##############################################################################
##############################################################################
###
### 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_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* 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 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 ... NOTE
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       37.365  1.734  39.494
FSmethod      35.325  1.639  37.241
corr_plot     35.014  1.595  36.790
pred_ensembel 14.465  0.508  10.923
enrichfindP    0.516  0.067   7.870
* 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: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-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/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** 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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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 95.031382 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.679656 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.000491 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.432165 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.014557 
final  value 94.052434 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.468727 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.118050 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.330941 
final  value 94.275363 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.079459 
iter  10 value 94.556665
iter  20 value 94.470306
final  value 94.470285 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.076969 
iter  10 value 94.212892
iter  20 value 86.700177
iter  30 value 86.293709
iter  40 value 86.281498
final  value 86.281482 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.055221 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.028821 
iter  10 value 92.192205
iter  20 value 85.010253
iter  30 value 84.734987
iter  40 value 84.727273
final  value 84.724804 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.812072 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.968158 
iter  10 value 93.805907
iter  20 value 93.672079
final  value 93.671795 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.223229 
iter  10 value 94.275371
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.169454 
iter  10 value 94.553713
iter  20 value 94.473919
iter  30 value 93.809250
iter  40 value 90.667484
iter  50 value 90.010703
iter  60 value 86.001070
iter  70 value 84.634596
iter  80 value 84.209152
iter  90 value 82.997294
iter 100 value 82.781434
final  value 82.781434 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.797256 
iter  10 value 94.476781
iter  20 value 94.138351
iter  30 value 93.825310
iter  40 value 93.638798
iter  50 value 93.051733
iter  60 value 93.037489
iter  70 value 93.031232
final  value 93.031184 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.719802 
iter  10 value 94.491638
iter  20 value 93.588739
iter  30 value 92.347760
iter  40 value 87.370877
iter  50 value 86.832367
iter  60 value 86.511602
iter  70 value 85.711123
iter  80 value 85.416055
iter  90 value 84.930281
iter 100 value 84.905055
final  value 84.905055 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.150140 
iter  10 value 94.330041
iter  20 value 93.854238
iter  30 value 88.521028
iter  40 value 88.080377
iter  50 value 87.883697
iter  60 value 86.174427
iter  70 value 85.458465
iter  80 value 85.376716
final  value 85.375001 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.063212 
iter  10 value 94.486808
iter  20 value 94.372011
iter  30 value 87.575792
iter  40 value 86.804122
iter  50 value 85.796644
iter  60 value 85.584828
iter  70 value 85.561416
final  value 85.559909 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.113448 
iter  10 value 94.407685
iter  20 value 94.081062
iter  30 value 92.423076
iter  40 value 90.041223
iter  50 value 87.136485
iter  60 value 85.429803
iter  70 value 82.368348
iter  80 value 82.048105
iter  90 value 81.776464
iter 100 value 81.235086
final  value 81.235086 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.332098 
iter  10 value 94.497570
iter  20 value 93.340314
iter  30 value 88.577817
iter  40 value 86.614467
iter  50 value 85.629177
iter  60 value 85.466054
iter  70 value 85.262647
iter  80 value 85.071384
iter  90 value 84.432920
iter 100 value 83.602259
final  value 83.602259 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.022126 
iter  10 value 94.578172
iter  20 value 88.409251
iter  30 value 86.368969
iter  40 value 85.772193
iter  50 value 84.205376
iter  60 value 82.694110
iter  70 value 81.742273
iter  80 value 81.629814
iter  90 value 81.446038
iter 100 value 81.394739
final  value 81.394739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.088434 
iter  10 value 94.296821
iter  20 value 87.276323
iter  30 value 85.667835
iter  40 value 84.734848
iter  50 value 82.694517
iter  60 value 81.976529
iter  70 value 81.709941
iter  80 value 81.482371
iter  90 value 81.358669
iter 100 value 81.099003
final  value 81.099003 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.560788 
iter  10 value 94.088672
iter  20 value 85.192583
iter  30 value 84.453605
iter  40 value 83.321782
iter  50 value 83.080181
iter  60 value 82.665881
iter  70 value 82.609638
iter  80 value 82.446759
iter  90 value 82.359631
iter 100 value 82.299506
final  value 82.299506 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.486507 
iter  10 value 95.259443
iter  20 value 88.391756
iter  30 value 86.601666
iter  40 value 85.525725
iter  50 value 85.124234
iter  60 value 83.575724
iter  70 value 83.279939
iter  80 value 82.595659
iter  90 value 82.551227
iter 100 value 82.150718
final  value 82.150718 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.943704 
iter  10 value 102.283797
iter  20 value 89.568688
iter  30 value 88.431743
iter  40 value 85.732241
