
iter  50 value 77.627655
iter  60 value 77.107409
iter  70 value 76.766364
iter  80 value 76.699651
iter  90 value 76.641057
iter 100 value 76.637472
final  value 76.637472 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.525399 
iter  10 value 94.352188
iter  20 value 94.175748
iter  30 value 93.802424
iter  40 value 88.669062
iter  50 value 83.819772
iter  60 value 82.530518
iter  70 value 81.382173
iter  80 value 81.003905
iter  90 value 79.577844
iter 100 value 79.366478
final  value 79.366478 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.915234 
iter  10 value 97.703788
iter  20 value 91.698696
iter  30 value 91.433336
iter  40 value 84.805161
iter  50 value 82.898878
iter  60 value 81.750403
iter  70 value 79.824696
iter  80 value 78.659634
iter  90 value 78.217615
iter 100 value 78.163270
final  value 78.163270 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.934975 
iter  10 value 94.138975
iter  20 value 93.462381
iter  30 value 92.488881
iter  40 value 81.103844
iter  50 value 79.308116
iter  60 value 79.136810
iter  70 value 78.578134
iter  80 value 78.376964
iter  90 value 78.067100
iter 100 value 77.400547
final  value 77.400547 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.692473 
iter  10 value 93.791606
iter  20 value 86.165232
iter  30 value 81.206401
iter  40 value 79.007121
iter  50 value 78.077207
iter  60 value 77.199369
iter  70 value 76.665494
iter  80 value 76.062950
iter  90 value 75.774670
iter 100 value 75.685214
final  value 75.685214 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.508817 
iter  10 value 86.443737
iter  20 value 79.537301
iter  30 value 78.885467
iter  40 value 78.557395
iter  50 value 78.266316
iter  60 value 78.178817
iter  70 value 78.134582
iter  80 value 78.075319
iter  90 value 78.045381
iter 100 value 78.002758
final  value 78.002758 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.975497 
iter  10 value 94.086883
iter  20 value 92.967266
iter  30 value 84.356461
iter  40 value 79.861868
iter  50 value 78.538967
iter  60 value 77.910249
iter  70 value 77.681216
iter  80 value 77.348704
iter  90 value 77.114801
iter 100 value 76.674283
final  value 76.674283 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.549587 
final  value 94.054667 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.531347 
iter  10 value 94.054143
final  value 94.053278 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.129938 
final  value 94.054789 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.415811 
final  value 94.054318 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.197050 
final  value 94.054427 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.030151 
iter  10 value 94.057148
iter  20 value 94.052921
iter  20 value 94.052920
final  value 94.052920 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.073118 
iter  10 value 93.249929
iter  20 value 93.247185
iter  30 value 91.657285
iter  40 value 91.591691
iter  50 value 90.931222
final  value 90.919097 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.228941 
iter  10 value 92.529035
iter  20 value 92.527057
iter  30 value 92.480743
iter  40 value 82.336214
iter  50 value 80.899341
iter  60 value 80.893590
final  value 80.893571 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.318809 
iter  10 value 94.057669
iter  20 value 94.053245
iter  30 value 91.758078
iter  40 value 89.372426
iter  50 value 89.346078
iter  60 value 89.343286
iter  70 value 85.632329
iter  80 value 85.285561
final  value 85.284109 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.048658 
iter  10 value 94.057598
iter  20 value 93.608300
iter  30 value 92.942978
iter  40 value 82.061363
iter  50 value 80.537730
iter  60 value 80.199173
iter  70 value 80.165645
iter  80 value 80.000851
iter  90 value 79.635266
iter 100 value 79.432141
final  value 79.432141 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.427233 
iter  10 value 87.795281
iter  20 value 82.167132
iter  30 value 82.166312
iter  40 value 81.502472
iter  50 value 81.489017
iter  60 value 81.487088
iter  70 value 81.446285
iter  80 value 81.411059
iter  90 value 81.319173
iter 100 value 77.797041
final  value 77.797041 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.914081 
