##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 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
Unknown package ‘ftrCOOL’ in Rd xrefs
* 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       26.669  1.208  27.931
corr_plot     25.545  1.278  26.891
FSmethod      24.016  1.093  25.134
pred_ensembel 11.257  0.492   7.733
enrichfindP    0.340  0.045   9.642
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 95.697060 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.407462 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.922775 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.883228 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.483146 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.915404 
iter  10 value 89.546184
iter  20 value 89.356213
iter  30 value 89.202696
iter  40 value 89.182419
iter  40 value 89.182419
iter  40 value 89.182419
final  value 89.182419 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.662117 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.481918 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.867523 
iter  10 value 94.482135
iter  20 value 94.473121
final  value 94.473118 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.929542 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.406642 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.019222 
iter  10 value 94.314174
iter  20 value 94.312056
final  value 94.312039 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.104708 
iter  10 value 94.288117
final  value 94.288077 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.464094 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.134076 
final  value 94.312038 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.113060 
iter  10 value 94.473928
iter  20 value 94.096722
iter  30 value 94.085311
iter  40 value 94.081789
iter  50 value 92.704785
iter  60 value 85.530327
iter  70 value 84.288446
iter  80 value 82.388149
iter  90 value 81.681633
iter 100 value 81.218163
final  value 81.218163 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.417317 
iter  10 value 94.488428
iter  20 value 91.852547
iter  30 value 89.256679
iter  40 value 89.121165
iter  50 value 87.758199
iter  60 value 83.999015
iter  70 value 83.627936
iter  80 value 83.187613
iter  90 value 82.971313
iter 100 value 82.197452
final  value 82.197452 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.098519 
iter  10 value 93.889225
iter  20 value 93.516082
iter  30 value 86.292073
iter  40 value 85.292912
iter  50 value 84.958029
iter  60 value 84.807495
iter  70 value 84.521820
final  value 84.488813 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.091698 
iter  10 value 94.467690
iter  20 value 93.319576
iter  30 value 84.881430
iter  40 value 83.814572
iter  50 value 83.530538
iter  60 value 83.483158
iter  70 value 83.445270
iter  80 value 83.348876
final  value 83.348766 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.046587 
iter  10 value 94.479975
iter  20 value 92.465319
iter  30 value 90.008995
iter  40 value 86.653910
iter  50 value 85.171762
iter  60 value 84.553381
iter  70 value 84.280018
final  value 84.279804 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.214174 
iter  10 value 94.547650
iter  20 value 88.855330
iter  30 value 87.503676
iter  40 value 85.464414
iter  50 value 84.704378
iter  60 value 84.062865
iter  70 value 83.983768
iter  80 value 81.414377
iter  90 value 81.279553
iter 100 value 81.234002
final  value 81.234002 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.391359 
iter  10 value 94.279672
iter  20 value 85.336391
iter  30 value 84.096793
iter  40 value 82.311672
iter  50 value 81.913027
iter  60 value 81.647404
iter  70 value 81.256097
iter  80 value 79.921328
iter  90 value 79.820073
iter 100 value 79.735324
final  value 79.735324 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.453845 
iter  10 value 94.417004
iter  20 value 94.082057
iter  30 value 93.178179
iter  40 value 92.442046
iter  50 value 85.894540
iter  60 value 83.535076
iter  70 value 83.177286
iter  80 value 83.051460
iter  90 value 82.914375
iter 100 value 82.854003
final  value 82.854003 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.052340 
iter  10 value 94.244347
iter  20 value 91.572714
iter  30 value 89.255114
iter  40 value 88.990713
iter  50 value 87.977458
iter  60 value 83.574151
iter  70 value 82.347388
iter  80 value 81.093289
iter  90 value 80.841604
iter 100 value 80.602645
final  value 80.602645 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.024005 
iter  10 value 94.530663
iter  20 value 87.648643
iter  30 value 84.949416
iter  40 value 84.739612
iter  50 value 84.207753
iter  60 value 82.146041
iter  70 value 80.629629
iter  80 value 80.400361
iter  90 value 80.391861
iter 100 value 80.269715
final  value 80.269715 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.950124 
iter  10 value 97.194261
iter  20 value 95.086446
iter  30 value 92.248340
iter  40 value 89.686133
iter  50 value 89.299733
iter  60 value 88.409269
iter  70 value 85.592648
iter  80 value 83.035055
iter  90 value 81.734085
iter 100 value 81.093516
final  value 81.093516 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.965298 
iter  10 value 94.485395
iter  20 value 85.541031
iter  30 value 83.529189
iter  40 value 82.661079
iter  50 value 81.373783
iter  60 value 80.869823
iter  70 value 80.568577
iter  80 value 80.517173
iter  90 value 80.465301
iter 100 value 80.194156
final  value 80.194156 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.231711 
iter  10 value 94.284050
iter  20 value 90.061386
iter  30 value 88.487999
iter  40 value 84.434105
iter  50 value 81.964502
iter  60 value 80.806616
iter  70 value 80.447236
iter  80 value 80.226676
iter  90 value 80.098589
iter 100 value 79.927658
final  value 79.927658 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.298414 
iter  10 value 96.149377
iter  20 value 91.923650
iter  30 value 89.603379
iter  40 value 88.749801
