##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 (2025-06-13)
* 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 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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 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       33.969  0.361  34.333
FSmethod      32.709  0.643  33.354
corr_plot     32.993  0.334  33.328
pred_ensembel 13.282  0.170  12.090
enrichfindP    0.467  0.030   8.148
* 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-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 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 97.314418 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.684952 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.926187 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.583374 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.403068 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.136741 
iter  10 value 85.232264
iter  20 value 84.402755
iter  30 value 84.348144
final  value 84.347930 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.566881 
final  value 94.387500 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.393235 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.502235 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.843329 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.172538 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.064528 
iter  10 value 94.387506
final  value 94.387500 
converged
Fitting Repeat 3 

# weights:  507
initial  value 130.976203 
iter  10 value 94.354645
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.301068 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.421451 
iter  10 value 88.707765
iter  20 value 87.181301
iter  30 value 87.169920
final  value 87.169492 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.213222 
iter  10 value 93.856389
iter  20 value 93.111286
iter  30 value 87.632758
iter  40 value 85.009858
iter  50 value 82.539253
iter  60 value 82.181764
iter  70 value 82.103033
iter  80 value 82.098924
iter  80 value 82.098924
iter  80 value 82.098924
final  value 82.098924 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.856988 
iter  10 value 94.478604
iter  20 value 93.811943
iter  30 value 90.049194
iter  40 value 87.653092
iter  50 value 87.192875
iter  60 value 83.847093
iter  70 value 82.289606
iter  80 value 81.976449
iter  90 value 81.758634
iter 100 value 81.684500
final  value 81.684500 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.197134 
iter  10 value 94.475411
iter  20 value 88.828326
iter  30 value 87.067072
iter  40 value 83.220633
iter  50 value 82.768221
iter  60 value 82.313694
iter  70 value 82.126369
iter  80 value 82.099393
final  value 82.098923 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.170298 
iter  10 value 94.446374
iter  20 value 94.105440
iter  30 value 93.932061
iter  40 value 86.318349
iter  50 value 85.493604
iter  60 value 84.894337
iter  70 value 83.034878
iter  80 value 81.047178
iter  90 value 80.986942
iter 100 value 80.766610
final  value 80.766610 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.228681 
iter  10 value 94.492953
iter  20 value 93.345232
iter  30 value 93.088850
iter  40 value 85.674163
iter  50 value 83.808811
iter  60 value 83.265900
iter  70 value 80.700291
iter  80 value 80.685075
iter  90 value 80.647212
iter 100 value 80.524571
final  value 80.524571 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.628662 
iter  10 value 94.481133
iter  20 value 87.939132
iter  30 value 82.768669
iter  40 value 82.515105
iter  50 value 81.975499
iter  60 value 81.905579
iter  70 value 81.839721
iter  80 value 81.629895
iter  90 value 81.394691
iter 100 value 80.444258
final  value 80.444258 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.173768 
iter  10 value 94.505402
iter  20 value 93.941735
iter  30 value 88.301319
iter  40 value 86.868574
iter  50 value 83.968122
iter  60 value 82.298088
iter  70 value 81.593443
iter  80 value 81.071121
iter  90 value 80.534252
iter 100 value 80.350511
final  value 80.350511 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.314629 
iter  10 value 94.534937
iter  20 value 94.131810
iter  30 value 94.006884
iter  40 value 89.325825
iter  50 value 88.784612
iter  60 value 87.569319
iter  70 value 83.707657
iter  80 value 81.119097
iter  90 value 80.500907
iter 100 value 80.167005
final  value 80.167005 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.413687 
iter  10 value 94.233075
iter  20 value 88.917456
iter  30 value 86.528296
iter  40 value 85.523200
iter  50 value 85.230049
iter  60 value 82.113685
iter  70 value 80.782039
iter  80 value 80.559927
iter  90 value 80.519007
iter 100 value 80.040121
final  value 80.040121 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.764724 
iter  10 value 94.305306
iter  20 value 86.708705
iter  30 value 82.758342
iter  40 value 81.297032
iter  50 value 80.955325
iter  60 value 80.354725
iter  70 value 80.125531
iter  80 value 79.959882
iter  90 value 79.456941
iter 100 value 79.249609
final  value 79.249609 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.181559 
iter  10 value 96.544041
iter  20 value 87.480623
iter  30 value 85.113931
iter  40 value 84.466177
iter  50 value 83.963392
iter  60 value 81.038226
iter  70 value 80.091136
iter  80 value 79.939687
iter  90 value 79.844874
iter 100 value 79.785858
final  value 79.785858 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.858110 
iter  10 value 94.763360
iter  20 value 86.156515
iter  30 value 85.666727
iter  40 value 84.602247
iter  50 value 82.451608
iter  60 value 81.304100
iter  70 value 80.605804
iter  80 value 79.606765
iter  90 value 79.157450
iter 100 value 79.067295
final  value 79.067295 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.776178 
iter  10 value 97.619391
iter  20 value 93.623341
iter  30 value 84.957545
iter  40 value 84.436184
iter  50 value 84.003384
iter  60 value 83.914113
iter  70 value 83.818454
iter  80 value 83.423070
iter  90 value 82.220848
iter 100 value 81.083138
final  value 81.083138 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.522565 
