##############################################################################
##############################################################################
###
### 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_1.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-04-29 05:23:36 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* 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
corr_plot     35.773  0.477  36.255
FSmethod      33.984  0.565  34.558
var_imp       33.465  0.535  34.012
pred_ensembel 13.184  0.130  11.950
enrichfindP    0.529  0.043  11.192
* 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 ‘1.18.0’
** 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 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 102.017110 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.835347 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.170406 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.277487 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.348497 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.948381 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.319200 
iter  10 value 93.001215
iter  20 value 92.762419
iter  30 value 92.674752
iter  40 value 92.672475
iter  40 value 92.672474
iter  40 value 92.672474
final  value 92.672474 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.805297 
final  value 93.904720 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.960121 
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  305
initial  value 141.051482 
iter  10 value 94.052912
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.779560 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.188471 
final  value 93.915747 
converged
Fitting Repeat 3 

# weights:  507
initial  value 140.201616 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.483610 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.390308 
iter  10 value 93.318066
final  value 93.288028 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.659306 
iter  10 value 94.002369
iter  20 value 90.896897
iter  30 value 88.054685
iter  40 value 84.605351
iter  50 value 83.508157
iter  60 value 83.487863
iter  70 value 81.746565
iter  80 value 81.698012
iter  90 value 81.147995
iter 100 value 80.989409
final  value 80.989409 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.532797 
iter  10 value 94.055107
iter  20 value 93.886553
iter  30 value 89.854563
iter  40 value 84.802138
iter  50 value 84.207206
iter  60 value 84.083953
iter  70 value 83.405916
iter  80 value 82.825475
iter  90 value 82.709182
iter 100 value 82.707702
final  value 82.707702 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.096444 
iter  10 value 93.989416
iter  20 value 93.945112
iter  30 value 93.545527
iter  40 value 86.197307
iter  50 value 85.446246
iter  60 value 85.426308
iter  70 value 84.996820
iter  80 value 83.062544
iter  90 value 82.738156
iter 100 value 82.716239
final  value 82.716239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.883384 
iter  10 value 93.206430
iter  20 value 85.621858
iter  30 value 85.324415
iter  40 value 84.981412
iter  50 value 83.493151
iter  60 value 82.650843
iter  70 value 82.308991
iter  80 value 82.304853
final  value 82.304827 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.154430 
iter  10 value 93.715700
iter  20 value 89.118604
iter  30 value 85.509472
iter  40 value 83.718820
iter  50 value 82.581967
iter  60 value 82.382729
iter  70 value 82.108903
iter  80 value 82.031502
iter  90 value 81.955906
final  value 81.954273 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.801600 
iter  10 value 94.049795
iter  20 value 92.326113
iter  30 value 86.141087
iter  40 value 83.923398
iter  50 value 83.026018
iter  60 value 82.032141
iter  70 value 81.066457
iter  80 value 80.737658
iter  90 value 80.582834
iter 100 value 80.448973
final  value 80.448973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.811142 
iter  10 value 93.994473
iter  20 value 85.157408
iter  30 value 82.585695
iter  40 value 82.135795
iter  50 value 81.962625
iter  60 value 81.820017
iter  70 value 81.802880
iter  80 value 81.797710
iter  90 value 81.794317
iter 100 value 81.774735
final  value 81.774735 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.763798 
iter  10 value 94.006489
iter  20 value 88.549141
iter  30 value 83.137283
iter  40 value 82.324728
iter  50 value 80.875706
iter  60 value 80.586664
iter  70 value 79.911142
iter  80 value 79.379833
iter  90 value 79.283139
iter 100 value 79.201300
final  value 79.201300 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.885853 
iter  10 value 94.625849
iter  20 value 91.040480
iter  30 value 84.131516
iter  40 value 82.989020
iter  50 value 82.628168
iter  60 value 81.409715
iter  70 value 81.028109
iter  80 value 80.851662
iter  90 value 80.807413
iter 100 value 80.702537
final  value 80.702537 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.916715 
iter  10 value 86.793076
iter  20 value 85.464800
iter  30 value 85.191638
iter  40 value 84.023165
iter  50 value 83.134321
iter  60 value 80.953105
iter  70 value 80.644911
iter  80 value 80.336616
iter  90 value 79.748219
iter 100 value 79.442407
final  value 79.442407 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 139.219278 
iter  10 value 94.089060
iter  20 value 90.109044
iter  30 value 86.594073
iter  40 value 85.431361
iter  50 value 82.713081
iter  60 value 81.944895
iter  70 value 81.667168
iter  80 value 80.871937
iter  90 value 79.752692
iter 100 value 79.272038
final  value 79.272038 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.903850 
iter  10 value 96.363001
iter  20 value 94.624665
iter  30 value 92.977672
iter  40 value 88.879378
iter  50 value 87.831245
iter  60 value 84.064952
iter  70 value 80.800492
iter  80 value 80.287231
iter  90 value 80.103694
iter 100 value 80.030576
final  value 80.030576 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.397729 
iter  10 value 94.331125
iter  20 value 88.454582
iter  30 value 83.738216
iter  40 value 82.957606
iter  50 value 82.017534
