##############################################################################
##############################################################################
###
### 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_1.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/HPiP.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: aarch64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.8.0’
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* 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       54.664  2.296  57.112
FSmethod      53.491  2.132  55.901
corr_plot     51.751  2.440  54.534
pred_ensembel 16.317  0.389  13.827
enrichfindP    0.513  0.080  28.657
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/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/4.3-arm64/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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (64-bit)

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 104.049264 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.487702 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.866829 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.079768 
iter  10 value 91.261674
iter  20 value 90.821890
final  value 90.821486 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.687990 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.264086 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.696761 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.283953 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.781539 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.050817 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.917983 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.365146 
final  value 94.484137 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.395673 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.819333 
iter  10 value 94.354476
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.353168 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.630055 
iter  10 value 94.456155
iter  20 value 88.886954
iter  30 value 86.813104
iter  40 value 86.241168
iter  50 value 86.083284
iter  60 value 86.082450
final  value 86.082428 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.591118 
iter  10 value 94.542628
iter  20 value 94.490689
iter  30 value 94.477634
iter  40 value 88.289082
iter  50 value 87.959666
iter  60 value 87.194084
iter  70 value 85.039024
iter  80 value 84.572191
iter  90 value 84.037322
iter 100 value 83.754617
final  value 83.754617 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.459704 
iter  10 value 94.501649
iter  20 value 89.699889
iter  30 value 86.933057
iter  40 value 86.413954
iter  50 value 86.238089
iter  60 value 86.206394
iter  60 value 86.206394
final  value 86.206394 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.439480 
iter  10 value 94.459641
iter  20 value 93.301448
iter  30 value 87.606533
iter  40 value 86.994352
iter  50 value 86.234548
iter  60 value 86.029046
iter  70 value 85.329288
iter  80 value 85.084147
iter  90 value 85.069967
final  value 85.068001 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.508460 
iter  10 value 94.024030
iter  20 value 90.016580
iter  30 value 86.521506
iter  40 value 85.062543
iter  50 value 84.902798
iter  60 value 84.734745
iter  70 value 84.247864
iter  80 value 83.961790
iter  90 value 83.597918
iter 100 value 83.446436
final  value 83.446436 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.395888 
iter  10 value 94.486808
iter  20 value 92.171980
iter  30 value 87.586003
iter  40 value 86.696617
iter  50 value 85.987242
iter  60 value 85.655338
iter  70 value 85.532161
iter  80 value 84.112911
iter  90 value 83.292447
iter 100 value 83.086115
final  value 83.086115 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.387905 
iter  10 value 93.996791
iter  20 value 89.426466
iter  30 value 89.001445
iter  40 value 83.786279
iter  50 value 83.485435
iter  60 value 83.129209
iter  70 value 82.587735
iter  80 value 82.434123
iter  90 value 82.394069
iter 100 value 82.348588
final  value 82.348588 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.285719 
iter  10 value 94.521611
iter  20 value 91.268630
iter  30 value 89.287521
iter  40 value 87.046446
iter  50 value 86.163638
iter  60 value 85.584452
iter  70 value 85.080419
iter  80 value 85.065083
iter  90 value 84.185558
iter 100 value 83.525219
final  value 83.525219 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.292795 
iter  10 value 94.461827
iter  20 value 91.063121
iter  30 value 87.878167
iter  40 value 86.444420
iter  50 value 82.941757
iter  60 value 82.125783
iter  70 value 81.994539
iter  80 value 81.797539
iter  90 value 81.758422
iter 100 value 81.755187
final  value 81.755187 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.159357 
iter  10 value 93.915355
iter  20 value 88.257781
iter  30 value 84.364408
iter  40 value 83.525101
iter  50 value 83.008450
iter  60 value 82.652174
iter  70 value 82.526826
iter  80 value 82.501107
iter  90 value 82.467061
iter 100 value 82.285751
final  value 82.285751 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.859580 
iter  10 value 94.662752
iter  20 value 90.951469
iter  30 value 86.687669
iter  40 value 86.616591
iter  50 value 85.340540
iter  60 value 84.653648
iter  70 value 83.599806
iter  80 value 83.347133
iter  90 value 82.959504
iter 100 value 82.639559
final  value 82.639559 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.323281 
iter  10 value 99.743430
iter  20 value 97.574453
iter  30 value 94.547643
iter  40 value 94.255897
iter  50 value 85.618582
iter  60 value 83.792098
iter  70 value 83.461683
iter  80 value 83.301761
iter  90 value 82.814876
iter 100 value 82.631858
final  value 82.631858 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.894492 
iter  10 value 93.596282
iter  20 value 86.823970
iter  30 value 85.701146
iter  40 value 85.178628
iter  50 value 84.783219
iter  60 value 84.257984
iter  70 value 84.008020
iter  80 value 83.356010
