##############################################################################
##############################################################################
###
### 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 4.4.0 Patched (2024-04-24 r86482)
* 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 12.7.4
* 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       52.930  1.803  64.493
corr_plot     51.246  1.786  58.753
FSmethod      50.622  2.119  57.948
pred_ensembel 25.040  0.542  24.505
calculateTC    4.686  0.486   5.600
enrichfindP    0.918  0.085  16.225
getFASTA       0.122  0.016   8.994
* 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 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
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 99.091733 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.076130 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.598816 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.087068 
iter  10 value 92.572943
iter  20 value 92.568197
iter  30 value 92.565908
final  value 92.565874 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.991359 
iter  10 value 93.734927
iter  20 value 84.616880
iter  30 value 84.113916
iter  40 value 84.113055
final  value 84.113054 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.996924 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.968664 
iter  10 value 93.867391
iter  10 value 93.867391
iter  10 value 93.867391
final  value 93.867391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.603604 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.013158 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.280036 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.611696 
iter  10 value 90.965600
final  value 90.965415 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.169913 
iter  10 value 93.528153
iter  20 value 93.517808
final  value 93.517805 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.575323 
iter  10 value 93.867395
final  value 93.867391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.499312 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.750946 
final  value 94.052915 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.680925 
iter  10 value 93.010339
iter  20 value 86.945615
iter  30 value 85.863256
iter  40 value 85.251271
iter  50 value 84.949607
iter  60 value 84.703955
iter  70 value 83.349676
iter  80 value 82.638298
iter  90 value 82.349935
iter 100 value 80.875692
final  value 80.875692 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 112.569472 
iter  10 value 93.788390
iter  20 value 89.881385
iter  30 value 88.795528
iter  40 value 87.371630
iter  50 value 85.584763
iter  60 value 85.484740
iter  70 value 85.125750
iter  80 value 84.346456
iter  90 value 84.265320
final  value 84.264744 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.150097 
iter  10 value 94.042111
iter  20 value 90.031179
iter  30 value 84.209146
iter  40 value 83.988814
iter  50 value 83.172954
iter  60 value 83.065904
iter  70 value 83.055471
final  value 83.055464 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.556867 
iter  10 value 94.166902
iter  20 value 94.056861
iter  30 value 85.803914
iter  40 value 84.794339
iter  50 value 84.169816
iter  60 value 84.092080
iter  70 value 84.048388
final  value 84.048358 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.531783 
iter  10 value 94.058896
iter  20 value 94.028395
iter  30 value 93.927605
iter  40 value 89.358139
iter  50 value 88.264766
iter  60 value 88.114202
iter  70 value 87.992656
iter  80 value 85.177797
iter  90 value 83.411588
iter 100 value 83.119084
final  value 83.119084 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.900887 
iter  10 value 93.604982
iter  20 value 93.343836
iter  30 value 93.332155
iter  40 value 92.163339
iter  50 value 89.165345
iter  60 value 87.005866
iter  70 value 84.120648
iter  80 value 81.236703
iter  90 value 80.185561
iter 100 value 79.256683
final  value 79.256683 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.405714 
iter  10 value 93.912603
iter  20 value 87.868749
iter  30 value 84.565951
iter  40 value 83.022057
iter  50 value 82.647781
iter  60 value 80.790412
iter  70 value 79.685069
iter  80 value 79.231816
iter  90 value 79.043274
iter 100 value 78.964589
final  value 78.964589 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.402474 
iter  10 value 94.034621
iter  20 value 93.915337
iter  30 value 89.208522
iter  40 value 86.023937
iter  50 value 85.223971
iter  60 value 84.940607
iter  70 value 82.857922
iter  80 value 82.000647
iter  90 value 81.838312
iter 100 value 81.486925
final  value 81.486925 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.512358 
iter  10 value 93.710937
iter  20 value 85.488045
iter  30 value 83.920541
iter  40 value 81.166207
iter  50 value 80.306599
iter  60 value 79.797788
iter  70 value 79.665219
iter  80 value 79.556283
iter  90 value 79.532927
iter 100 value 79.454209
final  value 79.454209 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.869734 
iter  10 value 93.581888
iter  20 value 91.504949
iter  30 value 87.957063
iter  40 value 86.282615
iter  50 value 83.875393
iter  60 value 81.674914
iter  70 value 81.119086
iter  80 value 79.639085
iter  90 value 79.302347
iter 100 value 79.152108
final  value 79.152108 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.960885 
iter  10 value 94.415716
iter  20 value 90.098075
iter  30 value 83.596400
iter  40 value 81.277102
iter  50 value 80.893741
iter  60 value 80.021970
iter  70 value 79.247732
iter  80 value 78.531631
iter  90 value 78.431739
iter 100 value 78.401384
final  value 78.401384 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.683427 
iter  10 value 98.098923
iter  20 value 92.989169
iter  30 value 92.781702
iter  40 value 90.600054
iter  50 value 86.120969
iter  60 value 81.733637
iter  70 value 81.396742
iter  80 value 80.150831
iter  90 value 79.319007
iter 100 value 78.845173
final  value 78.845173 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.869718 
iter  10 value 94.266595
iter  20 value 94.041112
iter  30 value 86.514262
iter  40 value 83.780615
