##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-11-04 r88984)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
  Code: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 FALSE, filename = "plots.pdf")
  Docs: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 TRUE, filename = "plots.pdf")
  Mismatches in argument default values:
    Name: 'plots' Code: FALSE Docs: TRUE

* 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
FSmethod      19.034  0.944  20.628
corr_plot     18.914  0.919  20.387
var_imp       18.574  0.962  20.645
pred_ensembel  6.496  0.143   6.341
enrichfindP    0.194  0.038  14.209
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 WARNING, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.1’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 102.027726 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.082691 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.502686 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.671350 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.707251 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.426489 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.815241 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.547827 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.657945 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.975917 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.841110 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.148012 
final  value 94.046703 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.442333 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.707980 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.989922 
iter  10 value 94.484212
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.317164 
iter  10 value 94.334272
iter  20 value 93.132516
iter  30 value 93.071179
iter  40 value 88.640262
iter  50 value 87.549763
iter  60 value 87.075051
iter  70 value 87.055554
iter  80 value 86.986937
iter  90 value 85.088545
iter 100 value 84.380337
final  value 84.380337 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.612574 
iter  10 value 94.602638
iter  20 value 94.485599
iter  30 value 89.126833
iter  40 value 88.427751
iter  50 value 85.984347
iter  60 value 85.290585
iter  70 value 85.201379
final  value 85.201352 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.696791 
iter  10 value 94.477966
iter  20 value 90.232387
iter  30 value 88.802958
iter  40 value 88.568758
iter  50 value 87.805628
iter  60 value 85.857036
iter  70 value 85.409250
iter  80 value 85.058035
iter  90 value 83.519557
iter 100 value 82.887497
final  value 82.887497 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.912545 
iter  10 value 90.305753
iter  20 value 85.856111
iter  30 value 85.540801
iter  40 value 84.259764
iter  50 value 84.139046
iter  60 value 84.033137
iter  70 value 83.893008
iter  80 value 83.886749
iter  90 value 83.831492
iter 100 value 83.557189
final  value 83.557189 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.167281 
iter  10 value 93.960029
iter  20 value 92.859141
iter  30 value 84.962761
iter  40 value 84.614106
iter  50 value 84.586862
iter  60 value 84.476522
iter  70 value 84.382867
iter  80 value 84.363666
final  value 84.363656 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.443874 
iter  10 value 94.408661
iter  20 value 90.775827
iter  30 value 86.846839
iter  40 value 84.757732
iter  50 value 84.195216
iter  60 value 83.669718
iter  70 value 82.825880
iter  80 value 82.132281
iter  90 value 81.884479
iter 100 value 81.851602
final  value 81.851602 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.722848 
iter  10 value 94.568547
iter  20 value 94.504965
iter  30 value 94.369247
iter  40 value 89.189318
iter  50 value 86.928699
iter  60 value 85.875854
iter  70 value 84.469321
iter  80 value 84.341040
iter  90 value 84.298717
iter 100 value 84.075640
final  value 84.075640 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.140254 
iter  10 value 94.488303
iter  20 value 94.293368
iter  30 value 90.947008
iter  40 value 90.333859
iter  50 value 84.516861
iter  60 value 83.634358
iter  70 value 83.486498
iter  80 value 83.457890
iter  90 value 83.278256
iter 100 value 83.009442
final  value 83.009442 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.468022 
iter  10 value 94.488874
iter  20 value 94.369428
iter  30 value 89.476451
iter  40 value 86.705036
iter  50 value 85.461139
iter  60 value 82.926926
iter  70 value 82.337133
iter  80 value 82.008645
iter  90 value 81.620847
iter 100 value 81.525314
final  value 81.525314 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.653150 
iter  10 value 89.917754
iter  20 value 85.246032
iter  30 value 84.875199
iter  40 value 84.460971
iter  50 value 84.135059
iter  60 value 83.937019
iter  70 value 83.850115
iter  80 value 83.505081
iter  90 value 82.555902
iter 100 value 82.191544
final  value 82.191544 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.477997 
iter  10 value 94.801514
iter  20 value 94.439882
iter  30 value 87.739826
iter  40 value 86.431125
iter  50 value 85.543943
iter  60 value 84.099813
iter  70 value 82.778942
iter  80 value 82.595828
iter  90 value 82.472424
iter 100 value 81.930953
final  value 81.930953 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 144.692901 
iter  10 value 94.502130
iter  20 value 88.428631
iter  30 value 85.858950
iter  40 value 85.563347
iter  50 value 85.013561
iter  60 value 83.737587
iter  70 value 82.904683
iter  80 value 82.330887
iter  90 value 82.197685
iter 100 value 81.748392
final  value 81.748392 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.924693 
iter  10 value 94.597883
iter  20 value 87.319380
iter  30 value 84.510271
iter  40 value 83.869237
iter  50 value 83.388118
iter  60 value 83.116390
iter  70 value 82.830378
iter  80 value 82.361031
iter  90 value 81.657309
