##############################################################################
##############################################################################
###
### 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       27.391  1.471  28.964
corr_plot     25.584  1.317  26.963
FSmethod      24.642  1.205  25.894
pred_ensembel 10.188  0.332   9.077
enrichfindP    0.339  0.051  39.727
* 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 100.817365 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.854401 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.794342 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.184686 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.343745 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.916740 
iter  10 value 92.881201
iter  20 value 85.487413
iter  30 value 85.485293
final  value 85.485236 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.136550 
iter  10 value 90.874861
iter  20 value 86.954316
final  value 86.952568 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.720695 
iter  10 value 93.979306
iter  20 value 93.055902
iter  30 value 89.358234
final  value 89.356077 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.770454 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.513055 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.458179 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.381366 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.920935 
iter  10 value 93.213986
iter  10 value 93.213985
iter  10 value 93.213985
final  value 93.213985 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.110500 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.169551 
iter  10 value 93.895308
final  value 93.895098 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.577971 
iter  10 value 94.447413
iter  20 value 89.727637
iter  30 value 88.983518
iter  40 value 88.737229
iter  50 value 85.629459
iter  60 value 85.213470
iter  70 value 85.107712
iter  80 value 84.966869
final  value 84.964852 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.326995 
iter  10 value 94.490438
iter  20 value 94.318990
iter  30 value 88.822350
iter  40 value 83.718786
iter  50 value 81.611431
iter  60 value 80.661239
iter  70 value 79.917557
iter  80 value 79.722936
iter  90 value 79.450332
final  value 79.442736 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.971636 
iter  10 value 94.482942
iter  20 value 94.334852
iter  30 value 89.871942
iter  40 value 87.866293
iter  50 value 85.550688
iter  60 value 82.839575
iter  70 value 80.959663
iter  80 value 80.536236
iter  90 value 80.305480
iter 100 value 80.248967
final  value 80.248967 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.123280 
iter  10 value 94.490116
iter  20 value 94.233006
iter  30 value 88.135435
iter  40 value 86.768652
iter  50 value 86.258208
iter  60 value 85.829580
iter  70 value 83.714843
iter  80 value 83.428343
iter  90 value 80.719884
iter 100 value 80.275459
final  value 80.275459 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.417092 
iter  10 value 94.401760
iter  20 value 93.972455
iter  30 value 93.967292
iter  40 value 93.960828
iter  50 value 93.717076
iter  60 value 90.895649
iter  70 value 88.125586
iter  80 value 84.789713
iter  90 value 84.053003
iter 100 value 83.318938
final  value 83.318938 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.215052 
iter  10 value 94.241569
iter  20 value 89.665587
iter  30 value 86.834190
iter  40 value 84.878328
iter  50 value 83.919879
iter  60 value 83.531562
iter  70 value 83.184273
iter  80 value 82.765742
iter  90 value 81.718432
iter 100 value 79.525612
final  value 79.525612 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.510236 
iter  10 value 94.428134
iter  20 value 88.606069
iter  30 value 83.177017
iter  40 value 83.026123
iter  50 value 80.610516
iter  60 value 80.168078
iter  70 value 79.855332
iter  80 value 79.576788
iter  90 value 79.187416
iter 100 value 78.860856
final  value 78.860856 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.398380 
iter  10 value 93.497537
iter  20 value 86.106530
iter  30 value 84.733907
iter  40 value 84.408358
iter  50 value 84.254227
iter  60 value 83.049434
iter  70 value 80.041884
iter  80 value 79.060231
iter  90 value 78.785985
iter 100 value 78.666684
final  value 78.666684 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.268184 
iter  10 value 94.479757
iter  20 value 93.612455
iter  30 value 90.082146
iter  40 value 83.612390
iter  50 value 81.442409
iter  60 value 79.726936
iter  70 value 78.731727
iter  80 value 78.140866
iter  90 value 77.884479
iter 100 value 77.733957
final  value 77.733957 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.677601 
iter  10 value 94.347726
iter  20 value 93.985164
iter  30 value 93.967252
iter  40 value 93.929985
iter  50 value 91.247483
iter  60 value 88.471623
iter  70 value 87.355833
iter  80 value 85.227209
iter  90 value 84.596220
iter 100 value 83.432307
final  value 83.432307 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.666097 
iter  10 value 94.229991
iter  20 value 91.992502
iter  30 value 88.046419
iter  40 value 87.129923
iter  50 value 86.595565
iter  60 value 85.072348
iter  70 value 81.319136
iter  80 value 79.462618
iter  90 value 79.106509
iter 100 value 78.319465
final  value 78.319465 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.993381 
iter  10 value 94.546351
iter  20 value 94.468630
iter  30 value 94.013118
iter  40 value 93.213992
iter  50 value 85.623197
iter  60 value 84.521186
iter  70 value 83.679314
iter  80 value 81.643017
iter  90 value 80.080413
iter 100 value 79.022680
final  value 79.022680 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.899827 
iter  10 value 94.661494
iter  20 value 90.757931
iter  30 value 81.621201
iter  40 value 80.846468