iter  90 value 82.724592
iter 100 value 82.668511
final  value 82.668511 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.850674 
iter  10 value 94.923375
iter  20 value 92.402144
iter  30 value 88.435828
iter  40 value 85.833936
iter  50 value 83.943457
iter  60 value 83.073175
iter  70 value 82.613848
iter  80 value 82.513120
iter  90 value 82.227474
iter 100 value 82.112141
final  value 82.112141 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.336421 
iter  10 value 94.873100
iter  20 value 94.331815
iter  30 value 87.305572
iter  40 value 86.190584
iter  50 value 86.101006
iter  60 value 86.030301
iter  70 value 84.887276
iter  80 value 83.022221
iter  90 value 82.515613
iter 100 value 82.412833
final  value 82.412833 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.947956 
final  value 94.485832 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.250836 
final  value 94.048304 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.218066 
final  value 94.486002 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.659944 
iter  10 value 94.485191
iter  20 value 93.785449
iter  30 value 93.277264
iter  40 value 86.561439
iter  50 value 85.988399
iter  60 value 85.988309
final  value 85.988184 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.434140 
final  value 94.485806 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.063692 
iter  10 value 94.489162
iter  20 value 94.460889
iter  30 value 94.354492
iter  30 value 94.354492
iter  30 value 94.354492
final  value 94.354492 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.119672 
iter  10 value 94.489229
iter  20 value 92.496163
iter  30 value 86.640220
iter  30 value 86.640219
iter  30 value 86.640219
final  value 86.640219 
converged
Fitting Repeat 3 

# weights:  305
initial  value 122.477001 
iter  10 value 94.359089
iter  20 value 94.355982
final  value 94.355119 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.555462 
iter  10 value 94.489210
iter  20 value 94.484215
iter  30 value 93.561462
iter  40 value 90.181361
iter  50 value 87.752546
iter  60 value 87.749210
iter  70 value 85.041414
iter  80 value 84.997023
iter  90 value 84.996796
iter 100 value 84.996448
final  value 84.996448 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.963330 
iter  10 value 93.786362
iter  20 value 93.783571
iter  30 value 93.781655
iter  40 value 88.041399
iter  50 value 84.804418
iter  60 value 81.501915
iter  70 value 81.412014
iter  80 value 81.382407
iter  90 value 81.380988
iter 100 value 81.380767
final  value 81.380767 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.611334 
iter  10 value 94.362697
iter  20 value 94.322238
iter  30 value 88.941130
iter  40 value 88.556102
iter  50 value 88.523512
iter  60 value 87.211998
iter  70 value 87.134844
iter  80 value 85.992303
iter  90 value 85.463762
iter 100 value 85.422231
final  value 85.422231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.188784 
iter  10 value 94.362624
iter  20 value 94.354783
iter  30 value 88.240514
iter  40 value 86.150486
iter  50 value 85.992164
iter  60 value 85.010361
iter  70 value 84.946666
iter  80 value 84.103905
iter  90 value 83.934068
iter 100 value 83.657835
final  value 83.657835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.167188 
iter  10 value 94.491992
iter  20 value 94.389731
iter  30 value 86.532044
iter  40 value 84.253036
iter  50 value 84.076553
iter  60 value 83.438672
iter  70 value 83.437983
iter  80 value 82.854925
iter  90 value 82.713047
iter 100 value 82.697942
final  value 82.697942 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.025831 
iter  10 value 94.361967
iter  20 value 94.353595
iter  30 value 94.179145
iter  40 value 91.658415
iter  50 value 86.802887
iter  60 value 86.284128
iter  70 value 85.946393
iter  80 value 85.875928
iter  90 value 85.353259
iter 100 value 84.344162
final  value 84.344162 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.764385 
iter  10 value 91.698958
iter  20 value 86.766154
iter  30 value 86.688122
iter  40 value 86.684175
iter  50 value 86.680700
iter  60 value 85.836730
iter  70 value 85.817730
iter  80 value 85.815564
iter  90 value 85.656274
final  value 85.654508 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.284153 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.666173 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.809909 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 118.636458 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.969472 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.274723 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.691118 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.888689 
iter  10 value 94.290491
iter  20 value 83.262952
iter  30 value 83.240200
iter  40 value 83.239538
final  value 83.239527 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.116439 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.289349 
iter  10 value 94.135765
final  value 94.132578 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.721554 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.597862 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.937972 
iter  10 value 94.452050
iter  20 value 85.810036
iter  30 value 82.323212
iter  40 value 82.311723
final  value 82.311690 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.922320 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 139.909360 
iter  10 value 94.919511
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.537180 
iter  10 value 94.406046
iter  20 value 86.314276
iter  30 value 85.323278
iter  40 value 84.100137
iter  50 value 83.866720
iter  60 value 83.119273
iter  70 value 83.072927
final  value 83.072923 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.737752 
iter  10 value 94.368060
iter  20 value 91.984500
iter  30 value 90.418650
iter  40 value 87.770901
iter  50 value 83.374210
iter  60 value 80.683066
iter  70 value 79.504112
iter  80 value 79.119994
iter  90 value 78.968977
iter 100 value 78.876991
