##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 Patched (2025-08-23 r88802)
* 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 ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking 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       34.975  0.284  35.304
corr_plot     34.061  0.460  34.524
FSmethod      33.264  0.528  33.795
pred_ensembel 13.109  0.386  12.214
enrichfindP    0.545  0.048   8.346
* 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-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.5.1 Patched (2025-08-23 r88802) -- "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 94.578207 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.320571 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.320046 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.801428 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.896129 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.733990 
iter  10 value 93.977034
iter  20 value 93.958070
final  value 93.956926 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.460415 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.528162 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.935279 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.410552 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.385695 
iter  10 value 94.025289
iter  10 value 94.025289
iter  10 value 94.025289
final  value 94.025289 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.649181 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.251248 
iter  10 value 92.438650
final  value 91.717242 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.411566 
iter  10 value 89.964326
iter  20 value 89.870875
final  value 89.870091 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.486493 
iter  10 value 84.507900
iter  20 value 83.157463
iter  30 value 82.901879
iter  40 value 82.901704
final  value 82.901697 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.552443 
iter  10 value 93.821790
iter  20 value 87.469450
iter  30 value 84.363421
iter  40 value 84.165112
iter  50 value 83.523141
iter  60 value 83.244137
final  value 83.243067 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.142650 
iter  10 value 93.857333
iter  20 value 87.315340
iter  30 value 85.370937
iter  40 value 85.109982
iter  50 value 84.100027
iter  60 value 84.009340
iter  70 value 83.893106
iter  80 value 83.888858
iter  90 value 83.885052
final  value 83.884938 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.790929 
iter  10 value 91.460605
iter  20 value 91.188743
iter  30 value 90.201342
iter  40 value 90.158513
iter  50 value 90.138826
final  value 90.138821 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.624850 
iter  10 value 93.975077
iter  20 value 87.393396
iter  30 value 86.390588
iter  40 value 85.119352
iter  50 value 84.577722
iter  60 value 84.334102
iter  70 value 84.312127
final  value 84.312049 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.232896 
iter  10 value 94.059599
iter  20 value 94.010385
iter  30 value 88.521242
iter  40 value 85.985241
iter  50 value 84.977596
iter  60 value 84.014763
iter  70 value 83.856699
iter  80 value 83.847582
iter  80 value 83.847581
iter  80 value 83.847581
final  value 83.847581 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.958166 
iter  10 value 89.274416
iter  20 value 87.484394
iter  30 value 83.784682
iter  40 value 82.653839
iter  50 value 82.474339
iter  60 value 82.278612
iter  70 value 81.770979
iter  80 value 81.107552
iter  90 value 80.655251
iter 100 value 80.374706
final  value 80.374706 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.069905 
iter  10 value 94.108178
iter  20 value 93.501677
iter  30 value 89.539096
iter  40 value 85.879803
iter  50 value 85.132324
iter  60 value 83.917327
iter  70 value 83.206973
iter  80 value 82.771449
iter  90 value 80.837102
iter 100 value 80.475238
final  value 80.475238 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.643325 
iter  10 value 92.970402
iter  20 value 85.734519
iter  30 value 84.149797
iter  40 value 83.957542
iter  50 value 83.783388
iter  60 value 83.094716
iter  70 value 81.623735
iter  80 value 81.501156
iter  90 value 81.378467
iter 100 value 80.710537
final  value 80.710537 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.874047 
iter  10 value 92.550202
iter  20 value 84.632460
iter  30 value 84.476873
iter  40 value 84.237765
iter  50 value 83.916111
iter  60 value 83.272402
iter  70 value 82.201263
iter  80 value 81.971141
iter  90 value 81.582740
iter 100 value 81.515031
final  value 81.515031 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.482227 
iter  10 value 94.039786
iter  20 value 90.653512
iter  30 value 89.493887
iter  40 value 83.533219
iter  50 value 82.989866
iter  60 value 81.933758
iter  70 value 81.223678
iter  80 value 81.156429
iter  90 value 80.960582
iter 100 value 80.748604
final  value 80.748604 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.323133 
iter  10 value 93.335807
iter  20 value 90.483667
iter  30 value 89.767578
iter  40 value 85.368322
iter  50 value 83.739554
iter  60 value 83.002473
iter  70 value 81.668703
iter  80 value 81.510152
iter  90 value 81.160318
iter 100 value 80.902961
final  value 80.902961 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.339205 
iter  10 value 94.050605
iter  20 value 85.734948
iter  30 value 84.725719
iter  40 value 84.404404
iter  50 value 83.936337
iter  60 value 82.134120
iter  70 value 81.657119
iter  80 value 81.585172
iter  90 value 81.526271
iter 100 value 81.500441
final  value 81.500441 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.258375 
iter  10 value 93.862906
iter  20 value 90.818072
iter  30 value 89.659785
iter  40 value 87.501929
iter  50 value 83.915709
iter  60 value 81.935661
iter  70 value 81.701383
iter  80 value 81.211798
iter  90 value 80.739492
iter 100 value 80.476183
final  value 80.476183 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.310505 
iter  10 value 93.998398
iter  20 value 90.156895
iter  30 value 89.705858
iter  40 value 87.552605