iter  50 value 85.620472
iter  60 value 83.259019
iter  70 value 82.118249
iter  80 value 81.384229
iter  90 value 80.860968
iter 100 value 80.404584
final  value 80.404584 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.187281 
iter  10 value 94.903733
iter  20 value 90.575235
iter  30 value 89.101378
iter  40 value 85.651742
iter  50 value 83.692588
iter  60 value 83.191115
iter  70 value 82.841125
iter  80 value 82.092555
iter  90 value 81.303352
iter 100 value 80.727218
final  value 80.727218 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.983734 
iter  10 value 94.474792
iter  20 value 87.264787
iter  30 value 84.646699
iter  40 value 84.646004
iter  50 value 84.645578
final  value 84.645481 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.745527 
final  value 94.474771 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.839005 
final  value 94.485730 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.586765 
final  value 94.474674 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.374254 
final  value 94.485735 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.263294 
iter  10 value 94.489102
iter  20 value 91.849405
iter  30 value 84.586156
iter  40 value 84.582629
iter  50 value 84.582468
iter  60 value 84.582255
iter  70 value 83.985405
iter  80 value 83.582162
iter  90 value 82.546018
iter 100 value 82.459693
final  value 82.459693 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.020395 
iter  10 value 94.488495
iter  20 value 94.476073
iter  30 value 94.165211
final  value 94.165201 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.974059 
iter  10 value 94.477706
iter  20 value 94.476036
iter  30 value 94.473151
final  value 94.473138 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.548413 
iter  10 value 94.477832
iter  20 value 94.472869
iter  30 value 87.226393
iter  40 value 83.453745
iter  50 value 83.411581
iter  60 value 83.411305
final  value 83.411152 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.754632 
iter  10 value 90.080864
iter  20 value 90.074843
iter  30 value 89.967906
iter  40 value 88.755819
iter  50 value 85.029193
iter  60 value 84.807703
iter  70 value 84.382431
iter  80 value 84.348626
iter  90 value 83.949315
iter 100 value 83.947316
final  value 83.947316 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.484184 
iter  10 value 94.485849
iter  20 value 94.208695
iter  30 value 94.038078
iter  40 value 84.616942
iter  50 value 84.612290
iter  60 value 84.608413
iter  70 value 83.572224
iter  80 value 83.398911
iter  90 value 83.397135
iter 100 value 83.396989
final  value 83.396989 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.213143 
iter  10 value 90.084115
iter  20 value 89.674627
iter  30 value 84.111058
iter  40 value 84.045776
iter  50 value 84.038826
iter  60 value 83.830158
iter  70 value 83.180926
iter  80 value 82.669164
iter  90 value 82.316217
iter 100 value 79.738390
final  value 79.738390 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.063611 
iter  10 value 93.352146
iter  20 value 91.372717
iter  30 value 84.213752
iter  40 value 83.324990
iter  50 value 82.961402
iter  60 value 82.829345
iter  70 value 82.823081
iter  80 value 81.706972
iter  90 value 81.705808
iter 100 value 81.644794
final  value 81.644794 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.395325 
iter  10 value 94.492691
iter  20 value 94.484686
iter  30 value 93.370978
iter  40 value 89.439905
iter  50 value 89.434707
final  value 89.434693 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.203885 
iter  10 value 94.491909
iter  20 value 91.806726
iter  30 value 84.721170
iter  40 value 84.633737
iter  50 value 84.447889
iter  60 value 82.297953
iter  70 value 80.993679
iter  80 value 80.990198
final  value 80.990174 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.857065 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.690820 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.297261 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.390078 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.506923 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.624931 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.719085 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.542935 
iter  10 value 93.697145
final  value 93.697144 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.911219 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.855305 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.785465 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.726621 
iter  10 value 88.785765
iter  20 value 85.815349
final  value 85.797862 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.256284 
iter  10 value 93.915833
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.198653 
iter  10 value 93.818382
iter  20 value 93.815635
final  value 93.815628 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.363965 
iter  10 value 90.830349
iter  20 value 89.507404
iter  30 value 88.765983
final  value 87.609756 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.847491 
iter  10 value 94.056449
iter  20 value 90.712445
iter  30 value 88.250141
iter  40 value 87.722185
iter  50 value 87.241728
iter  60 value 85.177588
iter  70 value 84.823486
iter  80 value 84.685118
iter  90 value 84.674011
iter 100 value 84.559369
final  value 84.559369 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.205879 
iter  10 value 93.983025
iter  20 value 93.517683
iter  30 value 90.092463
iter  40 value 88.584106
iter  50 value 87.254819
iter  60 value 86.384939
iter  70 value 86.235833
iter  80 value 84.489320
iter  90 value 83.402924
iter 100 value 83.385302
final  value 83.385302 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.562052 
iter  10 value 94.033898
iter  20 value 91.360655
iter  30 value 90.496619
iter  40 value 87.693266
iter  50 value 85.622929
iter  60 value 83.936911
iter  70 value 83.630314
iter  80 value 83.425502
final  value 83.371534 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.517666 