iter  10 value 93.956266
iter  20 value 84.609503
iter  30 value 82.448836
iter  40 value 82.006075
iter  50 value 81.219226
iter  60 value 80.641222
iter  70 value 80.263230
iter  80 value 79.961513
iter  90 value 79.679358
iter 100 value 79.321548
final  value 79.321548 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.564892 
iter  10 value 94.523280
iter  20 value 93.643584
iter  30 value 90.775462
iter  40 value 89.649308
iter  50 value 87.700767
iter  60 value 87.046639
iter  70 value 84.400538
iter  80 value 81.289723
iter  90 value 80.866388
iter 100 value 79.862435
final  value 79.862435 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.106903 
final  value 94.485642 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.031078 
iter  10 value 94.254787
iter  20 value 92.904226
iter  30 value 84.568218
iter  40 value 83.118511
final  value 83.067708 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.296471 
iter  10 value 94.485887
iter  20 value 94.484271
final  value 94.484205 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.567430 
final  value 94.486032 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.446257 
final  value 94.485766 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.293608 
iter  10 value 94.488818
iter  20 value 94.484247
iter  30 value 86.764279
iter  40 value 84.467952
iter  50 value 79.639357
iter  60 value 79.221372
iter  70 value 78.913942
iter  80 value 78.913436
iter  90 value 78.913125
iter  90 value 78.913125
final  value 78.913125 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.254632 
iter  10 value 94.168978
iter  20 value 94.165455
final  value 94.165453 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.901528 
iter  10 value 94.493752
iter  20 value 94.075864
iter  30 value 94.053608
final  value 94.053411 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.559896 
iter  10 value 91.324489
iter  20 value 84.369119
iter  30 value 82.000689
iter  40 value 80.852800
iter  50 value 80.848253
iter  60 value 80.639374
iter  70 value 80.595255
iter  80 value 80.586357
iter  90 value 80.575267
iter 100 value 80.571388
final  value 80.571388 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.079354 
iter  10 value 94.359503
iter  20 value 94.133882
iter  30 value 93.883684
iter  40 value 93.883006
final  value 93.882912 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.962274 
iter  10 value 94.488011
iter  20 value 94.283538
iter  30 value 82.315251
iter  40 value 81.687113
iter  50 value 81.683317
iter  60 value 81.648692
iter  70 value 81.111563
iter  80 value 79.296081
iter  90 value 78.506155
iter 100 value 78.143527
final  value 78.143527 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.564291 
iter  10 value 94.491472
iter  20 value 93.794925
iter  30 value 83.365910
final  value 83.336972 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.538813 
iter  10 value 92.782218
iter  20 value 86.965060
iter  30 value 86.961771
iter  40 value 85.445416
iter  50 value 83.563198
iter  60 value 83.473088
iter  70 value 83.472032
iter  80 value 83.469058
iter  90 value 83.265117
iter 100 value 80.798626
final  value 80.798626 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.615922 
iter  10 value 94.126480
iter  20 value 94.065181
iter  30 value 94.056899
iter  40 value 93.901921
iter  50 value 83.475943
iter  60 value 79.993838
iter  70 value 78.941505
iter  80 value 78.850624
iter  90 value 78.644692
iter 100 value 78.533505
final  value 78.533505 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.799482 
iter  10 value 94.145979
iter  20 value 94.142330
iter  30 value 94.139206
final  value 94.138978 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.495745 
iter  10 value 94.052917
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.122428 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 126.278194 
final  value 94.052448 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.930899 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.045826 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.951644 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.609728 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.657122 
final  value 93.962011 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.809135 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.329321 
iter  10 value 94.033150
iter  10 value 94.033149
iter  10 value 94.033149
final  value 94.033149 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.229476 
iter  10 value 94.126108
iter  20 value 91.318015
iter  30 value 90.901645
iter  40 value 90.863968
final  value 90.863210 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.596147 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.809162 
iter  10 value 92.961302
iter  20 value 91.824134
iter  20 value 91.824134
iter  30 value 91.760208
iter  40 value 91.726659
final  value 91.726481 
converged
Fitting Repeat 4 

# weights:  507
initial  value 146.056057 
iter  10 value 94.008709
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.743909 
final  value 93.990909 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.426005 
iter  10 value 94.109722
iter  20 value 92.051429
iter  30 value 87.656846
iter  40 value 87.468379
iter  50 value 87.202093
iter  60 value 87.096780
iter  70 value 86.169995
iter  80 value 85.589100
iter  90 value 85.557871
iter 100 value 84.994971
final  value 84.994971 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.151901 
iter  10 value 94.119468
iter  20 value 93.895904
iter  30 value 88.399102
iter  40 value 86.888778
iter  50 value 86.012889
iter  60 value 85.583667
iter  70 value 85.198062
final  value 85.091699 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.124952 
iter  10 value 94.022079
iter  20 value 93.718245
iter  30 value 91.149548
iter  40 value 90.773343
iter  50 value 90.225666
iter  60 value 87.869397
iter  70 value 87.109895
iter  80 value 86.802999
iter  90 value 86.771025
iter 100 value 86.752870
final  value 86.752870 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.164759 
iter  10 value 94.001902