iter  60 value 81.757426
iter  70 value 81.630799
iter  80 value 81.446787
iter  90 value 80.611335
iter 100 value 80.149058
final  value 80.149058 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.874791 
iter  10 value 97.298024
iter  20 value 92.663359
iter  30 value 91.950131
iter  40 value 83.695592
iter  50 value 82.040199
iter  60 value 80.639329
iter  70 value 80.263745
iter  80 value 79.845629
iter  90 value 79.534237
iter 100 value 79.435846
final  value 79.435846 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.993927 
iter  10 value 93.924121
iter  20 value 91.296586
iter  30 value 89.843718
iter  40 value 87.995794
iter  50 value 83.834237
iter  60 value 82.994524
iter  70 value 81.685223
iter  80 value 80.558735
iter  90 value 80.292085
iter 100 value 80.121211
final  value 80.121211 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.160223 
iter  10 value 92.542247
iter  20 value 84.368289
iter  30 value 84.352443
iter  40 value 84.338787
iter  50 value 84.272602
iter  60 value 84.257305
iter  70 value 84.184215
iter  80 value 83.869706
iter  90 value 83.858464
iter 100 value 83.850568
final  value 83.850568 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.237042 
final  value 94.054677 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.752306 
final  value 94.054712 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.214654 
final  value 94.054589 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.506107 
iter  10 value 93.276872
iter  20 value 92.840381
final  value 92.839520 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.471558 
iter  10 value 94.057384
iter  20 value 94.049786
iter  30 value 93.862635
iter  40 value 93.789446
iter  50 value 93.788888
iter  60 value 93.786836
iter  70 value 86.936536
iter  80 value 86.935381
iter  90 value 84.951101
iter 100 value 84.949486
final  value 84.949486 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.056955 
iter  10 value 93.920792
iter  20 value 93.519765
iter  30 value 82.449038
iter  40 value 82.227002
final  value 82.180530 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.833116 
iter  10 value 93.871015
iter  20 value 93.700271
iter  30 value 83.360915
iter  40 value 81.738040
final  value 81.718464 
converged
Fitting Repeat 4 

# weights:  305
initial  value 124.311863 
iter  10 value 93.920403
iter  20 value 93.915874
iter  30 value 86.888014
iter  40 value 84.621517
iter  50 value 82.908571
iter  60 value 82.869639
final  value 82.869605 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.859102 
iter  10 value 94.057546
iter  20 value 93.445014
iter  30 value 90.163490
iter  40 value 90.158416
iter  50 value 89.833490
iter  60 value 89.611243
final  value 89.609279 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.210259 
iter  10 value 94.061200
iter  20 value 94.054383
iter  30 value 93.387290
iter  40 value 84.960188
iter  50 value 84.958778
iter  60 value 84.608250
final  value 84.607002 
converged
Fitting Repeat 2 

# weights:  507
initial  value 134.037005 
iter  10 value 93.924996
iter  20 value 93.602425
iter  30 value 84.783069
iter  40 value 84.778907
iter  50 value 84.773218
final  value 84.773034 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.953932 
iter  10 value 94.059451
iter  20 value 93.875884
iter  30 value 88.406718
iter  40 value 82.742465
iter  50 value 81.516550
iter  60 value 81.243493
final  value 81.114303 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.100563 
iter  10 value 86.582810
iter  20 value 86.146069
iter  30 value 85.025468
iter  40 value 81.864375
iter  50 value 81.821878
iter  60 value 81.788788
iter  70 value 81.556051
iter  80 value 81.064383
iter  90 value 81.040224
iter 100 value 81.039500
final  value 81.039500 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.959255 
iter  10 value 87.016653
iter  20 value 86.294129
iter  30 value 86.261658
iter  40 value 86.260376
iter  50 value 85.415116
iter  60 value 85.414516
iter  70 value 85.412271
iter  80 value 85.353616
iter  90 value 85.260349
iter 100 value 85.259636
final  value 85.259636 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.978044 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.317059 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 118.467027 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.062822 
final  value 93.813953 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.145674 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.189081 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.575458 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.605723 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.310253 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.695638 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.456441 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.632081 
iter  10 value 92.580042
iter  20 value 90.808756
iter  30 value 90.786129
iter  40 value 90.785716
final  value 90.785715 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.906998 
iter  10 value 94.275418
final  value 94.275363 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.671258 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.015717 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.279809 
iter  10 value 94.221446
iter  20 value 91.454002
iter  30 value 91.323390
iter  40 value 91.255765
iter  50 value 91.250202
iter  50 value 91.250201
iter  50 value 91.250201
final  value 91.250201 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.797032 
iter  10 value 94.859763
iter  20 value 94.499623
iter  30 value 94.429199
iter  40 value 93.861101
iter  50 value 93.815825
iter  60 value 93.811310
iter  60 value 93.811310
iter  60 value 93.811310
final  value 93.811310 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.694164 
iter  10 value 94.492946
iter  20 value 94.005100
iter  30 value 93.875496
iter  40 value 93.814503
iter  50 value 93.811313
final  value 93.811309 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.528125 
iter  10 value 94.488636
iter  20 value 93.886581
iter  30 value 93.834874