iter  50 value 79.757426
iter  60 value 79.413280
iter  70 value 79.081795
iter  80 value 78.859010
iter  90 value 78.770293
iter 100 value 78.403859
final  value 78.403859 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.333188 
iter  10 value 94.292299
iter  20 value 90.278516
iter  30 value 85.473065
iter  40 value 84.207265
iter  50 value 83.548842
iter  60 value 83.355017
iter  70 value 83.039223
iter  80 value 82.799561
iter  90 value 82.450599
iter 100 value 80.014561
final  value 80.014561 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.356494 
iter  10 value 92.823624
iter  20 value 85.070964
iter  30 value 84.200437
iter  40 value 82.438144
iter  50 value 82.003010
iter  60 value 81.412048
iter  70 value 80.963499
iter  80 value 79.823785
iter  90 value 79.247295
iter 100 value 78.359184
final  value 78.359184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.679501 
final  value 94.485809 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.656371 
iter  10 value 94.355773
iter  20 value 94.355565
iter  30 value 94.355011
final  value 94.354554 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.924988 
final  value 94.485669 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.018191 
final  value 94.485884 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.361009 
final  value 94.485771 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.294974 
iter  10 value 94.488939
iter  20 value 94.478560
iter  30 value 93.912094
iter  40 value 93.912059
iter  40 value 93.912059
iter  40 value 93.912059
final  value 93.912059 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.784758 
iter  10 value 94.359336
iter  20 value 94.354527
iter  30 value 94.354405
iter  40 value 92.923484
iter  50 value 82.103901
iter  60 value 82.102616
iter  70 value 79.376783
iter  80 value 78.829136
iter  90 value 78.828321
iter 100 value 78.827969
final  value 78.827969 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.689631 
iter  10 value 94.488768
iter  20 value 87.270782
iter  30 value 85.544308
iter  40 value 85.527677
iter  50 value 85.526360
iter  60 value 82.827880
iter  70 value 82.332818
iter  80 value 82.317394
iter  90 value 81.492959
final  value 81.390105 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.015989 
iter  10 value 94.488720
iter  20 value 94.482101
iter  30 value 83.919471
iter  40 value 83.028793
iter  50 value 83.027967
iter  60 value 82.443926
iter  70 value 82.443882
iter  70 value 82.443881
iter  70 value 82.443881
final  value 82.443881 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.906033 
iter  10 value 94.487775
iter  20 value 94.472772
iter  30 value 85.053198
iter  40 value 85.046829
iter  50 value 85.041184
iter  60 value 84.477713
iter  70 value 84.463366
iter  80 value 84.444535
iter  90 value 84.231952
final  value 84.230752 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.073374 
iter  10 value 94.492561
iter  20 value 94.475999
iter  30 value 85.285371
iter  40 value 84.044728
iter  50 value 82.509629
iter  60 value 81.027665
iter  70 value 81.021972
iter  80 value 80.445623
iter  90 value 79.867547
iter 100 value 79.801170
final  value 79.801170 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.109365 
iter  10 value 94.362491
iter  20 value 93.970497
iter  30 value 92.792139
iter  40 value 85.701924
iter  50 value 85.689425
iter  60 value 85.689251
final  value 85.689232 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.843430 
iter  10 value 94.362406
iter  20 value 93.147321
iter  30 value 85.274063
iter  40 value 85.251875
final  value 85.251800 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.144096 
iter  10 value 94.363152
iter  20 value 94.356244
iter  30 value 94.323305
iter  40 value 87.121946
iter  50 value 87.119269
iter  60 value 87.119019
iter  70 value 87.118756
iter  80 value 83.530676
iter  90 value 83.512560
iter 100 value 82.760029
final  value 82.760029 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.177915 
iter  10 value 94.492246
iter  20 value 93.706590
iter  30 value 90.353101
iter  40 value 89.760153
iter  50 value 86.508717
iter  60 value 86.493107
iter  70 value 86.492886
final  value 86.492866 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.712721 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.100694 
final  value 94.053065 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.948152 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.050920 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.177439 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.316517 
iter  10 value 91.718019
iter  20 value 91.570712
final  value 91.489323 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.507599 
iter  10 value 90.836366
iter  20 value 90.809719
iter  30 value 90.809663
final  value 90.809637 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.406569 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.446916 
iter  10 value 90.427494
iter  20 value 88.447124
iter  30 value 87.841400
iter  40 value 87.562802
final  value 87.528305 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.276517 
iter  10 value 92.287392
iter  20 value 92.281087
final  value 92.281082 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.648403 
iter  10 value 91.822956
iter  20 value 91.444115
iter  30 value 91.439936
final  value 91.439926 
converged
Fitting Repeat 2 

# weights:  507
initial  value 134.354373 
iter  10 value 93.265885
iter  20 value 92.362727
iter  30 value 92.031985
iter  40 value 92.029801
final  value 92.029797 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.767932 
iter  10 value 86.453343
iter  20 value 83.334216
iter  30 value 83.322415
final  value 83.322348 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.673262 
iter  10 value 92.551681
iter  20 value 92.037366
iter  30 value 92.019988