iter  10 value 94.055923
iter  20 value 94.016345
iter  30 value 91.094806
iter  40 value 89.566706
iter  50 value 89.279939
iter  60 value 89.193195
iter  70 value 84.230779
iter  80 value 83.714562
iter  90 value 83.314633
iter 100 value 83.255491
final  value 83.255491 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.154170 
iter  10 value 92.595492
iter  20 value 84.908510
iter  30 value 83.295901
iter  40 value 82.507418
iter  50 value 82.478832
iter  60 value 82.455025
final  value 82.432315 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.842875 
iter  10 value 93.995950
iter  20 value 89.488755
iter  30 value 87.384055
iter  40 value 85.043602
iter  50 value 84.409705
iter  60 value 83.906307
iter  70 value 83.555776
iter  80 value 82.629308
iter  90 value 82.044103
iter 100 value 81.869703
final  value 81.869703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 126.559315 
iter  10 value 95.763371
iter  20 value 91.725311
iter  30 value 87.010258
iter  40 value 85.527925
iter  50 value 85.316613
iter  60 value 83.117637
iter  70 value 82.837025
iter  80 value 82.624388
iter  90 value 82.621219
iter 100 value 82.571830
final  value 82.571830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.328099 
iter  10 value 93.838937
iter  20 value 85.868734
iter  30 value 84.590868
iter  40 value 83.627394
iter  50 value 83.439274
iter  60 value 83.342152
iter  70 value 83.332490
iter  80 value 83.294383
iter  90 value 83.172607
iter 100 value 82.783462
final  value 82.783462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.694294 
iter  10 value 94.564045
iter  20 value 93.840522
iter  30 value 93.642694
iter  40 value 86.319077
iter  50 value 85.354339
iter  60 value 84.351198
iter  70 value 82.956500
iter  80 value 82.173254
iter  90 value 81.729136
iter 100 value 81.140798
final  value 81.140798 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.019400 
iter  10 value 94.050981
iter  20 value 92.262478
iter  30 value 88.336461
iter  40 value 87.601567
iter  50 value 86.277344
iter  60 value 84.603359
iter  70 value 84.459907
iter  80 value 83.762057
iter  90 value 83.522608
iter 100 value 83.404665
final  value 83.404665 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.488864 
iter  10 value 89.974559
iter  20 value 87.004376
iter  30 value 84.560525
iter  40 value 83.629296
iter  50 value 82.899312
iter  60 value 82.776332
iter  70 value 82.657219
iter  80 value 82.119338
iter  90 value 81.955813
iter 100 value 81.857888
final  value 81.857888 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.527197 
iter  10 value 94.507954
iter  20 value 88.920515
iter  30 value 84.429053
iter  40 value 83.576253
iter  50 value 83.083210
iter  60 value 82.642837
iter  70 value 82.229923
iter  80 value 82.030122
iter  90 value 81.874824
iter 100 value 81.823067
final  value 81.823067 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.760320 
iter  10 value 93.313968
iter  20 value 88.106088
iter  30 value 85.137761
iter  40 value 82.985976
iter  50 value 82.582511
iter  60 value 81.550274
iter  70 value 81.449757
iter  80 value 81.397162
iter  90 value 81.067000
iter 100 value 80.922422
final  value 80.922422 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.177410 
iter  10 value 94.466888
iter  20 value 94.071022
iter  30 value 92.454219
iter  40 value 85.657138
iter  50 value 84.420413
iter  60 value 83.986451
iter  70 value 83.698584
iter  80 value 83.024580
iter  90 value 81.937930
iter 100 value 81.437984
final  value 81.437984 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.343317 
iter  10 value 93.995379
iter  20 value 93.743369
iter  30 value 93.519887
iter  40 value 88.393791
iter  50 value 87.718975
iter  60 value 84.433440
iter  70 value 83.931470
iter  80 value 83.422105
iter  90 value 83.211329
iter 100 value 82.865195
final  value 82.865195 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 114.500939 
final  value 94.054525 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.059814 
final  value 94.054437 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.444417 
iter  10 value 87.612084
final  value 87.612054 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.282674 
iter  10 value 92.883892
iter  20 value 92.864896
iter  30 value 91.527062
final  value 91.526135 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.195679 
final  value 94.054451 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.328703 
iter  10 value 93.841172
iter  20 value 93.840766
iter  30 value 93.837888
iter  40 value 87.921666
iter  50 value 87.601354
iter  60 value 84.561470
iter  70 value 84.111079
iter  80 value 84.062201
final  value 84.061446 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.919320 
iter  10 value 94.057750
iter  20 value 94.015762
iter  30 value 85.230791
iter  40 value 84.576055
iter  50 value 82.684496
iter  60 value 81.142612
iter  70 value 80.880136
iter  80 value 80.876848
iter  90 value 80.876338
iter 100 value 80.875846
final  value 80.875846 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.183324 
iter  10 value 94.057958
iter  20 value 94.052990
iter  30 value 92.356998
iter  40 value 88.106776
iter  50 value 86.263428
iter  60 value 85.094708
iter  70 value 83.883586
iter  80 value 83.868658
iter  90 value 83.868189
iter 100 value 83.867637
final  value 83.867637 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.259955 
iter  10 value 93.990958
iter  20 value 86.481227
iter  30 value 85.533090
iter  40 value 85.530994
iter  50 value 85.373683
iter  60 value 82.995018
iter  70 value 82.942499
iter  80 value 82.939083
iter  90 value 82.843868
iter 100 value 81.549565
final  value 81.549565 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.793986 
iter  10 value 94.057579
iter  20 value 93.687286
iter  30 value 87.551719
iter  40 value 83.805179
iter  50 value 83.138233
iter  60 value 81.364521
iter  70 value 81.201154
final  value 81.200180 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.091999 