iter  40 value 93.495745
iter  50 value 91.075856
iter  60 value 87.219769
iter  70 value 85.387195
iter  80 value 83.271958
iter  90 value 82.000548
iter 100 value 81.623087
final  value 81.623087 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.014618 
iter  10 value 94.488554
iter  20 value 94.328770
iter  30 value 93.959606
iter  40 value 93.883622
final  value 93.883238 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.338875 
iter  10 value 94.516107
iter  20 value 94.241068
iter  30 value 92.527958
iter  40 value 86.531920
iter  50 value 84.864067
iter  60 value 84.586268
iter  70 value 82.929019
iter  80 value 81.318635
iter  90 value 81.137881
iter 100 value 80.628963
final  value 80.628963 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.829738 
iter  10 value 94.269239
iter  20 value 90.346047
iter  30 value 88.981937
iter  40 value 88.062690
iter  50 value 87.255195
iter  60 value 87.021746
iter  70 value 86.955539
iter  80 value 85.056436
iter  90 value 82.912546
iter 100 value 81.889540
final  value 81.889540 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.524052 
iter  10 value 97.424311
iter  20 value 94.493064
iter  30 value 91.704932
iter  40 value 87.832646
iter  50 value 87.289037
iter  60 value 87.250047
iter  70 value 87.022483
iter  80 value 84.693477
iter  90 value 83.518149
iter 100 value 83.470481
final  value 83.470481 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.916760 
iter  10 value 94.443280
iter  20 value 91.911312
iter  30 value 87.920373
iter  40 value 84.423696
iter  50 value 80.920818
iter  60 value 80.416208
iter  70 value 80.317952
iter  80 value 80.126511
iter  90 value 79.863480
iter 100 value 79.469985
final  value 79.469985 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.391631 
iter  10 value 94.502366
iter  20 value 94.418058
iter  30 value 92.424254
iter  40 value 86.014115
iter  50 value 83.937052
iter  60 value 83.741248
iter  70 value 83.117853
iter  80 value 81.817883
iter  90 value 81.200599
iter 100 value 80.771256
final  value 80.771256 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.703086 
iter  10 value 95.008593
iter  20 value 88.642854
iter  30 value 85.639976
iter  40 value 83.549306
iter  50 value 82.289418
iter  60 value 81.494022
iter  70 value 80.352650
iter  80 value 79.913868
iter  90 value 79.655047
iter 100 value 79.606783
final  value 79.606783 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.181160 
iter  10 value 95.831341
iter  20 value 87.819660
iter  30 value 85.996466
iter  40 value 83.535725
iter  50 value 82.829477
iter  60 value 82.256418
iter  70 value 82.007989
iter  80 value 81.425901
iter  90 value 81.369162
iter 100 value 81.230736
final  value 81.230736 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.239098 
iter  10 value 93.184783
iter  20 value 92.075341
iter  30 value 88.059497
iter  40 value 84.922156
iter  50 value 83.340368
iter  60 value 82.002412
iter  70 value 80.567677
iter  80 value 80.265808
iter  90 value 80.181900
iter 100 value 80.158072
final  value 80.158072 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.888684 
iter  10 value 94.473675
iter  20 value 94.041565
iter  30 value 92.413290
iter  40 value 88.245256
iter  50 value 87.463815
iter  60 value 87.278475
iter  70 value 87.098852
iter  80 value 86.961162
iter  90 value 82.709850
iter 100 value 80.390300
final  value 80.390300 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.693669 
iter  10 value 94.425527
iter  20 value 93.187332
iter  30 value 87.486996
iter  40 value 85.504889
iter  50 value 84.890324
iter  60 value 84.436826
iter  70 value 83.116746
iter  80 value 81.931005
iter  90 value 81.164229
iter 100 value 80.389117
final  value 80.389117 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.488213 
final  value 94.485834 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.027704 
final  value 94.054126 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.372277 
final  value 94.485921 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.960972 
final  value 94.485625 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.704963 
final  value 94.277381 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.123302 
iter  10 value 94.489085
iter  20 value 93.145819
iter  30 value 84.675915
iter  40 value 84.656687
iter  50 value 84.399506
iter  60 value 84.315580
iter  70 value 84.307510
iter  80 value 84.306850
iter  80 value 84.306850
final  value 84.306850 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.175913 
iter  10 value 94.488817
iter  20 value 93.539400
iter  30 value 86.456680
iter  40 value 84.854734
iter  50 value 84.399908
iter  60 value 84.380434
iter  70 value 83.840571
final  value 83.820407 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.686510 
iter  10 value 94.489396
iter  20 value 94.460087
iter  30 value 93.788230
final  value 93.788227 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.607537 
iter  10 value 94.486750
iter  20 value 93.224354
iter  30 value 91.511618
final  value 91.507596 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.361580 
iter  10 value 94.488523
iter  20 value 94.484242
iter  30 value 94.456462
iter  40 value 85.650824
iter  50 value 84.189690
iter  60 value 82.178912
iter  70 value 81.883742
iter  80 value 81.847484
iter  90 value 81.842894
iter 100 value 81.842711
final  value 81.842711 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.982608 
iter  10 value 94.490999
iter  20 value 94.482786
iter  30 value 94.161956
iter  40 value 91.282997
iter  50 value 84.387388
iter  60 value 81.458116
iter  70 value 80.528031
iter  80 value 79.415862
iter  90 value 79.192307
iter 100 value 79.163999
final  value 79.163999 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.933998 
iter  10 value 94.492036
iter  20 value 94.484632
iter  30 value 90.878628
iter  40 value 85.730192
iter  50 value 84.762473
iter  60 value 84.737572
iter  70 value 84.726097
iter  80 value 84.229893
iter  90 value 83.852644
iter 100 value 83.852335
final  value 83.852335 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.614413 