iter  50 value 83.311946
iter  60 value 83.080376
iter  70 value 82.783065
iter  80 value 81.154711
iter  90 value 80.278258
iter 100 value 79.845232
final  value 79.845232 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 139.849514 
iter  10 value 94.034325
iter  20 value 88.350357
iter  30 value 84.869323
iter  40 value 84.173392
iter  50 value 81.278207
iter  60 value 80.430215
iter  70 value 80.273498
iter  80 value 80.167686
iter  90 value 80.051686
iter 100 value 79.856648
final  value 79.856648 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.956547 
iter  10 value 96.196637
iter  20 value 87.839323
iter  30 value 86.325914
iter  40 value 85.872355
iter  50 value 84.194346
iter  60 value 82.516624
iter  70 value 81.215117
iter  80 value 80.845004
iter  90 value 80.797086
iter 100 value 80.573236
final  value 80.573236 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.057506 
final  value 94.054420 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.744408 
iter  10 value 94.054699
final  value 94.052940 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.729560 
iter  10 value 93.901605
iter  10 value 93.901605
iter  10 value 93.901605
final  value 93.901605 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.847922 
final  value 94.054593 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.817436 
final  value 94.054617 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.636397 
iter  10 value 84.772841
iter  20 value 84.577519
iter  30 value 84.463842
iter  40 value 83.609047
iter  50 value 83.598816
iter  60 value 83.598355
iter  70 value 83.582801
iter  80 value 83.545437
final  value 83.545418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.370150 
iter  10 value 94.057949
iter  20 value 93.949713
iter  30 value 92.146008
iter  40 value 87.153377
iter  50 value 85.730423
iter  60 value 85.586820
iter  70 value 85.513474
iter  80 value 85.512524
iter  90 value 85.376106
iter 100 value 85.351832
final  value 85.351832 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.059116 
iter  10 value 94.057528
iter  20 value 94.013322
iter  30 value 87.596807
iter  40 value 86.811334
final  value 86.811323 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.793871 
iter  10 value 93.852719
iter  20 value 93.286525
iter  30 value 93.091055
iter  40 value 92.883165
iter  50 value 92.570646
iter  60 value 92.569365
iter  70 value 92.568666
iter  80 value 92.568263
iter  90 value 92.554808
iter 100 value 92.271457
final  value 92.271457 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.446890 
iter  10 value 93.872338
iter  20 value 93.868154
iter  30 value 93.574813
iter  40 value 85.046965
iter  50 value 82.682307
iter  60 value 82.677311
iter  70 value 82.676046
final  value 82.675438 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.533218 
iter  10 value 94.057860
iter  20 value 93.760396
iter  30 value 93.237270
iter  40 value 93.219511
iter  50 value 92.147107
iter  60 value 86.141475
final  value 86.139140 
converged
Fitting Repeat 2 

# weights:  507
initial  value 144.538479 
iter  10 value 94.052645
iter  20 value 94.046483
iter  30 value 86.270217
iter  40 value 84.653373
iter  50 value 84.619304
iter  60 value 84.585390
iter  70 value 83.783675
iter  80 value 83.671455
iter  90 value 83.668424
iter 100 value 83.664965
final  value 83.664965 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.278195 
iter  10 value 85.135621
iter  20 value 84.123644
iter  30 value 84.121026
iter  40 value 84.114288
iter  50 value 84.030540
iter  60 value 83.598906
iter  70 value 83.511220
iter  80 value 83.510746
iter  90 value 83.510575
iter 100 value 83.510416
final  value 83.510416 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.558373 
iter  10 value 93.052674
iter  20 value 93.050730
iter  30 value 93.043038
iter  40 value 93.017506
iter  50 value 92.939967
iter  60 value 92.921258
iter  70 value 92.921144
iter  80 value 92.920934
iter  90 value 92.797484
iter 100 value 92.005971
final  value 92.005971 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.611240 
iter  10 value 94.060070
iter  20 value 93.822159
iter  30 value 86.051264
iter  40 value 82.740320
iter  50 value 80.000831
iter  60 value 79.232828
iter  70 value 79.050827
iter  80 value 78.759588
iter  90 value 78.757467
final  value 78.757383 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.823091 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.500486 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.824281 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.223547 
iter  10 value 94.096866
final  value 94.096669 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.194031 
final  value 94.448052 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.541499 
final  value 94.484209 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.657195 
iter  10 value 93.472004
iter  20 value 87.784233
iter  30 value 87.694041
final  value 87.694036 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.638402 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.070104 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.631360 
iter  10 value 93.110035
final  value 93.109890 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.627680 
iter  10 value 94.459249
iter  20 value 94.457926
final  value 94.457914 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.559202 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 127.887388 
iter  10 value 94.024875
final  value 93.974650 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.628301 
iter  10 value 94.169849
final  value 94.165120 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.831934 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.504185 
iter  10 value 94.284111
iter  20 value 88.597425
iter  30 value 84.385233
iter  40 value 83.499456
iter  50 value 82.888583
iter  60 value 82.007435
iter  70 value 81.877225
iter  80 value 81.861782
iter  80 value 81.861782
iter  80 value 81.861782
final  value 81.861782 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.479310 
iter  10 value 94.489095
iter  20 value 94.488385
iter  30 value 94.301292
iter  40 value 94.211423