iter  10 value 93.844844
iter  20 value 93.836356
iter  30 value 83.068397
iter  40 value 82.543901
iter  50 value 82.189550
iter  60 value 79.410138
iter  70 value 76.771775
iter  80 value 76.369408
iter  90 value 76.218530
iter 100 value 76.135529
final  value 76.135529 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.454795 
iter  10 value 93.619062
iter  20 value 93.609670
iter  30 value 93.590611
iter  40 value 92.649569
iter  50 value 92.483079
final  value 92.483028 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.419110 
iter  10 value 92.341842
iter  20 value 92.335520
iter  30 value 82.188897
final  value 82.159728 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.176003 
iter  10 value 93.845493
iter  20 value 93.839298
iter  30 value 82.223605
iter  40 value 80.459656
iter  50 value 80.457863
iter  60 value 80.250091
iter  70 value 80.124784
iter  80 value 80.121001
iter  90 value 79.545194
iter 100 value 79.314552
final  value 79.314552 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.943246 
iter  10 value 94.252925
final  value 94.252920 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.949926 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.599869 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.026744 
final  value 93.300000 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.344768 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.220971 
iter  10 value 88.685895
iter  20 value 87.761476
iter  30 value 87.760914
final  value 87.760888 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.980183 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.799979 
iter  10 value 89.216102
iter  20 value 83.507299
final  value 83.505184 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.485969 
final  value 94.310508 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.711768 
iter  10 value 92.746294
iter  20 value 92.731197
final  value 92.731184 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.184406 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.395199 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.450831 
iter  10 value 93.164280
iter  10 value 93.164280
iter  10 value 93.164280
final  value 93.164280 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.838908 
iter  10 value 91.210700
iter  20 value 91.208528
iter  30 value 88.346173
iter  40 value 81.094164
iter  50 value 80.857369
iter  60 value 80.856111
iter  70 value 80.702580
iter  80 value 80.697187
final  value 80.697171 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.053947 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.406688 
iter  10 value 94.102172
iter  20 value 87.409905
iter  30 value 84.812876
iter  40 value 84.351355
iter  50 value 83.789402
iter  60 value 83.146711
iter  70 value 82.319924
iter  80 value 82.317969
iter  80 value 82.317969
iter  80 value 82.317969
final  value 82.317969 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.771242 
iter  10 value 94.550585
iter  20 value 94.486681
iter  30 value 94.486522
iter  40 value 85.286134
iter  50 value 81.755360
iter  60 value 81.466658
iter  70 value 80.243568
iter  80 value 78.888472
iter  90 value 78.877227
final  value 78.877216 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.592821 
iter  10 value 94.488609
iter  20 value 94.217314
iter  30 value 93.595808
iter  40 value 93.366677
iter  50 value 92.752493
iter  60 value 86.048723
iter  70 value 84.629387
iter  80 value 84.620800
iter  90 value 84.603910
iter 100 value 84.595087
final  value 84.595087 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.435320 
iter  10 value 94.228423
iter  20 value 87.684683
iter  30 value 83.903674
iter  40 value 83.538921
iter  50 value 82.592059
iter  60 value 81.937279
final  value 81.937192 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.700181 
iter  10 value 94.489321
iter  20 value 94.369142
iter  30 value 93.452586
iter  40 value 93.277306
iter  50 value 83.944393
iter  60 value 83.177775
iter  70 value 82.052449
iter  80 value 81.251490
iter  90 value 81.179345
iter 100 value 81.111780
final  value 81.111780 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.580941 
iter  10 value 90.649284
iter  20 value 82.327797