iter  10 value 94.283556
iter  20 value 94.244280
iter  30 value 87.429287
iter  40 value 84.444974
iter  50 value 82.853695
iter  60 value 80.797107
iter  70 value 80.069788
iter  80 value 78.385710
iter  90 value 78.059080
iter 100 value 77.962547
final  value 77.962547 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.385677 
iter  10 value 94.262267
iter  20 value 94.236536
iter  30 value 94.231591
iter  40 value 94.223653
iter  50 value 88.948536
iter  60 value 86.182081
iter  70 value 86.122693
iter  80 value 86.122050
iter  90 value 86.093188
final  value 86.092594 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.593661 
iter  10 value 94.283510
iter  20 value 94.043990
iter  30 value 91.272773
iter  40 value 91.181799
final  value 91.123356 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.746491 
iter  10 value 91.495408
iter  20 value 89.386056
iter  30 value 89.254471
iter  40 value 89.221729
final  value 89.221721 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.808260 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.635755 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.857731 
iter  10 value 88.942279
iter  20 value 87.033973
final  value 87.032771 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.737880 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.444828 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.648079 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.487830 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.563969 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.774781 
iter  10 value 94.467392
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.086144 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.216657 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.402834 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.479173 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.560365 
iter  10 value 94.466667
iter  10 value 94.466667
iter  10 value 94.466667
final  value 94.466667 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.710524 
iter  10 value 94.650507
iter  20 value 94.488537
iter  30 value 94.478401
iter  40 value 94.471531
iter  50 value 93.151065
iter  60 value 91.184187
iter  70 value 90.823835
iter  80 value 88.730303
iter  90 value 86.538259
iter 100 value 85.619607
final  value 85.619607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.128777 
iter  10 value 94.329810
iter  20 value 86.954520
iter  30 value 85.901933
iter  40 value 85.256487
iter  50 value 84.520290
iter  60 value 84.030712
iter  70 value 83.527878
iter  80 value 83.182791
iter  90 value 83.027903
final  value 83.027839 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.422336 
iter  10 value 94.330547
iter  20 value 86.658830
iter  30 value 86.357500
iter  40 value 85.759689
iter  50 value 84.795224
iter  60 value 84.482861
iter  70 value 84.481427
iter  70 value 84.481426
iter  70 value 84.481426
final  value 84.481426 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.285912 
iter  10 value 93.538083
iter  20 value 86.279713
iter  30 value 85.777021
iter  40 value 85.134781
iter  50 value 84.930833
iter  60 value 84.907936
final  value 84.906603 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.872889 
iter  10 value 94.488654
iter  20 value 94.487685
iter  30 value 94.482328
iter  40 value 87.293451
iter  50 value 86.801368
iter  60 value 86.048512
iter  70 value 85.548706
iter  80 value 85.293137
final  value 85.291107 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.449636 
iter  10 value 94.549708
iter  20 value 87.886145
iter  30 value 86.077774
iter  40 value 85.836687
iter  50 value 85.375204
iter  60 value 82.926538
iter  70 value 82.614255
iter  80 value 82.326286
iter  90 value 82.033767
iter 100 value 81.907206
final  value 81.907206 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.371592 
iter  10 value 94.668160
iter  20 value 85.738096
iter  30 value 83.407867
iter  40 value 83.030219
iter  50 value 82.957097
iter  60 value 82.679223
iter  70 value 82.475512
iter  80 value 82.221721
iter  90 value 80.999935
iter 100 value 80.821890
final  value 80.821890 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.326764 
iter  10 value 94.504379
iter  20 value 91.409947
iter  30 value 90.098560
iter  40 value 88.515828
iter  50 value 87.632997
iter  60 value 87.202778
iter  70 value 84.645987
iter  80 value 83.694721
iter  90 value 83.480757
iter 100 value 82.354480
final  value 82.354480 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.503974 
iter  10 value 94.513671
iter  20 value 87.157520
iter  30 value 85.412750
iter  40 value 84.868795
iter  50 value 83.383072
iter  60 value 82.746756
iter  70 value 81.813608
iter  80 value 81.336905
iter  90 value 81.007371
iter 100 value 80.823553
final  value 80.823553 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.395162 
iter  10 value 94.525980
iter  20 value 93.210051
iter  30 value 90.882172
iter  40 value 87.779747
iter  50 value 85.028716
iter  60 value 83.162019
iter  70 value 81.446043
iter  80 value 80.659334
iter  90 value 80.482259
iter 100 value 80.355027
final  value 80.355027 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.094914 
iter  10 value 94.328061
iter  20 value 91.445014
iter  30 value 86.543209
iter  40 value 83.969472
iter  50 value 81.440596
iter  60 value 80.887635
iter  70 value 80.751653
iter  80 value 80.697928
iter  90 value 80.620511
iter 100 value 80.572333
final  value 80.572333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 133.528232 
iter  10 value 94.910528
iter  20 value 93.874672
iter  30 value 93.468486
iter  40 value 93.282988
iter  50 value 93.246077
iter  60 value 89.895488
iter  70 value 87.291910
iter  80 value 84.764353
iter  90 value 83.904575
iter 100 value 83.724516
final  value 83.724516 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.254014 
iter  10 value 94.469535
iter  20 value 93.818654
iter  30 value 85.457308
iter  40 value 83.967753
iter  50 value 83.177051
iter  60 value 82.797544
iter  70 value 82.523845
iter  80 value 82.083777