iter  50 value 86.955162
iter  60 value 85.026029
iter  70 value 84.640260
iter  80 value 84.401654
iter  90 value 84.320063
iter 100 value 83.768983
final  value 83.768983 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.443605 
iter  10 value 94.126963
iter  20 value 89.679594
iter  30 value 84.457092
iter  40 value 83.065790
iter  50 value 82.913704
iter  60 value 80.885282
iter  70 value 80.131930
iter  80 value 80.069486
iter  90 value 80.056989
iter 100 value 80.009394
final  value 80.009394 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.402561 
iter  10 value 94.597780
iter  20 value 94.477799
iter  30 value 94.272483
iter  40 value 94.209291
iter  50 value 94.126094
iter  60 value 84.993377
iter  70 value 83.793454
iter  80 value 82.456929
iter  90 value 82.267018
iter 100 value 82.122530
final  value 82.122530 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.277955 
iter  10 value 94.131115
iter  20 value 93.971776
iter  30 value 90.877401
iter  40 value 85.622299
iter  50 value 84.965891
iter  60 value 82.361905
iter  70 value 80.840304
iter  80 value 80.025086
iter  90 value 79.680857
iter 100 value 79.546703
final  value 79.546703 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.210948 
iter  10 value 94.396077
iter  20 value 85.295046
iter  30 value 82.955450
iter  40 value 82.684667
iter  50 value 82.085075
iter  60 value 81.814479
iter  70 value 81.510704
iter  80 value 81.345276
iter  90 value 81.283094
iter 100 value 80.646173
final  value 80.646173 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.830044 
iter  10 value 93.748149
iter  20 value 93.170704
iter  30 value 93.021541
iter  40 value 91.257942
iter  50 value 83.937472
iter  60 value 83.481520
iter  70 value 83.300714
iter  80 value 83.225789
iter  90 value 83.165337
iter 100 value 83.066301
final  value 83.066301 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.633112 
iter  10 value 89.941641
iter  20 value 83.070614
iter  30 value 82.070016
iter  40 value 79.758272
iter  50 value 79.064583
iter  60 value 78.481274
iter  70 value 78.214777
iter  80 value 78.187703
iter  90 value 78.118410
iter 100 value 78.081696
final  value 78.081696 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.323646 
iter  10 value 94.064841
iter  20 value 85.430289
iter  30 value 82.696427
iter  40 value 82.198829
iter  50 value 81.572878
iter  60 value 81.256742
iter  70 value 80.094396
iter  80 value 78.965957
iter  90 value 78.508459
iter 100 value 78.418857
final  value 78.418857 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.245652 
iter  10 value 95.173593
iter  20 value 93.057734
iter  30 value 86.802416
iter  40 value 84.187570
iter  50 value 82.855516
iter  60 value 82.342324
iter  70 value 81.902324
iter  80 value 81.537734
iter  90 value 81.425201
iter 100 value 81.181554
final  value 81.181554 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.255282 
iter  10 value 94.101317
iter  20 value 84.089738
iter  30 value 82.503076
iter  40 value 82.014328
iter  50 value 81.831799
iter  60 value 81.204585
iter  70 value 79.853882
iter  80 value 78.733617
iter  90 value 78.147340
iter 100 value 78.009921
final  value 78.009921 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 143.790957 
iter  10 value 94.470443
iter  20 value 86.399774
iter  30 value 84.967832
iter  40 value 83.252264
iter  50 value 80.654992
iter  60 value 79.170486
iter  70 value 78.728572
iter  80 value 78.125917
iter  90 value 77.966940
iter 100 value 77.771055
final  value 77.771055 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.435127 
iter  10 value 95.880004
iter  20 value 94.469929
iter  30 value 84.775424
iter  40 value 84.217490
iter  50 value 84.152695
iter  60 value 82.597529
iter  70 value 80.592730
iter  80 value 79.618008
iter  90 value 79.525589
iter 100 value 79.282904
final  value 79.282904 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.061813 
iter  10 value 94.534373
iter  20 value 93.050092
iter  30 value 91.891257
iter  40 value 86.578946
iter  50 value 85.135368
iter  60 value 81.593903
iter  70 value 81.051207
iter  80 value 79.687538
iter  90 value 78.569095
iter 100 value 78.173099
final  value 78.173099 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.583840 
iter  10 value 94.298039
iter  20 value 88.857421
iter  30 value 83.766463
iter  40 value 83.083500
iter  50 value 81.706689
iter  60 value 80.125655
iter  70 value 79.593929
iter  80 value 79.171204
iter  90 value 78.925484
iter 100 value 78.743902
final  value 78.743902 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.736679 
final  value 94.485884 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.695814 
final  value 94.028006 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.168019 
final  value 94.485579 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.043359 
final  value 94.485654 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.554793 
final  value 94.485671 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.631219 
iter  10 value 94.452799
iter  20 value 94.448840
final  value 94.448250 
converged
Fitting Repeat 2 

# weights:  305
initial  value 143.393956 
iter  10 value 94.489093
iter  20 value 94.484188
iter  30 value 92.580705
iter  40 value 85.446865
final  value 85.446555 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.478436 
iter  10 value 94.488325
iter  20 value 88.153146
iter  30 value 87.482678
iter  40 value 87.324000
final  value 87.317749 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.520957 
iter  10 value 94.488172
iter  20 value 93.727424
iter  30 value 85.392161
iter  40 value 85.314242
iter  50 value 85.312864
iter  60 value 85.256578
iter  70 value 85.242807
iter  80 value 85.052337
iter  90 value 85.051936
iter 100 value 85.049009
final  value 85.049009 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.435407 
iter  10 value 94.489080
final  value 94.485509 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.168782 
iter  10 value 94.491939
iter  20 value 94.008822
iter  30 value 83.256169
iter  40 value 83.157818
iter  50 value 83.059400
iter  60 value 82.466144
iter  70 value 82.306050
iter  80 value 82.295972