iter  10 value 93.794991
iter  20 value 93.783875
iter  30 value 93.693692
iter  40 value 91.013877
iter  50 value 89.920268
iter  60 value 89.164907
iter  70 value 88.492376
iter  80 value 88.379284
iter  90 value 88.172667
iter 100 value 87.753178
final  value 87.753178 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.010886 
iter  10 value 94.061530
iter  20 value 93.990055
iter  30 value 93.721832
iter  40 value 93.720305
final  value 93.719954 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.502919 
iter  10 value 90.822863
iter  20 value 88.147648
iter  30 value 88.105565
iter  40 value 86.179589
iter  50 value 85.838418
iter  60 value 85.834071
iter  70 value 85.829839
final  value 85.828592 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.520093 
iter  10 value 93.705818
iter  20 value 93.702096
iter  30 value 93.688838
iter  40 value 93.687782
iter  50 value 93.685542
final  value 93.685484 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.539198 
iter  10 value 94.109682
iter  20 value 94.066311
iter  30 value 89.510213
iter  40 value 85.873554
iter  50 value 85.439998
iter  60 value 85.351810
iter  70 value 85.333425
iter  80 value 84.961053
iter  90 value 84.104134
iter 100 value 84.064911
final  value 84.064911 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.551219 
iter  10 value 91.664173
iter  20 value 87.857942
iter  30 value 86.170263
iter  40 value 84.216674
iter  50 value 84.207846
final  value 84.207835 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.720974 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.035057 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.338753 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.605456 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.904879 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.645560 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.583677 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.746104 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.100042 
iter  10 value 94.484467
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.193239 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.126018 
iter  10 value 94.195715
iter  10 value 94.195714
iter  10 value 94.195714
final  value 94.195714 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.754009 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.571275 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.708152 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.190984 
iter  10 value 94.467982
iter  20 value 93.511133
iter  30 value 93.397070
iter  40 value 92.425838
iter  50 value 84.815744
iter  60 value 83.017539
iter  70 value 82.642119
iter  80 value 81.929978
iter  90 value 81.618657
iter 100 value 80.510961
final  value 80.510961 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.631294 
iter  10 value 94.132738
iter  20 value 87.002381
iter  30 value 83.903860
iter  40 value 82.540610
iter  50 value 81.511780
iter  60 value 81.292397
iter  70 value 81.058503
iter  80 value 80.973693
iter  90 value 80.609174
iter 100 value 80.476417
final  value 80.476417 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 111.984791 
iter  10 value 94.486588
iter  20 value 94.367510
iter  30 value 92.784418
iter  40 value 87.578735
iter  50 value 83.225060
iter  60 value 82.737892
iter  70 value 81.980223
iter  80 value 80.835462
iter  90 value 80.598660
iter 100 value 80.520078
final  value 80.520078 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.302793 
iter  10 value 94.425278
iter  20 value 88.281455
iter  30 value 87.726968
iter  40 value 85.914584
iter  50 value 85.595804
iter  60 value 85.374453
iter  70 value 84.889306
final  value 84.875975 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.674280 
iter  10 value 87.814754
iter  20 value 87.172363
iter  30 value 86.812369
iter  40 value 84.745138
iter  50 value 84.693397
iter  60 value 84.445813
final  value 84.433215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.849610 
iter  10 value 92.325349
iter  20 value 87.881013
iter  30 value 84.294958
iter  40 value 83.034825
iter  50 value 82.634528
iter  60 value 82.222968
iter  70 value 80.916960
iter  80 value 80.379292
iter  90 value 79.192597
iter 100 value 78.812353
final  value 78.812353 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.233056 
iter  10 value 94.469344
iter  20 value 94.049265
iter  30 value 93.423460
iter  40 value 90.751804
iter  50 value 88.619769
iter  60 value 86.300216
iter  70 value 85.800321
iter  80 value 85.238553
iter  90 value 84.813187
iter 100 value 83.888196
final  value 83.888196 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.091480 
iter  10 value 94.527065
iter  20 value 88.474255
iter  30 value 84.816560
iter  40 value 84.018827
iter  50 value 83.804782
iter  60 value 83.730441
iter  70 value 83.011416
iter  80 value 82.090076
iter  90 value 80.983861
iter 100 value 80.488735
final  value 80.488735 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.089583 
iter  10 value 94.457981
iter  20 value 89.815449
iter  30 value 86.511389
iter  40 value 83.888677
iter  50 value 83.011219
iter  60 value 82.156560
iter  70 value 80.665184
iter  80 value 80.256861
iter  90 value 79.360315
iter 100 value 79.258088
final  value 79.258088 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.677095 
iter  10 value 94.490513
iter  20 value 85.629835
iter  30 value 84.267312
iter  40 value 81.228240
iter  50 value 80.127396
iter  60 value 79.745594
iter  70 value 79.247071
iter  80 value 79.079686
iter  90 value 79.036719
iter 100 value 79.004097
final  value 79.004097 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.549303 
iter  10 value 95.917317
iter  20 value 93.528865
iter  30 value 91.070109
iter  40 value 86.955281
iter  50 value 85.662126
iter  60 value 85.106883
iter  70 value 84.716098
iter  80 value 81.928938
iter  90 value 80.735244
iter 100 value 80.318277