final  value 78.876991 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.939850 
iter  10 value 94.478913
iter  20 value 88.434350
iter  30 value 87.607356
iter  40 value 85.685861
iter  50 value 82.423445
iter  60 value 81.892098
iter  70 value 81.606069
iter  80 value 81.582514
final  value 81.582489 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.325751 
iter  10 value 94.488251
iter  20 value 94.401224
iter  30 value 84.477180
iter  40 value 83.540575
iter  50 value 82.893703
iter  60 value 81.798017
iter  70 value 81.597106
final  value 81.582546 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.527801 
iter  10 value 93.321074
iter  20 value 83.596962
iter  30 value 82.626961
iter  40 value 82.404552
iter  50 value 82.341770
iter  60 value 81.836100
iter  70 value 81.327156
final  value 81.313727 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.009766 
iter  10 value 94.260305
iter  20 value 86.151724
iter  30 value 82.227096
iter  40 value 81.606186
iter  50 value 81.381001
iter  60 value 80.681575
iter  70 value 79.748969
iter  80 value 78.113733
iter  90 value 77.787286
iter 100 value 77.725665
final  value 77.725665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.327769 
iter  10 value 87.716654
iter  20 value 85.458762
iter  30 value 84.635988
iter  40 value 82.068084
iter  50 value 81.744379
iter  60 value 81.465520
iter  70 value 78.870817
iter  80 value 78.048275
iter  90 value 77.452946
iter 100 value 77.064477
final  value 77.064477 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.905855 
iter  10 value 93.351719
iter  20 value 86.432441
iter  30 value 83.578180
iter  40 value 82.762315
iter  50 value 81.211512
iter  60 value 81.166792
iter  70 value 80.614234
iter  80 value 77.884719
iter  90 value 77.579449
iter 100 value 77.436217
final  value 77.436217 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.600958 
iter  10 value 86.834487
iter  20 value 79.991733
iter  30 value 78.455834
iter  40 value 77.849172
iter  50 value 77.287007
iter  60 value 76.659352
iter  70 value 76.612136
iter  80 value 76.554764
iter  90 value 76.529603
iter 100 value 76.500298
final  value 76.500298 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.836639 
iter  10 value 94.202154
iter  20 value 88.811329
iter  30 value 85.209012
iter  40 value 82.839026
iter  50 value 80.015338
iter  60 value 79.474501
iter  70 value 79.221143
iter  80 value 78.360234
iter  90 value 77.606424
iter 100 value 77.534002
final  value 77.534002 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.221329 
iter  10 value 92.689251
iter  20 value 83.693278
iter  30 value 83.503325
iter  40 value 83.264579
iter  50 value 80.032348
iter  60 value 78.372825
iter  70 value 77.734081
iter  80 value 77.337666
iter  90 value 77.236725
iter 100 value 76.736000
final  value 76.736000 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.451065 
iter  10 value 87.844157
iter  20 value 85.033312
iter  30 value 85.002695
iter  40 value 84.529784
iter  50 value 82.023667
iter  60 value 80.677660
iter  70 value 80.195945
iter  80 value 79.499895
iter  90 value 79.121943
iter 100 value 78.798763
final  value 78.798763 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.514794 
iter  10 value 94.463088
iter  20 value 86.745211
iter  30 value 82.583371
iter  40 value 80.809408
iter  50 value 79.248907
iter  60 value 78.526199
iter  70 value 78.269293
iter  80 value 77.900599
iter  90 value 77.572807
iter 100 value 77.487751
final  value 77.487751 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 139.582360 
iter  10 value 94.544118
iter  20 value 87.727477
iter  30 value 84.363589
iter  40 value 82.528569
iter  50 value 81.652347
iter  60 value 81.342012
iter  70 value 79.987810
iter  80 value 79.435765
iter  90 value 78.530135
iter 100 value 77.676461
final  value 77.676461 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.248784 
iter  10 value 96.425834
iter  20 value 87.884402
iter  30 value 83.531630
iter  40 value 79.686704
iter  50 value 78.854668
iter  60 value 78.363942
iter  70 value 78.158877
iter  80 value 77.246786
iter  90 value 76.816229
iter 100 value 76.734775
final  value 76.734775 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.984526 
final  value 94.485871 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.342799 
final  value 94.485927 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.778181 
final  value 94.485759 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.988401 
final  value 94.485791 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.915866 
final  value 94.485903 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.977614 
iter  10 value 94.491750
iter  20 value 94.486438
final  value 94.486419 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.596929 
iter  10 value 94.488748
iter  20 value 94.088528
iter  30 value 83.905687
iter  40 value 83.899618
iter  50 value 83.898366
iter  60 value 83.897235
iter  70 value 83.895258
iter  80 value 83.885261
iter  90 value 83.882695
iter 100 value 83.258103
final  value 83.258103 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.175448 
iter  10 value 94.359492
iter  20 value 94.354923
final  value 94.354522 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.211066 
iter  10 value 94.151886
iter  20 value 94.140175
iter  30 value 94.135625
iter  40 value 94.134866
iter  50 value 94.133025
final  value 94.133020 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.580083 
iter  10 value 93.115712
iter  20 value 93.055083
iter  30 value 81.240341
iter  40 value 80.273309
iter  50 value 80.262499
iter  60 value 80.262126
iter  70 value 80.249146
iter  80 value 78.598921
iter  90 value 77.323761
iter 100 value 77.309083
final  value 77.309083 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.005057 
iter  10 value 94.362811
iter  20 value 94.356151
final  value 94.355363 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.381569 
iter  10 value 94.491678
iter  20 value 92.787407
iter  30 value 92.453651
iter  40 value 91.318519