iter  90 value 82.093559
iter 100 value 79.890287
final  value 79.890287 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.892291 
iter  10 value 94.505930
iter  20 value 94.209747
iter  30 value 88.756116
iter  40 value 88.053207
iter  50 value 88.022097
final  value 88.021284 
converged
Fitting Repeat 3 

# weights:  507
initial  value 135.270576 
iter  10 value 94.492512
iter  20 value 94.484338
iter  20 value 94.484337
iter  20 value 94.484337
final  value 94.484337 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.109887 
iter  10 value 94.492070
iter  20 value 94.466916
iter  30 value 90.365078
iter  40 value 88.744463
iter  50 value 88.653910
iter  60 value 88.642284
iter  70 value 88.623523
iter  80 value 84.005295
iter  90 value 83.681390
iter 100 value 83.434505
final  value 83.434505 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.056758 
iter  10 value 94.261040
iter  20 value 94.034545
iter  30 value 93.942366
iter  40 value 90.741097
iter  50 value 86.798629
iter  60 value 84.925658
iter  70 value 84.311000
iter  80 value 81.229688
iter  90 value 80.174541
iter 100 value 79.905290
final  value 79.905290 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.824501 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.443403 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.469884 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.893944 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.618511 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.701382 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.669444 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.432853 
iter  10 value 94.479568
final  value 94.461531 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.047183 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.467868 
iter  10 value 86.266588
iter  20 value 84.403477
iter  30 value 83.595138
iter  40 value 83.536712
final  value 83.536615 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.452610 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.384700 
iter  10 value 94.027471
iter  20 value 94.026549
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.483151 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.358174 
iter  10 value 93.614827
final  value 93.614623 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.050116 
iter  10 value 94.484209
iter  10 value 94.484209
iter  10 value 94.484208
final  value 94.484208 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.661794 
iter  10 value 94.488297
iter  20 value 92.594419
iter  30 value 90.163334
iter  40 value 86.432734
iter  50 value 84.881700
iter  60 value 84.386082
iter  70 value 83.254333
iter  80 value 83.052364
iter  90 value 83.041666
iter 100 value 83.028806
final  value 83.028806 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.930454 
iter  10 value 94.488812
iter  20 value 93.787356
iter  30 value 88.688062
iter  40 value 88.486933
iter  50 value 88.149700
iter  60 value 85.171336
iter  70 value 84.905946
iter  80 value 84.410957
iter  90 value 84.383806
iter  90 value 84.383806
final  value 84.383806 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.602179 
iter  10 value 94.487430
iter  20 value 93.906979
iter  30 value 89.827801
iter  40 value 88.105518
iter  50 value 87.150574
iter  60 value 86.872165
iter  70 value 86.284564
iter  80 value 85.975985
iter  90 value 85.972841
iter  90 value 85.972841
iter  90 value 85.972841
final  value 85.972841 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.592354 
iter  10 value 94.492437
iter  20 value 94.325723
iter  30 value 93.780250
iter  40 value 93.770313
iter  50 value 92.861789
iter  60 value 90.043137
iter  70 value 88.976312
iter  80 value 87.717931
iter  90 value 84.550002
iter 100 value 83.872310
final  value 83.872310 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.174202 
iter  10 value 94.487227
iter  20 value 93.870542
iter  30 value 87.205851
iter  40 value 86.322290
iter  50 value 85.263773
iter  60 value 84.850694
iter  70 value 84.254283
iter  80 value 83.653780
iter  90 value 83.096818
iter 100 value 83.039929
final  value 83.039929 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.219469 
iter  10 value 90.616671
iter  20 value 88.190127
iter  30 value 87.252489
iter  40 value 86.641053
iter  50 value 86.032768
iter  60 value 85.638939
iter  70 value 85.190506
iter  80 value 85.027162
iter  90 value 84.945486
iter 100 value 84.827384
final  value 84.827384 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.326278 
iter  10 value 94.358307
iter  20 value 87.063786
iter  30 value 85.311602
iter  40 value 84.824872
iter  50 value 82.987547
iter  60 value 82.662147
iter  70 value 82.460669
iter  80 value 82.334304
iter  90 value 82.196577
iter 100 value 82.172323
final  value 82.172323 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.611899 
iter  10 value 93.799918
iter  20 value 87.901187
iter  30 value 87.527386
iter  40 value 87.150738
iter  50 value 85.726116
iter  60 value 84.116741
iter  70 value 83.226614
iter  80 value 82.288058
iter  90 value 82.185670
iter 100 value 82.043154
final  value 82.043154 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.907195 
iter  10 value 94.498831
iter  20 value 93.721481
iter  30 value 86.529436
iter  40 value 84.658183
iter  50 value 83.988967
iter  60 value 83.721227
iter  70 value 82.553461
iter  80 value 82.283920
iter  90 value 82.012251
iter 100 value 81.911505
final  value 81.911505 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.026293 
iter  10 value 94.670506
iter  20 value 94.301841
iter  30 value 85.741475
iter  40 value 85.134731
iter  50 value 84.844930
iter  60 value 83.156945
iter  70 value 82.585353
iter  80 value 82.347622
iter  90 value 81.750794
iter 100 value 81.577611
final  value 81.577611 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 132.701592 
iter  10 value 94.428139
iter  20 value 87.337378
iter  30 value 86.422270
iter  40 value 85.462537
iter  50 value 82.694032
iter  60 value 81.803371
iter  70 value 81.612041
iter  80 value 81.524050
iter  90 value 81.401469
iter 100 value 81.219935
final  value 81.219935 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.216902 