iter  50 value 84.111420
iter  60 value 83.537805
iter  70 value 82.275960
iter  80 value 81.270161
iter  90 value 80.972199
iter 100 value 80.145875
final  value 80.145875 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.373708 
iter  10 value 94.113915
iter  20 value 92.875689
iter  30 value 90.418787
iter  40 value 85.910015
iter  50 value 85.106867
iter  60 value 83.713595
iter  70 value 82.831333
iter  80 value 81.338280
iter  90 value 80.233567
iter 100 value 79.688359
final  value 79.688359 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.027183 
final  value 94.054528 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.229519 
final  value 94.054546 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.559254 
iter  10 value 94.010354
iter  20 value 94.008977
iter  30 value 93.965839
final  value 93.956956 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.807624 
final  value 94.054781 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.700451 
final  value 94.054410 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.938597 
iter  10 value 94.057054
iter  20 value 93.981262
iter  30 value 85.272388
final  value 85.218340 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.182388 
iter  10 value 94.046687
iter  20 value 92.621414
iter  30 value 90.928445
iter  40 value 90.571211
iter  50 value 90.569344
iter  60 value 90.555267
iter  70 value 90.554880
iter  80 value 90.518087
iter  90 value 90.447714
iter 100 value 90.447653
final  value 90.447653 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.442924 
iter  10 value 94.014080
iter  20 value 93.886791
iter  30 value 90.159239
iter  40 value 81.846824
iter  50 value 81.832266
iter  60 value 81.815800
iter  70 value 81.809673
final  value 81.809367 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.068239 
iter  10 value 89.481304
iter  20 value 82.415057
iter  30 value 82.238920
iter  30 value 82.238919
final  value 82.238919 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.489982 
iter  10 value 85.974502
iter  20 value 83.734875
iter  30 value 83.733137
iter  40 value 83.729604
iter  50 value 83.648129
iter  60 value 83.544831
iter  70 value 82.969042
final  value 82.905558 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.438562 
iter  10 value 94.061385
iter  20 value 93.597306
iter  30 value 85.247391
iter  40 value 85.223268
iter  50 value 85.221424
iter  60 value 85.219963
iter  70 value 85.101555
iter  80 value 85.100185
iter  90 value 84.963527
iter 100 value 82.902029
final  value 82.902029 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.968191 
iter  10 value 94.064046
iter  20 value 94.061705
iter  30 value 94.058340
iter  40 value 94.052823
iter  50 value 94.030854
iter  60 value 93.823553
iter  70 value 85.869193
iter  80 value 84.616224
final  value 84.616163 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.444440 
iter  10 value 94.017394
iter  20 value 94.008914
iter  30 value 93.696103
iter  40 value 87.891179
iter  50 value 85.039085
iter  60 value 83.289668
iter  70 value 81.895694
iter  80 value 81.894642
final  value 81.879207 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.536240 
iter  10 value 93.559964
iter  20 value 93.553597
final  value 93.552440 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.559845 
iter  10 value 94.061064
iter  20 value 93.939213
iter  30 value 86.814616
iter  40 value 86.697185
iter  50 value 86.695984
iter  60 value 85.279114
iter  70 value 84.858311
iter  80 value 81.345260
iter  90 value 80.797955
iter 100 value 80.791118
final  value 80.791118 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.893015 
final  value 94.312038 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.556961 
iter  10 value 94.165247
final  value 93.345953 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.465427 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.494776 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.953443 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.499295 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.906319 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.801471 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.116716 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.348525 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.761414 
iter  10 value 93.809664
final  value 93.792430 
converged
Fitting Repeat 2 

# weights:  507
initial  value 129.828197 
final  value 93.809646 
converged
Fitting Repeat 3 

# weights:  507
initial  value 137.115466 
iter  10 value 94.466832
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.406749 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.831726 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.067763 
iter  10 value 94.488634
iter  20 value 94.027117
iter  30 value 87.092351
iter  40 value 86.043802
iter  50 value 85.878337
iter  60 value 85.194211
iter  70 value 85.135303
final  value 85.135267 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.605148 
iter  10 value 94.432455
iter  20 value 88.628456
iter  30 value 82.925601
iter  40 value 82.767575
iter  50 value 81.912041
iter  60 value 80.807286
iter  70 value 80.665645
final  value 80.644385 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.020867 
iter  10 value 94.447811
iter  20 value 87.972345
iter  30 value 86.141835
iter  40 value 85.925767
iter  50 value 85.819918
iter  60 value 85.189335
iter  70 value 85.135616
iter  80 value 85.135286
final  value 85.135267 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.387985 
iter  10 value 94.476575
iter  20 value 94.194765
iter  30 value 93.724135
iter  40 value 91.755633
iter  50 value 88.372528
iter  60 value 86.841914
iter  70 value 85.290221
iter  80 value 83.246645
iter  90 value 82.669897
iter 100 value 82.444424
final  value 82.444424 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.211910 
iter  10 value 94.488320
iter  20 value 93.866628
iter  30 value 93.705208
iter  40 value 87.388063
iter  50 value 85.681765
iter  60 value 85.317313
iter  70 value 85.175829
iter  80 value 85.135279