iter 100 value 81.275480
final  value 81.275480 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.041761 
iter  10 value 94.445293
iter  20 value 87.028011
iter  30 value 85.681248
iter  40 value 85.115248
iter  50 value 84.318251
iter  60 value 83.565184
iter  70 value 83.154432
iter  80 value 82.351756
iter  90 value 81.887276
iter 100 value 81.428025
final  value 81.428025 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.844139 
iter  10 value 94.509419
iter  20 value 94.323646
iter  30 value 93.142361
iter  40 value 90.459492
iter  50 value 86.935301
iter  60 value 85.854427
iter  70 value 84.710164
iter  80 value 83.322859
iter  90 value 82.721504
iter 100 value 82.463875
final  value 82.463875 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.243275 
final  value 94.048458 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.255975 
final  value 94.485782 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.773272 
final  value 94.485689 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.880543 
final  value 94.485955 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.522290 
iter  10 value 94.277028
iter  20 value 94.275745
iter  30 value 94.275555
final  value 94.275537 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.353317 
iter  10 value 94.489362
iter  20 value 89.106120
iter  30 value 87.791117
iter  40 value 87.040900
iter  50 value 86.366083
iter  60 value 86.278915
iter  70 value 86.108820
iter  80 value 86.107356
final  value 86.106248 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.930085 
iter  10 value 94.280624
iter  20 value 94.276926
iter  30 value 90.748879
iter  40 value 86.653863
iter  50 value 85.934348
iter  60 value 85.913319
final  value 85.911091 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.814622 
iter  10 value 92.664399
iter  20 value 92.663507
iter  30 value 92.182704
iter  40 value 92.094570
iter  50 value 92.094313
iter  60 value 92.093367
iter  70 value 92.056985
iter  80 value 91.962476
iter  90 value 90.389293
iter 100 value 85.745593
final  value 85.745593 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.288668 
iter  10 value 94.485816
iter  20 value 94.428794
iter  30 value 93.899299
iter  40 value 93.860724
final  value 93.860632 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.486529 
iter  10 value 94.051946
iter  20 value 87.280956
final  value 86.864391 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.110519 
iter  10 value 94.492847
iter  20 value 94.484223
iter  30 value 85.273169
iter  40 value 85.197853
final  value 85.197320 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.716964 
iter  10 value 86.930948
iter  20 value 85.384756
iter  30 value 84.154301
iter  40 value 83.161996
iter  50 value 83.159970
iter  60 value 82.934009
iter  70 value 82.782691
iter  80 value 82.779955
iter  90 value 82.543735
iter 100 value 80.934647
final  value 80.934647 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.857714 
iter  10 value 94.490921
iter  20 value 94.470054
iter  30 value 86.786736
iter  40 value 86.229175
iter  50 value 86.184195
iter  60 value 86.183689
iter  70 value 86.080282
iter  80 value 84.054719
iter  90 value 83.362214
iter 100 value 83.306316
final  value 83.306316 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.531544 
iter  10 value 94.490323
iter  20 value 93.524012
iter  30 value 92.242580
iter  30 value 92.242579
final  value 92.242575 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.401268 
iter  10 value 94.283824
iter  20 value 94.276041
final  value 94.275550 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.570310 
iter  10 value 93.825846
final  value 93.809648 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.035458 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.040976 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.535160 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.217353 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.784190 
iter  10 value 89.478950
final  value 87.309035 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.719471 
final  value 94.484212 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.930739 
iter  10 value 93.614472
iter  20 value 93.394097
final  value 93.394090 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.850640 
iter  10 value 94.301132
iter  20 value 94.292215
final  value 94.292210 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.685972 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.308276 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.700243 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.980403 
final  value 94.317413 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.239918 
iter  10 value 94.102373
final  value 94.088890 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.218548 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.387876 
iter  10 value 94.489248
iter  20 value 90.687325
iter  30 value 87.555978
iter  40 value 86.810561
iter  50 value 86.622567
iter  60 value 82.283196
iter  70 value 81.244882
iter  80 value 81.175561
final  value 81.170276 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.941175 
iter  10 value 94.225267
iter  20 value 93.729262
iter  30 value 93.237425
iter  40 value 88.887147
iter  50 value 86.969977
iter  60 value 82.656311
iter  70 value 82.198400
iter  80 value 82.074567
final  value 82.074554 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.822969 
iter  10 value 94.795918
iter  20 value 94.467202
iter  30 value 90.751381
iter  40 value 87.927972
iter  50 value 87.492110
iter  60 value 87.083451
iter  70 value 83.072792
iter  80 value 81.258000
iter  90 value 79.811967
iter 100 value 79.257882
final  value 79.257882 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.034238 
iter  10 value 94.438194
iter  20 value 93.459443
iter  30 value 92.611056
iter  40 value 83.003879
iter  50 value 82.389691