iter  20 value 91.117067
iter  30 value 89.009214
iter  40 value 87.920608
iter  50 value 87.612945
iter  60 value 87.187654
iter  70 value 86.947478
iter  80 value 86.851426
iter  90 value 86.605171
final  value 86.596406 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.097694 
iter  10 value 94.120193
iter  20 value 94.028838
iter  30 value 93.612452
iter  40 value 92.933777
iter  50 value 91.399716
iter  60 value 91.182972
iter  70 value 88.090650
iter  80 value 86.919455
iter  90 value 86.760270
iter 100 value 86.496033
final  value 86.496033 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.664490 
iter  10 value 94.333156
iter  20 value 94.065934
iter  30 value 92.981200
iter  40 value 88.568353
iter  50 value 87.040807
iter  60 value 86.651248
iter  70 value 85.514067
iter  80 value 84.796056
iter  90 value 84.765302
iter 100 value 84.356167
final  value 84.356167 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.182711 
iter  10 value 94.162768
iter  20 value 94.055637
iter  30 value 93.966780
iter  40 value 93.181663
iter  50 value 88.064500
iter  60 value 85.690365
iter  70 value 84.319632
iter  80 value 84.184262
iter  90 value 83.741044
iter 100 value 83.598988
final  value 83.598988 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.204251 
iter  10 value 94.448666
iter  20 value 92.962092
iter  30 value 88.751009
iter  40 value 87.984531
iter  50 value 87.627331
iter  60 value 87.558484
iter  70 value 87.070714
iter  80 value 85.970418
iter  90 value 84.999270
iter 100 value 83.876631
final  value 83.876631 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.965345 
iter  10 value 94.044199
iter  20 value 92.914872
iter  30 value 89.837578
iter  40 value 88.463510
iter  50 value 87.580923
iter  60 value 87.140940
iter  70 value 87.097994
iter  80 value 87.023773
iter  90 value 85.845350
iter 100 value 85.044797
final  value 85.044797 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.628275 
iter  10 value 94.030405
iter  20 value 92.862743
iter  30 value 92.460511
iter  40 value 92.266191
iter  50 value 89.058429
iter  60 value 87.447369
iter  70 value 86.998941
iter  80 value 86.168232
iter  90 value 85.017016
iter 100 value 84.341039
final  value 84.341039 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.071878 
iter  10 value 94.124336
iter  20 value 89.232614
iter  30 value 88.872030
iter  40 value 88.274886
iter  50 value 86.658285
iter  60 value 85.021719
iter  70 value 84.209266
iter  80 value 83.887337
iter  90 value 83.735903
iter 100 value 83.504469
final  value 83.504469 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.876965 
iter  10 value 94.036026
iter  20 value 91.473286
iter  30 value 88.774189
iter  40 value 87.921174
iter  50 value 86.629908
iter  60 value 85.653001
iter  70 value 84.556834
iter  80 value 84.022804
iter  90 value 83.976933
iter 100 value 83.810654
final  value 83.810654 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.542243 
iter  10 value 94.142120
iter  20 value 94.014109
iter  30 value 93.978526
iter  40 value 93.209161
iter  50 value 89.025019
iter  60 value 87.285746
iter  70 value 86.287343
iter  80 value 86.211633
iter  90 value 85.337891
iter 100 value 84.919153
final  value 84.919153 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.536617 
iter  10 value 93.917698
iter  20 value 88.840126
iter  30 value 87.783781
iter  40 value 87.630943
iter  50 value 84.026352
iter  60 value 83.724793
iter  70 value 83.392651
iter  80 value 83.167390
iter  90 value 83.055515
iter 100 value 82.953253
final  value 82.953253 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.722040 
iter  10 value 94.020796
iter  20 value 89.232076
iter  30 value 86.265357
iter  40 value 84.443717
iter  50 value 84.038220
iter  60 value 83.899504
iter  70 value 83.700439
iter  80 value 83.643939
iter  90 value 83.569371
iter 100 value 83.448735
final  value 83.448735 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.557632 
final  value 94.054543 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.165538 
iter  10 value 94.054778
iter  20 value 94.052902
iter  30 value 89.761323
iter  40 value 89.578616
final  value 89.578543 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.211819 
final  value 94.054599 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.467140 
final  value 94.054325 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.561403 
final  value 94.054536 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.527399 
iter  10 value 94.013653
iter  20 value 93.965752
iter  30 value 93.962353
iter  40 value 93.960715
final  value 93.960594 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.559987 
iter  10 value 94.014342
iter  20 value 93.967577
iter  30 value 93.965063
final  value 93.962202 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.095237 
iter  10 value 94.057385
iter  20 value 94.052962
iter  30 value 93.929511
iter  40 value 92.709684
iter  50 value 92.645207
iter  60 value 92.505923
iter  70 value 92.504367
final  value 92.504269 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.261917 
iter  10 value 94.057764
iter  20 value 92.610444
iter  30 value 88.222684
iter  40 value 87.247786
iter  50 value 86.853287
final  value 86.797778 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.398689 
iter  10 value 94.057396
final  value 94.052914 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.188445 
iter  10 value 94.015259
iter  20 value 94.000456
iter  30 value 93.962238
iter  40 value 93.961783
iter  50 value 93.961735
iter  60 value 93.960589
iter  70 value 91.456747
iter  80 value 89.077826
iter  90 value 88.964045
iter 100 value 88.765351
final  value 88.765351 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.867763 
iter  10 value 94.016986
iter  20 value 93.969028
iter  30 value 93.893745
iter  40 value 87.941776
iter  50 value 86.281090
iter  60 value 86.278171
iter  70 value 85.681786
iter  80 value 85.455944
iter  90 value 85.362417
iter 100 value 85.248417
final  value 85.248417 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.538541 
iter  10 value 94.016910