final  value 85.135267 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.798485 
iter  10 value 93.745788
iter  20 value 85.349522
iter  30 value 83.284841
iter  40 value 82.737328
iter  50 value 81.464621
iter  60 value 81.356539
iter  70 value 81.130795
iter  80 value 80.585087
iter  90 value 79.992265
iter 100 value 79.926377
final  value 79.926377 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.001238 
iter  10 value 92.628712
iter  20 value 90.816104
iter  30 value 89.547360
iter  40 value 89.261724
iter  50 value 89.150979
iter  60 value 87.851055
iter  70 value 87.106162
iter  80 value 86.995195
iter  90 value 86.636946
iter 100 value 84.608138
final  value 84.608138 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.224110 
iter  10 value 94.714756
iter  20 value 93.913894
iter  30 value 86.212003
iter  40 value 82.669376
iter  50 value 82.371285
iter  60 value 81.856628
iter  70 value 81.035149
iter  80 value 80.767010
iter  90 value 80.231666
iter 100 value 79.854636
final  value 79.854636 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.522492 
iter  10 value 94.455113
iter  20 value 93.754798
iter  30 value 93.592165
iter  40 value 91.407931
iter  50 value 85.746519
iter  60 value 84.765645
iter  70 value 81.667605
iter  80 value 81.241250
iter  90 value 80.722085
iter 100 value 79.858354
final  value 79.858354 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.098735 
iter  10 value 94.487192
iter  20 value 86.188314
iter  30 value 86.067941
iter  40 value 85.230351
iter  50 value 84.775714
iter  60 value 84.705032
iter  70 value 84.373724
iter  80 value 83.087137
iter  90 value 81.504377
iter 100 value 80.930839
final  value 80.930839 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 147.224298 
iter  10 value 94.522290
iter  20 value 87.731291
iter  30 value 87.369880
iter  40 value 87.129440
iter  50 value 84.592454
iter  60 value 82.931447
iter  70 value 82.213855
iter  80 value 81.441272
iter  90 value 80.312020
iter 100 value 79.972084
final  value 79.972084 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.849842 
iter  10 value 94.321940
iter  20 value 86.855003
iter  30 value 86.018632
iter  40 value 84.846830
iter  50 value 83.377096
iter  60 value 82.550537
iter  70 value 82.075224
iter  80 value 81.691056
iter  90 value 81.384132
iter 100 value 81.250375
final  value 81.250375 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.101814 
iter  10 value 96.225124
iter  20 value 87.770927
iter  30 value 87.506840
iter  40 value 87.300210
iter  50 value 86.198699
iter  60 value 84.330849
iter  70 value 83.925363
iter  80 value 83.510824
iter  90 value 82.246319
iter 100 value 81.805242
final  value 81.805242 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.495352 
iter  10 value 94.590763
iter  20 value 94.388531
iter  30 value 92.596184
iter  40 value 90.748167
iter  50 value 89.686355
iter  60 value 86.158920
iter  70 value 83.415617
iter  80 value 81.052860
iter  90 value 80.527792
iter 100 value 79.950017
final  value 79.950017 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.501445 
iter  10 value 94.422785
iter  20 value 93.716315
iter  30 value 92.667641
iter  40 value 88.772770
iter  50 value 84.344614
iter  60 value 82.094022
iter  70 value 81.144069
iter  80 value 80.762437
iter  90 value 80.182300
iter 100 value 80.076335
final  value 80.076335 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.598419 
iter  10 value 94.486108
final  value 94.484217 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.172929 
iter  10 value 94.484421
iter  20 value 93.663061
final  value 93.660217 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.087937 
iter  10 value 94.468440
iter  20 value 94.457073
iter  30 value 89.430311
iter  40 value 89.414719
iter  50 value 89.373217
final  value 89.364685 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.240418 
iter  10 value 94.485862
iter  20 value 94.478156
iter  30 value 93.659765
final  value 93.659565 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.052610 
iter  10 value 94.485938
iter  20 value 94.484269
final  value 94.484217 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.959282 
iter  10 value 94.471307
iter  20 value 94.449302
iter  30 value 90.425904
iter  40 value 90.306852
iter  50 value 90.059145
iter  60 value 83.016391
iter  70 value 81.265316
iter  80 value 79.854988
iter  90 value 79.205672
iter 100 value 78.413545
final  value 78.413545 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.931133 
iter  10 value 94.471354
iter  20 value 94.124189
iter  30 value 87.652263
iter  40 value 87.604880
final  value 87.604846 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.899756 
iter  10 value 94.489005
iter  20 value 94.427992
iter  30 value 88.051120
iter  40 value 86.169890
iter  50 value 86.158438
iter  60 value 86.156450
iter  70 value 83.849118
iter  80 value 82.370602
iter  90 value 80.859763
iter 100 value 80.701711
final  value 80.701711 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.869341 
iter  10 value 94.471344
iter  20 value 91.958781
iter  30 value 87.288890
iter  40 value 87.017030
iter  50 value 86.925444
iter  60 value 86.925350
final  value 86.925347 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.622781 
iter  10 value 94.489493
iter  20 value 94.473297
iter  30 value 94.143859
iter  40 value 92.740288
iter  50 value 83.244806
iter  60 value 83.209653
iter  70 value 83.209594
final  value 83.209580 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.778927 
iter  10 value 94.474966
iter  20 value 94.428290
iter  30 value 89.061960
iter  40 value 87.315793
iter  50 value 87.315597
iter  60 value 86.989553
iter  70 value 86.988022
final  value 86.987978 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.156471 
iter  10 value 94.492227
iter  20 value 94.180764
iter  30 value 89.458810
iter  40 value 89.458535
iter  50 value 88.817477
final  value 88.556755 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.355097 
iter  10 value 94.492512
iter  20 value 94.477432
iter  30 value 94.474740
iter  40 value 94.392037