iter  60 value 82.259163
iter  70 value 81.440959
iter  80 value 81.178345
final  value 81.170278 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.701697 
iter  10 value 94.486441
final  value 94.486424 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.163456 
iter  10 value 94.426931
iter  20 value 89.897554
iter  30 value 83.471562
iter  40 value 81.318039
iter  50 value 79.695371
iter  60 value 78.285390
iter  70 value 78.069587
iter  80 value 77.980964
iter  90 value 77.752184
iter 100 value 77.601929
final  value 77.601929 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.346894 
iter  10 value 95.281251
iter  20 value 93.691611
iter  30 value 90.118034
iter  40 value 88.174114
iter  50 value 86.549805
iter  60 value 85.913327
iter  70 value 85.281927
iter  80 value 83.590198
iter  90 value 80.971404
iter 100 value 79.539890
final  value 79.539890 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.335375 
iter  10 value 94.341120
iter  20 value 86.082768
iter  30 value 83.538236
iter  40 value 80.643190
iter  50 value 78.832212
iter  60 value 78.540623
iter  70 value 78.050824
iter  80 value 77.535927
iter  90 value 77.311396
iter 100 value 77.147025
final  value 77.147025 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.211345 
iter  10 value 94.080056
iter  20 value 86.904835
iter  30 value 86.473981
iter  40 value 84.220179
iter  50 value 82.698068
iter  60 value 82.022084
iter  70 value 80.301022
iter  80 value 79.608424
iter  90 value 78.579490
iter 100 value 78.359662
final  value 78.359662 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.623682 
iter  10 value 94.556989
iter  20 value 94.503546
iter  30 value 93.812814
iter  40 value 88.329244
iter  50 value 83.997701
iter  60 value 82.198680
iter  70 value 81.712997
iter  80 value 80.643227
iter  90 value 79.491364
iter 100 value 79.375825
final  value 79.375825 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 143.232212 
iter  10 value 94.863525
iter  20 value 85.398082
iter  30 value 82.951891
iter  40 value 81.461696
iter  50 value 80.436769
iter  60 value 80.053681
iter  70 value 79.182174
iter  80 value 77.726299
iter  90 value 77.234571
iter 100 value 77.152341
final  value 77.152341 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.528319 
iter  10 value 88.185539
iter  20 value 84.140506
iter  30 value 82.023113
iter  40 value 79.584348
iter  50 value 78.928096
iter  60 value 78.414996
iter  70 value 78.061368
iter  80 value 77.974674
iter  90 value 77.897200
iter 100 value 77.754991
final  value 77.754991 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.365985 
iter  10 value 94.310733
iter  20 value 83.953837
iter  30 value 82.481536
iter  40 value 82.000402
iter  50 value 79.785419
iter  60 value 78.917528
iter  70 value 78.695936
iter  80 value 77.907262
iter  90 value 77.692066
iter 100 value 77.653316
final  value 77.653316 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.822447 
iter  10 value 93.782253
iter  20 value 91.326871
iter  30 value 88.707649
iter  40 value 87.687238
iter  50 value 82.216011
iter  60 value 81.139914
iter  70 value 79.227818
iter  80 value 78.197657
iter  90 value 77.640750
iter 100 value 77.580309
final  value 77.580309 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.400887 
iter  10 value 95.846122
iter  20 value 91.797128
iter  30 value 87.739776
iter  40 value 86.921927
iter  50 value 86.313519
iter  60 value 85.991985
iter  70 value 81.788943
iter  80 value 81.191275
iter  90 value 81.106705
iter 100 value 80.955903
final  value 80.955903 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.688179 
final  value 94.485592 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.976155 
iter  10 value 94.356388
iter  20 value 94.355583
final  value 94.354665 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.675508 
iter  10 value 94.438504
iter  20 value 94.431843
iter  30 value 94.090228
final  value 94.090169 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.973967 
final  value 94.485781 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.645130 
final  value 94.485791 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.600999 
iter  10 value 94.488204
iter  20 value 94.365085
iter  30 value 94.354838
iter  40 value 94.354490
iter  50 value 85.638241
iter  60 value 81.922890
iter  70 value 81.905213
iter  80 value 81.877244
iter  90 value 81.875945
iter 100 value 81.875725
final  value 81.875725 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.070961 
iter  10 value 94.488876
iter  20 value 94.429305
iter  30 value 82.603150
iter  40 value 82.561968
iter  50 value 82.561739
iter  60 value 82.266947
iter  70 value 82.263526
iter  80 value 82.263021
iter  90 value 82.262813
iter 100 value 82.244899
final  value 82.244899 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.718187 
iter  10 value 94.491516
iter  20 value 94.128448
iter  30 value 93.661821
iter  40 value 93.659568
iter  40 value 93.659568
final  value 93.659565 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.709888 
iter  10 value 94.359969
iter  20 value 94.270433
iter  30 value 93.641684
iter  30 value 93.641683
iter  30 value 93.641683
final  value 93.641683 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.109960 
iter  10 value 94.489185
iter  20 value 94.295143
iter  30 value 93.667515
iter  40 value 93.584252
final  value 93.583688 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.178062 
iter  10 value 94.362512
iter  20 value 94.179227
iter  30 value 83.652039
iter  40 value 80.223789
iter  50 value 76.425360
iter  60 value 76.364112
iter  70 value 76.363481
iter  80 value 76.360720
iter  90 value 76.337263
iter 100 value 76.210648
final  value 76.210648 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.975284 
iter  10 value 94.172106
iter  20 value 94.170904
iter  30 value 94.166247
iter  40 value 87.212688
iter  50 value 81.009675