iter  50 value 84.899208
iter  60 value 84.719171
iter  70 value 84.671125
iter  80 value 84.521078
iter  90 value 84.174192
iter 100 value 83.376137
final  value 83.376137 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.822368 
iter  10 value 94.417871
iter  20 value 88.642086
iter  30 value 87.043402
iter  40 value 85.996623
iter  50 value 85.428553
iter  60 value 84.253568
iter  70 value 83.285339
iter  80 value 82.860013
iter  90 value 82.139918
iter 100 value 81.899919
final  value 81.899919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.901848 
iter  10 value 94.411933
iter  20 value 90.423474
iter  30 value 87.856316
iter  40 value 86.781246
iter  50 value 86.324663
iter  60 value 84.652620
iter  70 value 82.897299
iter  80 value 82.066285
iter  90 value 81.054144
iter 100 value 80.630781
final  value 80.630781 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.083050 
iter  10 value 95.266631
iter  20 value 92.929671
iter  30 value 89.968885
iter  40 value 85.131776
iter  50 value 83.883808
iter  60 value 83.267988
iter  70 value 82.686337
iter  80 value 81.811348
iter  90 value 81.410958
iter 100 value 81.288622
final  value 81.288622 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.588796 
final  value 94.148969 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.255008 
final  value 94.485615 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.200343 
final  value 94.486184 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.394985 
final  value 94.485580 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.069866 
final  value 94.485722 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.005732 
iter  10 value 94.488877
iter  20 value 94.378770
iter  30 value 94.042743
iter  40 value 87.722653
iter  50 value 86.940488
iter  60 value 86.086192
iter  70 value 85.727760
iter  80 value 85.726626
final  value 85.726621 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.390851 
iter  10 value 94.280623
iter  20 value 94.276398
iter  30 value 94.275515
iter  30 value 94.275514
final  value 94.275514 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.151424 
iter  10 value 94.280226
iter  20 value 94.275637
iter  30 value 88.295699
iter  40 value 86.690231
iter  50 value 84.876822
iter  60 value 84.875354
iter  70 value 84.875176
iter  80 value 84.749168
iter  90 value 84.600740
final  value 84.600602 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.451129 
iter  10 value 94.488822
iter  20 value 94.439680
iter  30 value 89.662181
iter  40 value 84.345139
iter  50 value 84.320367
iter  60 value 84.316505
iter  70 value 84.019986
iter  80 value 83.753921
iter  90 value 83.316427
iter 100 value 83.116734
final  value 83.116734 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.111771 
iter  10 value 94.488854
iter  20 value 91.834267
iter  30 value 84.474161
iter  40 value 83.904509
final  value 83.902268 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.406565 
iter  10 value 94.492387
iter  20 value 94.424913
iter  30 value 90.387674
iter  40 value 86.446931
iter  50 value 84.657143
iter  60 value 83.707978
iter  70 value 81.477967
iter  80 value 80.367673
iter  90 value 79.872400
iter 100 value 79.684274
final  value 79.684274 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.068165 
iter  10 value 86.434248
iter  20 value 86.125243
iter  30 value 86.115369
iter  40 value 85.564384
iter  50 value 85.449728
iter  60 value 85.447827
iter  70 value 85.445693
iter  80 value 85.444031
iter  90 value 85.443644
iter 100 value 85.443288
final  value 85.443288 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.678997 
iter  10 value 93.840373
iter  20 value 93.825428
iter  30 value 93.817034
iter  40 value 87.957413
iter  50 value 83.764909
iter  60 value 83.022234
iter  70 value 82.838474
iter  80 value 82.411554
iter  90 value 82.365823
iter 100 value 82.285064
final  value 82.285064 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.846107 
iter  10 value 94.283981
iter  20 value 94.276663
final  value 94.275655 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.844769 
iter  10 value 94.492006
iter  20 value 94.484655
iter  30 value 94.458298
iter  40 value 88.174716
iter  50 value 87.829942
iter  60 value 87.709443
iter  70 value 85.954682
iter  80 value 84.714192
iter  90 value 83.864474
final  value 83.766752 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.736962 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.651454 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.148220 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.129983 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.350240 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.565305 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.504904 
iter  10 value 94.010688
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.951683 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 93.922155 
iter  10 value 91.610437
iter  20 value 90.760527
iter  20 value 90.760527
iter  20 value 90.760526
final  value 90.760526 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.125958 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.459810 
final  value 93.671508 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.051928 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.048606 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.925099 
iter  10 value 94.035089
final  value 94.035088 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.667145 
final  value 94.038252 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.219311 
iter  10 value 91.116750
iter  20 value 86.350587
iter  30 value 86.159889
iter  40 value 84.934955
iter  50 value 83.938448
iter  60 value 83.636983
iter  70 value 83.595825
iter  80 value 83.442583
final  value 83.440206 
converged
Fitting Repeat 2 

# weights:  103
initial  value 116.615677 
iter  10 value 93.499643
iter  20 value 90.455110
iter  30 value 87.357412
iter  40 value 86.747360