final  value 92.019964 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.191728 
iter  10 value 92.575693
final  value 92.563128 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.221011 
iter  10 value 93.598036
iter  20 value 92.102339
iter  30 value 84.175442
iter  40 value 83.032892
iter  50 value 81.992697
iter  60 value 80.537413
iter  70 value 80.114883
iter  80 value 80.108773
final  value 80.108771 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.992128 
iter  10 value 90.945664
iter  20 value 84.526622
iter  30 value 83.892368
iter  40 value 82.240458
iter  50 value 81.894885
iter  60 value 81.886722
final  value 81.886545 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.123623 
iter  10 value 94.056665
iter  20 value 93.414797
iter  30 value 93.029391
iter  40 value 89.917220
iter  50 value 84.142918
iter  60 value 82.777183
iter  70 value 81.331168
iter  80 value 81.147919
iter  90 value 80.128463
iter 100 value 79.990988
final  value 79.990988 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.966390 
iter  10 value 94.319188
iter  20 value 94.044390
iter  30 value 93.326855
iter  40 value 92.875796
iter  50 value 90.440565
iter  60 value 84.215759
iter  70 value 83.277330
iter  80 value 80.762238
iter  90 value 80.321276
iter 100 value 80.116344
final  value 80.116344 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.315702 
iter  10 value 94.051596
iter  20 value 92.688919
iter  30 value 84.491467
iter  40 value 82.986118
iter  50 value 81.105696
iter  60 value 80.897573
iter  70 value 80.425531
iter  80 value 80.111959
iter  90 value 80.108771
iter  90 value 80.108771
iter  90 value 80.108771
final  value 80.108771 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.213961 
iter  10 value 94.888235
iter  20 value 93.393170
iter  30 value 92.748098
iter  40 value 92.679456
iter  50 value 85.747271
iter  60 value 84.228049
iter  70 value 82.241694
iter  80 value 81.355372
iter  90 value 80.340475
iter 100 value 79.826448
final  value 79.826448 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.308315 
iter  10 value 93.922128
iter  20 value 85.987807
iter  30 value 85.155839
iter  40 value 83.577221
iter  50 value 82.630885
iter  60 value 82.007845
iter  70 value 81.009549
iter  80 value 80.805846
iter  90 value 80.439009
iter 100 value 79.982378
final  value 79.982378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.203405 
iter  10 value 90.613105
iter  20 value 81.807978
iter  30 value 81.449055
iter  40 value 81.265772
iter  50 value 81.226099
iter  60 value 81.209430
iter  70 value 80.924347
iter  80 value 79.381080
iter  90 value 78.649006
iter 100 value 78.275578
final  value 78.275578 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.406649 
iter  10 value 93.674175
iter  20 value 88.948352
iter  30 value 83.983788
iter  40 value 81.763805
iter  50 value 80.145846
iter  60 value 79.858208
iter  70 value 79.721981
iter  80 value 79.505520
iter  90 value 79.064506
iter 100 value 78.657353
final  value 78.657353 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.651390 
iter  10 value 93.115248
iter  20 value 86.250244
iter  30 value 83.258397
iter  40 value 82.827928
iter  50 value 82.549953
iter  60 value 82.423542
iter  70 value 81.899219
iter  80 value 80.383626
iter  90 value 79.705757
iter 100 value 79.544433
final  value 79.544433 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.254482 
iter  10 value 93.589277
iter  20 value 90.850626
iter  30 value 88.343150
iter  40 value 87.567133
iter  50 value 84.981716
iter  60 value 80.416773
iter  70 value 79.067981
iter  80 value 78.478724
iter  90 value 78.294080
iter 100 value 78.240152
final  value 78.240152 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.991990 
iter  10 value 93.276479
iter  20 value 88.624447
iter  30 value 84.762735
iter  40 value 81.623059
iter  50 value 79.641361
iter  60 value 78.988162
iter  70 value 78.753411
iter  80 value 78.476266
iter  90 value 78.331217
iter 100 value 78.269577
final  value 78.269577 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.677690 
iter  10 value 94.490102
iter  20 value 84.362482
iter  30 value 83.642044
iter  40 value 82.381491
iter  50 value 81.562019
iter  60 value 81.202851
iter  70 value 80.933380
iter  80 value 80.845949
iter  90 value 80.809413
iter 100 value 80.694225
final  value 80.694225 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.935170 
iter  10 value 93.080920
iter  20 value 92.586773
iter  30 value 91.483977
iter  40 value 88.238249
iter  50 value 84.271112
iter  60 value 80.954837
iter  70 value 80.309349
iter  80 value 80.014111
iter  90 value 79.501361
iter 100 value 79.242824
final  value 79.242824 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.332800 
iter  10 value 93.984404
iter  20 value 85.044807
iter  30 value 83.421507
iter  40 value 82.832320
iter  50 value 82.038531
iter  60 value 80.132486
iter  70 value 78.794627
iter  80 value 78.512393
iter  90 value 78.471090
iter 100 value 78.373637
final  value 78.373637 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.523648 
final  value 94.054491 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.706302 
final  value 94.054567 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.924214 
final  value 94.054554 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.187602 
iter  10 value 94.047098
final  value 94.023972 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.853199 
iter  10 value 94.054908
iter  20 value 93.979081
iter  30 value 92.273568
iter  40 value 92.038094
final  value 92.034823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.968725 
iter  10 value 94.057620
iter  20 value 94.052492
iter  30 value 92.362650
iter  40 value 92.344381
iter  50 value 90.046260
iter  60 value 89.102537
iter  70 value 89.094079
iter  80 value 89.015409