iter  50 value 87.731852
iter  60 value 87.097547
iter  70 value 86.267725
iter  80 value 80.956981
iter  90 value 80.341127
iter 100 value 79.044032
final  value 79.044032 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.563778 
iter  10 value 93.576334
iter  20 value 93.569045
iter  30 value 93.530977
iter  40 value 93.525869
iter  50 value 93.509636
iter  60 value 93.498571
iter  70 value 93.497979
iter  70 value 93.497978
iter  70 value 93.497978
final  value 93.497978 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.727303 
iter  10 value 94.475002
iter  20 value 94.467811
iter  30 value 94.117194
iter  40 value 93.230823
iter  50 value 85.860357
iter  60 value 84.855295
iter  70 value 84.695441
iter  80 value 84.443671
iter  90 value 84.430519
iter 100 value 84.166132
final  value 84.166132 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.278927 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.980681 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.439884 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.078297 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.738989 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.333056 
iter  10 value 93.102865
final  value 93.102857 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.848456 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.332108 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.023060 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.378031 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.836149 
iter  10 value 94.339035
iter  20 value 85.696099
iter  30 value 84.863506
final  value 84.863492 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.720230 
final  value 94.354285 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.050217 
iter  10 value 88.627358
iter  20 value 87.845115
iter  30 value 87.645837
iter  40 value 87.623477
iter  50 value 87.607681
iter  60 value 87.568930
final  value 87.568894 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.808222 
iter  10 value 94.484863
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.148493 
iter  10 value 94.467136
final  value 94.466824 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.860943 
iter  10 value 94.472859
iter  20 value 92.776884
iter  30 value 90.268266
iter  40 value 86.757029
iter  50 value 83.415256
iter  60 value 83.228550
iter  70 value 83.117250
final  value 83.116834 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.270208 
iter  10 value 94.488547
iter  20 value 94.367609
iter  30 value 94.319180
iter  40 value 93.466572
iter  50 value 83.451535
iter  60 value 83.123021
iter  70 value 82.733218
iter  80 value 81.866308
iter  90 value 81.482849
iter 100 value 81.363006
final  value 81.363006 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.965434 
iter  10 value 94.488459
iter  20 value 87.860849
iter  30 value 86.539313
iter  40 value 83.603883
iter  50 value 83.153162
iter  60 value 83.122776
iter  70 value 83.110800
final  value 83.110798 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.998140 
iter  10 value 93.548659
iter  20 value 87.492729
iter  30 value 86.570213
iter  40 value 84.089157
iter  50 value 81.651636
iter  60 value 81.169840
iter  70 value 80.983008
final  value 80.981893 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.295608 
iter  10 value 94.446033
iter  20 value 88.744938
iter  30 value 84.430884
iter  40 value 83.788897
iter  50 value 83.316402
iter  60 value 83.168790
final  value 83.168722 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.654309 
iter  10 value 90.866609
iter  20 value 87.106909
iter  30 value 85.810555
iter  40 value 85.454916
iter  50 value 85.019464
iter  60 value 84.550595
iter  70 value 84.366579
iter  80 value 82.129964
iter  90 value 80.681281
iter 100 value 79.665823
final  value 79.665823 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.307739 
iter  10 value 94.420197
iter  20 value 86.458387
iter  30 value 86.080768
iter  40 value 83.854779
iter  50 value 83.557478
iter  60 value 83.231810
iter  70 value 81.838510
iter  80 value 81.001314
iter  90 value 80.860809
iter 100 value 80.770755
final  value 80.770755 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.531606 
iter  10 value 87.904047
iter  20 value 84.776895
iter  30 value 84.122369
iter  40 value 83.751903
iter  50 value 82.154141
iter  60 value 81.589471
iter  70 value 81.322325
iter  80 value 80.576307
iter  90 value 80.283259
iter 100 value 79.948789
final  value 79.948789 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.728058 
iter  10 value 94.356338
iter  20 value 87.304877
iter  30 value 83.876675
iter  40 value 82.939306
iter  50 value 82.752907
iter  60 value 82.624550
iter  70 value 82.447497
iter  80 value 82.417450
iter  90 value 82.334428
iter 100 value 81.775394
final  value 81.775394 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.925042 
iter  10 value 94.324042
iter  20 value 87.413123
iter  30 value 80.844015
iter  40 value 80.158749
iter  50 value 80.021882
iter  60 value 79.841651
iter  70 value 79.799610
iter  80 value 79.729252
iter  90 value 79.600102
iter 100 value 79.476667
final  value 79.476667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.846938 
iter  10 value 94.747374
iter  20 value 90.840921
iter  30 value 89.140615
iter  40 value 87.415098
iter  50 value 85.067695
iter  60 value 82.825595
iter  70 value 81.849599
iter  80 value 81.456442
iter  90 value 80.322229
iter 100 value 80.152980
final  value 80.152980 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.222548 
iter  10 value 94.722889
iter  20 value 93.950949
iter  30 value 87.090767
iter  40 value 83.697851
iter  50 value 83.352498
iter  60 value 82.731852
iter  70 value 82.409929
iter  80 value 82.171688
iter  90 value 80.869570
iter 100 value 80.297949
final  value 80.297949 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.104703 
iter  10 value 94.733284
iter  20 value 88.449261
iter  30 value 85.417065
iter  40 value 83.131810
iter  50 value 81.381710
iter  60 value 80.599015
iter  70 value 80.350221