iter  50 value 86.484673
iter  60 value 84.265589
iter  70 value 83.479748
iter  80 value 83.464460
iter  90 value 83.440533
final  value 83.440071 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.071739 
iter  10 value 93.944889
iter  20 value 92.567460
iter  30 value 91.145173
iter  40 value 91.082386
iter  50 value 90.208704
iter  60 value 88.456267
iter  70 value 88.302146
iter  80 value 84.295868
iter  90 value 82.900698
iter 100 value 82.585712
final  value 82.585712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 108.135613 
iter  10 value 94.069097
iter  20 value 93.970715
iter  30 value 90.929675
iter  40 value 89.403440
iter  50 value 89.123329
iter  60 value 88.247030
iter  70 value 87.654978
iter  80 value 84.320750
iter  90 value 83.695842
iter 100 value 83.499090
final  value 83.499090 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.568570 
iter  10 value 94.002047
iter  20 value 92.246830
iter  30 value 91.858871
iter  40 value 91.630930
iter  50 value 91.610784
iter  60 value 88.606781
iter  70 value 88.223758
iter  80 value 87.664767
iter  90 value 87.288270
iter 100 value 86.603598
final  value 86.603598 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.575494 
iter  10 value 93.850911
iter  20 value 88.628194
iter  30 value 87.650711
iter  40 value 84.312715
iter  50 value 83.112957
iter  60 value 82.735179
iter  70 value 81.931458
iter  80 value 80.858898
iter  90 value 80.417083
iter 100 value 80.299315
final  value 80.299315 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.496389 
iter  10 value 94.375222
iter  20 value 92.213569
iter  30 value 88.220675
iter  40 value 84.880822
iter  50 value 83.733624
iter  60 value 82.548734
iter  70 value 82.117813
iter  80 value 81.605733
iter  90 value 80.373218
iter 100 value 80.110264
final  value 80.110264 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.492060 
iter  10 value 94.099129
iter  20 value 94.055131
iter  30 value 93.927003
iter  40 value 91.811650
iter  50 value 88.126895
iter  60 value 87.703910
iter  70 value 87.051681
iter  80 value 84.873322
iter  90 value 84.068901
iter 100 value 83.953041
final  value 83.953041 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.774034 
iter  10 value 94.326417
iter  20 value 94.039106
iter  30 value 90.574234
iter  40 value 89.985108
iter  50 value 86.256299
iter  60 value 83.209980
iter  70 value 82.929709
iter  80 value 82.746733
iter  90 value 82.697962
iter 100 value 82.656562
final  value 82.656562 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.109075 
iter  10 value 95.124189
iter  20 value 92.863325
iter  30 value 87.704959
iter  40 value 85.740692
iter  50 value 84.162334
iter  60 value 82.604749
iter  70 value 80.841387
iter  80 value 80.563068
iter  90 value 80.428561
iter 100 value 79.962233
final  value 79.962233 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.706683 
iter  10 value 94.079634
iter  20 value 88.104978
iter  30 value 86.752011
iter  40 value 84.961908
iter  50 value 82.537143
iter  60 value 82.216171
iter  70 value 81.368764
iter  80 value 81.084909
iter  90 value 80.837947
iter 100 value 80.340091
final  value 80.340091 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.087212 
iter  10 value 93.914041
iter  20 value 92.158779
iter  30 value 89.646852
iter  40 value 86.844164
iter  50 value 84.360672
iter  60 value 83.844949
iter  70 value 83.045868
iter  80 value 81.566807
iter  90 value 80.853249
iter 100 value 80.773038
final  value 80.773038 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.343474 
iter  10 value 94.356094
iter  20 value 90.914755
iter  30 value 88.230764
iter  40 value 83.731902
iter  50 value 82.075579
iter  60 value 81.514696
iter  70 value 80.272030
iter  80 value 79.810400
iter  90 value 79.647222
iter 100 value 79.454489
final  value 79.454489 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.071155 
iter  10 value 94.187905
iter  20 value 94.089643
iter  30 value 93.816181
iter  40 value 89.303141
iter  50 value 87.574247
iter  60 value 86.952286
iter  70 value 86.457865
iter  80 value 86.079310
iter  90 value 85.347409
iter 100 value 84.265984
final  value 84.265984 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.358799 
iter  10 value 95.194500
iter  20 value 93.927622
iter  30 value 89.360413
iter  40 value 88.568559
iter  50 value 87.374256
iter  60 value 86.812716
iter  70 value 86.663177
iter  80 value 85.043402
iter  90 value 82.171750
iter 100 value 80.995750
final  value 80.995750 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.048277 
final  value 94.054326 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.845359 
final  value 94.054325 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.003507 
final  value 94.054419 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.444086 
final  value 94.054740 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.588785 
final  value 94.054611 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.025509 
iter  10 value 94.053194
iter  20 value 87.096230
iter  30 value 85.880142
iter  40 value 83.736047
iter  50 value 82.296975
iter  60 value 80.113191
iter  70 value 78.097309
iter  80 value 77.776822
iter  90 value 77.747086
iter 100 value 77.705041
final  value 77.705041 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.848236 
iter  10 value 94.057357
iter  20 value 94.041670
iter  30 value 94.039258
final  value 94.039210 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.487897 
iter  10 value 94.057039
iter  20 value 94.055605
iter  30 value 94.052377
iter  40 value 94.051108
final  value 94.051021 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.973969 
iter  10 value 94.057349
iter  20 value 94.052917
iter  30 value 93.422604
iter  40 value 85.527589
iter  50 value 85.432960
iter  60 value 85.432557
iter  70 value 85.424790
iter  80 value 83.832599
iter  90 value 82.366647
iter 100 value 82.208984
final  value 82.208984 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.998858 