iter  90 value 88.954172
final  value 88.953508 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.594163 
iter  10 value 94.058070
iter  20 value 93.884383
iter  30 value 88.247912
iter  40 value 85.589814
iter  50 value 84.701462
final  value 84.699300 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.970921 
iter  10 value 94.078081
iter  20 value 93.728559
iter  30 value 89.982331
iter  40 value 89.941624
iter  50 value 89.296745
iter  60 value 88.651954
iter  70 value 88.622042
iter  80 value 88.614983
iter  90 value 88.610197
iter 100 value 88.119370
final  value 88.119370 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.368007 
iter  10 value 92.298101
iter  20 value 92.292078
iter  30 value 85.326542
iter  40 value 81.514139
iter  50 value 81.481479
iter  60 value 81.480930
iter  70 value 81.480559
final  value 81.479488 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.682546 
iter  10 value 92.296114
iter  20 value 92.292348
iter  30 value 92.288463
iter  40 value 92.063443
iter  50 value 87.817343
iter  60 value 86.402843
iter  70 value 85.128925
iter  80 value 82.218123
iter  90 value 77.140635
iter 100 value 76.908541
final  value 76.908541 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.411272 
iter  10 value 90.661850
iter  20 value 90.369316
iter  30 value 90.367217
iter  40 value 90.332239
iter  50 value 86.502928
iter  60 value 86.299872
iter  70 value 86.293038
iter  80 value 86.291508
iter  90 value 86.160301
iter 100 value 84.736358
final  value 84.736358 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.720411 
iter  10 value 92.297210
iter  20 value 92.293618
iter  30 value 92.100465
iter  40 value 92.038121
iter  50 value 92.036777
final  value 92.035076 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.795680 
iter  10 value 92.514932
iter  20 value 92.300428
iter  30 value 92.295590
iter  40 value 91.998605
iter  50 value 90.068840
iter  60 value 79.783683
iter  70 value 78.500989
iter  80 value 77.011190
iter  90 value 76.821239
iter 100 value 76.799697
final  value 76.799697 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.076857 
iter  10 value 92.300823
iter  20 value 92.294730
iter  30 value 91.973928
iter  40 value 91.589009
iter  50 value 81.900272
iter  60 value 81.681728
iter  70 value 81.660449
iter  80 value 81.575754
iter  90 value 81.574178
iter 100 value 81.569416
final  value 81.569416 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.860286 
iter  10 value 94.060854
iter  20 value 93.967839
iter  30 value 81.633130
iter  40 value 80.800206
iter  50 value 80.468458
iter  60 value 80.448500
iter  70 value 80.365208
iter  80 value 80.337791
iter  90 value 80.254834
iter 100 value 80.041409
final  value 80.041409 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.198532 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.859285 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.359178 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.775572 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.631477 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.948332 
final  value 94.088889 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.582650 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.010790 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.897120 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.165500 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.403470 
final  value 93.903448 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.562355 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.860825 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.378075 
iter  10 value 94.484496
iter  20 value 94.465271
iter  30 value 94.294443
final  value 94.242065 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.515874 
final  value 94.466822 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.826871 
iter  10 value 94.440448
iter  20 value 94.162539
iter  30 value 89.272877
iter  40 value 88.144434
iter  50 value 87.580357
final  value 87.572789 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.302420 
iter  10 value 94.485548
iter  20 value 92.023275
iter  30 value 87.612834
iter  40 value 86.641599
iter  50 value 86.383513
iter  60 value 85.723109
iter  70 value 85.629624
iter  80 value 85.609241
iter  90 value 85.514213
iter 100 value 85.460025
final  value 85.460025 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.968656 
iter  10 value 93.382237
iter  20 value 87.678741
iter  30 value 87.507880
iter  40 value 86.876273
iter  50 value 86.364143
iter  60 value 86.113370
iter  70 value 86.047901
iter  80 value 85.986758
final  value 85.985119 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.238565 
iter  10 value 94.488694
iter  20 value 92.055850
iter  30 value 88.282149
iter  40 value 86.798625
iter  50 value 86.555118
iter  60 value 85.897819
iter  70 value 85.103242
iter  80 value 84.517754
iter  90 value 84.317455
final  value 84.315001 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.186639 
iter  10 value 90.416785
iter  20 value 87.823381
iter  30 value 87.444114
iter  40 value 86.626884
iter  50 value 85.382251
iter  60 value 84.893545
iter  70 value 84.255351
iter  80 value 84.169131
iter  90 value 84.140089
final  value 84.129548 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.047210 
iter  10 value 94.513191
iter  20 value 93.494416
iter  30 value 92.703680
iter  40 value 91.209901
iter  50 value 90.196052
iter  60 value 84.782213
iter  70 value 84.293594
iter  80 value 83.828088
iter  90 value 83.597098
iter 100 value 83.372603
final  value 83.372603 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 130.919394 
iter  10 value 94.455988
iter  20 value 89.845296
iter  30 value 88.007840
iter  40 value 87.320136
iter  50 value 86.642595
iter  60 value 84.876512