iter  30 value 79.581825
iter  40 value 78.868755
iter  50 value 78.266771
iter  60 value 78.020663
iter  70 value 77.859397
iter  80 value 77.740469
iter  90 value 77.558683
iter 100 value 77.483625
final  value 77.483625 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.874345 
iter  10 value 94.494181
iter  20 value 93.545640
iter  30 value 92.038717
iter  40 value 81.592060
iter  50 value 81.271349
iter  60 value 80.962365
iter  70 value 80.709369
iter  80 value 78.867652
iter  90 value 78.111217
iter 100 value 77.699066
final  value 77.699066 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.380008 
iter  10 value 93.518245
iter  20 value 86.621661
iter  30 value 82.118259
iter  40 value 81.503278
iter  50 value 81.315539
iter  60 value 80.550048
iter  70 value 78.904365
iter  80 value 78.343698
iter  90 value 78.240115
iter 100 value 77.956669
final  value 77.956669 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.673944 
iter  10 value 94.581790
iter  20 value 94.246984
iter  30 value 91.261494
iter  40 value 85.026193
iter  50 value 83.264434
iter  60 value 80.455014
iter  70 value 79.791749
iter  80 value 79.059469
iter  90 value 78.406318
iter 100 value 78.061424
final  value 78.061424 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.885605 
iter  10 value 94.430489
iter  20 value 93.374818
iter  30 value 92.542920
iter  40 value 86.954415
iter  50 value 86.058405
iter  60 value 84.111805
iter  70 value 83.972465
iter  80 value 83.836233
iter  90 value 83.805733
iter 100 value 83.693153
final  value 83.693153 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.305021 
iter  10 value 94.375771
iter  20 value 86.064539
iter  30 value 83.066472
iter  40 value 82.026975
iter  50 value 81.325183
iter  60 value 80.919308
iter  70 value 80.370066
iter  80 value 80.296504
iter  90 value 80.197600
iter 100 value 79.387244
final  value 79.387244 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.003766 
iter  10 value 94.430430
iter  20 value 86.665555
iter  30 value 84.196572
iter  40 value 82.523277
iter  50 value 81.359442
iter  60 value 78.692371
iter  70 value 77.652522
iter  80 value 77.275550
iter  90 value 77.081593
iter 100 value 76.900652
final  value 76.900652 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.174410 
iter  10 value 96.354259
iter  20 value 83.687247
iter  30 value 82.185808
iter  40 value 80.319828
iter  50 value 78.991739
iter  60 value 77.975852
iter  70 value 77.527862
iter  80 value 77.241507
iter  90 value 76.915450
iter 100 value 76.642252
final  value 76.642252 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.239707 
iter  10 value 94.328117
iter  20 value 92.419745
iter  30 value 86.624748
iter  40 value 80.575616
iter  50 value 79.165547
iter  60 value 78.596995
iter  70 value 78.412629
iter  80 value 78.165174
iter  90 value 78.101324
iter 100 value 78.031859
final  value 78.031859 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.579984 
iter  10 value 94.439908
iter  20 value 93.248197
iter  30 value 87.365803
iter  40 value 84.731449
iter  50 value 79.022327
iter  60 value 78.403403
iter  70 value 77.808992
iter  80 value 77.465691
iter  90 value 77.219144
iter 100 value 77.138340
final  value 77.138340 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.020579 
final  value 94.485857 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.618108 
final  value 94.485940 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.394196 
final  value 94.485992 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.701644 
final  value 94.485849 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.495264 
final  value 94.485618 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.645677 
iter  10 value 94.359322
iter  20 value 94.312420
iter  30 value 85.759463
final  value 85.277985 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.953997 
iter  10 value 94.488477
iter  20 value 94.480252
iter  30 value 83.663649
iter  40 value 83.369389
iter  50 value 78.443836
iter  60 value 77.534953
iter  70 value 77.444376
iter  80 value 77.444011
iter  90 value 76.995777
iter 100 value 76.285293
final  value 76.285293 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.921867 
iter  10 value 94.489110