iter  60 value 80.549161
iter  70 value 80.526481
iter  80 value 80.181048
final  value 80.180936 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.101944 
iter  10 value 93.293844
iter  20 value 93.288535
iter  30 value 93.165045
iter  40 value 90.474301
iter  50 value 81.474562
iter  60 value 77.820241
iter  70 value 77.749635
iter  80 value 77.651451
iter  90 value 77.413359
final  value 77.412226 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.144362 
iter  10 value 94.320241
iter  20 value 94.313475
final  value 94.313034 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.026774 
iter  10 value 89.316418
iter  20 value 84.865343
iter  30 value 84.834263
iter  40 value 84.826574
iter  50 value 81.531607
iter  60 value 81.148778
iter  70 value 81.106799
iter  80 value 81.079120
iter  90 value 81.077500
iter 100 value 81.075146
final  value 81.075146 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.871437 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.105037 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.896831 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.872364 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.124084 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.109938 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.813072 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.454807 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.753186 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.913184 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.141244 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 132.007010 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.546877 
iter  10 value 93.257640
final  value 93.257143 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.227912 
iter  10 value 88.955492
iter  20 value 88.606087
final  value 88.606061 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.520223 
iter  10 value 94.038252
iter  10 value 94.038252
iter  10 value 94.038252
final  value 94.038252 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.876852 
iter  10 value 94.045824
iter  20 value 90.928887
iter  30 value 90.355314
iter  40 value 89.994427
iter  50 value 89.975240
final  value 89.974881 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.975882 
iter  10 value 93.408497
iter  20 value 86.883046
iter  30 value 86.124300
iter  40 value 85.986395
iter  50 value 85.891234
iter  60 value 85.229550
iter  70 value 85.041140
final  value 85.041118 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.956222 
iter  10 value 93.777288
iter  20 value 88.964587
iter  30 value 88.033862
iter  40 value 87.707454
iter  50 value 87.579633
iter  60 value 87.025179
iter  70 value 86.750053
iter  80 value 86.596504
iter  90 value 86.568088
final  value 86.568016 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.074475 
iter  10 value 93.776498
iter  20 value 87.020625
iter  30 value 86.058502
iter  40 value 85.427369
iter  50 value 85.099637
final  value 85.089405 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.360378 
iter  10 value 92.795410
iter  20 value 89.935131
iter  30 value 89.439360
iter  40 value 87.867472
iter  50 value 86.999551
iter  60 value 86.343392
iter  70 value 86.322943
iter  80 value 86.193038
final  value 86.182521 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.026337 
iter  10 value 94.138536
iter  20 value 93.661148
iter  30 value 90.066667
iter  40 value 86.738583
iter  50 value 85.360777
iter  60 value 84.098108
iter  70 value 83.720833
iter  80 value 83.441272
iter  90 value 83.266213
iter 100 value 83.063173
final  value 83.063173 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.262407 
iter  10 value 94.002171
iter  20 value 88.358126
iter  30 value 85.662790
iter  40 value 85.189659
iter  50 value 85.100669
iter  60 value 84.467688
iter  70 value 83.718074
iter  80 value 83.552965
iter  90 value 83.406607
iter 100 value 83.316074
final  value 83.316074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.783782 
iter  10 value 94.345264
iter  20 value 92.019392
iter  30 value 90.280811
iter  40 value 89.882972
iter  50 value 89.838120
iter  60 value 88.925531
iter  70 value 86.020244
iter  80 value 84.540773
iter  90 value 83.591953
iter 100 value 83.455393
final  value 83.455393 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.542596 
iter  10 value 94.057700
iter  20 value 88.655251
iter  30 value 87.687277
iter  40 value 84.283634
iter  50 value 83.484015
iter  60 value 82.480205
iter  70 value 82.204362
iter  80 value 82.152635
iter  90 value 82.121635
iter 100 value 82.082252
final  value 82.082252 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.091749 
iter  10 value 91.519368
iter  20 value 87.865501
iter  30 value 87.570479
iter  40 value 86.965451
iter  50 value 85.106464
iter  60 value 83.625068
iter  70 value 83.399573
iter  80 value 83.247160
iter  90 value 82.982877
iter 100 value 82.939694
final  value 82.939694 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 144.288766 
iter  10 value 95.567799
iter  20 value 94.064216
iter  30 value 91.034041
iter  40 value 90.613563
iter  50 value 88.271195
iter  60 value 87.165112
iter  70 value 82.989733
iter  80 value 82.002369
iter  90 value 81.460208
iter 100 value 81.336361
final  value 81.336361 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.274025 
iter  10 value 94.132785
iter  20 value 93.646222
iter  30 value 92.548478
iter  40 value 91.358801
iter  50 value 90.605839
iter  60 value 87.903796
iter  70 value 86.559641
iter  80 value 86.092820
iter  90 value 85.570094
iter 100 value 84.334876
final  value 84.334876 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.851038 
iter  10 value 95.283388
iter  20 value 93.283985
iter  30 value 92.421708
iter  40 value 91.735227
iter  50 value 88.278521
iter  60 value 84.782272
iter  70 value 84.184455
iter  80 value 83.829383