iter  70 value 84.478291
iter  80 value 84.074724
iter  90 value 83.805158
iter 100 value 83.667789
final  value 83.667789 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.813031 
iter  10 value 94.126969
iter  20 value 89.358760
iter  30 value 86.494448
iter  40 value 86.332731
iter  50 value 86.195260
iter  60 value 85.771002
iter  70 value 85.413522
iter  80 value 85.062277
iter  90 value 84.872614
iter 100 value 84.334570
final  value 84.334570 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.083866 
iter  10 value 94.875599
iter  20 value 94.496443
iter  30 value 94.420952
iter  40 value 93.068322
iter  50 value 89.886179
iter  60 value 87.893010
iter  70 value 86.099228
iter  80 value 84.249240
iter  90 value 83.659256
iter 100 value 83.591316
final  value 83.591316 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.746949 
iter  10 value 92.685106
iter  20 value 91.178508
iter  30 value 87.842982
iter  40 value 86.563393
iter  50 value 85.509906
iter  60 value 84.028354
iter  70 value 83.296698
iter  80 value 83.225215
iter  90 value 83.054882
iter 100 value 82.857356
final  value 82.857356 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.797484 
iter  10 value 94.981113
iter  20 value 92.927514
iter  30 value 87.986050
iter  40 value 85.873207
iter  50 value 84.345364
iter  60 value 84.172370
iter  70 value 83.823294
iter  80 value 83.085219
iter  90 value 82.870299
iter 100 value 82.622771
final  value 82.622771 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.028837 
iter  10 value 94.697144
iter  20 value 89.189874
iter  30 value 86.653761
iter  40 value 85.780605
iter  50 value 85.349694
iter  60 value 85.117976
iter  70 value 84.477364
iter  80 value 83.960527
iter  90 value 83.655393
iter 100 value 83.455618
final  value 83.455618 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.197320 
iter  10 value 94.442153
iter  20 value 93.028524
iter  30 value 87.888126
iter  40 value 87.598551
iter  50 value 87.132403
iter  60 value 85.410449
iter  70 value 84.578615
iter  80 value 83.564947
iter  90 value 83.287472
iter 100 value 83.100584
final  value 83.100584 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.014429 
iter  10 value 95.037222
iter  20 value 94.071925
iter  30 value 88.621057
iter  40 value 88.138496
iter  50 value 85.993453
iter  60 value 85.127535
iter  70 value 84.154989
iter  80 value 83.602859
iter  90 value 83.277148
iter 100 value 82.814434
final  value 82.814434 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.192807 
iter  10 value 94.510941
iter  20 value 92.341834
iter  30 value 89.913047
iter  40 value 86.809047
iter  50 value 85.041061
iter  60 value 83.186012
iter  70 value 83.074829
iter  80 value 82.979885
iter  90 value 82.956066
iter 100 value 82.907849
final  value 82.907849 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.583718 
final  value 94.485754 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.034091 
final  value 94.485743 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.161417 
final  value 94.485796 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.608508 
iter  10 value 94.005297
iter  20 value 93.949402
iter  30 value 93.573162
iter  40 value 93.571040
final  value 93.565965 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.664599 
final  value 94.485950 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.476148 
iter  10 value 94.569938
iter  20 value 91.083546
iter  30 value 89.396122
iter  40 value 89.374042
iter  50 value 89.373212
iter  60 value 87.396866
iter  70 value 87.231687
iter  80 value 86.569738
iter  90 value 86.206873
iter 100 value 86.176838
final  value 86.176838 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.878492 
iter  10 value 88.437244
iter  20 value 87.358683
iter  30 value 87.356442
iter  40 value 87.337013
iter  50 value 87.336581
iter  60 value 87.265677
iter  70 value 87.166000
iter  80 value 87.156892
iter  90 value 87.147565
iter 100 value 87.147439
final  value 87.147439 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.234258 
iter  10 value 94.472345
iter  20 value 94.467269
iter  30 value 94.292815
final  value 94.089661 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.425097 
iter  10 value 94.101615
iter  20 value 94.083006
iter  30 value 94.082079
iter  40 value 94.080645
iter  50 value 94.080512
iter  60 value 93.169937
iter  70 value 87.281380
iter  80 value 86.575749
iter  90 value 86.514868
iter 100 value 86.513832
final  value 86.513832 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.118659 
iter  10 value 94.489545
iter  20 value 94.210885
iter  30 value 92.446314
iter  40 value 90.149429
iter  50 value 85.243960
iter  60 value 84.911748
iter  70 value 84.910728
iter  80 value 84.909067
iter  90 value 84.907388
iter 100 value 84.907098
final  value 84.907098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.772726 
iter  10 value 94.473626
iter  20 value 94.461333
iter  30 value 89.521274
iter  40 value 87.688809
iter  50 value 86.037063
iter  60 value 84.987505
iter  70 value 84.588229
iter  80 value 84.433890
iter  90 value 83.819317
iter 100 value 82.667338
final  value 82.667338 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.111247 
iter  10 value 94.489946
iter  20 value 94.418366
iter  30 value 91.214447
iter  40 value 88.676776
iter  50 value 86.188856
iter  60 value 85.972172
iter  70 value 85.968883
iter  80 value 85.964166
iter  90 value 85.963751
iter 100 value 85.963283
final  value 85.963283 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.662831 
iter  10 value 94.475041
iter  20 value 94.469579
iter  30 value 94.279037
iter  40 value 94.080616
iter  50 value 93.731466
iter  60 value 87.039658
iter  70 value 85.783045
final  value 85.780640 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.967905 
iter  10 value 93.061572