iter  80 value 79.975239
iter  90 value 79.543628
iter 100 value 79.401411
final  value 79.401411 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.686396 
iter  10 value 95.104567
iter  20 value 87.974957
iter  30 value 86.448784
iter  40 value 84.515653
iter  50 value 82.780589
iter  60 value 81.829281
iter  70 value 81.381744
iter  80 value 80.998023
iter  90 value 80.557883
iter 100 value 79.815630
final  value 79.815630 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.901290 
iter  10 value 95.007108
iter  20 value 88.574528
iter  30 value 83.965943
iter  40 value 81.770453
iter  50 value 81.031213
iter  60 value 80.480815
iter  70 value 80.226609
iter  80 value 80.117105
iter  90 value 79.980522
iter 100 value 79.745378
final  value 79.745378 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.658064 
final  value 94.468429 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.374285 
iter  10 value 94.485823
iter  20 value 94.484220
final  value 94.484215 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.134801 
final  value 94.485855 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.038747 
final  value 94.486081 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.703195 
iter  10 value 94.486000
iter  20 value 94.484224
final  value 94.484213 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.948591 
iter  10 value 94.488485
iter  20 value 88.459430
iter  30 value 87.656771
iter  40 value 87.464269
iter  50 value 85.274891
iter  60 value 85.272187
iter  60 value 85.272186
iter  60 value 85.272186
final  value 85.272186 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.548192 
iter  10 value 94.489628
iter  20 value 94.459165
iter  30 value 88.514724
iter  40 value 87.035750
iter  50 value 85.120784
iter  60 value 84.245229
iter  70 value 79.670202
iter  80 value 79.557331
iter  90 value 79.537981
iter 100 value 79.518958
final  value 79.518958 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.854284 
iter  10 value 94.485080
iter  20 value 83.732966
iter  30 value 82.935107
iter  40 value 81.802435
iter  50 value 81.088156
iter  60 value 80.938070
iter  70 value 80.937474
iter  80 value 80.934859
iter  90 value 80.934421
final  value 80.934213 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.932386 
iter  10 value 94.488930
iter  20 value 86.601464
final  value 86.564633 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.420202 
iter  10 value 92.943489
iter  20 value 92.902120
iter  30 value 92.901082
iter  40 value 92.889857
iter  50 value 92.859991
iter  60 value 92.858803
iter  70 value 92.822353
iter  80 value 92.821596
iter  90 value 92.746904
iter 100 value 92.745347
final  value 92.745347 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.732063 
iter  10 value 94.492960
iter  20 value 94.487925
iter  30 value 94.046517
iter  40 value 86.830355
iter  50 value 86.655747
final  value 86.655441 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.954360 
iter  10 value 94.491519
iter  20 value 94.346100
iter  30 value 94.319931
iter  40 value 89.212768
iter  50 value 85.650560
iter  60 value 85.548602
iter  70 value 82.590417
iter  80 value 82.515206
iter  90 value 82.511664
final  value 82.511376 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.659156 
iter  10 value 92.499043
iter  20 value 83.675349
iter  30 value 83.646985
iter  40 value 83.549845
iter  50 value 83.077348
iter  60 value 83.046412
iter  70 value 83.041671
iter  80 value 83.018609
iter  90 value 82.983529
iter 100 value 82.983067
final  value 82.983067 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.393261 
iter  10 value 92.228905
iter  20 value 88.814932
iter  30 value 84.751806
iter  40 value 84.527213
iter  50 value 84.521886
iter  60 value 84.456818
iter  70 value 83.910472
iter  80 value 83.578910
iter  90 value 83.194844
iter 100 value 83.194601
final  value 83.194601 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.843964 
iter  10 value 83.498354
iter  20 value 82.747230
iter  30 value 82.651608
iter  40 value 82.649441
iter  50 value 82.645898
iter  60 value 82.220504
iter  70 value 82.095790
iter  80 value 81.531672
final  value 81.531627 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.206455 
iter  10 value 92.971267
final  value 92.971247 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.621685 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.355160 
iter  10 value 93.672975
final  value 93.672973 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.188349 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.010546 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.011140 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.346389 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.127014 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.816080 
iter  10 value 93.604547
final  value 93.604521 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.632979 
final  value 93.604520 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.616430 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.599592 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.653869 
final  value 94.050155 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.350490 
iter  10 value 93.712587
iter  20 value 86.629372
iter  30 value 86.025525
final  value 86.013413 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.367978 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.874436 
iter  10 value 94.072200
iter  20 value 94.056725
iter  30 value 93.890864
iter  40 value 92.839557
iter  50 value 92.756022
iter  60 value 92.572164
iter  70 value 86.098559
iter  80 value 84.503743
iter  90 value 82.734641
iter 100 value 82.476009
final  value 82.476009 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.607038 
iter  10 value 94.064445
iter  20 value 94.022625
iter  30 value 88.790151
iter  40 value 87.944814
iter  50 value 85.578746
iter  60 value 84.011311
iter  70 value 83.849482
iter  80 value 83.848061
iter  90 value 83.845653
iter  90 value 83.845653
iter  90 value 83.845653
final  value 83.845653 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.373193 