final  value 80.318277 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 153.459640 
iter  10 value 95.084611
iter  20 value 86.256333
iter  30 value 83.798074
iter  40 value 83.410067
iter  50 value 83.017462
iter  60 value 80.911581
iter  70 value 80.097255
iter  80 value 79.706575
iter  90 value 79.495041
iter 100 value 79.098489
final  value 79.098489 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.337972 
iter  10 value 94.483769
iter  20 value 93.931152
iter  30 value 85.051821
iter  40 value 83.323945
iter  50 value 82.696992
iter  60 value 81.355470
iter  70 value 81.009245
iter  80 value 80.542012
iter  90 value 80.295044
iter 100 value 80.201712
final  value 80.201712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.959969 
iter  10 value 94.581656
iter  20 value 88.218019
iter  30 value 86.552883
iter  40 value 84.786873
iter  50 value 84.535758
iter  60 value 82.458459
iter  70 value 80.854849
iter  80 value 80.078524
iter  90 value 79.911623
iter 100 value 79.727356
final  value 79.727356 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.585343 
iter  10 value 94.238548
iter  20 value 87.577009
iter  30 value 85.581340
iter  40 value 85.268939
iter  50 value 84.869875
iter  60 value 82.019973
iter  70 value 80.601133
iter  80 value 79.671809
iter  90 value 79.572700
iter 100 value 79.474626
final  value 79.474626 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.930775 
final  value 94.485836 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.582536 
iter  10 value 94.485967
iter  20 value 94.484224
iter  20 value 94.484223
iter  20 value 94.484223
final  value 94.484223 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.163901 
final  value 94.469591 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.285029 
final  value 94.485898 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.988923 
final  value 94.485886 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.833724 
iter  10 value 94.359224
iter  20 value 94.357620
iter  30 value 94.069491
iter  40 value 86.712348
iter  50 value 85.095345
iter  60 value 85.050170
iter  70 value 85.012100
iter  80 value 85.011400
iter  90 value 85.010514
iter 100 value 85.004835
final  value 85.004835 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.514341 
iter  10 value 94.489397
iter  20 value 94.484741
iter  30 value 89.916367
iter  40 value 84.927781
iter  50 value 83.970491
iter  60 value 83.962671
iter  70 value 83.961093
iter  80 value 83.956950
iter  90 value 83.954947
iter 100 value 83.917307
final  value 83.917307 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.842583 
iter  10 value 94.460490
iter  20 value 94.456161
final  value 94.455755 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.817221 
iter  10 value 94.359331
iter  20 value 94.249609
iter  30 value 84.609788
iter  40 value 83.037648
iter  50 value 83.015610
final  value 83.015082 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.529489 
iter  10 value 94.488575
iter  20 value 94.093579
iter  30 value 88.323372
iter  40 value 84.887428
iter  50 value 84.887130
iter  60 value 84.675147
iter  70 value 82.923082
iter  80 value 82.919121
iter  90 value 82.300996
final  value 82.241809 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.753870 
iter  10 value 94.491996
iter  20 value 94.355492
final  value 94.355005 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.657506 
iter  10 value 94.492357
iter  20 value 94.444167
iter  30 value 93.972351
iter  40 value 91.418799
iter  50 value 83.361256
iter  60 value 83.351955
iter  70 value 83.089974
iter  80 value 83.079319
final  value 83.079305 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.025547 
iter  10 value 94.362553
iter  20 value 94.355848
iter  30 value 94.355393
iter  40 value 88.061129
iter  50 value 84.849035
final  value 84.847222 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.008247 
iter  10 value 94.492622
iter  20 value 94.461665
iter  30 value 89.843507
iter  40 value 83.694747
iter  50 value 83.415103
iter  60 value 83.225372
iter  70 value 82.264238
iter  80 value 82.230021
iter  90 value 82.183813
iter 100 value 82.181298
final  value 82.181298 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.487272 
iter  10 value 94.492692
iter  20 value 94.482282
iter  30 value 92.985987
iter  40 value 83.412014
iter  50 value 83.382433
iter  60 value 83.380485
iter  70 value 83.258804
iter  80 value 83.251987
iter  90 value 83.157330
iter 100 value 82.358731
final  value 82.358731 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.576666 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.689394 
final  value 93.810010 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.837469 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.797930 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.650068 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.463228 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.242260 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.233131 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.285590 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.124558 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.180402 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.179620 
final  value 93.969040 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.871258 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.473894 
iter  10 value 93.969031
final  value 93.921212 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.514938 
iter  10 value 93.921212
iter  10 value 93.921212
iter  10 value 93.921212
final  value 93.921212 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.874570 
iter  10 value 94.089065
iter  20 value 93.901119
iter  30 value 93.885312
iter  40 value 93.838170
iter  50 value 93.837823
final  value 93.837804 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.354118 
iter  10 value 93.817204
iter  20 value 88.385202
iter  30 value 86.979905
iter  40 value 86.619885
iter  50 value 86.320620