iter  20 value 92.940405
iter  30 value 92.937264
iter  40 value 92.936827
iter  50 value 92.933232
iter  60 value 92.931273
iter  70 value 92.931240
iter  80 value 92.930822
iter  90 value 92.779734
iter 100 value 90.495310
final  value 90.495310 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.931402 
iter  10 value 94.475725
iter  20 value 94.468023
final  value 94.467280 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.629239 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.965530 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.058124 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.749342 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.147398 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.979618 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.930401 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.983842 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.784615 
iter  10 value 94.053153
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.076584 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.646825 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.909398 
iter  10 value 93.549676
iter  20 value 93.429487
iter  20 value 93.429487
iter  20 value 93.429487
final  value 93.429487 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.312594 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.409221 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.695087 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.384410 
iter  10 value 94.046579
iter  20 value 85.839413
iter  30 value 84.950243
iter  40 value 84.869040
iter  50 value 84.737257
iter  60 value 84.338190
iter  70 value 84.108225
final  value 84.103953 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.657291 
iter  10 value 93.975565
iter  20 value 87.713634
iter  30 value 84.238684
iter  40 value 81.945763
iter  50 value 81.299104
iter  60 value 79.805773
iter  70 value 79.017515
iter  80 value 78.998490
final  value 78.991188 
converged
Fitting Repeat 3 

# weights:  103
initial  value 116.929067 
iter  10 value 94.048292
iter  20 value 93.703151
iter  30 value 85.233055
iter  40 value 82.089165
iter  50 value 80.998944
iter  60 value 80.513421
iter  70 value 80.506879
iter  80 value 79.810336
iter  90 value 79.658722
final  value 79.658689 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.130798 
iter  10 value 94.054373
iter  20 value 85.365018
iter  30 value 84.812876
iter  40 value 84.773279
iter  50 value 84.689982
iter  60 value 84.147190
final  value 84.103953 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.196324 
iter  10 value 94.054923
iter  20 value 93.933552
iter  30 value 93.675690
iter  40 value 90.052227
iter  50 value 87.194860
iter  60 value 86.370331
iter  70 value 85.531991
iter  80 value 81.016892
iter  90 value 79.920975
iter 100 value 79.041553
final  value 79.041553 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.864253 
iter  10 value 94.239459
iter  20 value 94.007703
iter  30 value 89.221261
iter  40 value 85.008520
iter  50 value 84.769324
iter  60 value 84.037740
iter  70 value 81.591305
iter  80 value 78.957431
iter  90 value 78.291765
iter 100 value 77.840916
final  value 77.840916 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.710062 
iter  10 value 92.947975
iter  20 value 87.772150
iter  30 value 85.344049
iter  40 value 81.658299
iter  50 value 81.428109
final  value 81.426042 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.622558 
iter  10 value 93.411198
iter  20 value 87.221427
iter  30 value 85.577805
iter  40 value 85.071062
iter  50 value 84.020649
iter  60 value 80.712119
iter  70 value 80.300216
iter  80 value 79.206265
iter  90 value 78.291237
iter 100 value 77.415023
final  value 77.415023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.527303 
iter  10 value 93.994262
iter  20 value 87.342922
iter  30 value 84.740170
iter  40 value 84.276979
iter  50 value 84.029561
iter  60 value 84.005005
iter  70 value 83.823471
iter  80 value 82.125368
iter  90 value 78.691111
iter 100 value 78.032051
final  value 78.032051 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.066775 
iter  10 value 93.938805
iter  20 value 88.596005
iter  30 value 85.490369
iter  40 value 84.327294
iter  50 value 81.658863
iter  60 value 80.807616
iter  70 value 80.223869
iter  80 value 79.929280
iter  90 value 79.881250
iter 100 value 79.519586
final  value 79.519586 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.197861 
iter  10 value 94.347257
iter  20 value 86.966612
iter  30 value 84.886782
iter  40 value 83.012899
iter  50 value 80.765928
iter  60 value 80.198729
iter  70 value 79.146086
iter  80 value 78.528992
iter  90 value 78.261258
iter 100 value 77.551327
final  value 77.551327 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.814279 
iter  10 value 94.058970
iter  20 value 93.121826
iter  30 value 85.649856
iter  40 value 82.850303
iter  50 value 80.035043
iter  60 value 79.729987
iter  70 value 79.121516
iter  80 value 78.304975
iter  90 value 77.654799
iter 100 value 77.536789
final  value 77.536789 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.642422 
iter  10 value 94.094825
iter  20 value 93.692365
iter  30 value 92.460683
iter  40 value 91.555344
iter  50 value 86.903521
iter  60 value 81.846307
iter  70 value 80.475408
iter  80 value 79.917013
iter  90 value 79.549466
iter 100 value 79.417718
final  value 79.417718 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.677813 
iter  10 value 95.356384
iter  20 value 94.404966
iter  30 value 94.192166
iter  40 value 86.238926
iter  50 value 84.399590
iter  60 value 80.622101
iter  70 value 78.677645
iter  80 value 78.102200
iter  90 value 77.756572
iter 100 value 77.321165
final  value 77.321165 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.320028 