iter  20 value 93.978581
iter  30 value 93.960704
iter  40 value 93.960576
final  value 93.960575 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.821916 
iter  10 value 93.199195
iter  20 value 92.897169
iter  30 value 92.834770
iter  40 value 91.828053
iter  50 value 91.826863
iter  60 value 91.530177
iter  70 value 88.193044
iter  80 value 88.192069
iter  90 value 88.191822
iter 100 value 88.191132
final  value 88.191132 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.743071 
iter  10 value 94.061031
iter  20 value 93.745348
iter  30 value 89.922678
iter  40 value 89.375955
iter  50 value 89.047991
iter  60 value 89.045886
iter  60 value 89.045885
iter  60 value 89.045885
final  value 89.045885 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.471453 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.748195 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.952665 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.885130 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.419076 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.946259 
iter  10 value 94.466829
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.626944 
final  value 94.484227 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.525493 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.962688 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.165552 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.147779 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.587200 
iter  10 value 94.144702
iter  10 value 94.144701
iter  10 value 94.144701
final  value 94.144701 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.661588 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.690191 
iter  10 value 93.103496
final  value 93.102857 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.669955 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.138096 
iter  10 value 94.497271
iter  20 value 91.695344
iter  30 value 91.294165
iter  40 value 91.242880
iter  50 value 87.799443
iter  60 value 85.405613
iter  70 value 84.225077
iter  80 value 83.084997
iter  90 value 82.876819
final  value 82.875880 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.802388 
iter  10 value 94.471847
iter  20 value 92.929632
iter  30 value 86.248187
iter  40 value 85.248853
iter  50 value 85.106907
iter  60 value 85.075248
iter  70 value 85.042908
iter  80 value 84.252090
iter  90 value 83.206732
iter 100 value 83.173851
final  value 83.173851 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.810281 
iter  10 value 94.531403
iter  20 value 94.488493
iter  30 value 94.287642
iter  40 value 93.422248
iter  50 value 87.284508
iter  60 value 84.856969
iter  70 value 84.434009
iter  80 value 83.913662
iter  90 value 83.775621
iter 100 value 83.767008
final  value 83.767008 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.727273 
iter  10 value 94.485339
iter  20 value 92.268462
iter  30 value 91.201523
iter  40 value 91.134334
iter  50 value 91.103042
iter  60 value 91.066506
iter  70 value 91.066363
final  value 91.066266 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.918089 
iter  10 value 94.502898
iter  20 value 86.825157
iter  30 value 83.685062
iter  40 value 83.081217
iter  50 value 81.565929
iter  60 value 81.110312
iter  70 value 81.065809
iter  80 value 80.637672
iter  90 value 80.588699
final  value 80.588692 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.987601 
iter  10 value 94.487292
iter  20 value 88.348110
iter  30 value 86.474635
iter  40 value 85.693538
iter  50 value 85.401490
iter  60 value 85.263465
iter  70 value 85.196355
iter  80 value 85.143238
iter  90 value 85.117606
iter 100 value 84.258240
final  value 84.258240 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.460586 
iter  10 value 93.701018
iter  20 value 87.783663
iter  30 value 84.288734
iter  40 value 83.527077
iter  50 value 83.286485
iter  60 value 82.878467
iter  70 value 82.029689
iter  80 value 81.006772
iter  90 value 80.894311
iter 100 value 79.735298
final  value 79.735298 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.006686 
iter  10 value 94.291418
iter  20 value 87.398419
iter  30 value 86.174799
iter  40 value 83.866644
iter  50 value 82.559871
iter  60 value 81.360099
iter  70 value 80.616155
iter  80 value 79.734807
iter  90 value 79.299348
iter 100 value 79.249092
final  value 79.249092 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.164657 
iter  10 value 91.196949
iter  20 value 85.885478
iter  30 value 85.648977
iter  40 value 84.933268
iter  50 value 83.463186
iter  60 value 83.120849
iter  70 value 82.632625
iter  80 value 82.453875
iter  90 value 81.730942
iter 100 value 81.550191
final  value 81.550191 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.735414 
iter  10 value 94.420028
iter  20 value 86.522622
iter  30 value 85.677916
iter  40 value 85.500440
iter  50 value 85.441487
iter  60 value 85.410689
iter  70 value 83.375579
iter  80 value 82.196186
iter  90 value 81.103278
iter 100 value 81.056146
final  value 81.056146 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.200103 
iter  10 value 90.162957
iter  20 value 86.108807
iter  30 value 84.672273
iter  40 value 83.942624
iter  50 value 80.074330
iter  60 value 79.411822
iter  70 value 79.333318
iter  80 value 79.250244
iter  90 value 79.156498
iter 100 value 79.148961
final  value 79.148961 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.335143 
iter  10 value 94.595413
iter  20 value 91.022023
iter  30 value 84.507502
iter  40 value 82.001727
iter  50 value 80.205274
iter  60 value 79.510308
iter  70 value 79.409113
iter  80 value 79.133530
iter  90 value 78.873996
iter 100 value 78.527964
final  value 78.527964 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.653080 
iter  10 value 94.150767
iter  20 value 84.737220
iter  30 value 83.597117
iter  40 value 82.309859
iter  50 value 81.693815
iter  60 value 80.672836
iter  70 value 79.591824
iter  80 value 79.278959
iter  90 value 78.705201
iter 100 value 78.524668
final  value 78.524668 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.206702 