iter  50 value 91.271748
iter  60 value 91.270046
final  value 91.270028 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.263834 
iter  10 value 93.405798
iter  20 value 86.230995
iter  30 value 82.433683
iter  40 value 82.335778
iter  50 value 82.297761
iter  60 value 82.296022
iter  70 value 82.295876
iter  80 value 82.126562
iter  90 value 81.605344
iter 100 value 81.547412
final  value 81.547412 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.720047 
iter  10 value 94.488848
iter  20 value 94.075391
iter  30 value 93.016238
iter  40 value 93.015464
iter  50 value 93.015242
iter  60 value 93.015198
final  value 93.015122 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.829564 
iter  10 value 94.167739
iter  20 value 94.146316
iter  30 value 94.144940
iter  40 value 93.952392
iter  50 value 83.518192
iter  60 value 83.243137
iter  70 value 83.237469
iter  80 value 83.217102
iter  90 value 82.881937
iter 100 value 79.162045
final  value 79.162045 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.080473 
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.147837 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.300570 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.370123 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.570054 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.480216 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.749563 
iter  10 value 93.284198
final  value 93.279878 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.075936 
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.289539 
iter  10 value 93.328420
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.233444 
final  value 94.042012 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.196806 
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.721789 
final  value 94.011428 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.831526 
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.288884 
iter  10 value 89.993719
iter  20 value 86.344482
iter  20 value 86.344482
iter  20 value 86.344482
final  value 86.344482 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.638513 
iter  10 value 93.328261
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.184550 
iter  10 value 94.045309
iter  20 value 84.113387
iter  30 value 83.263567
iter  40 value 83.011913
iter  50 value 82.818681
iter  60 value 82.675928
iter  70 value 82.624499
final  value 82.622871 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.298596 
iter  10 value 94.062553
iter  20 value 93.591757
iter  30 value 92.770503
iter  40 value 89.886458
iter  50 value 83.954446
iter  60 value 82.404655
iter  70 value 82.294627
iter  80 value 82.160255
iter  90 value 81.221471
iter 100 value 80.949295
final  value 80.949295 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.609341 
iter  10 value 94.052364
iter  20 value 93.870641
iter  30 value 90.604189
iter  40 value 88.729432
iter  50 value 85.536113
iter  60 value 85.017264
iter  70 value 82.285062
iter  80 value 81.553858
iter  90 value 81.505335
iter 100 value 81.225388
final  value 81.225388 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.591333 
iter  10 value 94.057324
iter  20 value 94.021558
iter  30 value 93.441791
iter  40 value 93.197088
iter  50 value 93.107405
iter  60 value 85.384492
iter  70 value 83.960323
iter  80 value 83.261756
iter  90 value 83.121561
iter 100 value 82.276610
final  value 82.276610 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.169442 
iter  10 value 94.059603
iter  20 value 94.035833
iter  30 value 93.685828
iter  40 value 89.785022
iter  50 value 84.696543
iter  60 value 83.123700
iter  70 value 83.053881
iter  80 value 82.638327
iter  90 value 82.622881
final  value 82.622875 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.983926 
iter  10 value 94.015124
iter  20 value 93.744201
iter  30 value 87.476193
iter  40 value 86.022178
iter  50 value 85.579704
iter  60 value 83.206069
iter  70 value 80.880291
iter  80 value 80.388931
iter  90 value 80.182259
iter 100 value 80.040814
final  value 80.040814 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.458646 
iter  10 value 93.915447
iter  20 value 93.313243
iter  30 value 92.985146
iter  40 value 84.818051
iter  50 value 83.885146
iter  60 value 83.447988
iter  70 value 81.504522
iter  80 value 81.064355
iter  90 value 80.149719
iter 100 value 80.039459
final  value 80.039459 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.073530 
iter  10 value 91.131574
iter  20 value 87.044481
iter  30 value 84.840353
iter  40 value 83.976144
iter  50 value 82.594042
iter  60 value 82.294779
iter  70 value 82.001761
iter  80 value 81.630079
iter  90 value 81.518318
iter 100 value 81.516866
final  value 81.516866 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.762860 
iter  10 value 94.329118
iter  20 value 92.309204
iter  30 value 90.357273
iter  40 value 87.526992
iter  50 value 86.133226
iter  60 value 85.279752
iter  70 value 83.585101
iter  80 value 81.214445
iter  90 value 79.988285
iter 100 value 79.414045
final  value 79.414045 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.759233 
iter  10 value 93.681807
iter  20 value 87.191303
iter  30 value 85.728608
iter  40 value 84.241218
iter  50 value 82.209634
iter  60 value 81.936661
iter  70 value 81.622965
iter  80 value 81.292721
iter  90 value 81.038310
iter 100 value 80.478547
final  value 80.478547 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.322655 
iter  10 value 96.253980
iter  20 value 94.106487
iter  30 value 94.042794
iter  40 value 92.509935
iter  50 value 87.678024
iter  60 value 86.254297
iter  70 value 86.206361
iter  80 value 85.922111
iter  90 value 85.741465
iter 100 value 85.038043
final  value 85.038043 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.210586 
iter  10 value 94.730973
iter  20 value 93.628902
iter  30 value 87.252224
iter  40 value 86.202406
iter  50 value 85.496147
iter  60 value 84.414020
iter  70 value 81.496227
iter  80 value 80.682967
iter  90 value 80.452424