iter  90 value 83.160661
iter 100 value 82.765563
final  value 82.765563 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.444919 
iter  10 value 94.079341
iter  20 value 91.460429
iter  30 value 87.917805
iter  40 value 85.914667
iter  50 value 84.900718
iter  60 value 84.616219
iter  70 value 83.132297
iter  80 value 82.730025
iter  90 value 82.231844
iter 100 value 81.747009
final  value 81.747009 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.996046 
iter  10 value 93.345847
iter  20 value 90.976539
iter  30 value 89.823213
iter  40 value 85.765384
iter  50 value 84.937503
iter  60 value 83.653351
iter  70 value 83.180837
iter  80 value 82.484155
iter  90 value 82.143800
iter 100 value 81.970610
final  value 81.970610 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.028162 
final  value 94.054678 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.983024 
final  value 94.054478 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.700383 
final  value 94.039967 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.848449 
iter  10 value 94.054359
iter  20 value 94.034500
iter  30 value 85.894044
final  value 85.864501 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.280507 
final  value 94.054461 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.777823 
iter  10 value 94.057927
iter  20 value 94.047487
iter  30 value 93.448838
iter  40 value 87.869497
iter  50 value 87.852985
iter  60 value 87.833048
iter  70 value 87.722591
iter  80 value 87.715637
iter  90 value 87.715087
iter 100 value 87.713228
final  value 87.713228 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.994397 
iter  10 value 94.057772
iter  20 value 94.051040
iter  30 value 93.496188
iter  40 value 90.610204
iter  50 value 90.471631
iter  60 value 90.469428
iter  70 value 90.469308
iter  70 value 90.469308
final  value 90.469308 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.613347 
iter  10 value 94.089186
iter  20 value 94.081301
iter  30 value 93.857728
iter  40 value 90.909843
iter  50 value 90.795147
iter  60 value 90.779136
iter  70 value 90.695943
iter  80 value 90.651977
iter  90 value 90.651281
iter 100 value 90.650131
final  value 90.650131 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.912506 
iter  10 value 91.990233
iter  20 value 91.864060
final  value 91.863857 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.890833 
iter  10 value 94.057628
iter  20 value 94.051793
iter  30 value 92.098523
iter  40 value 91.030626
iter  50 value 91.030168
iter  60 value 88.145911
iter  70 value 87.823444
final  value 87.822903 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.653957 
iter  10 value 92.686320
iter  20 value 92.682387
iter  30 value 91.807777
iter  40 value 91.802681
iter  50 value 91.801110
iter  60 value 91.798269
iter  70 value 91.604951
iter  80 value 91.503305
iter  90 value 90.210392
iter 100 value 89.516880
final  value 89.516880 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.594676 
iter  10 value 94.037442
iter  20 value 94.011726
iter  30 value 86.202426
iter  40 value 83.699175
iter  50 value 83.633548
iter  60 value 83.346852
iter  70 value 82.770873
iter  80 value 82.102996
iter  90 value 81.965867
final  value 81.958557 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.041188 
iter  10 value 89.654560
iter  20 value 89.443372
iter  30 value 89.414707
iter  40 value 88.406419
iter  50 value 87.679359
iter  60 value 87.374185
final  value 87.370617 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.937881 
iter  10 value 94.061773
iter  20 value 93.585070
iter  30 value 92.263290
iter  40 value 90.690777
iter  50 value 89.834022
iter  60 value 89.832911
iter  70 value 88.475402
iter  80 value 88.469052
final  value 88.468051 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.614033 
iter  10 value 93.298517
iter  20 value 91.564804
iter  30 value 87.227273
iter  40 value 87.226943
final  value 87.226602 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.981938 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.596481 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.242285 
iter  10 value 93.328427
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.571354 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.209909 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.251275 
iter  10 value 93.328422
final  value 93.328261 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.611066 
final  value 94.052913 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.591290 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.746647 
final  value 92.933333 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.927181 
iter  10 value 85.168304
iter  20 value 83.796214
iter  30 value 82.000071
iter  40 value 81.900396
iter  50 value 81.860492
iter  60 value 81.859991
iter  60 value 81.859991
iter  60 value 81.859991
final  value 81.859991 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.452926 
final  value 94.052448 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.381878 
iter  10 value 93.188603
final  value 93.188588 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.793364 
iter  10 value 93.328304
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.312785 
final  value 93.324697 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.440411 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.217865 
iter  10 value 93.787516
iter  20 value 86.795850
iter  30 value 85.726980
iter  40 value 85.463963
iter  50 value 84.954840
iter  60 value 84.866988
final  value 84.863755 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.980876 
iter  10 value 94.055165
iter  20 value 93.166801
iter  30 value 92.656720
iter  40 value 87.456901
iter  50 value 84.340830
iter  60 value 82.727455
iter  70 value 82.340771
iter  80 value 82.302396
final  value 82.302314 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.030442 