iter  10 value 95.119747
iter  20 value 91.882379
iter  30 value 86.341681
iter  40 value 83.882737
iter  50 value 83.351307
iter  60 value 82.665560
iter  70 value 82.160255
iter  80 value 81.142435
iter  90 value 80.627280
iter 100 value 80.525019
final  value 80.525019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.879626 
iter  10 value 95.863125
iter  20 value 94.512615
iter  30 value 90.504388
iter  40 value 83.776883
iter  50 value 81.307845
iter  60 value 80.501536
iter  70 value 79.495593
iter  80 value 79.157307
iter  90 value 78.930896
iter 100 value 78.823039
final  value 78.823039 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.922653 
final  value 94.485945 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.535459 
final  value 94.485759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.013951 
final  value 94.485682 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.312600 
final  value 94.485754 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.975333 
final  value 94.489696 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.480355 
iter  10 value 94.488815
iter  20 value 94.324419
iter  30 value 85.528146
iter  40 value 85.527967
final  value 85.527949 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.980941 
iter  10 value 92.733707
iter  20 value 92.713671
iter  30 value 92.606240
iter  40 value 92.602461
iter  50 value 92.600695
iter  60 value 92.531841
final  value 92.530692 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.589363 
iter  10 value 91.711762
iter  20 value 91.697541
iter  30 value 91.697007
iter  40 value 91.696567
iter  50 value 91.694686
final  value 91.694082 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.137722 
iter  10 value 88.510118
iter  20 value 86.103481
iter  30 value 85.921676
iter  40 value 85.916432
iter  50 value 85.914389
iter  60 value 85.913505
iter  70 value 85.911784
iter  80 value 85.911611
final  value 85.911593 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.671009 
iter  10 value 94.491187
iter  20 value 94.467954
iter  30 value 87.909534
iter  40 value 86.786523
iter  50 value 86.619218
iter  60 value 85.772965
final  value 85.744226 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.461601 
iter  10 value 94.495063
iter  20 value 94.486868
iter  30 value 93.736248
iter  40 value 90.813252
iter  50 value 90.804437
final  value 90.804225 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.627907 
iter  10 value 94.491745
iter  20 value 94.459150
iter  30 value 92.791629
iter  40 value 90.624649
iter  50 value 81.374398
iter  60 value 80.552675
iter  70 value 80.470305
iter  80 value 80.303228
iter  90 value 80.058804
iter 100 value 80.058286
final  value 80.058286 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.809912 
iter  10 value 94.474964
iter  20 value 94.348242
iter  30 value 87.441352
iter  40 value 81.273957
iter  50 value 78.308010
iter  60 value 77.253590
iter  70 value 77.155009
iter  80 value 77.144968
iter  90 value 77.134051
iter 100 value 77.133231
final  value 77.133231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.409765 
iter  10 value 94.474861
iter  20 value 93.870843
iter  30 value 90.460319
iter  40 value 90.447248
iter  50 value 90.446888
iter  50 value 90.446888
final  value 90.446888 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.105657 
iter  10 value 94.491598
iter  20 value 94.469464
iter  30 value 92.605890
iter  40 value 92.603633
final  value 92.603614 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.959700 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.025056 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.191164 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.809627 
iter  10 value 94.253256
final  value 94.252921 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.455987 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.253051 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.264322 
iter  10 value 94.536229
iter  20 value 94.484285
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.791450 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.535659 
iter  10 value 94.075416
iter  20 value 93.922750
iter  20 value 93.922749
iter  20 value 93.922749
final  value 93.922749 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.641573 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.584445 
iter  10 value 94.443243
iter  10 value 94.443243
iter  10 value 94.443243
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.416126 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.348777 
iter  10 value 93.638377
iter  20 value 91.664912
iter  30 value 83.355558
iter  40 value 82.747662
iter  50 value 82.733330
final  value 82.733272 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.902259 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.539022 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.788174 
iter  10 value 94.425786
iter  20 value 92.863347
iter  30 value 89.140592
iter  40 value 85.927414
iter  50 value 84.252693
iter  60 value 83.561388
iter  70 value 82.672224
iter  80 value 81.101119
iter  90 value 80.460348
iter 100 value 80.457497
final  value 80.457497 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.648816 
iter  10 value 94.472752
iter  20 value 93.300850
iter  30 value 83.475750
iter  40 value 82.619668
iter  50 value 82.352963
iter  60 value 81.900569
final  value 81.894449 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.492579 
iter  10 value 94.488588
iter  20 value 93.990221
iter  30 value 92.112736
iter  40 value 91.971657
iter  50 value 91.812427
final  value 91.806358 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.288882 
iter  10 value 94.483483
iter  20 value 94.260980
iter  30 value 94.082137
iter  40 value 93.791612
iter  50 value 91.977058
iter  60 value 87.276018
iter  70 value 86.846985
iter  80 value 83.808018
iter  90 value 82.574358
iter 100 value 82.299047
final  value 82.299047 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.076575 
iter  10 value 94.487363
iter  20 value 90.070178
iter  30 value 86.529532
iter  40 value 85.208526
iter  50 value 83.894954