iter  10 value 93.833226
iter  20 value 87.639512
iter  30 value 87.223420
iter  40 value 86.513183
iter  50 value 84.951980
iter  60 value 84.817403
iter  70 value 84.804033
iter  80 value 84.801413
final  value 84.801410 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.746486 
iter  10 value 94.056711
iter  20 value 93.991055
iter  30 value 91.965775
iter  40 value 91.394526
iter  50 value 90.897120
iter  60 value 86.367915
iter  70 value 84.459507
iter  80 value 83.397039
iter  90 value 83.170785
iter 100 value 82.833339
final  value 82.833339 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.795985 
iter  10 value 94.036064
iter  20 value 93.240494
iter  30 value 93.209924
iter  40 value 92.819724
iter  50 value 87.897415
iter  60 value 86.748375
iter  70 value 84.597580
iter  80 value 84.279405
iter  90 value 83.628177
iter 100 value 83.445767
final  value 83.445767 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 129.977301 
iter  10 value 94.111883
iter  20 value 86.968685
iter  30 value 85.690435
iter  40 value 85.376492
iter  50 value 84.928932
iter  60 value 83.530564
iter  70 value 82.446140
iter  80 value 81.782575
iter  90 value 81.494536
iter 100 value 81.345675
final  value 81.345675 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.434591 
iter  10 value 93.831021
iter  20 value 87.228089
iter  30 value 85.567654
iter  40 value 85.235557
iter  50 value 85.022572
iter  60 value 84.249246
iter  70 value 84.208970
iter  80 value 83.891457
iter  90 value 82.925243
iter 100 value 82.507987
final  value 82.507987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.962320 
iter  10 value 93.818077
iter  20 value 93.494426
iter  30 value 87.957140
iter  40 value 84.773656
iter  50 value 83.186218
iter  60 value 82.811460
iter  70 value 82.560015
iter  80 value 81.967709
iter  90 value 81.587059
iter 100 value 81.080466
final  value 81.080466 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.603282 
iter  10 value 93.871456
iter  20 value 87.823895
iter  30 value 85.503816
iter  40 value 83.743086
iter  50 value 82.995928
iter  60 value 82.359534
iter  70 value 81.952387
iter  80 value 81.661707
iter  90 value 81.562198
iter 100 value 81.538893
final  value 81.538893 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.206610 
iter  10 value 94.166224
iter  20 value 91.572506
iter  30 value 88.720377
iter  40 value 86.062682
iter  50 value 85.795651
iter  60 value 83.553560
iter  70 value 82.956151
iter  80 value 81.465600
iter  90 value 81.294868
iter 100 value 81.279134
final  value 81.279134 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.458523 
iter  10 value 93.988613
iter  20 value 93.194937
iter  30 value 91.227364
iter  40 value 90.527226
iter  50 value 87.679374
iter  60 value 86.445834
iter  70 value 84.978692
iter  80 value 83.357574
iter  90 value 82.309730
iter 100 value 81.363416
final  value 81.363416 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.235318 
iter  10 value 94.404686
iter  20 value 94.062017
iter  30 value 89.907521
iter  40 value 86.646988
iter  50 value 86.366870
iter  60 value 85.773679
iter  70 value 83.974186
iter  80 value 83.068351
iter  90 value 82.222167
iter 100 value 81.527197
final  value 81.527197 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.140190 
iter  10 value 93.940873
iter  20 value 90.392930
iter  30 value 86.438758
iter  40 value 83.579666
iter  50 value 82.576156
iter  60 value 82.033927
iter  70 value 81.821875
iter  80 value 81.388226
iter  90 value 81.115266
iter 100 value 81.029221
final  value 81.029221 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.259354 
iter  10 value 94.248849
iter  20 value 86.996356
iter  30 value 86.636046
iter  40 value 86.437541
iter  50 value 85.666826
iter  60 value 85.265769
iter  70 value 84.033949
iter  80 value 82.990707
iter  90 value 81.908936
iter 100 value 81.472498
final  value 81.472498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.136209 
iter  10 value 93.856591
iter  20 value 88.232869
iter  30 value 86.923470
iter  40 value 85.981480
iter  50 value 85.821812
iter  60 value 85.379037
iter  70 value 84.739375
iter  80 value 83.179120
iter  90 value 81.917414
iter 100 value 81.431937
final  value 81.431937 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.866539 
final  value 94.054569 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.146007 
iter  10 value 94.054691
iter  20 value 94.044892
iter  30 value 90.545399
final  value 90.459627 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.558451 
final  value 94.054642 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.933510 
final  value 94.054467 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.811994 
final  value 94.054752 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.128904 
iter  10 value 94.057721
iter  20 value 94.052782
iter  30 value 86.246768
iter  40 value 85.460344
iter  50 value 85.451696
iter  60 value 85.322765
iter  70 value 85.316103
iter  80 value 83.321676
iter  90 value 82.090998
iter 100 value 81.935483
final  value 81.935483 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.862715 
iter  10 value 94.057976
iter  20 value 94.053199
final  value 94.053100 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.896401 
iter  10 value 94.057945
iter  20 value 93.920402
iter  30 value 90.192157
iter  40 value 87.877980
final  value 87.877977 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.484463 
iter  10 value 93.920640
iter  20 value 93.744901
iter  30 value 90.623660
iter  40 value 90.543961
iter  50 value 90.149408
iter  60 value 90.144001
iter  60 value 90.144001
final  value 90.144001 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.450056 
iter  10 value 93.920533
iter  20 value 93.915942
iter  30 value 91.956845
iter  40 value 84.184836
iter  50 value 83.461725
iter  60 value 83.388299
iter  70 value 83.372685
iter  70 value 83.372685
iter  70 value 83.372684
final  value 83.372684 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.713206 
iter  10 value 93.912401
iter  20 value 85.818479