iter  10 value 94.250520
iter  20 value 91.358914
iter  30 value 86.571597
iter  40 value 84.590001
iter  50 value 79.565403
iter  60 value 78.953101
iter  70 value 77.901782
iter  80 value 77.345573
iter  90 value 77.122055
iter 100 value 76.960422
final  value 76.960422 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.622200 
final  value 94.054627 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.736929 
iter  10 value 94.034494
iter  20 value 90.281694
iter  30 value 89.320197
iter  40 value 89.316784
iter  50 value 88.367120
iter  60 value 87.758656
iter  70 value 84.463475
iter  80 value 81.791015
iter  90 value 81.639154
iter 100 value 81.632989
final  value 81.632989 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.963902 
iter  10 value 94.034735
iter  20 value 93.920639
iter  30 value 83.574871
iter  40 value 83.562469
iter  50 value 83.453992
iter  60 value 83.453090
iter  70 value 83.450974
iter  80 value 83.450678
iter  90 value 83.450593
final  value 83.450589 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.051274 
final  value 94.054410 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.758627 
iter  10 value 94.054821
iter  20 value 94.052922
iter  20 value 94.052922
iter  20 value 94.052921
final  value 94.052921 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.815244 
iter  10 value 93.506382
iter  20 value 92.757173
iter  30 value 92.755338
iter  30 value 92.755338
final  value 92.755338 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.514247 
iter  10 value 94.037614
iter  20 value 94.034557
final  value 94.033822 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.303094 
iter  10 value 94.057398
iter  20 value 94.044675
iter  30 value 87.958069
iter  40 value 85.830643
iter  50 value 85.370775
final  value 85.370752 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.203997 
iter  10 value 94.057288
iter  20 value 94.053034
final  value 94.052745 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.186274 
iter  10 value 94.057802
iter  20 value 94.052923
final  value 94.052921 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.845630 
iter  10 value 94.060182
iter  20 value 87.834263
iter  30 value 82.426775
iter  40 value 82.173607
iter  50 value 81.673576
iter  60 value 81.392419
iter  70 value 80.945389
iter  80 value 79.963105
iter  90 value 79.333784
iter 100 value 77.834429
final  value 77.834429 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.295163 
iter  10 value 93.888362
iter  20 value 93.882050
iter  30 value 93.876886
iter  40 value 87.031807
iter  50 value 83.158002
iter  60 value 83.147837
iter  70 value 83.145666
iter  80 value 82.596526
iter  90 value 81.746906
iter 100 value 81.742368
final  value 81.742368 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.858711 
iter  10 value 94.049731
iter  20 value 93.771745
iter  30 value 83.578065
iter  40 value 83.568090
iter  50 value 83.453370
iter  60 value 83.451413
iter  70 value 83.274163
iter  80 value 79.483920
iter  90 value 77.009433
iter 100 value 75.883992
final  value 75.883992 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.179371 
iter  10 value 94.025528
iter  20 value 93.959677
iter  30 value 88.050521
iter  40 value 82.163847
iter  50 value 81.628161
iter  60 value 81.621101
final  value 81.621075 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.291723 
iter  10 value 93.754666
iter  20 value 92.248103
iter  30 value 92.239020
iter  40 value 92.236187
iter  50 value 92.233772
iter  60 value 92.233159
iter  70 value 92.231254
iter  80 value 92.230679
iter  90 value 92.230146
iter 100 value 92.039763
final  value 92.039763 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.061234 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.438865 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.867267 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.277530 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.146898 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.040292 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 126.863810 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.337877 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.234700 
final  value 94.322897 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.451790 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.212583 
iter  10 value 92.228782
final  value 92.227947 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.697879 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.659852 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.616495 
iter  10 value 93.580112
iter  20 value 90.346132
iter  30 value 90.345747
final  value 90.345709 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.142728 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.686074 
iter  10 value 94.454911
iter  20 value 90.153269
iter  30 value 86.307293
iter  40 value 85.174117
iter  50 value 84.319325
iter  60 value 83.704058
iter  70 value 83.680728
iter  80 value 83.543058
iter  90 value 83.473523
final  value 83.473238 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.133412 
iter  10 value 94.458511
iter  20 value 92.403612
iter  30 value 91.222668
iter  40 value 86.929811
iter  50 value 84.847100
iter  60 value 84.212650
iter  70 value 82.791654
iter  80 value 82.152925
iter  90 value 81.997552
final  value 81.989783 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.929654 
iter  10 value 94.488590
iter  20 value 94.440839
iter  30 value 86.143575
iter  40 value 85.310247
iter  50 value 84.471189
iter  60 value 84.291913
iter  70 value 83.841620
iter  80 value 83.484606
iter  90 value 83.473247
final  value 83.473239 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.497705 
iter  10 value 94.488432
iter  20 value 94.177503
iter  30 value 89.400043
iter  40 value 88.121113
iter  50 value 87.983546