iter  10 value 94.057755
iter  20 value 91.647535
iter  30 value 84.823585
iter  40 value 83.848984
iter  50 value 82.821685
iter  60 value 82.539112
iter  70 value 82.507094
iter  80 value 82.377542
iter  90 value 82.319875
final  value 82.319789 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.938772 
iter  10 value 94.050484
iter  20 value 88.991824
iter  30 value 85.833017
iter  40 value 84.816020
iter  50 value 83.921329
iter  60 value 83.097197
iter  70 value 82.932882
final  value 82.932752 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.218728 
iter  10 value 93.673387
iter  20 value 92.635927
iter  30 value 88.674183
iter  40 value 86.559017
iter  50 value 86.416316
iter  60 value 84.405772
iter  70 value 83.841001
iter  80 value 83.700906
iter  90 value 83.588051
final  value 83.573710 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.943765 
iter  10 value 94.351875
iter  20 value 88.486888
iter  30 value 82.947873
iter  40 value 81.076296
iter  50 value 80.210349
iter  60 value 79.218713
iter  70 value 78.933595
iter  80 value 78.665528
iter  90 value 78.628733
iter 100 value 78.605733
final  value 78.605733 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.504012 
iter  10 value 93.845466
iter  20 value 91.817124
iter  30 value 85.774372
iter  40 value 83.875958
iter  50 value 82.992366
iter  60 value 80.028836
iter  70 value 79.217180
iter  80 value 79.128989
iter  90 value 79.069659
iter 100 value 79.011713
final  value 79.011713 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.230732 
iter  10 value 93.970716
iter  20 value 92.298765
iter  30 value 84.978189
iter  40 value 82.160592
iter  50 value 81.035634
iter  60 value 79.986593
iter  70 value 79.495562
iter  80 value 79.384946
iter  90 value 79.275831
iter 100 value 79.212494
final  value 79.212494 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.226688 
iter  10 value 88.695609
iter  20 value 86.777367
iter  30 value 84.003582
iter  40 value 81.399895
iter  50 value 80.131056
iter  60 value 79.950392
iter  70 value 79.882750
iter  80 value 79.757844
iter  90 value 79.670377
iter 100 value 79.216178
final  value 79.216178 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 133.956289 
iter  10 value 93.589568
iter  20 value 91.486715
iter  30 value 86.627502
iter  40 value 83.391760
iter  50 value 82.198052
iter  60 value 79.189170
iter  70 value 79.085097
iter  80 value 79.066616
iter  90 value 79.044507
iter 100 value 79.009969
final  value 79.009969 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.796238 
iter  10 value 93.608755
iter  20 value 82.712849
iter  30 value 80.288420
iter  40 value 80.073307
iter  50 value 79.841760
iter  60 value 79.642662
iter  70 value 79.453950
iter  80 value 78.857187
iter  90 value 78.714040
iter 100 value 78.621214
final  value 78.621214 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.613323 
iter  10 value 93.718121
iter  20 value 87.820015
iter  30 value 85.558978
iter  40 value 82.036053
iter  50 value 80.560457
iter  60 value 80.040662
iter  70 value 79.531007
iter  80 value 79.339087
iter  90 value 78.718938
iter 100 value 78.591662
final  value 78.591662 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.579059 
iter  10 value 93.866308
iter  20 value 90.011734
iter  30 value 83.472379
iter  40 value 81.754020
iter  50 value 81.049504
iter  60 value 80.558547
iter  70 value 80.464063
iter  80 value 80.291376
iter  90 value 80.255078
iter 100 value 80.209990
final  value 80.209990 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.703462 
iter  10 value 95.626315
iter  20 value 87.598058
iter  30 value 84.962318
iter  40 value 81.231452
iter  50 value 79.652571
iter  60 value 79.078547
iter  70 value 78.812205
iter  80 value 78.663699
iter  90 value 78.644586
iter 100 value 78.598025
final  value 78.598025 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.405394 
iter  10 value 94.628334
iter  20 value 92.432795
iter  30 value 91.463084
iter  40 value 91.128859
iter  50 value 90.847896
iter  60 value 86.963264
iter  70 value 84.371602
iter  80 value 82.567244
iter  90 value 81.487799
iter 100 value 81.096216
final  value 81.096216 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.939304 
final  value 94.054603 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.657825 
final  value 94.054643 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.782759 
iter  10 value 92.938481
iter  20 value 92.935739
iter  30 value 92.923831
final  value 92.923791 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.145381 
final  value 94.054768 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.529255 
final  value 94.054719 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.103660 
iter  10 value 93.339023
iter  20 value 86.562591
iter  30 value 86.380403
iter  40 value 86.379927
iter  50 value 86.377216
iter  60 value 86.007105
iter  70 value 85.784134
iter  80 value 85.231164
iter  90 value 85.179626
iter 100 value 85.177432
final  value 85.177432 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.419913 
iter  10 value 94.057658
iter  20 value 92.905289
iter  30 value 84.023161
iter  40 value 83.936242
iter  50 value 82.637496
iter  60 value 82.629433
iter  70 value 82.618014
iter  80 value 82.607673
iter  90 value 82.607376
iter 100 value 82.042819
final  value 82.042819 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.957101 
iter  10 value 93.333612
iter  20 value 93.330380
iter  30 value 89.537326
iter  40 value 84.677342
iter  50 value 84.666812
iter  60 value 84.657671
iter  70 value 84.653606
iter  80 value 84.648977
iter  90 value 84.342392
iter 100 value 82.109070
final  value 82.109070 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.066854 
iter  10 value 94.057568
iter  20 value 93.510027
final  value 93.329472 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.110594 
iter  10 value 94.057727