iter 100 value 79.959245
final  value 79.959245 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 140.695295 
iter  10 value 94.186715
iter  20 value 89.567612
iter  30 value 84.621554
iter  40 value 83.490090
iter  50 value 81.618740
iter  60 value 81.019418
iter  70 value 80.294637
iter  80 value 80.081141
iter  90 value 79.893534
iter 100 value 79.811675
final  value 79.811675 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.887408 
iter  10 value 96.557235
iter  20 value 95.431849
iter  30 value 89.846345
iter  40 value 85.850554
iter  50 value 85.199686
iter  60 value 84.727038
iter  70 value 82.108837
iter  80 value 81.092150
iter  90 value 80.692962
iter 100 value 80.639094
final  value 80.639094 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.587250 
iter  10 value 94.075179
iter  20 value 93.850030
iter  30 value 90.702887
iter  40 value 85.297093
iter  50 value 83.328338
iter  60 value 82.754723
iter  70 value 81.003274
iter  80 value 80.691282
iter  90 value 80.439715
iter 100 value 80.114418
final  value 80.114418 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.192156 
final  value 94.054348 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.243524 
final  value 94.054490 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.012921 
final  value 94.054635 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.875402 
final  value 94.054761 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.385524 
final  value 94.054898 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.915234 
iter  10 value 94.057834
iter  20 value 94.053354
iter  30 value 93.603919
iter  40 value 93.387104
iter  50 value 93.256898
iter  60 value 92.933801
iter  70 value 89.917119
iter  80 value 89.369984
iter  90 value 88.676917
iter 100 value 88.199464
final  value 88.199464 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.396266 
iter  10 value 94.057581
iter  20 value 94.052903
iter  30 value 94.043362
final  value 94.043275 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.025384 
iter  10 value 92.055944
iter  20 value 82.997562
iter  30 value 82.981153
iter  40 value 82.979187
iter  50 value 82.977187
iter  60 value 81.567361
iter  70 value 81.162169
iter  80 value 81.161317
iter  90 value 80.686902
iter 100 value 79.279017
final  value 79.279017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.954029 
iter  10 value 94.054286
iter  20 value 94.052970
iter  30 value 93.488174
iter  40 value 93.283940
iter  50 value 86.809836
iter  60 value 84.022651
iter  70 value 82.982907
final  value 82.972160 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.831605 
iter  10 value 93.802510
iter  20 value 93.684479
iter  30 value 93.640446
iter  40 value 93.621122
iter  50 value 87.777649
iter  60 value 85.457654
iter  70 value 82.953704
iter  80 value 81.350696
iter  90 value 81.299849
iter 100 value 81.150872
final  value 81.150872 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.178062 
iter  10 value 94.060096
iter  20 value 85.370417
iter  30 value 85.088175
iter  40 value 84.981649
iter  50 value 84.522611
iter  60 value 82.891515
iter  70 value 82.873576
iter  80 value 82.434892
iter  90 value 82.062994
iter 100 value 82.048528
final  value 82.048528 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.113813 
iter  10 value 93.253789
iter  20 value 93.005312
iter  30 value 92.757341
iter  40 value 92.754779
iter  50 value 92.754292
iter  60 value 91.364766
iter  70 value 91.064949
iter  80 value 91.064413
iter  90 value 90.926300
iter 100 value 90.599408
final  value 90.599408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.512627 
iter  10 value 94.025322
iter  20 value 94.024610
iter  30 value 94.022028
iter  40 value 87.865596
iter  50 value 84.679572
iter  60 value 82.646582
iter  70 value 81.180236
iter  80 value 80.349575
iter  90 value 80.008344
iter 100 value 79.867417
final  value 79.867417 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.141585 
iter  10 value 94.060822
iter  20 value 94.022091
iter  30 value 92.242712
iter  40 value 91.690124
iter  50 value 91.688706
iter  60 value 87.275644
iter  70 value 87.218430
iter  80 value 86.591765
iter  90 value 86.122331
iter 100 value 85.868614
final  value 85.868614 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.987941 
iter  10 value 94.061412
iter  20 value 93.913921
iter  30 value 87.451214
iter  40 value 84.936297
final  value 84.934535 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.125736 
iter  10 value 93.659814
final  value 93.578672 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.396360 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.812929 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.953505 
iter  10 value 93.533314
iter  20 value 93.421827
final  value 93.421697 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.656995 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.707056 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.609772 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.139034 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.974931 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.112821 
iter  10 value 93.266611
final  value 93.224692 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.383047 
final  value 93.636782 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.018806 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 132.853864 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.407602 
final  value 94.000449 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.772864 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.787608 
iter  10 value 93.981804
iter  20 value 83.911012
iter  30 value 83.234998
iter  40 value 83.156997
iter  50 value 81.831880
iter  60 value 80.733983
iter  70 value 80.466139
iter  80 value 80.371115
iter  90 value 80.308344
final  value 80.305501 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.764999 
iter  10 value 94.055070
iter  20 value 84.884025
iter  30 value 84.016772
iter  40 value 83.845646
iter  50 value 82.849247