iter  10 value 94.058297
iter  20 value 94.053249
iter  30 value 87.580076
iter  40 value 87.250643
iter  50 value 87.214407
iter  60 value 87.213498
iter  70 value 86.505913
iter  80 value 83.551740
iter  90 value 83.526862
iter 100 value 83.330309
final  value 83.330309 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.691208 
iter  10 value 94.047176
iter  20 value 94.039862
iter  30 value 91.264362
iter  40 value 86.144872
final  value 86.087395 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.193413 
iter  10 value 87.538811
iter  20 value 87.039092
iter  30 value 87.034488
final  value 87.031497 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.169193 
iter  10 value 94.046227
iter  20 value 94.038473
iter  30 value 86.388849
iter  40 value 86.016269
final  value 86.012894 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.533679 
iter  10 value 93.251810
iter  20 value 93.238574
iter  30 value 93.238068
iter  40 value 93.054856
iter  50 value 93.054296
iter  60 value 92.959640
iter  70 value 92.731290
iter  80 value 92.731020
iter  90 value 92.623770
iter 100 value 86.314978
final  value 86.314978 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.745433 
iter  10 value 94.047116
iter  20 value 94.037151
iter  30 value 94.034709
iter  40 value 86.294160
iter  50 value 84.645184
iter  60 value 81.149065
iter  70 value 80.780849
iter  80 value 80.702716
iter  90 value 80.702243
iter 100 value 80.699950
final  value 80.699950 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.850384 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.699621 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.361913 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.889986 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.660516 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.642005 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.266930 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.416203 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.211607 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.600888 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.635110 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.087008 
iter  10 value 94.484021
iter  20 value 94.468558
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.578646 
final  value 94.442072 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.016274 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.177723 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.627372 
iter  10 value 94.490459
iter  20 value 94.375488
iter  30 value 91.296485
iter  40 value 88.381295
iter  50 value 85.205545
iter  60 value 82.429170
iter  70 value 82.150023
iter  80 value 82.141800
final  value 82.141798 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.932889 
iter  10 value 94.488634
iter  20 value 94.175238
iter  30 value 94.025024
iter  40 value 93.799274
iter  50 value 91.354853
iter  60 value 85.741374
iter  70 value 84.683474
iter  80 value 84.342639
iter  90 value 82.718227
iter 100 value 82.439835
final  value 82.439835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.518200 
iter  10 value 94.346443
iter  20 value 92.591888
iter  30 value 92.362615
iter  40 value 92.238757
iter  50 value 86.426592
iter  60 value 84.542377
iter  70 value 84.346639
iter  80 value 82.413804
iter  90 value 82.353131
iter 100 value 82.350714
final  value 82.350714 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.376862 
iter  10 value 94.511533
iter  20 value 93.975304
iter  30 value 85.185641
iter  40 value 84.733501
iter  50 value 82.742264
iter  60 value 82.155575
iter  70 value 82.141839
final  value 82.141795 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.727704 
iter  10 value 94.165054
iter  20 value 87.333683
iter  30 value 81.392462
iter  40 value 80.451414
iter  50 value 80.100988
iter  60 value 80.028108
iter  70 value 79.946431
iter  80 value 79.873989
iter  90 value 79.866891
iter  90 value 79.866891
iter  90 value 79.866891
final  value 79.866891 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.275749 
iter  10 value 94.384372
iter  20 value 82.962276
iter  30 value 82.586138
iter  40 value 82.162182
iter  50 value 81.928643
iter  60 value 81.709343
iter  70 value 81.530369
iter  80 value 80.805844
iter  90 value 79.808482
iter 100 value 79.667810
final  value 79.667810 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.483483 
iter  10 value 87.349494
iter  20 value 82.825221
iter  30 value 81.700657
iter  40 value 80.726908
iter  50 value 80.246178
iter  60 value 79.807337
iter  70 value 78.958643
iter  80 value 78.600347
iter  90 value 78.575206
iter 100 value 78.528779
final  value 78.528779 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 134.834483 
iter  10 value 94.365595
iter  20 value 85.247922
iter  30 value 84.267754
iter  40 value 83.338067
iter  50 value 82.112754
iter  60 value 81.032496
iter  70 value 80.661337
iter  80 value 80.521683
iter  90 value 80.438755
iter 100 value 80.365768
final  value 80.365768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.931585 
iter  10 value 94.779180
iter  20 value 87.735123
iter  30 value 83.877231
iter  40 value 80.916758
iter  50 value 80.780886
iter  60 value 80.695425
iter  70 value 80.606787
iter  80 value 80.531524
iter  90 value 80.462413
iter 100 value 80.396319
final  value 80.396319 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.154038 
iter  10 value 94.611887
iter  20 value 94.084266
iter  30 value 85.224754
iter  40 value 81.347398
iter  50 value 80.971146
iter  60 value 80.267316
iter  70 value 79.897845
iter  80 value 79.510194
iter  90 value 79.274242
iter 100 value 79.231775
final  value 79.231775 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.206327 
iter  10 value 94.339539
iter  20 value 90.361108
iter  30 value 89.554065
iter  40 value 85.701883
iter  50 value 85.206216
iter  60 value 83.826909
iter  70 value 81.837704