iter  20 value 94.365621
final  value 94.354746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.476824 
iter  10 value 94.489245
iter  20 value 94.484645
iter  30 value 94.466314
iter  40 value 89.950105
iter  50 value 89.414038
iter  60 value 89.412921
iter  70 value 88.258845
iter  80 value 88.076058
iter  90 value 88.070244
final  value 88.069507 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.130567 
iter  10 value 94.488640
iter  20 value 93.682235
final  value 93.165292 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.414058 
iter  10 value 94.491727
iter  20 value 94.361099
iter  30 value 94.355650
iter  40 value 90.722279
iter  50 value 86.515819
iter  60 value 84.739009
iter  70 value 82.672042
iter  80 value 82.663675
iter  90 value 82.470811
iter 100 value 82.357223
final  value 82.357223 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.835314 
iter  10 value 94.063923
iter  20 value 91.493911
iter  30 value 83.518630
iter  40 value 83.515371
iter  50 value 82.740983
iter  60 value 82.386313
iter  70 value 82.381464
iter  80 value 82.381240
iter  80 value 82.381240
iter  80 value 82.381240
final  value 82.381240 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.931985 
iter  10 value 94.362215
iter  20 value 93.692011
iter  30 value 85.637179
final  value 85.637128 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.674438 
iter  10 value 94.492782
iter  20 value 94.101549
iter  30 value 87.693246
iter  40 value 87.670886
iter  50 value 85.462635
iter  60 value 82.723734
iter  70 value 82.712205
iter  80 value 81.886114
iter  90 value 81.879284
iter 100 value 80.766230
final  value 80.766230 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.387719 
iter  10 value 94.261945
iter  20 value 94.253339
iter  30 value 93.060761
iter  40 value 81.898035
iter  50 value 81.082576
iter  60 value 80.944418
iter  70 value 80.940885
iter  80 value 80.936278
iter  90 value 78.236418
iter 100 value 78.232718
final  value 78.232718 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.636826 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.119113 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.696208 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.272590 
iter  10 value 92.033956
final  value 91.956163 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.108110 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.942111 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.810055 
iter  10 value 87.456700
iter  20 value 86.691145
iter  30 value 85.891162
iter  40 value 85.826643
final  value 85.826162 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.913991 
iter  10 value 94.120664
iter  10 value 94.120664
iter  10 value 94.120664
final  value 94.120664 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.031296 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.408758 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.454025 
iter  10 value 94.269872
final  value 94.263224 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.425271 
iter  10 value 94.275434
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.695860 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.508783 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.440395 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.519926 
iter  10 value 94.334849
iter  20 value 94.324207
iter  30 value 94.246147
iter  40 value 91.418354
iter  50 value 89.252600
iter  60 value 87.083646
iter  70 value 85.655199
iter  80 value 85.361333
iter  90 value 84.764683
iter 100 value 84.743352
final  value 84.743352 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.103477 
iter  10 value 94.396721
iter  20 value 89.348897
iter  30 value 87.808618
iter  40 value 85.662389
iter  50 value 85.388891
iter  60 value 83.659171
iter  70 value 83.520246
iter  80 value 83.104130
iter  90 value 83.076113
iter 100 value 83.071691
final  value 83.071691 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.301115 
iter  10 value 95.241261
iter  20 value 93.350248
iter  30 value 90.161333
iter  40 value 88.078404
iter  50 value 87.558678
iter  60 value 86.194005
iter  70 value 85.832799
iter  80 value 85.529732
iter  90 value 85.500820
final  value 85.500699 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.394420 