iter  60 value 82.251095
final  value 82.250103 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.587829 
iter  10 value 94.054980
iter  20 value 93.360721
iter  30 value 88.593746
iter  40 value 84.286007
iter  50 value 83.497995
iter  60 value 82.791017
iter  70 value 82.319859
iter  80 value 82.252746
iter  90 value 82.250103
iter  90 value 82.250102
iter  90 value 82.250102
final  value 82.250102 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.167458 
iter  10 value 94.058463
iter  20 value 94.054809
iter  30 value 89.225819
iter  40 value 85.960579
iter  50 value 83.128966
iter  60 value 82.354099
iter  70 value 82.255480
iter  80 value 82.227682
final  value 82.227278 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.044452 
iter  10 value 93.983237
iter  20 value 87.940890
iter  30 value 83.902463
iter  40 value 83.051946
iter  50 value 81.738290
iter  60 value 80.518322
iter  70 value 80.454303
iter  80 value 80.432329
iter  90 value 80.336256
iter 100 value 80.305504
final  value 80.305504 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.101687 
iter  10 value 92.567297
iter  20 value 83.972348
iter  30 value 83.890470
iter  40 value 83.274258
iter  50 value 81.841439
iter  60 value 80.703017
iter  70 value 80.352407
iter  80 value 80.199172
iter  90 value 80.130797
iter 100 value 80.093180
final  value 80.093180 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.162274 
iter  10 value 92.134484
iter  20 value 85.581500
iter  30 value 85.070318
iter  40 value 83.028446
iter  50 value 82.297675
iter  60 value 81.340023
iter  70 value 80.801583
iter  80 value 80.109468
iter  90 value 79.916850
iter 100 value 79.549005
final  value 79.549005 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.048818 
iter  10 value 94.164942
iter  20 value 94.069891
iter  30 value 93.960063
iter  40 value 91.346728
iter  50 value 84.415193
iter  60 value 82.471562
iter  70 value 81.894684
iter  80 value 79.895978
iter  90 value 79.363527
iter 100 value 79.120427
final  value 79.120427 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.485079 
iter  10 value 92.673367
iter  20 value 87.679534
iter  30 value 85.646382
iter  40 value 82.897931
iter  50 value 81.019671
iter  60 value 79.831575
iter  70 value 79.676670
iter  80 value 79.647726
iter  90 value 79.616209
iter 100 value 79.575549
final  value 79.575549 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.719110 
iter  10 value 93.958422
iter  20 value 87.056299
iter  30 value 86.375803
iter  40 value 84.318483
iter  50 value 82.318373
iter  60 value 82.155882
iter  70 value 82.080911
iter  80 value 81.646879
iter  90 value 81.309704
iter 100 value 81.210206
final  value 81.210206 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.116483 
iter  10 value 95.947777
iter  20 value 93.789226
iter  30 value 83.948626
iter  40 value 80.765479
iter  50 value 79.892643
iter  60 value 79.471519
iter  70 value 78.900795
iter  80 value 78.728647
iter  90 value 78.486775
iter 100 value 78.434675
final  value 78.434675 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.691812 
iter  10 value 93.979239
iter  20 value 87.220539
iter  30 value 84.712964
iter  40 value 82.866428
iter  50 value 82.581171
iter  60 value 81.775353
iter  70 value 81.401301
iter  80 value 81.225762
iter  90 value 81.192217
iter 100 value 81.022239
final  value 81.022239 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 150.505091 
iter  10 value 95.063289
iter  20 value 84.244417
iter  30 value 82.370331
iter  40 value 82.169987
iter  50 value 80.864771
iter  60 value 80.537264
iter  70 value 80.366112
iter  80 value 80.224056
iter  90 value 79.506108
iter 100 value 79.289391
final  value 79.289391 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.038966 
iter  10 value 89.899336
iter  20 value 84.312464
iter  30 value 83.276599
iter  40 value 82.645596
iter  50 value 82.014245
iter  60 value 81.870096
iter  70 value 81.628549
iter  80 value 80.225986
iter  90 value 79.660469
iter 100 value 79.309311
final  value 79.309311 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.235632 
iter  10 value 93.767177
iter  20 value 93.626078
iter  30 value 91.541381
iter  40 value 87.089919
iter  50 value 85.502093
iter  60 value 82.672552
iter  70 value 81.165607
iter  80 value 80.263044
iter  90 value 79.374047
iter 100 value 79.106736
final  value 79.106736 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.195294 
iter  10 value 94.054548
iter  20 value 94.051160
iter  30 value 93.518175
final  value 93.518148 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.863602 
final  value 94.054516 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.827293 
final  value 94.054613 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.658108 
final  value 94.054741 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.615729 
final  value 94.054648 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.445715 
iter  10 value 94.059562
iter  20 value 94.054721
iter  30 value 84.376607
iter  40 value 83.300999
iter  50 value 83.096898
final  value 83.096564 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.538674 
iter  10 value 94.057755
iter  20 value 94.052974
iter  30 value 93.978476
iter  40 value 93.519861
iter  50 value 93.518077
iter  50 value 93.518077
iter  50 value 93.518077
final  value 93.518077 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.167275 
iter  10 value 93.677364
iter  20 value 92.074385
iter  30 value 92.036208
iter  40 value 91.752090
iter  50 value 91.736817
final  value 91.735281 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.943235 
iter  10 value 94.057868
iter  20 value 93.998395
iter  30 value 83.301422
final  value 83.296979 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.321148 
iter  10 value 93.877608
iter  20 value 93.875173
iter  30 value 93.869776
iter  40 value 93.868873
iter  50 value 88.040200
iter  60 value 88.008537
iter  70 value 84.672352
iter  80 value 84.590473
iter  90 value 84.570269
iter 100 value 84.563494