iter  80 value 81.370269
iter  90 value 80.829967
iter 100 value 80.557948
final  value 80.557948 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.961764 
iter  10 value 93.412902
iter  20 value 83.423391
iter  30 value 82.764905
iter  40 value 81.460089
iter  50 value 80.743683
iter  60 value 80.326119
iter  70 value 79.850287
iter  80 value 79.565849
iter  90 value 78.954269
iter 100 value 78.801534
final  value 78.801534 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 133.597410 
iter  10 value 94.571602
iter  20 value 93.903319
iter  30 value 84.608897
iter  40 value 83.261398
iter  50 value 81.182839
iter  60 value 80.052793
iter  70 value 79.790402
iter  80 value 79.638431
iter  90 value 79.521171
iter 100 value 79.292814
final  value 79.292814 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.638802 
iter  10 value 94.434251
iter  20 value 89.091206
iter  30 value 87.146072
iter  40 value 82.343218
iter  50 value 81.113912
iter  60 value 80.693785
iter  70 value 79.550440
iter  80 value 78.972228
iter  90 value 78.721651
iter 100 value 78.662704
final  value 78.662704 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.047769 
iter  10 value 95.437262
iter  20 value 94.384763
iter  30 value 89.006945
iter  40 value 87.135123
iter  50 value 82.900426
iter  60 value 82.261313
iter  70 value 80.288268
iter  80 value 79.672191
iter  90 value 79.411864
iter 100 value 78.867952
final  value 78.867952 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.918720 
iter  10 value 94.485864
iter  20 value 94.484251
iter  30 value 93.300678
final  value 93.300604 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.855020 
final  value 94.485752 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.028375 
final  value 94.486046 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.641996 
final  value 94.485839 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.573733 
final  value 94.485638 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.889960 
iter  10 value 94.489758
iter  20 value 94.424456
iter  30 value 93.882253
iter  40 value 91.394389
iter  50 value 91.389746
iter  60 value 91.387656
iter  70 value 91.384617
iter  80 value 91.360260
iter  90 value 91.324457
iter 100 value 91.323436
final  value 91.323436 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.004510 
iter  10 value 94.488400
iter  20 value 85.160004
iter  30 value 83.944631
iter  40 value 83.941936
iter  40 value 83.941936
iter  40 value 83.941936
final  value 83.941936 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.101186 
iter  10 value 94.487786
iter  20 value 93.644074
iter  30 value 83.859264
iter  40 value 81.234557
iter  50 value 81.056315
iter  60 value 81.053744
iter  70 value 81.053589
iter  80 value 81.052610
iter  90 value 80.957031
iter 100 value 80.241425
final  value 80.241425 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.201421 
iter  10 value 94.489056
iter  20 value 92.225223
iter  30 value 85.483599
iter  40 value 85.244170
iter  50 value 84.458177
iter  60 value 84.229158
iter  70 value 84.209365
iter  80 value 84.208788
iter  90 value 84.206992
final  value 84.206612 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.032546 
iter  10 value 94.489119
iter  20 value 94.484225
final  value 94.484217 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.647007 
iter  10 value 94.492035
iter  20 value 94.472052
iter  30 value 90.816458
iter  40 value 88.682283
iter  50 value 87.381475
iter  60 value 84.872552
iter  70 value 84.579258
iter  80 value 84.126720
iter  90 value 83.822582
iter 100 value 83.812650
final  value 83.812650 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.711142 
iter  10 value 94.491919
iter  20 value 94.476345
iter  30 value 94.466803
final  value 94.466745 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.858121 
iter  10 value 94.492286
iter  20 value 94.408005
iter  30 value 93.183739
iter  40 value 88.324126
iter  50 value 87.227945
iter  60 value 85.207774
iter  70 value 84.432313
iter  80 value 84.432223
iter  90 value 82.841535
iter 100 value 80.026784
final  value 80.026784 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.854533 
iter  10 value 94.492333
iter  20 value 94.463848
iter  30 value 93.300620
iter  30 value 93.300620
iter  30 value 93.300620
final  value 93.300620 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.712598 
iter  10 value 94.492478
iter  20 value 94.476989
iter  30 value 84.419444
iter  40 value 84.416509
iter  50 value 84.207373
iter  60 value 84.188749
final  value 84.188347 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.385510 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.840410 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.003001 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.688501 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.098357 
final  value 94.017143 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.154446 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.155440 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.490248 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.236131 
iter  10 value 93.877694
iter  20 value 93.720941
iter  20 value 93.720940
iter  20 value 93.720940
final  value 93.720940 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.572725 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.721383 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 93.089043 
iter  10 value 89.424389
iter  20 value 89.391363
iter  20 value 89.391362
final  value 89.391362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.863052 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.086128 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.471313 
iter  10 value 93.647829
final  value 93.647673 
converged
Fitting Repeat 1 

# weights:  103
initial  value 117.010941 
iter  10 value 94.069306
iter  20 value 92.465143
iter  30 value 89.081585
iter  40 value 85.956764
iter  50 value 84.851669
iter  60 value 84.771338