iter  10 value 94.728576
iter  20 value 93.827168
iter  30 value 89.867941
iter  40 value 86.213942
iter  50 value 85.103308
iter  60 value 84.661870
iter  70 value 84.075738
iter  80 value 83.226665
iter  90 value 82.463020
iter 100 value 82.327956
final  value 82.327956 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.572047 
iter  10 value 94.695773
iter  20 value 94.466178
iter  30 value 88.161888
iter  40 value 86.686976
iter  50 value 84.751503
iter  60 value 83.775654
iter  70 value 82.753456
iter  80 value 82.363186
iter  90 value 82.196993
iter 100 value 81.992942
final  value 81.992942 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.596249 
iter  10 value 94.117962
iter  20 value 87.293435
iter  30 value 86.563650
iter  40 value 85.124558
iter  50 value 83.627791
iter  60 value 82.999924
iter  70 value 82.506908
iter  80 value 82.084664
iter  90 value 81.781545
iter 100 value 81.510919
final  value 81.510919 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.939882 
iter  10 value 89.031255
iter  20 value 86.899346
iter  30 value 83.969191
iter  40 value 82.943688
iter  50 value 82.486736
iter  60 value 82.277775
iter  70 value 82.219823
iter  80 value 82.177352
iter  90 value 82.138096
iter 100 value 81.773109
final  value 81.773109 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.773582 
final  value 94.485708 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.924732 
final  value 94.485769 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.442404 
final  value 94.485757 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.866370 
iter  10 value 92.491962
iter  20 value 90.792612
iter  30 value 90.785973
iter  40 value 90.603919
final  value 90.603830 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.807497 
iter  10 value 93.639331
iter  20 value 93.638550
iter  30 value 93.637600
iter  40 value 93.588122
iter  50 value 87.321363
final  value 87.319007 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.573380 
iter  10 value 94.485520
iter  20 value 94.484246
iter  30 value 94.479745
iter  40 value 93.481400
iter  50 value 90.202201
iter  60 value 88.551546
iter  70 value 86.713443
iter  80 value 83.262788
iter  90 value 81.984696
iter 100 value 81.966933
final  value 81.966933 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.024417 
iter  10 value 94.031504
iter  20 value 93.854547
iter  30 value 89.185367
iter  40 value 88.484554
iter  50 value 88.221086
iter  60 value 88.218801
final  value 88.216839 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.710887 
iter  10 value 94.307057
iter  20 value 93.231635
iter  30 value 93.231096
iter  40 value 93.228356
iter  50 value 89.366435
iter  60 value 88.426160
iter  70 value 88.399782
final  value 88.399740 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.850341 
iter  10 value 94.032368
iter  20 value 94.028900
iter  30 value 90.248322
iter  40 value 88.577252
iter  50 value 88.560524
iter  60 value 88.560388
iter  70 value 88.488844
iter  80 value 83.753766
iter  90 value 83.535248
iter 100 value 82.227559
final  value 82.227559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.882749 
iter  10 value 94.031579
iter  20 value 94.027472
final  value 94.026793 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.127940 
iter  10 value 94.490940
iter  20 value 94.480215
iter  30 value 91.539899
iter  40 value 91.534792
iter  50 value 90.988195
iter  60 value 89.850855
iter  70 value 89.843402
iter  80 value 87.574741
iter  90 value 87.315408
iter 100 value 87.305797
final  value 87.305797 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.280279 
iter  10 value 94.311501
iter  20 value 94.042824
iter  30 value 94.034092
iter  40 value 93.968743
iter  50 value 88.797101
iter  60 value 87.978323
iter  70 value 87.820690
iter  80 value 87.819717
final  value 87.819670 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.173727 
iter  10 value 94.034965
iter  20 value 94.027802
iter  30 value 93.811599
iter  40 value 88.636004
final  value 88.321166 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.405806 
iter  10 value 94.024606
iter  20 value 94.011814
iter  30 value 94.005175
iter  40 value 93.214159
iter  50 value 87.609779
iter  60 value 86.555229
iter  70 value 84.502842
iter  80 value 84.264351
iter  90 value 84.260127
final  value 84.259659 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.840662 
iter  10 value 94.034662
iter  20 value 94.026743
iter  30 value 92.318889
iter  40 value 91.805732
iter  50 value 91.724580
iter  60 value 91.152111
iter  70 value 88.165194
iter  80 value 88.020713
iter  90 value 87.731621
iter 100 value 87.729621
final  value 87.729621 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.206238 
iter  10 value 86.947108
iter  20 value 85.733406
iter  30 value 85.322775
final  value 85.322764 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.882958 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.853840 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.696582 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.490033 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.026819 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.735391 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.114564 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.011939 
iter  10 value 93.833962
iter  20 value 89.855194
iter  30 value 86.568723
iter  40 value 86.476339
iter  50 value 86.475690
iter  60 value 86.355516
final  value 86.355427 
converged
Fitting Repeat 5 

# weights:  305
initial  value 93.830155 
iter  10 value 85.976793
final  value 85.976099 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.309665 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.931302 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.242649 
iter  10 value 92.864368
iter  10 value 92.864368
iter  10 value 92.864368
final  value 92.864368 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.192166 
final  value 92.707576 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.572680 
iter  10 value 87.409757
iter  20 value 84.923981
iter  30 value 84.549395