iter  60 value 83.593806
iter  70 value 82.713587
iter  80 value 82.475101
final  value 82.469301 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.448088 
iter  10 value 94.385080
iter  20 value 88.822679
iter  30 value 85.829460
iter  40 value 84.091862
iter  50 value 79.685917
iter  60 value 78.881365
iter  70 value 78.739420
iter  80 value 78.715290
iter  90 value 78.701046
iter 100 value 78.696869
final  value 78.696869 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 130.291472 
iter  10 value 94.484324
iter  20 value 93.796043
iter  30 value 91.834338
iter  40 value 91.546942
iter  50 value 91.257347
iter  60 value 87.125592
iter  70 value 82.872677
iter  80 value 82.159818
iter  90 value 81.556119
iter 100 value 80.656893
final  value 80.656893 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.657529 
iter  10 value 94.456925
iter  20 value 83.663103
iter  30 value 82.452917
iter  40 value 82.315383
iter  50 value 81.655777
iter  60 value 81.304386
iter  70 value 80.844009
iter  80 value 79.956351
iter  90 value 79.689880
iter 100 value 79.542787
final  value 79.542787 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.237623 
iter  10 value 94.512147
iter  20 value 85.747270
iter  30 value 85.300068
iter  40 value 83.557027
iter  50 value 81.763009
iter  60 value 81.246137
iter  70 value 80.856732
iter  80 value 80.753277
iter  90 value 80.533404
iter 100 value 79.618274
final  value 79.618274 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.612889 
iter  10 value 94.603396
iter  20 value 94.348710
iter  30 value 91.721494
iter  40 value 88.247233
iter  50 value 83.689003
iter  60 value 82.986968
iter  70 value 82.864059
iter  80 value 82.476933
iter  90 value 82.285554
iter 100 value 79.904536
final  value 79.904536 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.909859 
iter  10 value 94.759646
iter  20 value 93.367800
iter  30 value 85.936653
iter  40 value 83.029921
iter  50 value 80.731777
iter  60 value 80.037550
iter  70 value 79.820634
iter  80 value 79.535536
iter  90 value 79.483664
iter 100 value 79.326310
final  value 79.326310 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.283681 
iter  10 value 93.097750
iter  20 value 83.733444
iter  30 value 83.141562
iter  40 value 82.036969
iter  50 value 81.322574
iter  60 value 80.001960
iter  70 value 79.420991
iter  80 value 78.943946
iter  90 value 78.704806
iter 100 value 78.520453
final  value 78.520453 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.584212 
iter  10 value 94.458105
iter  20 value 90.348346
iter  30 value 84.032599
iter  40 value 82.201599
iter  50 value 81.818531
iter  60 value 80.578772
iter  70 value 79.253982
iter  80 value 79.012447
iter  90 value 78.843553
iter 100 value 78.784146
final  value 78.784146 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 144.069857 
iter  10 value 109.185607
iter  20 value 86.697787
iter  30 value 84.481405
iter  40 value 81.763373
iter  50 value 80.633356
iter  60 value 80.182919
iter  70 value 79.950960
iter  80 value 79.283905
iter  90 value 79.002313
iter 100 value 78.857338
final  value 78.857338 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.254983 
iter  10 value 93.985802
iter  20 value 89.394988
iter  30 value 84.802795
iter  40 value 84.373812
iter  50 value 81.606825
iter  60 value 79.561686
iter  70 value 79.440567
iter  80 value 79.275644
iter  90 value 79.075784
iter 100 value 78.880345
final  value 78.880345 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.662977 
iter  10 value 94.485979
iter  20 value 94.484277
iter  30 value 94.320783
iter  40 value 93.724596
iter  50 value 93.688887
iter  60 value 93.688800
iter  60 value 93.688799
iter  60 value 93.688799
final  value 93.688799 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.405580 
final  value 94.486059 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.973692 
final  value 94.485774 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.930664 
final  value 94.485756 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.012526 
final  value 94.485570 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.926469 
iter  10 value 94.486926
iter  20 value 94.475620
iter  30 value 88.201026
iter  40 value 82.201462
iter  50 value 82.078232
iter  60 value 82.049436
iter  70 value 81.965411
iter  80 value 81.535067
iter  90 value 81.534557
final  value 81.534401 
converged
Fitting Repeat 2 

# weights:  305
initial  value 127.553551 
iter  10 value 94.448337
iter  20 value 94.443748
iter  30 value 88.410078
iter  40 value 86.331006
iter  50 value 86.310032
iter  60 value 85.848535
iter  70 value 82.870024
iter  80 value 82.705829
iter  90 value 82.670277
iter 100 value 82.670084
final  value 82.670084 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.008411 
iter  10 value 94.489054
final  value 94.484408 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.642900 
iter  10 value 94.448073
iter  20 value 94.172424
iter  30 value 89.462622
iter  40 value 88.938367
iter  50 value 88.670252
iter  60 value 87.348803
iter  70 value 86.566626
final  value 86.564172 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.617532 
iter  10 value 94.488745
iter  20 value 94.390612
iter  30 value 82.990368
iter  40 value 80.597103
iter  50 value 80.174722
iter  60 value 79.392673
iter  70 value 77.285279
iter  80 value 77.264896
iter  90 value 77.263661
iter 100 value 77.262945
final  value 77.262945 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.698107 
iter  10 value 83.542961
iter  20 value 82.754286
iter  30 value 81.913489
iter  40 value 81.850764
iter  50 value 81.847028
iter  60 value 81.842943
iter  70 value 81.696791
iter  80 value 81.278491
iter  90 value 81.247817
iter 100 value 80.265428
final  value 80.265428 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.981002 
iter  10 value 94.451037
iter  20 value 94.447171
iter  30 value 94.415164
iter  40 value 90.380603
iter  50 value 89.388305
iter  60 value 85.043534
iter  70 value 81.341726
iter  80 value 80.690335
iter  90 value 80.397224
iter 100 value 80.338752