iter  60 value 84.172927
iter  70 value 84.026705
final  value 84.023416 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.189588 
iter  10 value 93.955026
iter  20 value 91.812343
iter  30 value 91.443455
iter  40 value 86.321043
iter  50 value 84.159798
iter  60 value 84.130004
iter  70 value 84.093512
iter  80 value 84.086841
final  value 84.086347 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.463603 
iter  10 value 93.999333
iter  20 value 88.851048
iter  30 value 84.350232
iter  40 value 84.111617
iter  50 value 83.944341
iter  60 value 83.924111
final  value 83.923718 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.847420 
iter  10 value 94.054820
iter  20 value 89.015988
iter  30 value 86.622934
iter  40 value 84.935692
iter  50 value 84.650618
iter  60 value 84.327033
final  value 84.327026 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.093711 
iter  10 value 94.112386
iter  20 value 93.561883
iter  30 value 93.115737
iter  40 value 89.518736
iter  50 value 85.785562
iter  60 value 82.435836
iter  70 value 81.924769
iter  80 value 81.356995
iter  90 value 81.113372
iter 100 value 80.962862
final  value 80.962862 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.801055 
iter  10 value 94.048533
iter  20 value 92.545038
iter  30 value 91.171824
iter  40 value 87.005262
iter  50 value 84.551602
iter  60 value 83.567328
iter  70 value 83.179659
iter  80 value 82.513180
iter  90 value 82.338936
iter 100 value 82.319497
final  value 82.319497 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.614133 
iter  10 value 94.588627
iter  20 value 91.255145
iter  30 value 87.327308
iter  40 value 86.612365
iter  50 value 84.496948
iter  60 value 84.145590
iter  70 value 84.086230
iter  80 value 83.995881
iter  90 value 83.320641
iter 100 value 81.805957
final  value 81.805957 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.060026 
iter  10 value 93.481343
iter  20 value 92.668153
iter  30 value 91.075209
iter  40 value 90.853513
iter  50 value 90.773950
iter  60 value 90.595369
iter  70 value 87.081211
iter  80 value 82.473933
iter  90 value 81.668455
iter 100 value 81.445896
final  value 81.445896 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.637044 
iter  10 value 94.768878
iter  20 value 87.279385
iter  30 value 85.996827
iter  40 value 81.985000
iter  50 value 81.227266
iter  60 value 81.090265
iter  70 value 80.962494
iter  80 value 80.885013
iter  90 value 80.828512
iter 100 value 80.769186
final  value 80.769186 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.776358 
iter  10 value 92.607298
iter  20 value 84.791248
iter  30 value 84.285441
iter  40 value 82.863417
iter  50 value 82.716005
iter  60 value 82.584641
iter  70 value 82.477587
iter  80 value 82.432752
iter  90 value 81.709345
iter 100 value 81.532391
final  value 81.532391 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.255705 
iter  10 value 93.275083
iter  20 value 85.368297
iter  30 value 82.754014
iter  40 value 81.902469
iter  50 value 81.181693
iter  60 value 81.054695
iter  70 value 81.030167
iter  80 value 80.957518
iter  90 value 80.507270
iter 100 value 80.467295
final  value 80.467295 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.442030 
iter  10 value 94.064776
iter  20 value 92.999591
iter  30 value 86.888896
iter  40 value 86.406080
iter  50 value 84.920273
iter  60 value 84.712744
iter  70 value 84.050835
iter  80 value 83.813348
iter  90 value 83.096861
iter 100 value 82.413774
final  value 82.413774 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.278529 
iter  10 value 92.810113
iter  20 value 87.303343
iter  30 value 84.363445
iter  40 value 81.836547
iter  50 value 81.092554
iter  60 value 80.605314
iter  70 value 80.528025
iter  80 value 80.432428
iter  90 value 80.398342
iter 100 value 80.384330
final  value 80.384330 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.992064 
iter  10 value 94.044109
iter  20 value 87.392189
iter  30 value 83.873206
iter  40 value 83.260278
iter  50 value 82.043636
iter  60 value 81.194746
iter  70 value 80.979246
iter  80 value 80.924782
iter  90 value 80.897245
iter 100 value 80.826322
final  value 80.826322 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.582377 
final  value 94.054508 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.231565 
final  value 94.054680 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.806126 
final  value 93.990710 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.058062 
iter  10 value 93.837682
iter  20 value 93.836023
iter  30 value 92.446959
iter  40 value 92.405388
final  value 91.227748 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.144129 
final  value 94.054423 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.113206 
iter  10 value 94.057766
iter  20 value 94.050823
iter  30 value 85.285969
iter  40 value 85.049659
iter  50 value 85.007748
iter  60 value 85.006887
final  value 85.006862 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.150893 
iter  10 value 93.972827
iter  20 value 93.836057
final  value 93.834473 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.134726 
iter  10 value 93.840705
iter  20 value 93.836858
final  value 93.836743 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.799233 
iter  10 value 94.054174
iter  20 value 93.375725
iter  30 value 88.671409
iter  40 value 88.638060
iter  50 value 88.510294
iter  60 value 87.520213
iter  70 value 87.504126
iter  80 value 87.451111
iter  90 value 87.282305
iter 100 value 87.281467
final  value 87.281467 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.000419 
iter  10 value 94.056782
iter  20 value 93.805303
iter  30 value 85.589493
iter  40 value 82.266303
iter  50 value 80.317716
iter  60 value 80.004041
iter  70 value 79.776583
iter  80 value 79.680674
iter  90 value 79.608427
iter 100 value 79.593185
final  value 79.593185 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.101325 
iter  10 value 93.843898
iter  20 value 93.795305
iter  30 value 86.637245