iter  20 value 93.791580
final  value 93.535433 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.990923 
iter  10 value 92.864946
iter  20 value 92.768108
iter  30 value 92.708198
iter  40 value 92.707353
iter  50 value 92.704243
final  value 92.131596 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.799808 
iter  10 value 94.060686
iter  20 value 94.028080
iter  30 value 85.000277
iter  40 value 82.384091
iter  50 value 81.193450
iter  60 value 80.841310
iter  60 value 80.841310
final  value 80.841310 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.100141 
iter  10 value 93.354094
iter  20 value 93.334167
iter  30 value 91.358267
iter  40 value 84.657367
iter  50 value 84.457140
iter  60 value 84.077431
iter  70 value 84.076554
final  value 84.076523 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.613095 
iter  10 value 93.336871
iter  20 value 93.329240
iter  30 value 92.708998
iter  40 value 92.393564
iter  50 value 89.539020
iter  60 value 86.202101
iter  70 value 84.520673
iter  80 value 84.440054
iter  90 value 84.288575
iter 100 value 84.198474
final  value 84.198474 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.812117 
iter  10 value 94.030918
iter  20 value 93.387176
iter  30 value 85.328084
iter  40 value 83.173857
iter  50 value 82.901419
iter  60 value 82.863322
iter  70 value 82.535635
iter  80 value 82.387037
iter  90 value 82.386597
final  value 82.386571 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.471739 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.105662 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.070641 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.363945 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.395316 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.607592 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.159989 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.787506 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.689396 
iter  10 value 94.263155
final  value 94.263148 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.142310 
iter  10 value 94.483894
iter  20 value 94.468946
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.300518 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.237860 
iter  10 value 93.621691
final  value 93.606161 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.394541 
iter  10 value 93.358402
final  value 93.350441 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.646793 
final  value 94.129871 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.468409 
final  value 93.567525 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.613362 
iter  10 value 94.510865
iter  20 value 94.468750
iter  30 value 86.737132
iter  40 value 84.273883
iter  50 value 83.778149
iter  60 value 83.774160
final  value 83.774157 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.807685 
iter  10 value 94.695139
iter  20 value 94.483994
iter  30 value 94.245238
iter  40 value 87.540545
iter  50 value 85.913015
iter  60 value 84.814433
final  value 84.810397 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.471642 
iter  10 value 94.491623
iter  20 value 94.020394
iter  30 value 93.894803
iter  40 value 93.738759
iter  50 value 92.353896
iter  60 value 83.841550
iter  70 value 83.113437
iter  80 value 82.397787
iter  90 value 82.219340
iter 100 value 80.448232
final  value 80.448232 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.729022 
iter  10 value 85.745937
iter  20 value 84.286226
iter  30 value 83.510226
iter  40 value 83.381726
iter  50 value 83.333414
iter  60 value 83.312711
final  value 83.312671 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.434633 
iter  10 value 94.486897
iter  20 value 93.692052
iter  30 value 92.898821
iter  40 value 88.511829
iter  50 value 86.025189
iter  60 value 83.238036
iter  70 value 83.029120
iter  80 value 81.839353
iter  90 value 81.178203
iter 100 value 80.579220
final  value 80.579220 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.193796 
iter  10 value 94.576788
iter  20 value 93.138791
iter  30 value 92.610897
iter  40 value 91.876828
iter  50 value 85.994155
iter  60 value 80.892499
iter  70 value 80.662128
iter  80 value 80.304803
iter  90 value 80.063517
iter 100 value 79.547667
final  value 79.547667 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.652946 
iter  10 value 93.850575
iter  20 value 86.787704
iter  30 value 83.306167
iter  40 value 82.531655
iter  50 value 81.437364
iter  60 value 80.605293
iter  70 value 80.328281
iter  80 value 80.207869
iter  90 value 80.111297
iter 100 value 79.859215
final  value 79.859215 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.858659 
iter  10 value 94.680711
iter  20 value 88.580675
iter  30 value 86.643679
iter  40 value 84.478230
iter  50 value 83.345689
iter  60 value 82.489056
iter  70 value 81.691572
iter  80 value 80.749462
iter  90 value 80.423890
iter 100 value 80.287133
final  value 80.287133 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.796714 
iter  10 value 94.659314
iter  20 value 90.299186
iter  30 value 85.556406
iter  40 value 85.207105
iter  50 value 84.344280
iter  60 value 82.872765
iter  70 value 80.136728
iter  80 value 79.110535
iter  90 value 78.968581
iter 100 value 78.777879
final  value 78.777879 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.859085 
iter  10 value 94.481038
iter  20 value 94.011994
iter  30 value 87.297089
iter  40 value 85.810563
iter  50 value 84.937823
iter  60 value 82.991535
iter  70 value 82.292836
iter  80 value 81.758694
iter  90 value 81.650020
iter 100 value 81.531687
final  value 81.531687 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 138.514259 
iter  10 value 94.565467
iter  20 value 93.931896
iter  30 value 88.752086
iter  40 value 85.148010
iter  50 value 83.855523
iter  60 value 82.614651
iter  70 value 82.318965
iter  80 value 82.135110