iter  90 value 81.685767
iter 100 value 81.451207
final  value 81.451207 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.064440 
iter  10 value 94.847101
iter  20 value 94.148489
iter  30 value 89.938876
iter  40 value 89.330013
iter  50 value 89.134424
iter  60 value 88.860393
iter  70 value 88.500194
iter  80 value 86.428762
iter  90 value 85.173464
iter 100 value 82.995692
final  value 82.995692 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.398904 
iter  10 value 93.590862
iter  20 value 84.295335
iter  30 value 82.286679
iter  40 value 81.957502
iter  50 value 81.390453
iter  60 value 81.053215
iter  70 value 80.845422
iter  80 value 80.497041
iter  90 value 80.250563
iter 100 value 80.063378
final  value 80.063378 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.832173 
final  value 94.485785 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.043242 
final  value 94.485885 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.310837 
iter  10 value 94.485846
iter  20 value 94.481979
iter  30 value 89.135060
iter  40 value 87.168118
iter  50 value 86.759449
iter  60 value 85.511810
iter  70 value 85.308841
final  value 85.308591 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.362037 
final  value 94.486123 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.707491 
final  value 94.484136 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.549548 
iter  10 value 94.471962
iter  20 value 94.467858
iter  30 value 94.466492
iter  40 value 87.746818
iter  50 value 85.177629
iter  60 value 84.797100
iter  70 value 83.860849
iter  80 value 83.549870
iter  90 value 83.482254
iter 100 value 83.481470
final  value 83.481470 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.564288 
iter  10 value 94.471928
iter  20 value 94.468224
final  value 94.467422 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.121930 
iter  10 value 94.472651
iter  20 value 94.467753
final  value 94.467573 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.166236 
iter  10 value 94.488635
iter  20 value 94.478698
iter  30 value 89.221433
iter  40 value 87.040451
iter  50 value 87.037796
iter  60 value 87.028426
iter  70 value 86.961421
iter  80 value 84.193949
iter  90 value 84.149708
iter 100 value 83.050209
final  value 83.050209 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.300015 
iter  10 value 93.608827
iter  20 value 93.417637
iter  30 value 93.376506
iter  40 value 93.293415
iter  50 value 93.287865
iter  60 value 93.282948
iter  70 value 93.280989
iter  80 value 93.278804
iter  90 value 92.001281
iter 100 value 89.358641
final  value 89.358641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.883907 
iter  10 value 94.491913
iter  20 value 94.484415
iter  30 value 87.228634
iter  40 value 86.028580
iter  50 value 83.360349
iter  60 value 80.453914
iter  70 value 80.399421
final  value 80.399084 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.201460 
iter  10 value 94.492412
iter  20 value 94.380680
iter  30 value 90.995333
iter  40 value 89.993189
iter  50 value 89.558957
iter  60 value 89.520738
iter  70 value 89.520577
final  value 89.520167 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.552369 
iter  10 value 94.481452
iter  20 value 94.475178
iter  30 value 94.470122
final  value 94.467795 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.229850 
iter  10 value 93.700089
iter  20 value 93.691329
iter  30 value 93.687192
iter  40 value 93.685650
iter  50 value 92.702440
iter  60 value 91.771406
iter  70 value 91.473379
iter  80 value 91.430080
final  value 91.430057 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.610036 
iter  10 value 92.789526
iter  20 value 87.269257
iter  30 value 85.992706
iter  40 value 85.946766
iter  50 value 85.904580
iter  60 value 85.731055
iter  70 value 85.709048
iter  80 value 83.082012
iter  90 value 82.956288
iter 100 value 82.630837
final  value 82.630837 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.692386 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.936558 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.178069 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.478904 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.413658 
final  value 93.300000 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.718467 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.101026 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.425268 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.073950 
iter  10 value 93.022862
final  value 93.022222 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.398907 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.380901 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.158597 
final  value 93.300000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.978239 
iter  10 value 93.772979
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.677895 
iter  10 value 94.476057
final  value 94.472273 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.560784 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.885363 
iter  10 value 93.726573
iter  20 value 86.963799
iter  30 value 83.805896
iter  40 value 82.949208
iter  50 value 81.581752
iter  60 value 80.618590
iter  70 value 80.110707
iter  80 value 80.051255
final  value 80.050235 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.833249 
iter  10 value 94.280623
iter  20 value 88.304220
iter  30 value 84.349401
iter  40 value 83.560646
iter  50 value 81.728103
iter  60 value 81.435384
iter  70 value 81.433003
iter  80 value 81.432584
final  value 81.432415 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.314852 
iter  10 value 93.699081
iter  20 value 86.923206
iter  30 value 86.621654
iter  40 value 84.911485
iter  50 value 84.465970
iter  60 value 84.343538
iter  70 value 84.330847
final  value 84.330844 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.443665 
iter  10 value 94.462867
iter  20 value 89.297376
iter  30 value 85.342071
iter  40 value 84.417591
iter  50 value 83.982571
iter  60 value 83.847344
iter  70 value 82.191890
iter  80 value 81.103996