final  value 86.636252 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.096387 
iter  10 value 93.844039
iter  20 value 93.837409
final  value 93.836329 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.899473 
iter  10 value 93.844476
iter  20 value 93.641538
iter  30 value 86.386883
iter  40 value 84.594986
iter  50 value 83.896226
iter  60 value 83.894338
final  value 83.893353 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.788761 
iter  10 value 86.594958
iter  20 value 86.530770
iter  30 value 86.281726
iter  40 value 85.984840
iter  50 value 85.947305
iter  60 value 85.909356
iter  70 value 85.908216
iter  80 value 85.836408
iter  90 value 85.656698
iter 100 value 84.076453
final  value 84.076453 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.476008 
iter  10 value 90.590712
iter  20 value 86.287783
iter  30 value 85.688204
iter  40 value 85.573692
iter  50 value 85.566819
iter  60 value 85.565580
iter  70 value 85.562764
iter  80 value 85.561657
iter  90 value 84.321857
iter 100 value 83.523243
final  value 83.523243 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.523231 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.397133 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.450672 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.066620 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.308654 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.647904 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.219127 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.553764 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.296245 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.369036 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.895293 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.211590 
iter  10 value 94.349777
iter  20 value 94.236111
final  value 94.165117 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.943585 
final  value 94.132773 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.247382 
iter  10 value 81.737089
iter  20 value 79.918663
iter  30 value 78.730415
iter  40 value 78.601176
iter  50 value 78.599808
final  value 78.599297 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.492122 
iter  10 value 94.276942
iter  20 value 94.275367
final  value 94.275363 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.086092 
iter  10 value 94.282738
iter  20 value 90.904302
iter  30 value 86.370423
iter  40 value 85.562539
iter  50 value 84.815430
iter  60 value 82.585260
iter  70 value 82.567914
iter  80 value 82.554233
iter  90 value 82.550456
iter 100 value 82.545282
final  value 82.545282 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.064712 
iter  10 value 94.570620
iter  20 value 94.489271
iter  30 value 94.194490
iter  40 value 91.757797
iter  50 value 85.950773
iter  60 value 83.827011
iter  70 value 83.699827
iter  80 value 83.673397
iter  90 value 83.526582
iter 100 value 83.131266
final  value 83.131266 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.283723 
iter  10 value 94.400191
iter  20 value 93.013201
iter  30 value 92.127847
iter  40 value 91.342341
iter  50 value 91.316953
final  value 91.316950 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.477640 
iter  10 value 94.487724
iter  20 value 91.309680
iter  30 value 90.578459
iter  40 value 88.067566
iter  50 value 84.986410
iter  60 value 82.991218
iter  70 value 81.576553
iter  80 value 80.854867
iter  90 value 80.581361
iter 100 value 80.415566
final  value 80.415566 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.780199 
iter  10 value 94.448645
iter  20 value 94.143125
iter  30 value 94.129096
iter  40 value 90.383513
iter  50 value 84.805876
iter  60 value 84.709158
iter  70 value 83.148221
final  value 83.096526 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.026070 
iter  10 value 95.328978
iter  20 value 93.040766
iter  30 value 85.576372
iter  40 value 85.008221
iter  50 value 84.657796
iter  60 value 83.355510
iter  70 value 80.910673
iter  80 value 79.758932
iter  90 value 79.231753
iter 100 value 78.605692
final  value 78.605692 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.708807 
iter  10 value 94.374078
iter  20 value 86.302352
iter  30 value 85.557765
iter  40 value 84.693648
iter  50 value 84.157120
iter  60 value 83.059554
iter  70 value 81.197794
iter  80 value 80.763315
iter  90 value 80.400806
iter 100 value 79.386223
final  value 79.386223 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.440845 
iter  10 value 92.472504
iter  20 value 87.116445
iter  30 value 84.021257
iter  40 value 83.370738
iter  50 value 82.429269
iter  60 value 81.960347
iter  70 value 81.532672
iter  80 value 80.613549
iter  90 value 80.462686
iter 100 value 80.390512
final  value 80.390512 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.894778 
iter  10 value 94.480133
iter  20 value 94.211196
iter  30 value 90.902784
iter  40 value 87.219311
iter  50 value 84.577681
iter  60 value 83.116775
iter  70 value 81.663129
iter  80 value 81.581511
iter  90 value 81.394283
iter 100 value 81.286153
final  value 81.286153 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.780984 
iter  10 value 94.369382
iter  20 value 93.864954
iter  30 value 90.415676
iter  40 value 89.265255
iter  50 value 83.557450
iter  60 value 82.558541
iter  70 value 80.373617
iter  80 value 79.812528
iter  90 value 79.604844
iter 100 value 79.296258
final  value 79.296258 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.752129 
iter  10 value 94.560250
iter  20 value 93.731812
iter  30 value 85.798565
iter  40 value 83.582216
iter  50 value 82.495442
iter  60 value 81.135941
iter  70 value 80.140851
iter  80 value 79.973080
iter  90 value 79.686670
iter 100 value 79.527978
final  value 79.527978 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.560387 
iter  10 value 94.377295
iter  20 value 90.569966
iter  30 value 85.082444
iter  40 value 82.896033
iter  50 value 80.933948
iter  60 value 80.586964