iter  40 value 83.527082
final  value 83.526674 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.600451 
iter  10 value 94.056744
iter  20 value 89.750230
iter  30 value 85.924181
iter  40 value 83.094252
iter  50 value 82.906031
iter  60 value 82.768018
iter  70 value 82.754039
iter  80 value 82.737787
final  value 82.737749 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.062582 
iter  10 value 94.062415
iter  20 value 93.896873
iter  30 value 93.651134
iter  40 value 91.962009
iter  50 value 91.084792
iter  60 value 90.817922
iter  70 value 90.057892
iter  80 value 89.964574
iter  90 value 89.954405
final  value 89.954354 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.567031 
iter  10 value 94.056572
iter  10 value 94.056571
iter  20 value 83.593535
iter  30 value 83.206965
iter  40 value 82.907850
iter  50 value 82.782837
iter  60 value 82.745475
final  value 82.745309 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.959673 
iter  10 value 93.999970
iter  20 value 93.248745
iter  30 value 93.178188
iter  40 value 93.156637
iter  50 value 92.404785
iter  60 value 87.113317
iter  70 value 83.332194
iter  80 value 83.222049
iter  90 value 83.184151
iter 100 value 83.179163
final  value 83.179163 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.534663 
iter  10 value 94.069159
iter  20 value 93.981546
iter  30 value 93.742298
iter  40 value 93.465705
iter  50 value 89.312505
iter  60 value 83.777973
iter  70 value 83.487823
iter  80 value 83.382766
iter  90 value 83.366698
final  value 83.364537 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.045551 
iter  10 value 94.068005
iter  20 value 93.841205
iter  30 value 90.599055
iter  40 value 87.860023
iter  50 value 84.599669
iter  60 value 83.210274
iter  70 value 82.103487
iter  80 value 80.833365
iter  90 value 80.634071
iter 100 value 80.585091
final  value 80.585091 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.890298 
iter  10 value 94.057992
iter  20 value 88.964019
iter  30 value 86.585217
iter  40 value 83.295695
iter  50 value 83.103276
iter  60 value 83.011857
iter  70 value 82.851400
iter  80 value 82.246985
iter  90 value 80.982884
iter 100 value 80.453157
final  value 80.453157 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.957314 
iter  10 value 94.057692
iter  20 value 89.609208
iter  30 value 86.243848
iter  40 value 83.313255
iter  50 value 82.395607
iter  60 value 82.060712
iter  70 value 81.806528
iter  80 value 81.733205
iter  90 value 81.481749
iter 100 value 80.847561
final  value 80.847561 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.576607 
iter  10 value 94.028087
iter  20 value 88.611464
iter  30 value 87.031237
iter  40 value 83.950469
iter  50 value 82.120164
iter  60 value 81.310045
iter  70 value 80.308059
iter  80 value 79.963738
iter  90 value 79.900735
iter 100 value 79.880136
final  value 79.880136 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.929230 
iter  10 value 93.807651
iter  20 value 87.961988
iter  30 value 85.058931
iter  40 value 83.439393
iter  50 value 82.930184
iter  60 value 82.851550
iter  70 value 82.696580
iter  80 value 82.385965
iter  90 value 80.945690
iter 100 value 80.421880
final  value 80.421880 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.134908 
iter  10 value 93.773922
iter  20 value 88.359929
iter  30 value 85.493997
iter  40 value 84.021123
iter  50 value 81.652131
iter  60 value 81.075859
iter  70 value 80.651703
iter  80 value 80.332779
iter  90 value 79.936656
iter 100 value 79.736034
final  value 79.736034 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.186989 
iter  10 value 94.117802
iter  20 value 85.398582
iter  30 value 83.392909
iter  40 value 83.069513
iter  50 value 81.931902
iter  60 value 81.684511
iter  70 value 81.610062
iter  80 value 81.443129
iter  90 value 80.978280
iter 100 value 80.284972
final  value 80.284972 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.796891 
iter  10 value 94.030772
iter  20 value 86.172507
iter  30 value 85.129876
iter  40 value 84.274956
iter  50 value 82.332679
iter  60 value 81.155506
iter  70 value 80.787905
iter  80 value 80.421526
iter  90 value 80.185298
iter 100 value 79.993004
final  value 79.993004 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.528081 
iter  10 value 94.089858
iter  20 value 90.078104
iter  30 value 88.671317
iter  40 value 85.778962
iter  50 value 83.827100
iter  60 value 83.375202
iter  70 value 82.382056
iter  80 value 81.280828
iter  90 value 81.023990
iter 100 value 80.821198
final  value 80.821198 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.725866 
iter  10 value 98.671744
iter  20 value 90.458527
iter  30 value 87.160880
iter  40 value 83.981611
iter  50 value 83.742594
iter  60 value 82.811859
iter  70 value 81.736652
iter  80 value 80.944161
iter  90 value 80.558841
iter 100 value 80.503894
final  value 80.503894 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.896996 
final  value 94.054548 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.751040 
final  value 94.054671 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.917007 
iter  10 value 94.054791
iter  20 value 94.052915
iter  30 value 91.374532
iter  40 value 82.511007
iter  50 value 82.322673
iter  60 value 82.320664
iter  70 value 82.314417
iter  80 value 82.313245
iter  90 value 82.312854
iter 100 value 82.312739
final  value 82.312739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.349556 
final  value 94.054513 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.259357 
final  value 94.054431 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.228038 
iter  10 value 94.013939
iter  20 value 94.008838
iter  30 value 93.762506
iter  40 value 85.163407
iter  50 value 82.557288
iter  60 value 81.655328
iter  70 value 81.164077
iter  80 value 81.131588
iter  90 value 81.131304
iter 100 value 81.129750
final  value 81.129750 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.161259 
iter  10 value 94.013878
iter  20 value 93.937183
iter  30 value 91.529924
iter  40 value 90.784482
iter  50 value 90.765553
iter  60 value 90.764666
iter  70 value 90.764467