iter  90 value 80.185168
iter 100 value 80.081881
final  value 80.081881 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.312052 
iter  10 value 94.507295
iter  20 value 94.472069
iter  30 value 90.062271
iter  40 value 87.610091
iter  50 value 87.322949
iter  60 value 85.192531
iter  70 value 84.471592
iter  80 value 84.352313
iter  90 value 84.333352
final  value 84.330844 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.783184 
iter  10 value 97.958325
iter  20 value 94.913816
iter  30 value 93.592087
iter  40 value 91.975268
iter  50 value 91.005247
iter  60 value 89.087830
iter  70 value 88.940213
iter  80 value 87.476783
iter  90 value 81.355647
iter 100 value 79.666336
final  value 79.666336 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.967076 
iter  10 value 93.808010
iter  20 value 87.804718
iter  30 value 85.411630
iter  40 value 84.476501
iter  50 value 82.810182
iter  60 value 81.005204
iter  70 value 80.423442
iter  80 value 79.833612
iter  90 value 79.440970
iter 100 value 79.354807
final  value 79.354807 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.053539 
iter  10 value 94.710870
iter  20 value 94.538898
iter  30 value 94.495194
iter  40 value 92.831873
iter  50 value 85.860960
iter  60 value 82.340187
iter  70 value 80.587980
iter  80 value 80.327905
iter  90 value 79.886028
iter 100 value 79.585118
final  value 79.585118 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.434203 
iter  10 value 91.833201
iter  20 value 84.543915
iter  30 value 81.996075
iter  40 value 80.311494
iter  50 value 79.431206
iter  60 value 79.171622
iter  70 value 79.121295
iter  80 value 79.069682
iter  90 value 78.981444
iter 100 value 78.898524
final  value 78.898524 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.185571 
iter  10 value 94.387695
iter  20 value 93.525782
iter  30 value 86.284215
iter  40 value 84.227968
iter  50 value 83.135312
iter  60 value 80.701768
iter  70 value 80.452836
iter  80 value 79.371730
iter  90 value 79.052916
iter 100 value 78.976071
final  value 78.976071 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.578521 
iter  10 value 94.524908
iter  20 value 88.063999
iter  30 value 86.222453
iter  40 value 84.549074
iter  50 value 83.598818
iter  60 value 83.566211
iter  70 value 83.413731
iter  80 value 82.730575
iter  90 value 80.160014
iter 100 value 79.475778
final  value 79.475778 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 142.296492 
iter  10 value 98.383085
iter  20 value 93.367918
iter  30 value 92.290601
iter  40 value 90.695072
iter  50 value 85.098991
iter  60 value 82.878882
iter  70 value 80.595075
iter  80 value 79.616782
iter  90 value 79.280483
iter 100 value 79.121491
final  value 79.121491 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.931690 
iter  10 value 91.469304
iter  20 value 89.672550
iter  30 value 84.716098
iter  40 value 83.370866
iter  50 value 82.206793
iter  60 value 81.879810
iter  70 value 81.652610
iter  80 value 80.641749
iter  90 value 80.246940
iter 100 value 80.068472
final  value 80.068472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.211301 
iter  10 value 94.311065
iter  20 value 87.375821
iter  30 value 83.659098
iter  40 value 82.128956
iter  50 value 81.417853
iter  60 value 79.791701
iter  70 value 79.357832
iter  80 value 79.288829
iter  90 value 79.064708
iter 100 value 79.047810
final  value 79.047810 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.634795 
iter  10 value 94.892324
iter  20 value 87.777024
iter  30 value 86.912446
iter  40 value 85.916950
iter  50 value 82.031029
iter  60 value 81.042686
iter  70 value 80.619461
iter  80 value 79.777634
iter  90 value 79.162344
iter 100 value 79.013362
final  value 79.013362 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.107326 
final  value 94.485840 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.699463 
iter  10 value 94.486058
iter  20 value 94.484232
iter  20 value 94.484232
iter  20 value 94.484232
final  value 94.484232 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.818494 
iter  10 value 89.824108
iter  20 value 86.959406
iter  30 value 86.626905
iter  40 value 86.351070
final  value 86.350571 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.276923 
final  value 94.485909 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.817412 
final  value 94.485818 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.690024 
iter  10 value 94.489107
iter  20 value 93.850156
iter  30 value 90.618271
iter  40 value 87.567419
iter  50 value 84.323500
iter  60 value 84.157514
iter  70 value 84.155686
iter  80 value 84.154580
iter  90 value 84.130794
iter 100 value 82.939856
final  value 82.939856 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.122991 
iter  10 value 94.488599
iter  20 value 94.402481
iter  30 value 93.256290
iter  40 value 90.231683
iter  50 value 81.315056
iter  60 value 80.041443
iter  70 value 79.960051
iter  80 value 79.959835
final  value 79.959786 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.029074 
iter  10 value 94.489260
iter  20 value 94.474941
iter  30 value 84.158245
iter  40 value 82.497645
iter  50 value 80.544695
iter  60 value 80.525523
final  value 80.525459 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.685753 
iter  10 value 88.830114
iter  20 value 88.798346
iter  30 value 88.794567
iter  40 value 87.489401
iter  50 value 87.155840
final  value 87.155732 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.958804 
iter  10 value 94.451648
iter  20 value 94.192387
iter  30 value 91.620640
iter  40 value 91.616542
iter  50 value 91.615323
iter  60 value 91.392699
iter  70 value 90.148276
final  value 90.148271 
converged
Fitting Repeat 1 

# weights:  507
initial  value 130.771090 
iter  10 value 94.457803
iter  20 value 94.186309
iter  30 value 93.757164
iter  40 value 89.938264
iter  50 value 87.429905
iter  60 value 87.272557
final  value 87.272017 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.397510 
iter  10 value 94.492439
iter  20 value 93.286694
iter  30 value 87.430137
iter  40 value 86.019724
iter  50 value 81.214383