iter  90 value 81.156802
iter 100 value 79.945222
final  value 79.945222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.015086 
iter  10 value 89.804808
iter  20 value 85.279214
iter  30 value 84.905611
iter  40 value 83.692698
iter  50 value 81.029612
iter  60 value 80.225465
iter  70 value 79.842037
iter  80 value 79.579036
iter  90 value 79.459761
iter 100 value 79.338949
final  value 79.338949 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.797786 
iter  10 value 92.875482
iter  20 value 85.532821
iter  30 value 83.848913
iter  40 value 82.770890
iter  50 value 81.828519
iter  60 value 81.039831
iter  70 value 80.769606
iter  80 value 80.528973
iter  90 value 80.300461
iter 100 value 79.939350
final  value 79.939350 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.861772 
iter  10 value 94.588331
iter  20 value 86.593318
iter  30 value 85.314308
iter  40 value 84.766834
iter  50 value 83.697093
iter  60 value 83.263689
iter  70 value 81.642273
iter  80 value 81.313306
iter  90 value 80.983862
iter 100 value 80.325517
final  value 80.325517 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.510022 
iter  10 value 93.876980
iter  20 value 84.431875
iter  30 value 82.144219
iter  40 value 81.552627
iter  50 value 81.303296
iter  60 value 81.203480
iter  70 value 81.071630
iter  80 value 81.058595
iter  90 value 80.375557
iter 100 value 79.899367
final  value 79.899367 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.049003 
final  value 94.485648 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.874918 
final  value 94.485752 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.234578 
final  value 94.485787 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.701678 
iter  10 value 93.458446
iter  20 value 93.352327
iter  30 value 93.350799
final  value 93.350684 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.188685 
iter  10 value 94.468700
iter  20 value 94.156675
iter  30 value 85.828939
iter  40 value 82.361923
iter  50 value 82.282687
iter  60 value 82.279943
final  value 82.279691 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.553507 
iter  10 value 94.489881
iter  20 value 94.184473
iter  30 value 93.610646
iter  40 value 88.463037
iter  50 value 88.021926
iter  60 value 87.216766
iter  70 value 86.618868
iter  80 value 86.031306
iter  90 value 86.019368
final  value 86.016604 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.899785 
iter  10 value 94.489583
iter  20 value 94.311670
iter  30 value 84.900929
iter  40 value 84.777423
iter  50 value 84.748500
iter  60 value 84.725773
iter  70 value 84.722704
iter  80 value 84.003708
iter  90 value 80.917299
iter 100 value 80.069284
final  value 80.069284 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.404212 
iter  10 value 94.488939
iter  20 value 94.484372
final  value 94.484356 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.395081 
iter  10 value 94.489131
final  value 94.467084 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.688268 
iter  10 value 94.471365
iter  20 value 94.235199
iter  30 value 85.976535
iter  40 value 84.924633
iter  40 value 84.924633
iter  40 value 84.924632
final  value 84.924632 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.684421 
iter  10 value 94.474577
iter  20 value 94.181777
iter  30 value 82.104624
iter  40 value 81.816437
iter  50 value 81.792193
final  value 81.791861 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.924833 
iter  10 value 94.492361
iter  20 value 84.870340
iter  30 value 82.493366
iter  40 value 80.174476
iter  50 value 80.162920
iter  60 value 80.160851
iter  70 value 80.157761
final  value 80.156925 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.895333 
iter  10 value 94.461688
iter  20 value 94.441480
iter  30 value 94.440621
iter  40 value 93.939415
iter  50 value 93.876172
iter  60 value 93.549222
iter  70 value 93.520468
iter  80 value 93.508414
iter  90 value 93.319974
final  value 93.309939 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.317292 
iter  10 value 94.492627
iter  20 value 94.383713
iter  30 value 93.558805
final  value 93.558487 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.322345 
iter  10 value 94.493197
iter  20 value 94.309688
iter  30 value 87.559614
iter  40 value 85.295184
iter  50 value 85.294223
iter  60 value 85.243251
iter  70 value 85.242356
iter  80 value 84.777916
iter  90 value 84.725814
iter 100 value 84.725415
final  value 84.725415 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 158.123498 
iter  10 value 117.894459
iter  20 value 117.767441
iter  30 value 117.743588
iter  40 value 117.620737
iter  50 value 117.511417
iter  60 value 117.502015
final  value 117.500027 
converged
Fitting Repeat 2 

# weights:  507
initial  value 138.978161 
iter  10 value 117.106069
iter  20 value 117.096051
iter  30 value 116.113229
iter  40 value 110.320618
iter  50 value 104.720777
iter  60 value 101.232093
iter  70 value 99.458665
iter  80 value 99.078110
iter  90 value 98.856056
iter 100 value 98.776022
final  value 98.776022 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.289035 
iter  10 value 117.119656
iter  20 value 117.106506
iter  30 value 117.027961
iter  40 value 107.038690
iter  50 value 104.292610
iter  60 value 104.281361
iter  70 value 104.281119
final  value 104.279908 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.464170 
iter  10 value 117.877999
iter  20 value 114.718266
iter  30 value 109.806665
iter  40 value 109.587345
iter  50 value 109.582381
iter  50 value 109.582381
final  value 109.582381 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.484429 
iter  10 value 117.897714
iter  20 value 117.635733
iter  30 value 117.080496
iter  40 value 116.873131
final  value 116.862059 
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 -- Mon Dec 22 20:24:00 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 
 19.942   0.472  72.932