iter  10 value 94.377103
iter  20 value 94.330454
iter  30 value 94.013099
iter  40 value 92.368213
iter  50 value 88.942315
iter  60 value 86.974200
iter  70 value 86.613781
iter  80 value 86.430442
iter  90 value 85.954477
final  value 85.954155 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.662940 
iter  10 value 94.540812
iter  20 value 94.482097
iter  30 value 86.187335
iter  40 value 85.398723
iter  50 value 85.200550
iter  60 value 85.151866
iter  70 value 85.137227
final  value 85.137150 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.443520 
iter  10 value 94.397463
iter  20 value 93.780204
iter  30 value 93.536308
iter  40 value 88.469284
iter  50 value 88.184625
iter  60 value 87.352745
iter  70 value 86.915358
iter  80 value 86.536441
iter  90 value 84.419975
iter 100 value 83.408024
final  value 83.408024 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.348609 
iter  10 value 94.472515
iter  20 value 87.358100
iter  30 value 84.720383
iter  40 value 84.083461
iter  50 value 83.760882
iter  60 value 83.141371
iter  70 value 82.751742
iter  80 value 82.621874
iter  90 value 82.409771
iter 100 value 82.213677
final  value 82.213677 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.112373 
iter  10 value 94.230874
iter  20 value 91.409807
iter  30 value 88.637801
iter  40 value 87.867968
iter  50 value 86.472083
iter  60 value 85.720740
iter  70 value 83.992916
iter  80 value 83.262863
iter  90 value 82.641097
iter 100 value 82.505757
final  value 82.505757 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.666460 
iter  10 value 94.468671
iter  20 value 87.720340
iter  30 value 84.303760
iter  40 value 84.006076
iter  50 value 83.715184
iter  60 value 83.485836
iter  70 value 83.405271
iter  80 value 83.403584
iter  90 value 83.293491
iter 100 value 82.571024
final  value 82.571024 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.286587 
iter  10 value 96.213899
iter  20 value 88.584067
iter  30 value 88.027428
iter  40 value 87.788720
iter  50 value 86.697233
iter  60 value 83.861384
iter  70 value 83.506227
iter  80 value 83.202392
iter  90 value 82.592087
iter 100 value 82.364092
final  value 82.364092 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.838550 
iter  10 value 94.511495
iter  20 value 94.128537
iter  30 value 90.642260
iter  40 value 86.959870
iter  50 value 85.046035
iter  60 value 84.389306
iter  70 value 83.707032
iter  80 value 82.925820
iter  90 value 82.460853
iter 100 value 82.339090
final  value 82.339090 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.014860 
iter  10 value 97.871512
iter  20 value 94.662200
iter  30 value 93.753759
iter  40 value 89.380110
iter  50 value 87.565274
iter  60 value 86.692791
iter  70 value 84.892355
iter  80 value 84.177813
iter  90 value 83.723842
iter 100 value 83.524050
final  value 83.524050 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.483296 
iter  10 value 94.306881
iter  20 value 86.695844
iter  30 value 85.710362
iter  40 value 83.858814
iter  50 value 83.241717
iter  60 value 82.820492
iter  70 value 82.550232
iter  80 value 82.315196
iter  90 value 82.172275
iter 100 value 82.028614
final  value 82.028614 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.323383 
iter  10 value 94.966282
iter  20 value 88.053791
iter  30 value 84.597342
iter  40 value 83.684062
iter  50 value 83.147861
iter  60 value 82.921956
iter  70 value 82.592289
iter  80 value 82.505764
iter  90 value 82.411118
iter 100 value 82.243188
final  value 82.243188 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.556202 
iter  10 value 94.911118
iter  20 value 94.514886
iter  30 value 94.312340
iter  40 value 93.294578
iter  50 value 87.355358
iter  60 value 85.647462
iter  70 value 84.183158
iter  80 value 83.840747
iter  90 value 83.547473
iter 100 value 83.460081
final  value 83.460081 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.467803 
final  value 94.277191 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.533474 
final  value 94.485848 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.530034 
iter  10 value 94.485915
iter  20 value 94.281643
iter  30 value 94.276914
iter  40 value 94.275466