iter  70 value 84.399949
iter  80 value 84.382300
final  value 84.382288 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.526983 
iter  10 value 94.145971
iter  20 value 93.028196
iter  30 value 86.663587
iter  40 value 86.513660
iter  50 value 85.613615
iter  60 value 85.027459
iter  70 value 85.020993
iter  70 value 85.020993
iter  70 value 85.020993
final  value 85.020993 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.207300 
iter  10 value 94.056819
iter  20 value 93.601287
iter  30 value 88.758074
iter  40 value 88.467363
iter  50 value 87.162237
iter  60 value 85.508750
iter  70 value 83.857282
iter  80 value 83.784478
final  value 83.782287 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.566015 
iter  10 value 94.055887
iter  20 value 93.433458
iter  30 value 87.079061
iter  40 value 86.356441
iter  50 value 84.787269
iter  60 value 84.394771
iter  70 value 83.846205
final  value 83.802224 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.919080 
iter  10 value 93.547900
iter  20 value 85.601553
iter  30 value 84.602630
iter  40 value 84.267971
iter  50 value 83.607331
iter  60 value 83.386085
final  value 83.385625 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.572486 
iter  10 value 94.051967
iter  20 value 88.027517
iter  30 value 86.785573
iter  40 value 84.874410
iter  50 value 83.965916
iter  60 value 83.277360
iter  70 value 83.143638
iter  80 value 83.091291
iter  90 value 83.012055
iter 100 value 82.403615
final  value 82.403615 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.260041 
iter  10 value 93.873308
iter  20 value 85.687883
iter  30 value 83.735395
iter  40 value 82.333484
iter  50 value 82.248407
iter  60 value 82.131905
iter  70 value 81.288193
iter  80 value 80.628100
iter  90 value 80.381438
iter 100 value 80.263326
final  value 80.263326 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.791244 
iter  10 value 94.102512
iter  20 value 93.993773
iter  30 value 90.794850
iter  40 value 86.487710
iter  50 value 85.967370
iter  60 value 85.083699
iter  70 value 82.543130
iter  80 value 81.478878
iter  90 value 80.853657
iter 100 value 80.743885
final  value 80.743885 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 134.338961 
iter  10 value 93.990873
iter  20 value 92.539293
iter  30 value 85.492998
iter  40 value 83.235288
iter  50 value 82.775315
iter  60 value 82.722745
iter  70 value 82.644449
iter  80 value 82.151150
iter  90 value 81.768536
iter 100 value 81.598956
final  value 81.598956 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.679593 
iter  10 value 93.945587
iter  20 value 88.252154
iter  30 value 87.665830
iter  40 value 87.294916
iter  50 value 86.634174
iter  60 value 85.004679
iter  70 value 83.245517
iter  80 value 82.592639
iter  90 value 82.124511
iter 100 value 82.081373
final  value 82.081373 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.166552 
iter  10 value 94.654613
iter  20 value 91.494825
iter  30 value 86.734809
iter  40 value 85.344058
iter  50 value 83.580269
iter  60 value 82.869391
iter  70 value 81.758824
iter  80 value 81.737997
iter  90 value 81.688942
iter 100 value 81.466407
final  value 81.466407 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.668318 
iter  10 value 93.916252
iter  20 value 92.967733
iter  30 value 92.861672
iter  40 value 90.118400
iter  50 value 89.549424
iter  60 value 88.391885
iter  70 value 83.888736
iter  80 value 81.625383
iter  90 value 81.190707
iter 100 value 80.938577
final  value 80.938577 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.212685 
iter  10 value 93.074026
iter  20 value 86.569169
iter  30 value 83.723666
iter  40 value 82.626038
iter  50 value 82.311962
iter  60 value 82.026876
iter  70 value 81.998179
iter  80 value 81.979874
iter  90 value 81.545612
iter 100 value 81.266840
final  value 81.266840 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.147542 
iter  10 value 94.138803
iter  20 value 93.959428
iter  30 value 90.544232
iter  40 value 86.518871
iter  50 value 84.662803
iter  60 value 83.379360
iter  70 value 82.937363
iter  80 value 82.746599
iter  90 value 82.191993
iter 100 value 81.384139
final  value 81.384139 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.135041 
iter  10 value 93.942126
iter  20 value 90.456502
iter  30 value 85.259554
iter  40 value 84.062347
iter  50 value 82.717409
iter  60 value 81.854276
iter  70 value 81.539318
iter  80 value 81.178076
iter  90 value 80.671627
iter 100 value 80.467060
final  value 80.467060 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.015135 
iter  10 value 94.054808
iter  20 value 94.048883
iter  30 value 91.610434
iter  40 value 91.269364
iter  50 value 91.242228
iter  60 value 91.241922
iter  70 value 91.238656
final  value 91.238571 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.660561 
final  value 94.054679 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.789891 
iter  10 value 94.034882
iter  20 value 92.703888
iter  30 value 86.178102
iter  40 value 86.079780
iter  50 value 86.079447
final  value 86.079436 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.891593 
final  value 94.054638 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.685651 
final  value 94.054425 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.599886 
iter  10 value 94.212869
iter  20 value 94.188866
iter  30 value 91.331076
iter  40 value 91.261026
iter  50 value 91.227372
iter  60 value 90.710959
iter  70 value 90.405340
iter  80 value 85.862002
iter  90 value 85.174146
iter 100 value 85.170975
final  value 85.170975 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.217348 
iter  10 value 91.473116
iter  20 value 88.972270
iter  30 value 87.970166
final  value 87.918920 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.580078 
iter  10 value 94.038498
iter  20 value 94.035827
iter  30 value 94.020714
iter  40 value 91.518477
iter  50 value 91.515114
iter  60 value 91.513842
iter  70 value 91.512244