iter  30 value 85.182343
iter  40 value 85.174725
iter  40 value 85.174725
final  value 85.174725 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.379774 
iter  10 value 93.396968
iter  20 value 92.883352
iter  30 value 92.882188
iter  40 value 92.881055
iter  50 value 92.820951
iter  60 value 86.977279
iter  70 value 84.570531
iter  80 value 83.823558
iter  90 value 83.480133
iter 100 value 83.477773
final  value 83.477773 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.630010 
iter  10 value 93.925828
iter  20 value 93.696209
iter  30 value 86.792653
iter  40 value 85.928323
iter  50 value 83.857905
iter  60 value 83.657243
iter  70 value 83.649370
iter  80 value 83.648146
iter  90 value 83.646518
iter 100 value 82.925531
final  value 82.925531 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.930569 
iter  10 value 93.923521
iter  20 value 93.731037
iter  30 value 85.045096
iter  40 value 82.335935
iter  50 value 82.176747
final  value 82.175712 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.447747 
iter  10 value 94.064671
iter  20 value 93.815083
iter  30 value 87.314826
iter  40 value 82.534334
iter  50 value 82.486342
iter  60 value 82.473808
iter  70 value 82.469122
iter  80 value 82.468048
iter  90 value 82.467396
iter 100 value 82.466930
final  value 82.466930 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.300086 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.614879 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.584660 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.592699 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.707182 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.380926 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.034007 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.161717 
iter  10 value 93.494014
final  value 93.485037 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.260449 
iter  10 value 93.772980
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.928157 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.667999 
iter  10 value 93.772978
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.096702 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.575964 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.709916 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.844663 
final  value 94.409357 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.918738 
iter  10 value 94.475861
iter  20 value 94.142035
iter  30 value 94.008314
iter  40 value 93.997230
iter  50 value 93.982057
iter  60 value 93.453573
iter  70 value 89.066437
iter  80 value 85.524704
iter  90 value 83.958282
iter 100 value 82.752220
final  value 82.752220 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.732106 
iter  10 value 93.997851
iter  20 value 93.117665
iter  30 value 90.472204
iter  40 value 86.347998
iter  50 value 85.549269
iter  60 value 84.504323
iter  70 value 83.314957
iter  80 value 83.227969
iter  90 value 83.217475
iter 100 value 83.199949
final  value 83.199949 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.375819 
iter  10 value 94.451755
iter  20 value 91.618767
iter  30 value 90.333167
iter  40 value 86.648213
iter  50 value 84.595708
iter  60 value 83.323973
iter  70 value 82.618920
iter  80 value 82.403895
iter  90 value 82.403617
final  value 82.403592 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.344583 
iter  10 value 94.467291
iter  20 value 93.768664
iter  30 value 93.751587
iter  40 value 93.749696
iter  50 value 93.287881
iter  60 value 90.398175
iter  70 value 85.759000
iter  80 value 83.683494
iter  90 value 83.371543
iter 100 value 83.050294
final  value 83.050294 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.668973 
iter  10 value 94.475498
iter  20 value 94.029372
iter  30 value 93.991866
iter  40 value 93.980468
iter  50 value 93.044731
iter  60 value 87.771674
iter  70 value 84.600793
iter  80 value 84.280878
iter  90 value 83.492558
iter 100 value 83.215411
final  value 83.215411 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 116.544539 
iter  10 value 94.738282
iter  20 value 93.980652
iter  30 value 93.943050
iter  40 value 87.831951
iter  50 value 85.972527
iter  60 value 85.162526
iter  70 value 82.883366
iter  80 value 82.223272
iter  90 value 81.848732
iter 100 value 81.653198
final  value 81.653198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.464031 
iter  10 value 94.461313
iter  20 value 88.393379
iter  30 value 87.941631
iter  40 value 87.233912
iter  50 value 86.869909
iter  60 value 86.675825
iter  70 value 84.388034
iter  80 value 82.773501
iter  90 value 81.725987
iter 100 value 81.413176
final  value 81.413176 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.302751 
iter  10 value 94.924682
iter  20 value 90.675216
iter  30 value 87.266723
iter  40 value 85.695028
iter  50 value 84.961059
iter  60 value 84.264392
iter  70 value 83.873528
iter  80 value 83.011151
iter  90 value 82.590800
iter 100 value 82.554585
final  value 82.554585 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.401682 
iter  10 value 93.954934
iter  20 value 88.870682
iter  30 value 88.279703
iter  40 value 85.665521
iter  50 value 83.957783
iter  60 value 83.887934
iter  70 value 83.822705
iter  80 value 83.763544
iter  90 value 83.147315
iter 100 value 82.085156
final  value 82.085156 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.353578 
iter  10 value 94.438615
iter  20 value 87.713433
iter  30 value 86.495346
iter  40 value 84.608544
iter  50 value 81.908083
iter  60 value 81.511977
iter  70 value 81.392271
iter  80 value 81.348921
iter  90 value 81.317088
iter 100 value 81.271500
final  value 81.271500 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.524918 
iter  10 value 94.698386
iter  20 value 93.840607
iter  30 value 90.710750
iter  40 value 85.692513
iter  50 value 82.980271
iter  60 value 82.469408
iter  70 value 81.781258
iter  80 value 81.265212
iter  90 value 81.132735
iter 100 value 80.800924
final  value 80.800924 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.782255 
iter  10 value 94.570652