iter  60 value 80.913396
iter  70 value 80.876286
iter  80 value 80.875323
iter  90 value 80.708071
iter 100 value 79.927891
final  value 79.927891 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.592388 
iter  10 value 91.992075
iter  20 value 91.989723
iter  30 value 91.350296
iter  40 value 89.671984
iter  50 value 89.662434
iter  60 value 89.661669
iter  70 value 89.660973
final  value 89.660708 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.885200 
iter  10 value 93.779459
iter  20 value 93.730584
iter  30 value 93.326091
iter  40 value 92.968347
iter  50 value 92.964679
iter  60 value 92.961125
iter  70 value 91.597679
iter  80 value 81.900767
iter  90 value 79.401234
iter 100 value 79.262569
final  value 79.262569 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.888465 
iter  10 value 90.176613
iter  20 value 85.189238
iter  30 value 84.839762
iter  40 value 84.536729
iter  50 value 84.467750
iter  60 value 84.029120
iter  70 value 83.633327
iter  80 value 83.631678
iter  90 value 83.629925
iter 100 value 82.475671
final  value 82.475671 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.641966 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.068698 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.504278 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.186605 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.257948 
final  value 93.653870 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.439634 
final  value 93.653870 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.114786 
iter  10 value 93.810011
iter  10 value 93.810011
iter  10 value 93.810011
final  value 93.810011 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.965162 
iter  10 value 86.765730
final  value 82.735065 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.415402 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.786840 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.125475 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.838936 
iter  10 value 94.031442
iter  20 value 91.624788
iter  30 value 86.197654
iter  40 value 85.678207
iter  50 value 85.676667
final  value 85.675815 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.867260 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.913777 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.736857 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.988689 
iter  10 value 94.065407
iter  20 value 86.436326
iter  30 value 83.974372
iter  40 value 83.645101
iter  50 value 83.555413
iter  60 value 82.601247
iter  70 value 82.533608
iter  80 value 81.840871
iter  90 value 81.569437
iter 100 value 81.382232
final  value 81.382232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.351572 
iter  10 value 94.118185
iter  20 value 94.057129
iter  30 value 89.317038
iter  40 value 87.055752
iter  50 value 86.329999
iter  60 value 86.128738
iter  70 value 84.326743
iter  80 value 83.244070
iter  90 value 83.159335
iter 100 value 82.691312
final  value 82.691312 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 114.144603 
iter  10 value 93.899862
iter  20 value 84.154735
iter  30 value 83.853707
iter  40 value 82.556509
iter  50 value 82.400640
iter  60 value 82.327341
iter  70 value 81.751624
iter  80 value 81.391068
final  value 81.384197 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.578169 
iter  10 value 93.893007
iter  20 value 90.804469
iter  30 value 87.591219
iter  40 value 83.917757
iter  50 value 83.574582
iter  60 value 82.816059
iter  70 value 82.152930
iter  80 value 82.116535
iter  90 value 81.969662
iter 100 value 81.519671
final  value 81.519671 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.249630 
iter  10 value 94.865484
iter  20 value 94.021138
iter  30 value 89.913567
iter  40 value 83.129765
iter  50 value 83.038460
iter  60 value 82.858109
iter  70 value 82.665403
iter  80 value 82.594293
final  value 82.594250 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.425627 
iter  10 value 93.846469
iter  20 value 84.125125
iter  30 value 83.550294
iter  40 value 83.259141
iter  50 value 82.428104
iter  60 value 82.369284
iter  70 value 81.987527
iter  80 value 81.496635
iter  90 value 81.318758
iter 100 value 81.285554
final  value 81.285554 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.630277 
iter  10 value 94.075175
iter  20 value 92.857800
iter  30 value 85.694804
iter  40 value 85.300640
iter  50 value 82.811741
iter  60 value 81.980384
iter  70 value 81.713821
iter  80 value 81.567523
iter  90 value 81.496527
iter 100 value 81.319506
final  value 81.319506 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.282154 
iter  10 value 94.068637
iter  20 value 93.933043
iter  30 value 85.589357
iter  40 value 83.592052
iter  50 value 82.886960
iter  60 value 81.919081
iter  70 value 81.491786
iter  80 value 81.063253
iter  90 value 80.646798
iter 100 value 80.328641
final  value 80.328641 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.224337 
iter  10 value 94.076824
iter  20 value 91.769801
iter  30 value 86.961171
iter  40 value 85.985534
iter  50 value 85.911486
iter  60 value 85.494370
iter  70 value 82.374580
iter  80 value 81.760954
iter  90 value 81.039076
iter 100 value 80.665523
final  value 80.665523 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.642096 
iter  10 value 94.157504
iter  20 value 93.709238
iter  30 value 93.250896
iter  40 value 93.043471
iter  50 value 83.015290
iter  60 value 82.534462
iter  70 value 82.310731
iter  80 value 82.283924
iter  90 value 82.150906
iter 100 value 81.413514
final  value 81.413514 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.820567 
iter  10 value 93.926272
iter  20 value 91.407516
iter  30 value 84.111500
iter  40 value 83.868307
iter  50 value 83.552299
iter  60 value 82.072630
iter  70 value 81.002037
iter  80 value 80.769137
iter  90 value 80.247765
iter 100 value 79.973411
final  value 79.973411 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.661159 
iter  10 value 93.291104
iter  20 value 86.474774
iter  30 value 83.274080
iter  40 value 82.778401