final  value 84.563494 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.346401 
iter  10 value 94.059722
iter  20 value 94.012318
iter  30 value 93.536940
iter  40 value 91.740018
iter  50 value 82.176675
iter  60 value 81.471106
final  value 81.460605 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.819799 
iter  10 value 94.061820
iter  20 value 94.053094
iter  30 value 83.734713
iter  40 value 80.995136
iter  50 value 80.898785
iter  60 value 80.892781
iter  70 value 80.885239
iter  80 value 80.878393
iter  90 value 80.855204
iter 100 value 80.718773
final  value 80.718773 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.795193 
iter  10 value 94.056976
final  value 94.053572 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.626642 
iter  10 value 87.247042
iter  20 value 87.241960
iter  30 value 87.163475
iter  40 value 85.153335
iter  50 value 85.088006
iter  60 value 85.087626
iter  70 value 83.035822
iter  80 value 82.874933
iter  90 value 80.519546
iter 100 value 79.280377
final  value 79.280377 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.841760 
iter  10 value 87.156820
iter  20 value 86.326933
iter  30 value 84.330487
iter  40 value 82.642620
iter  50 value 80.777651
iter  60 value 80.338868
final  value 80.332580 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.765666 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.795300 
iter  10 value 94.026546
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.156384 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.411413 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.684647 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.066495 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.025427 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.550549 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.886285 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.721166 
iter  10 value 94.026556
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.154614 
iter  10 value 93.581769
final  value 93.581395 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.595580 
final  value 93.047059 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.237453 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.961758 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.732247 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.702450 
iter  10 value 93.508160
iter  20 value 89.296563
iter  30 value 87.082426
iter  40 value 85.418110
iter  50 value 84.544107
iter  60 value 84.342139
iter  70 value 84.262746
final  value 84.248079 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.467294 
iter  10 value 94.458760
iter  20 value 93.998118
iter  30 value 93.887435
iter  40 value 88.049697
iter  50 value 86.833247
iter  60 value 85.986005
iter  70 value 84.438409
iter  80 value 84.179911
final  value 84.178164 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.191652 
iter  10 value 94.444825
iter  20 value 90.911862
iter  30 value 88.245960
iter  40 value 87.991098
iter  50 value 87.768987
iter  60 value 87.523813
final  value 87.523170 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.247611 
iter  10 value 94.435814
iter  20 value 93.903437
iter  30 value 93.741409
iter  40 value 87.504767
iter  50 value 87.031028
iter  60 value 85.605472
iter  70 value 85.264566
final  value 85.260084 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.820068 
iter  10 value 94.549704
iter  20 value 91.198013
iter  30 value 87.500096
iter  40 value 87.230626
iter  50 value 86.708456
iter  60 value 85.584727
iter  70 value 85.319215
iter  80 value 85.260127
final  value 85.260084 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.167305 
iter  10 value 94.389980
iter  20 value 93.701304
iter  30 value 88.047319
iter  40 value 87.296352
iter  50 value 85.387944
iter  60 value 84.989485
iter  70 value 84.434704
iter  80 value 84.320108
iter  90 value 84.132676
iter 100 value 83.586520
final  value 83.586520 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.687578 
iter  10 value 93.945915
iter  20 value 92.284184
iter  30 value 87.233175
iter  40 value 86.797311
iter  50 value 85.871227
iter  60 value 84.435305
iter  70 value 84.215071
iter  80 value 84.070827
iter  90 value 83.946007
iter 100 value 83.796739
final  value 83.796739 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.474218 
iter  10 value 94.604484
iter  20 value 94.138714
iter  30 value 94.115128
iter  40 value 93.841517
iter  50 value 91.300094
iter  60 value 90.698407
iter  70 value 89.894732
iter  80 value 86.585030
iter  90 value 84.760655
iter 100 value 84.007121
final  value 84.007121 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.937311 
iter  10 value 94.903201
iter  20 value 94.323426
iter  30 value 94.090521
iter  40 value 89.177013
iter  50 value 88.054563
iter  60 value 87.582940
iter  70 value 86.752429
iter  80 value 85.380483
iter  90 value 84.128268
iter 100 value 84.012410
final  value 84.012410 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.635324 
iter  10 value 94.779152
iter  20 value 92.068938
iter  30 value 89.010087
iter  40 value 88.591917
iter  50 value 87.531896
iter  60 value 87.442129
iter  70 value 87.379027
iter  80 value 86.595519
iter  90 value 85.322936
iter 100 value 84.364011
final  value 84.364011 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.205576 
iter  10 value 94.643073
iter  20 value 94.034342
iter  30 value 88.716284
iter  40 value 87.706223
iter  50 value 86.643354
iter  60 value 84.549116
iter  70 value 84.285286
iter  80 value 84.007638
iter  90 value 83.611419
iter 100 value 83.505023
final  value 83.505023 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.900191 
iter  10 value 94.440157
iter  20 value 91.195355
iter  30 value 87.526683
iter  40 value 86.585270
iter  50 value 85.756197
iter  60 value 85.118659
iter  70 value 84.971080
iter  80 value 84.639190
iter  90 value 83.945632
iter 100 value 83.808752
final  value 83.808752 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.276452 