final  value 80.338752 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.155720 
iter  10 value 89.173535
iter  20 value 89.172605
iter  30 value 84.660988
iter  40 value 84.428986
iter  50 value 84.419894
iter  60 value 84.302438
iter  70 value 84.301508
iter  80 value 84.300750
iter  90 value 84.299232
iter 100 value 84.298955
final  value 84.298955 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.263183 
iter  10 value 94.492692
iter  20 value 94.483974
iter  20 value 94.483974
iter  30 value 87.061993
iter  40 value 86.957098
iter  50 value 83.598185
iter  60 value 83.430087
iter  70 value 83.428784
final  value 83.428781 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.545773 
iter  10 value 94.402762
iter  20 value 94.271933
iter  30 value 94.085125
iter  40 value 94.084983
iter  50 value 94.084181
iter  60 value 94.083853
iter  60 value 94.083852
iter  60 value 94.083852
final  value 94.083852 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.725283 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.464263 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.613539 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.377436 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.700388 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.483169 
iter  10 value 89.243192
iter  20 value 86.210751
iter  30 value 81.481416
iter  40 value 81.196304
iter  50 value 80.817625
final  value 80.817248 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.857465 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.075578 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.402228 
iter  10 value 93.604520
iter  10 value 93.604520
iter  10 value 93.604520
final  value 93.604520 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.986351 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.976773 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.379399 
iter  10 value 89.630147
iter  20 value 89.621723
final  value 89.621672 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.128287 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.625246 
iter  10 value 90.897930
iter  20 value 83.046572
iter  30 value 81.120974
iter  40 value 80.797404
iter  50 value 80.793375
final  value 80.793371 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.556077 
final  value 93.084594 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.568873 
iter  10 value 93.997477
iter  20 value 92.578577
iter  30 value 91.697957
iter  40 value 81.940155
iter  50 value 81.661541
iter  60 value 81.048076
iter  70 value 80.794246
iter  80 value 80.285863
iter  90 value 79.997650
iter 100 value 79.944920
final  value 79.944920 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.757075 
iter  10 value 94.055468
iter  20 value 93.898873
iter  30 value 92.544866
iter  40 value 92.496270
iter  50 value 92.495317
iter  60 value 86.396404
iter  70 value 83.076151
iter  80 value 82.392439
iter  90 value 82.079871
iter 100 value 82.071620
final  value 82.071620 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.789154 
iter  10 value 94.070209
iter  20 value 92.397277
iter  30 value 92.233743
iter  40 value 92.145526
iter  50 value 91.508340
iter  60 value 87.673544
iter  70 value 82.523836
iter  80 value 81.680755
iter  90 value 81.615246
final  value 81.615104 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.310131 
iter  10 value 93.529552
iter  20 value 87.187913
iter  30 value 82.305819
iter  40 value 82.092710
iter  50 value 82.087809
iter  60 value 82.079631
iter  70 value 82.071772
final  value 82.071617 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.961920 
iter  10 value 94.055617
iter  20 value 93.502897
iter  30 value 93.061583
iter  40 value 92.502744
iter  50 value 88.570705
iter  60 value 83.325611
iter  70 value 82.378469
iter  80 value 82.089820
iter  90 value 81.271733
iter 100 value 80.669086
final  value 80.669086 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.102795 
iter  10 value 94.196758
iter  20 value 92.330221
iter  30 value 82.855601
iter  40 value 81.733788
iter  50 value 81.347426
iter  60 value 80.426365
iter  70 value 80.039385
iter  80 value 79.769604
iter  90 value 79.645432
iter 100 value 79.598334
final  value 79.598334 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.689492 
iter  10 value 90.473074
iter  20 value 89.718844
iter  30 value 88.326571
iter  40 value 84.144097
iter  50 value 83.227041
iter  60 value 82.775884
iter  70 value 82.654773
iter  80 value 81.548762
iter  90 value 79.487669
iter 100 value 78.900740
final  value 78.900740 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.012750 
iter  10 value 90.319315
iter  20 value 86.138924
iter  30 value 85.142316
iter  40 value 82.410387
iter  50 value 81.476060
iter  60 value 81.117200
iter  70 value 80.616415
iter  80 value 79.739693
iter  90 value 79.459527
iter 100 value 79.055486
final  value 79.055486 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.586167 
iter  10 value 90.605567
iter  20 value 86.622249
iter  30 value 81.010669
iter  40 value 79.431837
iter  50 value 79.097226
iter  60 value 78.903668
iter  70 value 78.777122
iter  80 value 78.730968
iter  90 value 78.654118
iter 100 value 78.599795
final  value 78.599795 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.640135 
iter  10 value 93.792299
iter  20 value 84.269905
iter  30 value 83.201744
iter  40 value 82.178038
iter  50 value 81.347423
iter  60 value 81.066200
iter  70 value 80.421029
iter  80 value 79.881633
iter  90 value 79.681916
iter 100 value 79.030669
final  value 79.030669 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.527014 
iter  10 value 94.597420
iter  20 value 88.101749
iter  30 value 86.408701
iter  40 value 85.443846
iter  50 value 81.950719
iter  60 value 79.643100
iter  70 value 79.175442
iter  80 value 79.102579
iter  90 value 79.022407
iter 100 value 78.993967
final  value 78.993967 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 134.549207 
iter  10 value 94.061298
iter  20 value 86.666059
iter  30 value 83.167100
iter  40 value 82.362550
iter  50 value 80.856084
iter  60 value 80.293398
iter  70 value 79.744833