iter  80 value 91.512193
iter  90 value 91.434682
iter 100 value 91.434086
final  value 91.434086 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.931264 
final  value 94.059606 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.442516 
iter  10 value 94.022019
iter  20 value 94.017556
final  value 94.017226 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.083030 
iter  10 value 94.040464
iter  20 value 93.655051
iter  30 value 93.654303
iter  40 value 93.576703
iter  50 value 93.532630
final  value 93.532240 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.772396 
iter  10 value 94.061226
iter  20 value 94.046675
iter  30 value 85.742722
iter  40 value 85.171259
iter  50 value 85.154236
iter  60 value 84.194072
iter  70 value 83.983244
final  value 83.983235 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.133087 
iter  10 value 94.060446
iter  20 value 94.003045
iter  30 value 93.810720
final  value 93.810658 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.351779 
iter  10 value 94.057352
iter  20 value 93.228007
iter  30 value 85.659987
iter  40 value 85.654136
iter  50 value 85.266833
final  value 85.261321 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.308281 
iter  10 value 88.004996
iter  20 value 86.506496
iter  30 value 85.667474
iter  40 value 85.643469
iter  50 value 84.355902
iter  60 value 83.928302
iter  70 value 83.926654
iter  80 value 83.856828
iter  90 value 83.820685
iter 100 value 83.815763
final  value 83.815763 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.569746 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.260394 
iter  10 value 94.277469
final  value 94.275364 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.026420 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.372988 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.567457 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.235133 
final  value 93.320225 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.974321 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.181821 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.314993 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.468993 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.650201 
iter  10 value 93.215707
final  value 93.153558 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.622887 
iter  10 value 92.552761
iter  20 value 92.507819
final  value 92.507816 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.667959 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.619833 
iter  10 value 93.394938
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.349435 
iter  10 value 90.541343
iter  20 value 90.367454
final  value 90.367204 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.869552 
iter  10 value 93.807596
iter  20 value 86.447950
iter  30 value 86.337654
iter  40 value 84.680888
iter  50 value 84.516104
iter  60 value 84.481370
final  value 84.481206 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.962652 
iter  10 value 94.197731
iter  20 value 92.753421
iter  30 value 92.685455
iter  40 value 92.665200
iter  50 value 84.167443
iter  60 value 83.599668
iter  70 value 81.963551
iter  80 value 81.701484
iter  90 value 81.240951
iter 100 value 80.780698
final  value 80.780698 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.649875 
iter  10 value 93.679904
iter  20 value 86.934655
iter  30 value 84.783269
iter  40 value 84.483484
iter  50 value 84.482168
iter  60 value 84.472132
iter  70 value 84.356691
final  value 84.344239 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.626989 
iter  10 value 92.949592
iter  20 value 92.346501
iter  30 value 90.435714
iter  40 value 85.909194
iter  50 value 85.638929
iter  60 value 84.611118
iter  70 value 83.489937
iter  80 value 81.044981
iter  90 value 80.565835
iter 100 value 80.540965
final  value 80.540965 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 113.892664 
iter  10 value 94.375341
iter  20 value 92.807729
iter  30 value 92.657556
iter  40 value 92.653918
iter  50 value 91.796552
iter  60 value 83.887399
iter  70 value 83.716817
iter  80 value 83.444527
iter  90 value 81.444063
iter 100 value 80.899279
final  value 80.899279 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.080072 
iter  10 value 96.984455
iter  20 value 92.748186
iter  30 value 84.657737
iter  40 value 84.528047
iter  50 value 83.947905
iter  60 value 82.432251
iter  70 value 81.191301
iter  80 value 80.610047
iter  90 value 80.299536
iter 100 value 80.104125
final  value 80.104125 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.818603 
iter  10 value 92.956186
iter  20 value 89.143901
iter  30 value 87.692442
iter  40 value 87.422270
iter  50 value 84.328910
iter  60 value 82.798863
iter  70 value 81.837075
iter  80 value 80.876435
iter  90 value 79.969750
iter 100 value 79.413602
final  value 79.413602 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.394257 
iter  10 value 94.238437
iter  20 value 92.880225
iter  30 value 92.660573
iter  40 value 91.126313
iter  50 value 86.609071
iter  60 value 82.519165
iter  70 value 81.168521
iter  80 value 80.581775
iter  90 value 79.886096
iter 100 value 79.474556
final  value 79.474556 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.735206 
iter  10 value 93.426851
iter  20 value 87.676426
iter  30 value 83.815189
iter  40 value 80.521481
iter  50 value 80.271935
iter  60 value 80.160825
iter  70 value 80.066356
iter  80 value 79.929660
iter  90 value 79.888522
iter 100 value 79.778296
final  value 79.778296 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.936561 
iter  10 value 96.758797
iter  20 value 87.150988
iter  30 value 84.442123
iter  40 value 83.778185
iter  50 value 83.403324
iter  60 value 81.931525
iter  70 value 81.038084
iter  80 value 80.018931
iter  90 value 79.745426
iter 100 value 79.549163
final  value 79.549163 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.353567 
iter  10 value 94.669987