final  value 94.275448 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.796651 
iter  10 value 94.277097
iter  20 value 94.275925
iter  30 value 91.113702
iter  40 value 85.542434
iter  50 value 85.039272
iter  60 value 84.993484
final  value 84.993360 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.916799 
final  value 94.486254 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.658385 
iter  10 value 94.488947
iter  20 value 94.484200
iter  30 value 90.185835
iter  40 value 90.116066
iter  50 value 90.100802
iter  60 value 90.095753
iter  70 value 89.976188
iter  80 value 87.219848
iter  90 value 84.945087
iter 100 value 84.916891
final  value 84.916891 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.453694 
iter  10 value 94.489177
iter  20 value 92.491498
iter  30 value 87.099126
iter  40 value 87.097401
iter  50 value 85.726218
iter  60 value 85.472930
iter  70 value 85.471471
final  value 85.471459 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.951479 
iter  10 value 94.490055
iter  20 value 89.652303
final  value 85.936821 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.916496 
iter  10 value 94.489284
iter  20 value 94.423315
iter  30 value 90.682148
iter  40 value 86.760663
iter  50 value 86.219537
iter  60 value 86.206864
iter  70 value 86.205792
iter  80 value 86.203245
final  value 86.203204 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.074917 
iter  10 value 94.280883
iter  20 value 94.278091
final  value 94.276059 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.701242 
iter  10 value 94.332425
iter  20 value 91.189610
iter  30 value 86.718092
iter  40 value 86.692885
iter  50 value 85.697169
iter  60 value 85.528088
iter  70 value 85.317802
iter  80 value 85.317539
iter  90 value 85.316541
iter 100 value 85.008758
final  value 85.008758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.931592 
iter  10 value 92.902160
iter  20 value 91.599106
iter  30 value 91.249558
iter  40 value 91.238829
iter  50 value 91.227957
iter  60 value 91.170789
iter  70 value 91.154725
iter  80 value 85.521704
iter  90 value 83.983301
iter 100 value 83.827893
final  value 83.827893 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.357190 
iter  10 value 94.283963
iter  20 value 94.276779
iter  30 value 85.977538
iter  40 value 85.936826
final  value 85.936709 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.815748 
iter  10 value 94.492538
iter  20 value 94.415210
iter  30 value 87.749120
iter  40 value 86.705446
iter  50 value 86.568347
iter  60 value 86.557377
iter  70 value 86.546806
final  value 86.546769 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.797975 
iter  10 value 94.492127
iter  20 value 94.277202
iter  30 value 94.273089
iter  40 value 88.898562
iter  50 value 85.659722
iter  60 value 85.599712
iter  70 value 83.831779
iter  80 value 83.676631
iter  90 value 83.640829
iter 100 value 83.625307
final  value 83.625307 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.355283 
iter  10 value 117.558246
iter  20 value 116.695692
iter  30 value 115.177257
iter  40 value 114.628400
iter  50 value 110.183842
iter  60 value 109.106598
iter  70 value 109.104224
final  value 109.104133 
converged
Fitting Repeat 2 

# weights:  507
initial  value 135.724483 
iter  10 value 117.777967
iter  20 value 117.751581
final  value 117.728566 
converged
Fitting Repeat 3 

# weights:  507
initial  value 145.236630 
iter  10 value 107.426572
iter  20 value 105.312586
iter  30 value 105.275285
iter  40 value 104.805514
iter  50 value 104.711314
iter  60 value 104.698121
iter  70 value 104.692813
iter  80 value 104.691448
final  value 104.690317 
converged
Fitting Repeat 4 

# weights:  507
initial  value 133.423419 
iter  10 value 117.898715
iter  20 value 117.890346
iter  30 value 114.357979
final  value 114.315864 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.969470 
iter  10 value 117.893334
iter  20 value 117.556990
iter  30 value 114.071097
iter  40 value 108.554218
iter  50 value 108.529540
iter  60 value 108.528784
iter  70 value 107.185183
final  value 107.181986 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Mar 13 00:18:09 2026 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 40.911   1.345  92.526