iter  80 value 79.629760
iter  90 value 79.030566
iter 100 value 78.635666
final  value 78.635666 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.295084 
iter  10 value 94.774585
iter  20 value 94.078008
iter  30 value 91.093570
iter  40 value 83.129552
iter  50 value 81.512849
iter  60 value 80.625216
iter  70 value 80.353100
iter  80 value 80.059982
iter  90 value 79.348613
iter 100 value 78.845260
final  value 78.845260 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.119177 
iter  10 value 93.949102
iter  20 value 91.414947
iter  30 value 82.028516
iter  40 value 81.069614
iter  50 value 79.860390
iter  60 value 79.757285
iter  70 value 79.669351
iter  80 value 79.587330
iter  90 value 79.240793
iter 100 value 79.059438
final  value 79.059438 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.505442 
iter  10 value 95.363147
iter  20 value 84.917080
iter  30 value 82.148222
iter  40 value 79.719434
iter  50 value 78.680652
iter  60 value 78.372649
iter  70 value 78.246095
iter  80 value 78.198881
iter  90 value 78.110377
iter 100 value 78.048549
final  value 78.048549 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.091411 
iter  10 value 94.055084
final  value 94.053115 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.577110 
final  value 94.054666 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.539316 
iter  10 value 94.054704
iter  20 value 94.052920
iter  30 value 83.321233
iter  40 value 82.563018
iter  50 value 82.548807
iter  60 value 82.546687
iter  70 value 81.640329
iter  80 value 81.621138
iter  90 value 81.577994
iter 100 value 80.964105
final  value 80.964105 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.672620 
final  value 94.054888 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.565900 
final  value 94.054572 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.800903 
iter  10 value 94.057850
iter  20 value 93.950565
iter  30 value 92.390201
final  value 92.390192 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.831099 
iter  10 value 94.057734
iter  20 value 93.694786
iter  30 value 84.462467
iter  40 value 84.451686
iter  50 value 84.451499
iter  60 value 82.443057
iter  70 value 82.389277
iter  80 value 82.388485
iter  90 value 81.058793
iter 100 value 80.310471
final  value 80.310471 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 127.813969 
iter  10 value 94.059062
iter  20 value 94.053813
final  value 94.053783 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.715347 
iter  10 value 93.587916
iter  20 value 93.583523
final  value 93.582685 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.475980 
iter  10 value 94.057462
iter  20 value 94.004229
iter  30 value 85.117268
iter  40 value 81.615977
final  value 81.615264 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.279520 
iter  10 value 92.492073
iter  20 value 92.487194
iter  30 value 91.705442
iter  40 value 90.749465
iter  50 value 90.256676
iter  60 value 89.893360
iter  70 value 89.516321
iter  80 value 89.258174
iter  90 value 89.255433
final  value 89.255181 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.537173 
iter  10 value 87.160781
iter  20 value 81.623522
iter  30 value 81.402670
iter  40 value 80.966355
iter  50 value 80.944675
iter  60 value 80.938729
iter  70 value 80.937086
iter  80 value 80.135034
iter  90 value 78.596276
iter 100 value 78.560818
final  value 78.560818 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.529850 
iter  10 value 92.450532
iter  20 value 92.396090
iter  30 value 92.311808
iter  40 value 92.308176
final  value 92.306837 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.433767 
iter  10 value 93.093218
iter  20 value 93.091170
iter  30 value 93.090142
iter  40 value 92.019249
iter  50 value 85.001744
iter  60 value 81.251717
iter  70 value 78.922108
iter  80 value 78.267605
iter  90 value 78.195843
iter 100 value 78.192222
final  value 78.192222 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.389890 
iter  10 value 94.055919
iter  20 value 93.984320
iter  30 value 93.348356
iter  40 value 86.310228
iter  50 value 84.456335
iter  60 value 84.455037
iter  70 value 84.454957
iter  80 value 84.454905
iter  90 value 84.454551
final  value 84.454473 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.901616 
iter  10 value 117.582867
iter  20 value 114.524614
iter  30 value 108.951092
iter  40 value 107.598443
iter  50 value 106.973265
iter  60 value 106.489027
iter  70 value 106.323030
iter  80 value 105.763755
iter  90 value 103.785957
iter 100 value 103.057388
final  value 103.057388 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 167.332223 
iter  10 value 117.767359
iter  20 value 115.458870
iter  30 value 114.922054
iter  40 value 114.587947
iter  50 value 114.306398
iter  60 value 111.693999
iter  70 value 105.847873
iter  80 value 102.837617
iter  90 value 101.821326
iter 100 value 101.047965
final  value 101.047965 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.648184 
iter  10 value 113.493345
iter  20 value 106.480379
iter  30 value 106.118860
iter  40 value 105.668683
iter  50 value 104.343702
iter  60 value 103.363344
iter  70 value 101.983025
iter  80 value 101.386303
iter  90 value 101.085500
iter 100 value 100.824213
final  value 100.824213 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 130.921020 
iter  10 value 117.737434
iter  20 value 110.159686
iter  30 value 108.903573
iter  40 value 108.279682
iter  50 value 105.020908
iter  60 value 104.664367
iter  70 value 104.511102
iter  80 value 104.474607
iter  90 value 103.909604
iter 100 value 102.642496
final  value 102.642496 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.493162 
iter  10 value 117.926356
iter  20 value 116.328678
iter  30 value 115.346952
iter  40 value 108.648554
iter  50 value 105.304948
iter  60 value 103.955690
iter  70 value 102.596547
iter  80 value 101.633330
iter  90 value 101.087555
iter 100 value 100.973930
final  value 100.973930 
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 Sep 11 00:52:31 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 
 39.371   0.971 126.388