final  value 90.764446 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.505396 
iter  10 value 93.815169
iter  20 value 93.808914
iter  30 value 93.808514
iter  40 value 93.777456
iter  50 value 85.655417
iter  60 value 82.364428
iter  70 value 82.250844
iter  80 value 82.201581
iter  90 value 82.181503
iter 100 value 81.746322
final  value 81.746322 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.373236 
iter  10 value 94.053890
final  value 94.052925 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.896105 
iter  10 value 94.058132
iter  20 value 93.323849
iter  30 value 90.997508
iter  40 value 85.858758
iter  50 value 85.840911
iter  60 value 85.839531
iter  70 value 85.836419
iter  80 value 85.815739
iter  90 value 84.142489
iter 100 value 80.521928
final  value 80.521928 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.284399 
iter  10 value 94.017032
iter  20 value 94.009711
final  value 94.009228 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.735361 
iter  10 value 94.060015
iter  20 value 93.996279
iter  30 value 92.358506
iter  40 value 91.838964
iter  50 value 87.173146
iter  60 value 85.258165
iter  70 value 84.127353
iter  80 value 84.012187
iter  90 value 84.002896
iter 100 value 82.880667
final  value 82.880667 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.070387 
iter  10 value 94.061238
iter  20 value 94.019758
iter  30 value 91.504949
iter  40 value 86.737895
iter  50 value 84.470632
iter  60 value 83.585676
iter  70 value 83.320942
final  value 83.320806 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.493661 
iter  10 value 93.671928
iter  20 value 93.670430
iter  30 value 93.669699
iter  40 value 93.069633
iter  50 value 89.883918
iter  60 value 89.561021
iter  70 value 89.543826
iter  80 value 89.543599
iter  90 value 89.543506
iter 100 value 89.542695
final  value 89.542695 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.087440 
iter  10 value 94.061428
final  value 94.058036 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.026956 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.639634 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.696607 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.402556 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.746276 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.323933 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.116521 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.475895 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.263432 
final  value 93.701657 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.613101 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.544481 
iter  10 value 94.353977
final  value 94.353550 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.600594 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.859977 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.191685 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.007303 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.458908 
iter  10 value 94.461163
iter  20 value 91.467699
iter  30 value 87.851258
iter  40 value 87.045732
iter  50 value 84.655571
iter  60 value 84.408789
iter  70 value 83.329905
iter  80 value 82.598049
iter  90 value 82.478224
iter 100 value 82.445249
final  value 82.445249 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.724867 
iter  10 value 94.493215
iter  20 value 94.448247
iter  30 value 92.250181
iter  40 value 91.639051
iter  50 value 88.781732
iter  60 value 87.013629
iter  70 value 86.543090
iter  80 value 85.281230
iter  90 value 85.060123
iter 100 value 85.020710
final  value 85.020710 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.475128 
iter  10 value 94.486177
iter  20 value 94.314515
iter  30 value 94.191059
iter  40 value 90.450440
iter  50 value 85.922204
iter  60 value 85.327028
iter  70 value 83.506173
iter  80 value 82.766857
iter  90 value 82.624091
iter 100 value 82.545699
final  value 82.545699 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.046864 
iter  10 value 94.486474
iter  20 value 94.421090
iter  30 value 93.765537
iter  40 value 89.300059
iter  50 value 85.096929
iter  60 value 84.600753
iter  70 value 84.432753
iter  80 value 83.676629
iter  90 value 82.967048
iter 100 value 82.589858
final  value 82.589858 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.958664 
iter  10 value 94.413220
iter  20 value 87.992491
iter  30 value 86.697851
iter  40 value 86.285232
iter  50 value 85.575225
iter  60 value 85.170479
iter  70 value 84.983086
iter  80 value 84.948049
iter  90 value 84.813308
iter 100 value 84.784353
final  value 84.784353 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.303529 
iter  10 value 94.164208
iter  20 value 89.943839
iter  30 value 83.822091
iter  40 value 82.828995
iter  50 value 82.445799
iter  60 value 82.174584
iter  70 value 81.897363
iter  80 value 81.858519
iter  90 value 81.791065
iter 100 value 81.710228
final  value 81.710228 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.902300 
iter  10 value 93.951476
iter  20 value 88.466280
iter  30 value 88.276143
iter  40 value 87.085059
iter  50 value 85.282082
iter  60 value 84.979338
iter  70 value 83.255367
iter  80 value 82.871410
iter  90 value 82.715727
iter 100 value 82.439504
final  value 82.439504 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.915109 
iter  10 value 95.859477
iter  20 value 94.500663
iter  30 value 94.222053
iter  40 value 94.162622
iter  50 value 90.061515
iter  60 value 86.309844
iter  70 value 85.829224
iter  80 value 85.010981
iter  90 value 84.491177
iter 100 value 83.274679
final  value 83.274679 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.410822 
iter  10 value 94.465638
iter  20 value 89.434441
iter  30 value 86.701853
iter  40 value 84.620321
iter  50 value 83.595161
iter  60 value 82.803018
iter  70 value 82.492390
iter  80 value 82.233825
iter  90 value 81.679624
iter 100 value 81.012552
final  value 81.012552 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.036364 
iter  10 value 94.452174
iter  20 value 93.648302
iter  30 value 88.985279
iter  40 value 86.021880
iter  50 value 85.410852
iter  60 value 84.203526
iter  70 value 82.907454