iter  20 value 93.981977
iter  30 value 90.374433
iter  40 value 86.927562
iter  50 value 85.148063
iter  60 value 82.108584
iter  70 value 80.899747
iter  80 value 80.355093
iter  90 value 80.021888
iter 100 value 79.586069
final  value 79.586069 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.141847 
iter  10 value 94.679835
iter  20 value 84.468599
iter  30 value 83.451018
iter  40 value 83.372776
iter  50 value 81.681375
iter  60 value 80.216895
iter  70 value 79.766190
iter  80 value 79.610589
iter  90 value 79.497712
iter 100 value 79.393876
final  value 79.393876 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.239069 
iter  10 value 95.163304
iter  20 value 92.691854
iter  30 value 86.674127
iter  40 value 84.539127
iter  50 value 83.704687
iter  60 value 83.243860
iter  70 value 82.200441
iter  80 value 81.186429
iter  90 value 80.496485
iter 100 value 79.995576
final  value 79.995576 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.328822 
iter  10 value 91.732374
iter  20 value 91.106937
iter  30 value 86.340283
iter  40 value 81.352410
iter  50 value 80.593939
iter  60 value 80.301773
iter  70 value 79.766642
iter  80 value 79.205522
iter  90 value 79.076759
iter 100 value 78.867674
final  value 78.867674 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.041737 
iter  10 value 94.094162
iter  20 value 93.069579
iter  30 value 92.474099
iter  40 value 84.598255
iter  50 value 83.783119
iter  60 value 83.642604
iter  70 value 81.380870
iter  80 value 80.638754
iter  90 value 80.227445
iter 100 value 79.688084
final  value 79.688084 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.545535 
final  value 94.485796 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.586600 
final  value 94.486301 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.324391 
final  value 94.485858 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.022665 
final  value 94.485923 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.854529 
final  value 94.485463 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.396358 
iter  10 value 94.489105
iter  20 value 94.484454
iter  30 value 93.497623
final  value 93.395473 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.526967 
iter  10 value 94.489151
final  value 94.484213 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.765472 
iter  10 value 93.232535
iter  20 value 93.146457
iter  30 value 93.143670
iter  40 value 93.131334
iter  50 value 84.554081
iter  60 value 82.790391
iter  70 value 82.639304
final  value 82.634841 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.043017 
iter  10 value 94.438851
iter  20 value 93.852504
iter  30 value 92.589059
iter  40 value 81.907455
iter  50 value 81.554006
iter  60 value 81.525892
final  value 81.525807 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.312406 
iter  10 value 94.487315
iter  20 value 92.218668
iter  30 value 85.401097
iter  40 value 85.362424
iter  50 value 85.351120
final  value 85.347745 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.938279 
iter  10 value 92.362591
iter  20 value 92.357816
iter  30 value 91.076099
iter  40 value 82.925759
iter  50 value 82.671906
iter  60 value 82.615474
iter  70 value 82.613611
iter  80 value 82.452397
iter  90 value 82.365826
iter 100 value 82.349504
final  value 82.349504 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.938414 
iter  10 value 94.492781
final  value 94.485204 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.837349 
iter  10 value 93.533223
iter  20 value 93.404930
iter  30 value 93.402534
iter  40 value 93.400313
iter  50 value 93.393173
iter  60 value 92.114561
iter  70 value 86.763045
iter  80 value 86.305022
iter  90 value 85.830762
iter 100 value 85.077522
final  value 85.077522 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.952763 
iter  10 value 94.487639
iter  20 value 94.213569
iter  30 value 87.880099
iter  40 value 87.815206
iter  50 value 87.802625
iter  60 value 86.063043
iter  70 value 81.679701
iter  80 value 81.678137
iter  90 value 81.675644
iter 100 value 80.528289
final  value 80.528289 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.914171 
iter  10 value 94.323734
iter  20 value 92.517701
iter  30 value 92.511342
iter  40 value 92.409746
final  value 92.346106 
converged
Fitting Repeat 1 

# weights:  507
initial  value 130.883404 
iter  10 value 117.908069
iter  20 value 117.885315
iter  30 value 116.432073
iter  40 value 115.188745
iter  50 value 115.184932
iter  60 value 113.704711
iter  70 value 107.233937
iter  80 value 107.009902
iter  90 value 106.913590
iter 100 value 106.905073
final  value 106.905073 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.743804 
iter  10 value 117.898824
iter  20 value 117.770394
iter  30 value 112.112966
iter  40 value 112.107808
iter  50 value 112.058973
iter  60 value 108.529009
iter  70 value 107.477415
iter  80 value 106.229303
iter  90 value 106.184653
iter 100 value 106.184441
final  value 106.184441 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.113473 
iter  10 value 117.898178
iter  20 value 117.688625
iter  30 value 105.526479
iter  40 value 104.285300
final  value 104.284485 
converged
Fitting Repeat 4 

# weights:  507
initial  value 140.003348 
iter  10 value 117.722668
iter  20 value 117.681562
iter  30 value 117.544278
iter  40 value 117.539339
iter  50 value 117.537806
iter  60 value 110.345157
iter  70 value 107.171933
iter  80 value 106.462803
iter  90 value 103.895795
iter 100 value 103.848618
final  value 103.848618 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 168.879686 
iter  10 value 117.900182
iter  20 value 117.891085
iter  30 value 117.861319
iter  40 value 110.796722
iter  50 value 107.006598
iter  60 value 107.004850
final  value 107.004846 
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 Jul 15 21:15:51 2024 
*********************************************** 
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 
 42.505   2.072  43.939