iter  50 value 82.529148
iter  60 value 82.310275
iter  70 value 82.236966
iter  80 value 82.018854
iter  90 value 80.916114
iter 100 value 80.277333
final  value 80.277333 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.669986 
iter  10 value 94.100772
iter  20 value 93.561847
iter  30 value 93.381524
iter  40 value 85.799971
iter  50 value 82.704030
iter  60 value 82.474572
iter  70 value 81.710704
iter  80 value 81.189532
iter  90 value 80.935204
iter 100 value 80.715365
final  value 80.715365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.602911 
iter  10 value 92.258174
iter  20 value 86.637736
iter  30 value 84.951450
iter  40 value 83.066079
iter  50 value 81.755091
iter  60 value 80.726102
iter  70 value 80.358514
iter  80 value 80.243600
iter  90 value 80.064426
iter 100 value 79.790251
final  value 79.790251 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.311373 
iter  10 value 94.068886
iter  20 value 93.571746
iter  30 value 87.949608
iter  40 value 84.452647
iter  50 value 83.386636
iter  60 value 83.170814
iter  70 value 82.922323
iter  80 value 80.750674
iter  90 value 80.225105
iter 100 value 80.143896
final  value 80.143896 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 93.985289 
iter  10 value 93.675088
iter  20 value 93.674339
iter  30 value 87.533720
iter  40 value 85.720742
iter  50 value 85.664103
iter  60 value 85.662005
iter  70 value 84.572485
iter  80 value 84.572257
iter  90 value 84.494155
iter 100 value 84.491646
final  value 84.491646 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.635966 
final  value 94.054533 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.668832 
iter  10 value 94.054475
iter  20 value 94.053000
final  value 94.052916 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.763036 
final  value 94.054686 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.647115 
final  value 94.054418 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.758787 
iter  10 value 94.057240
iter  20 value 93.990173
iter  30 value 88.417991
iter  40 value 82.696103
iter  50 value 82.544465
final  value 82.543453 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.629847 
iter  10 value 94.037868
iter  20 value 93.281731
iter  30 value 93.258239
iter  30 value 93.258238
iter  30 value 93.258238
final  value 93.258238 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.221479 
iter  10 value 94.058329
iter  20 value 93.992237
iter  30 value 82.553811
iter  40 value 82.499043
iter  50 value 82.494890
iter  60 value 82.296758
iter  70 value 82.285429
iter  80 value 82.239404
iter  90 value 82.033473
iter 100 value 81.091513
final  value 81.091513 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.692216 
iter  10 value 93.284130
iter  20 value 90.454685
iter  30 value 85.317636
iter  40 value 85.315427
iter  50 value 85.314820
final  value 85.314802 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.634740 
iter  10 value 94.057541
iter  20 value 94.053026
iter  30 value 92.889741
iter  30 value 92.889741
iter  30 value 92.889741
final  value 92.889741 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.613670 
iter  10 value 94.057202
iter  20 value 88.857365
iter  30 value 82.542908
iter  40 value 82.531977
iter  50 value 82.523804
iter  60 value 82.283917
iter  70 value 82.251053
final  value 82.251009 
converged
Fitting Repeat 2 

# weights:  507
initial  value 132.192575 
iter  10 value 94.040948
iter  20 value 93.800704
iter  30 value 93.287269
iter  40 value 90.897941
iter  50 value 90.037057
iter  60 value 82.554917
iter  70 value 80.816081
iter  80 value 80.675244
iter  90 value 80.601353
iter 100 value 80.406921
final  value 80.406921 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.128529 
iter  10 value 93.297142
iter  20 value 93.290847
iter  30 value 87.818561
iter  40 value 81.309998
iter  50 value 81.093747
iter  60 value 80.880720
final  value 80.782815 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.372112 
iter  10 value 94.040911
iter  20 value 85.669842
iter  30 value 85.637253
iter  40 value 85.629988
iter  50 value 85.596011
iter  60 value 82.612011
iter  70 value 80.846073
iter  80 value 80.840578
iter  90 value 80.527904
iter 100 value 80.474840
final  value 80.474840 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.787393 
iter  10 value 94.041181
iter  20 value 94.039583
iter  30 value 94.039113
iter  40 value 93.943571
iter  50 value 93.021201
iter  60 value 85.339279
iter  70 value 85.313385
iter  80 value 85.102327
iter  90 value 85.099450
iter 100 value 85.072815
final  value 85.072815 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.424148 
iter  10 value 117.767076
iter  20 value 117.752243
iter  30 value 117.314363
iter  40 value 116.024508
iter  50 value 109.544489
iter  60 value 107.228337
iter  70 value 106.038451
iter  80 value 102.791865
iter  90 value 101.713963
iter 100 value 100.946606
final  value 100.946606 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.813792 
iter  10 value 117.766756
iter  20 value 117.760134
iter  30 value 107.494377
iter  40 value 105.168903
iter  50 value 105.053060
iter  60 value 104.570651
iter  70 value 103.498478
final  value 103.483226 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.422348 
iter  10 value 107.421980
iter  20 value 103.089441
iter  30 value 102.038320
iter  40 value 101.598490
iter  50 value 101.590808
iter  60 value 101.164604
iter  70 value 101.030550
iter  80 value 101.022859
iter  90 value 100.935522
iter 100 value 100.268123
final  value 100.268123 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.844682 
iter  10 value 115.445798
iter  20 value 115.306150
iter  30 value 114.610973
iter  40 value 114.605403
final  value 114.604423 
converged
Fitting Repeat 5 

# weights:  507
initial  value 129.580406 
iter  10 value 117.560362
iter  20 value 117.553789
iter  30 value 117.534600
iter  40 value 117.512140
final  value 117.511996 
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 -- Wed Apr 29 01:28:54 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 
 41.410   1.505  92.265