iter  80 value 82.761464
iter  90 value 82.275268
iter 100 value 81.669714
final  value 81.669714 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.093379 
iter  10 value 93.267976
iter  20 value 86.203717
iter  30 value 84.950336
iter  40 value 84.518183
iter  50 value 83.334461
iter  60 value 82.776021
iter  70 value 82.679340
iter  80 value 82.585649
iter  90 value 82.206318
iter 100 value 82.095095
final  value 82.095095 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.840434 
iter  10 value 95.812244
iter  20 value 90.246431
iter  30 value 89.264772
iter  40 value 86.316727
iter  50 value 85.983255
iter  60 value 85.352109
iter  70 value 85.127358
iter  80 value 85.034447
iter  90 value 84.961888
iter 100 value 83.847947
final  value 83.847947 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.094282 
iter  10 value 94.661724
iter  20 value 94.477808
iter  30 value 89.568927
iter  40 value 87.718978
iter  50 value 87.359126
iter  60 value 84.372452
iter  70 value 82.422686
iter  80 value 82.334433
iter  90 value 81.895434
iter 100 value 81.664360
final  value 81.664360 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.608329 
iter  10 value 94.563476
iter  20 value 86.914997
iter  30 value 86.092530
iter  40 value 85.333202
iter  50 value 83.168641
iter  60 value 81.836166
iter  70 value 81.583506
iter  80 value 81.179660
iter  90 value 80.955875
iter 100 value 80.871802
final  value 80.871802 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.966457 
iter  10 value 94.895296
iter  20 value 94.391658
iter  30 value 93.453846
iter  40 value 88.645177
iter  50 value 84.860990
iter  60 value 82.857918
iter  70 value 82.211652
iter  80 value 81.626309
iter  90 value 81.094408
iter 100 value 80.995143
final  value 80.995143 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.971486 
final  value 94.355876 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.341607 
final  value 94.485710 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.153869 
iter  10 value 94.485725
iter  20 value 94.484227
iter  30 value 94.480688
iter  40 value 94.288706
final  value 94.288668 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.843964 
iter  10 value 87.288585
iter  20 value 87.288409
iter  30 value 87.287241
iter  40 value 86.690756
iter  50 value 83.829408
iter  60 value 83.589259
iter  70 value 83.554967
iter  80 value 83.554870
iter  80 value 83.554869
iter  80 value 83.554869
final  value 83.554869 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.603568 
final  value 94.486125 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.046069 
iter  10 value 94.488286
iter  20 value 94.484223
iter  20 value 94.484223
final  value 94.484223 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.375606 
iter  10 value 94.488723
iter  20 value 94.484242
final  value 94.484227 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.154053 
iter  10 value 94.359341
iter  20 value 94.358502
iter  30 value 94.353658
final  value 94.353596 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.846581 
iter  10 value 94.487137
iter  20 value 94.354465
iter  20 value 94.354465
iter  20 value 94.354465
final  value 94.354465 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.918497 
iter  10 value 94.489204
iter  20 value 94.460066
iter  30 value 94.145903
iter  40 value 94.142636
final  value 94.142504 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.201099 
iter  10 value 94.362765
iter  20 value 93.800758
iter  30 value 88.802985
iter  40 value 86.968450
iter  50 value 86.957330
iter  60 value 84.552985
iter  70 value 83.703834
final  value 83.703107 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.365032 
iter  10 value 94.361691
iter  20 value 94.293292
iter  30 value 94.268313
iter  40 value 93.262009
iter  50 value 86.909308
iter  60 value 86.907167
iter  70 value 86.903536
iter  80 value 86.732299
iter  90 value 86.095982
iter 100 value 86.091011
final  value 86.091011 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.318328 
iter  10 value 94.485083
iter  20 value 90.506860
iter  30 value 90.486628
iter  40 value 87.609388
iter  50 value 87.328224
iter  60 value 87.290605
iter  70 value 87.288729
iter  80 value 86.738117
iter  90 value 83.043436
iter 100 value 82.038098
final  value 82.038098 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.408596 
iter  10 value 94.494368
iter  20 value 89.382231
iter  30 value 86.579559
iter  40 value 86.315391
iter  50 value 86.269527
iter  60 value 86.268065
iter  70 value 86.267600
final  value 86.267389 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.669305 
iter  10 value 87.635288
iter  20 value 85.917556
iter  30 value 85.648830
iter  40 value 85.641910
final  value 85.640975 
converged
Fitting Repeat 1 

# weights:  507
initial  value 144.476666 
iter  10 value 117.898168
iter  20 value 117.874826
iter  30 value 110.326836
iter  40 value 106.685064
iter  50 value 106.656434
iter  60 value 106.656052
final  value 106.656050 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.617915 
iter  10 value 117.736658
iter  20 value 116.619639
iter  30 value 104.794639
iter  40 value 103.790068
iter  50 value 102.893740
iter  60 value 102.860602
iter  70 value 102.854286
iter  80 value 102.844446
iter  90 value 102.832144
iter 100 value 102.794916
final  value 102.794916 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.851731 
iter  10 value 114.590991
iter  20 value 108.971848
iter  30 value 108.967374
iter  40 value 106.977172
iter  50 value 106.167850
iter  60 value 106.167522
final  value 106.167118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.843817 
iter  10 value 117.758576
iter  20 value 117.736067
iter  30 value 117.734050
iter  40 value 117.729754
iter  50 value 117.728673
final  value 117.728389 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.445341 
iter  10 value 117.766324
iter  20 value 117.610567
iter  30 value 107.530270
iter  40 value 106.873920
iter  50 value 106.806298
final  value 106.806291 
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 Jun 10 05:03:36 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 
 73.172   2.202  81.313