iter  70 value 80.141852
iter  80 value 79.848196
iter  90 value 79.125773
iter 100 value 78.884356
final  value 78.884356 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.966352 
iter  10 value 93.954232
iter  20 value 84.780342
iter  30 value 84.440206
iter  40 value 81.939942
iter  50 value 80.633825
iter  60 value 80.176027
iter  70 value 80.045393
iter  80 value 79.317012
iter  90 value 78.530888
iter 100 value 78.369088
final  value 78.369088 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.596787 
iter  10 value 94.815630
iter  20 value 93.214368
iter  30 value 90.112125
iter  40 value 86.431164
iter  50 value 83.346345
iter  60 value 82.172338
iter  70 value 80.949547
iter  80 value 80.214179
iter  90 value 79.260209
iter 100 value 78.691017
final  value 78.691017 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.670614 
iter  10 value 94.794035
iter  20 value 92.252096
iter  30 value 89.048897
iter  40 value 85.430006
iter  50 value 83.256810
iter  60 value 81.446168
iter  70 value 80.661447
iter  80 value 79.683429
iter  90 value 78.904396
iter 100 value 78.836181
final  value 78.836181 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 114.375124 
final  value 94.485769 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.772991 
final  value 94.485817 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.600966 
final  value 94.485575 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.673456 
final  value 94.486288 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.987048 
iter  10 value 94.486033
iter  20 value 94.464883
final  value 94.354324 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.503670 
iter  10 value 94.349524
iter  20 value 94.279932
iter  30 value 93.806179
iter  40 value 88.661455
iter  50 value 88.116022
iter  60 value 85.157244
iter  70 value 84.097714
iter  80 value 84.095942
iter  90 value 83.968781
iter 100 value 82.585420
final  value 82.585420 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.985252 
iter  10 value 94.280222
iter  20 value 94.275865
iter  30 value 91.973534
iter  40 value 91.692281
iter  50 value 91.625299
iter  60 value 91.625165
final  value 91.625158 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.531170 
iter  10 value 94.280212
iter  20 value 94.263023
iter  30 value 94.076946
final  value 94.071894 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.431006 
iter  10 value 94.489051
iter  20 value 94.476275
final  value 94.275499 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.622635 
iter  10 value 94.488989
iter  20 value 94.484255
final  value 94.484235 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.454328 
iter  10 value 94.226500
iter  20 value 94.111741
iter  30 value 94.079834
iter  40 value 94.078703
iter  50 value 89.308401
iter  60 value 83.033018
iter  70 value 81.801830
iter  80 value 81.569632
final  value 81.568272 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.267803 
iter  10 value 94.283752
iter  20 value 94.277287
iter  30 value 94.276664
iter  40 value 94.268678
iter  50 value 94.127939
iter  60 value 94.127309
final  value 94.127266 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.835400 
iter  10 value 94.491811
iter  20 value 94.407786
iter  30 value 89.579014
iter  40 value 85.556535
iter  50 value 85.511468
iter  60 value 85.336047
iter  70 value 85.182958
iter  80 value 85.181164
iter  90 value 85.172741
iter 100 value 85.111794
final  value 85.111794 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.325119 
iter  10 value 94.283891
iter  20 value 94.051275
iter  30 value 87.273109
iter  40 value 87.099786
iter  50 value 84.456600
iter  60 value 84.431669
iter  70 value 83.669969
iter  80 value 79.140413
iter  90 value 78.851358
final  value 78.849458 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.349522 
iter  10 value 94.491064
iter  20 value 93.173250
iter  30 value 84.219453
iter  40 value 84.217451
iter  50 value 84.214821
iter  60 value 84.021516
iter  70 value 83.148311
iter  80 value 81.087972
iter  90 value 80.412615
iter 100 value 80.047532
final  value 80.047532 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 123.337662 
iter  10 value 114.389243
iter  20 value 107.831264
iter  30 value 106.538671
iter  40 value 105.340624
iter  50 value 104.686887
iter  60 value 104.573659
iter  70 value 104.404921
iter  80 value 104.394230
iter  90 value 104.368885
iter 100 value 104.322582
final  value 104.322582 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.676858 
iter  10 value 117.955142
iter  20 value 109.636633
iter  30 value 106.155390
iter  40 value 103.528531
iter  50 value 102.203568
iter  60 value 101.409281
iter  70 value 101.372133
iter  80 value 101.364199
iter  90 value 101.358978
iter 100 value 101.354627
final  value 101.354627 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 123.579978 
iter  10 value 118.235086
iter  20 value 117.907019
iter  30 value 117.814003
iter  40 value 109.419229
iter  50 value 107.427164
iter  60 value 106.156345
iter  70 value 105.685510
iter  80 value 105.612861
iter  90 value 104.125939
iter 100 value 103.342549
final  value 103.342549 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 133.318290 
iter  10 value 116.580097
iter  20 value 112.016372
iter  30 value 106.721638
iter  40 value 105.524202
iter  50 value 105.220171
iter  60 value 103.089222
iter  70 value 101.920656
iter  80 value 101.229170
iter  90 value 100.611092
iter 100 value 100.452210
final  value 100.452210 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.907766 
iter  10 value 117.920190
iter  20 value 115.727834
iter  30 value 108.471603
iter  40 value 107.304823
iter  50 value 107.258094
iter  60 value 104.078521
iter  70 value 102.348509
iter  80 value 101.978625
iter  90 value 101.627053
iter 100 value 101.460964
final  value 101.460964 
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 -- Fri Nov  1 23:22:22 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 
 35.473   1.479  37.574