iter  20 value 89.448185
iter  30 value 87.799922
iter  40 value 85.374998
iter  50 value 84.845912
iter  60 value 84.370401
iter  70 value 84.003291
iter  80 value 83.544084
iter  90 value 83.083825
iter 100 value 81.911364
final  value 81.911364 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.592913 
iter  10 value 94.584681
iter  20 value 88.919294
iter  30 value 86.164436
iter  40 value 85.450053
iter  50 value 84.762137
iter  60 value 84.237024
iter  70 value 83.489048
iter  80 value 82.931313
iter  90 value 82.270814
iter 100 value 81.433129
final  value 81.433129 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.008464 
iter  10 value 94.163881
iter  20 value 90.725733
iter  30 value 88.750609
iter  40 value 86.188327
iter  50 value 82.660284
iter  60 value 81.677770
iter  70 value 81.459586
iter  80 value 81.182434
iter  90 value 81.134822
iter 100 value 81.104432
final  value 81.104432 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.572681 
iter  10 value 95.409142
iter  20 value 89.223209
iter  30 value 85.863280
iter  40 value 85.202034
iter  50 value 83.373814
iter  60 value 82.261418
iter  70 value 81.983140
iter  80 value 81.638296
iter  90 value 81.528913
iter 100 value 81.237667
final  value 81.237667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.886343 
final  value 94.485652 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.727520 
final  value 94.485661 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.671085 
iter  10 value 87.037515
iter  20 value 84.758935
iter  30 value 84.739933
iter  40 value 84.739685
iter  50 value 84.738177
iter  60 value 84.486632
iter  70 value 84.465964
final  value 84.465642 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.539138 
final  value 94.486025 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.511199 
iter  10 value 93.774827
iter  20 value 93.773856
iter  30 value 93.568485
iter  40 value 89.253486
final  value 89.165851 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.193021 
iter  10 value 93.778005
iter  20 value 93.776674
iter  30 value 93.666346
iter  40 value 92.585315
iter  50 value 90.553567
iter  60 value 90.540168
iter  70 value 90.457696
iter  80 value 89.989590
iter  90 value 89.874296
iter 100 value 89.874187
final  value 89.874187 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.090525 
iter  10 value 94.280513
iter  20 value 94.276705
iter  30 value 94.276466
iter  40 value 93.739926
iter  50 value 93.637988
iter  60 value 93.551572
final  value 93.541163 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.534149 
iter  10 value 94.488413
iter  20 value 94.275878
iter  30 value 93.541812
final  value 93.541803 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.709018 
iter  10 value 94.489157
iter  20 value 94.484882
iter  30 value 93.811946
final  value 93.773419 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.955147 
iter  10 value 94.488898
iter  20 value 94.484235
iter  20 value 94.484235
iter  30 value 89.671108
iter  40 value 85.694788
final  value 85.694688 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.327435 
iter  10 value 93.782020
iter  20 value 93.774658
iter  30 value 88.965115
iter  40 value 87.000647
iter  50 value 85.896497
iter  60 value 84.783002
iter  70 value 82.258187
iter  80 value 81.755225
iter  90 value 81.576072
iter 100 value 81.265897
final  value 81.265897 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.290511 
iter  10 value 94.490454
iter  20 value 94.167900
iter  30 value 94.166812
iter  40 value 93.639068
final  value 93.639038 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.376709 
iter  10 value 94.491730
final  value 94.484865 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.003937 
iter  10 value 93.754889
iter  20 value 93.749391
iter  30 value 93.696455
iter  40 value 91.907283
final  value 91.889233 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.729790 
iter  10 value 93.781812
iter  20 value 93.775161
iter  30 value 93.555843
iter  40 value 91.843508
iter  50 value 91.670935
iter  60 value 91.449632
iter  70 value 90.296614
iter  80 value 90.293097
iter  90 value 87.359871
iter 100 value 87.335861
final  value 87.335861 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 163.293327 
iter  10 value 117.961057
iter  20 value 114.125194
iter  30 value 105.363858
iter  40 value 104.371406
iter  50 value 102.492957
iter  60 value 101.714780
iter  70 value 101.212558
iter  80 value 101.005547
iter  90 value 100.974316
iter 100 value 100.830676
final  value 100.830676 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 141.748171 
iter  10 value 116.853608
iter  20 value 110.857185
iter  30 value 109.249451
iter  40 value 108.330681
iter  50 value 103.531903
iter  60 value 101.924597
iter  70 value 101.461156
iter  80 value 101.343725
iter  90 value 101.308248
iter 100 value 101.043472
final  value 101.043472 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 140.282548 
iter  10 value 118.148816
iter  20 value 108.318204
iter  30 value 107.339594
iter  40 value 106.851947
iter  50 value 103.009711
iter  60 value 101.856365
iter  70 value 101.396744
iter  80 value 101.251679
iter  90 value 101.180921
iter 100 value 101.143034
final  value 101.143034 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 135.312353 
iter  10 value 117.879154
iter  20 value 117.507370
iter  30 value 107.712063
iter  40 value 104.260194
iter  50 value 104.089663
iter  60 value 103.158818
iter  70 value 101.978376
iter  80 value 101.709165
iter  90 value 101.363703
iter 100 value 101.235204
final  value 101.235204 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 150.686970 
iter  10 value 118.336102
iter  20 value 114.785915
iter  30 value 114.626292
iter  40 value 110.058850
iter  50 value 106.839732
iter  60 value 105.204406
iter  70 value 104.795057
iter  80 value 103.899906
iter  90 value 102.646657
iter 100 value 102.517104
final  value 102.517104 
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 01:40:30 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 
 40.889   1.134 153.993