iter  10 value 95.363023
iter  20 value 93.188416
iter  30 value 87.234840
iter  40 value 85.671295
iter  50 value 84.710326
iter  60 value 84.437013
iter  70 value 84.190660
iter  80 value 84.032901
iter  90 value 83.963477
iter 100 value 83.892847
final  value 83.892847 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.432901 
iter  10 value 97.350423
iter  20 value 91.927879
iter  30 value 88.937165
iter  40 value 87.432188
iter  50 value 87.174784
iter  60 value 87.121539
iter  70 value 86.972015
iter  80 value 85.851672
iter  90 value 84.759849
iter 100 value 84.107530
final  value 84.107530 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.657921 
iter  10 value 92.166166
iter  20 value 87.860570
iter  30 value 87.197539
iter  40 value 86.474871
iter  50 value 85.834236
iter  60 value 85.072138
iter  70 value 84.252824
iter  80 value 83.888501
iter  90 value 83.692679
iter 100 value 83.531349
final  value 83.531349 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.968992 
final  value 94.486072 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.820017 
final  value 94.485915 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.621068 
final  value 94.485623 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.283090 
final  value 94.485705 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.669779 
iter  10 value 94.485807
iter  20 value 94.470027
iter  30 value 87.391099
final  value 87.334264 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.678488 
iter  10 value 94.489273
iter  20 value 94.480400
iter  30 value 93.980294
final  value 93.976431 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.348793 
iter  10 value 94.489334
iter  20 value 94.484255
iter  30 value 93.991056
final  value 93.976414 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.744748 
iter  10 value 94.488562
iter  20 value 93.680914
iter  30 value 93.152846
iter  40 value 93.150120
iter  50 value 93.147535
iter  60 value 92.729153
iter  70 value 92.564043
iter  80 value 92.549464
iter  90 value 91.698122
iter 100 value 91.019392
final  value 91.019392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.740138 
iter  10 value 93.551793
iter  20 value 93.548738
iter  30 value 92.093761
iter  40 value 89.060124
iter  50 value 88.987231
iter  60 value 88.258619
iter  70 value 86.552009
iter  80 value 84.493883
iter  90 value 84.390264
iter 100 value 84.192128
final  value 84.192128 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.928505 
iter  10 value 88.800437
iter  20 value 88.760028
iter  30 value 88.633873
iter  40 value 88.630985
final  value 88.630916 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.727280 
iter  10 value 94.492202
iter  20 value 94.455388
iter  30 value 89.752974
iter  40 value 89.398690
iter  50 value 87.256426
iter  60 value 87.112802
iter  70 value 86.911162
iter  80 value 86.810239
iter  90 value 86.807585
iter 100 value 86.804837
final  value 86.804837 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.080698 
iter  10 value 94.034593
iter  20 value 94.029099
iter  30 value 91.529271
iter  40 value 88.384036
iter  50 value 88.223622
iter  60 value 88.218270
iter  70 value 88.217725
iter  80 value 88.215816
iter  90 value 88.048997
iter 100 value 86.687383
final  value 86.687383 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.733246 
iter  10 value 94.491951
iter  20 value 94.478162
iter  30 value 94.028570
iter  40 value 94.028281
final  value 94.028120 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.497646 
iter  10 value 94.490605
iter  20 value 94.434586
iter  30 value 88.654453
iter  40 value 88.014908
iter  50 value 86.669575
iter  60 value 85.640421
iter  70 value 85.617880
iter  80 value 85.617466
iter  90 value 84.781885
iter 100 value 84.508037
final  value 84.508037 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.090389 
iter  10 value 94.457249
iter  20 value 94.431853
iter  30 value 92.117451
iter  40 value 86.506017
iter  50 value 85.799490
iter  60 value 85.610781
iter  70 value 83.393069
iter  80 value 83.100700
iter  90 value 83.099491
iter 100 value 82.920230
final  value 82.920230 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 135.737373 
iter  10 value 117.612927
iter  20 value 108.693033
iter  30 value 103.776189
iter  40 value 102.998839
iter  50 value 101.981664
iter  60 value 101.844239
iter  70 value 101.676279
iter  80 value 101.466168
iter  90 value 101.175813
iter 100 value 100.954722
final  value 100.954722 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.463415 
iter  10 value 117.936835
iter  20 value 116.872980
iter  30 value 112.742371
iter  40 value 112.322616
iter  50 value 108.615074
iter  60 value 107.270997
iter  70 value 106.057797
iter  80 value 105.649325
iter  90 value 105.233993
iter 100 value 104.656722
final  value 104.656722 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 142.491803 
iter  10 value 117.689344
iter  20 value 110.377908
iter  30 value 109.156429
iter  40 value 108.502449
iter  50 value 106.384254
iter  60 value 105.147365
iter  70 value 105.040680
iter  80 value 104.770022
iter  90 value 102.636010
iter 100 value 101.103957
final  value 101.103957 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 141.266980 
iter  10 value 118.216770
iter  20 value 110.096772
iter  30 value 104.397938
iter  40 value 103.096532
iter  50 value 102.472685
iter  60 value 102.325791
iter  70 value 102.315354
iter  80 value 102.117057
iter  90 value 102.112619
iter 100 value 102.106831
final  value 102.106831 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 127.743434 
iter  10 value 117.927768
iter  20 value 116.983318
iter  30 value 109.549819
iter  40 value 108.241325
iter  50 value 105.193554
iter  60 value 104.952790
iter  70 value 104.812673
iter  80 value 104.662131
iter  90 value 104.007151
iter 100 value 102.398940
final  value 102.398940 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Apr 17 16:37:24 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 
 45.834   1.193  67.807