iter  60 value 87.682343
iter  70 value 86.727389
iter  80 value 85.444609
iter  90 value 83.338376
iter 100 value 83.151344
final  value 83.151344 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.492450 
iter  10 value 94.422394
iter  20 value 86.320247
iter  30 value 85.592578
iter  40 value 84.097933
iter  50 value 83.744204
iter  60 value 83.487641
final  value 83.473238 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.420197 
iter  10 value 94.489480
iter  20 value 87.037293
iter  30 value 86.513689
iter  40 value 85.925066
iter  50 value 82.610814
iter  60 value 81.461091
iter  70 value 80.990623
iter  80 value 80.803368
iter  90 value 80.668427
iter 100 value 80.594803
final  value 80.594803 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.813058 
iter  10 value 94.538623
iter  20 value 92.621303
iter  30 value 86.173271
iter  40 value 84.547260
iter  50 value 82.679645
iter  60 value 82.240274
iter  70 value 81.814145
iter  80 value 81.386993
iter  90 value 81.211630
iter 100 value 81.138987
final  value 81.138987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 123.082007 
iter  10 value 92.938163
iter  20 value 84.839355
iter  30 value 83.451897
iter  40 value 82.539504
iter  50 value 81.746025
iter  60 value 81.244994
iter  70 value 80.921307
iter  80 value 80.885998
iter  90 value 80.871192
iter 100 value 80.826336
final  value 80.826336 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.717440 
iter  10 value 87.903646
iter  20 value 84.447847
iter  30 value 84.196455
iter  40 value 82.618296
iter  50 value 81.505638
iter  60 value 80.950712
iter  70 value 80.850301
iter  80 value 80.799489
iter  90 value 80.726518
iter 100 value 80.594118
final  value 80.594118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.481853 
iter  10 value 94.295132
iter  20 value 92.589278
iter  30 value 85.660616
iter  40 value 84.618338
iter  50 value 82.903871
iter  60 value 82.365647
iter  70 value 81.567970
iter  80 value 81.313339
iter  90 value 81.270393
iter 100 value 81.102862
final  value 81.102862 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.646434 
iter  10 value 91.135174
iter  20 value 86.969230
iter  30 value 82.467328
iter  40 value 81.965556
iter  50 value 81.492811
iter  60 value 81.256400
iter  70 value 81.090421
iter  80 value 80.956658
iter  90 value 80.786729
iter 100 value 80.710946
final  value 80.710946 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.732630 
iter  10 value 94.508716
iter  20 value 92.814921
iter  30 value 85.705633
iter  40 value 84.939590
iter  50 value 83.900279
iter  60 value 83.350132
iter  70 value 82.582633
iter  80 value 82.303121
iter  90 value 82.026128
iter 100 value 81.514478
final  value 81.514478 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.532705 
iter  10 value 95.172350
iter  20 value 93.323749
iter  30 value 91.241412
iter  40 value 90.986470
iter  50 value 84.285425
iter  60 value 83.417316
iter  70 value 83.114354
iter  80 value 82.636138
iter  90 value 82.084652
iter 100 value 81.514585
final  value 81.514585 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.379674 
iter  10 value 94.551608
iter  20 value 87.235619
iter  30 value 86.199025
iter  40 value 84.932293
iter  50 value 82.043565
iter  60 value 81.380881
iter  70 value 81.047218
iter  80 value 80.892174
iter  90 value 80.705264
iter 100 value 80.620957
final  value 80.620957 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.682830 
iter  10 value 94.620413
iter  20 value 87.406833
iter  30 value 85.723633
iter  40 value 83.540860
iter  50 value 83.032297
iter  60 value 82.842498
iter  70 value 82.785438
iter  80 value 82.421289
iter  90 value 82.090927
iter 100 value 81.780609
final  value 81.780609 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.198878 
final  value 94.485911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.544465 
final  value 94.485686 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.063025 
final  value 94.485743 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.584294 
final  value 94.485727 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.301099 
final  value 94.473950 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.243247 
iter  10 value 94.491506
iter  20 value 94.479956
iter  30 value 93.407439
iter  40 value 85.249014
iter  50 value 84.520777
iter  60 value 84.194383
iter  70 value 84.135278
iter  80 value 84.133456
iter  90 value 84.129820
iter 100 value 83.797628
final  value 83.797628 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.221248 
iter  10 value 94.488951
iter  20 value 94.478282
iter  30 value 86.751665
iter  40 value 83.070605
iter  50 value 82.600332
iter  60 value 82.094960
iter  70 value 82.052045
iter  80 value 82.049917
final  value 82.049794 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.602096 
iter  10 value 94.488748
iter  20 value 94.326505
iter  30 value 88.189254
iter  40 value 87.850280
iter  50 value 86.392455
iter  60 value 85.283568
iter  70 value 85.279447
final  value 85.279377 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.921411 
iter  10 value 94.472370
iter  20 value 94.468000
iter  30 value 90.525773
iter  40 value 85.211703
iter  50 value 85.165802
iter  60 value 85.164321
iter  70 value 85.164245
iter  70 value 85.164244
final  value 85.164244 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.029266 
iter  10 value 94.489526
iter  20 value 94.258641
iter  30 value 84.603018
iter  40 value 84.600555
iter  50 value 84.545678
iter  60 value 84.540792
iter  70 value 84.536840
iter  80 value 84.532448
iter  90 value 83.956331
iter 100 value 83.812268
final  value 83.812268 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.670362 
iter  10 value 94.492368
iter  20 value 94.484106
iter  30 value 92.329121
iter  40 value 90.693492
iter  50 value 82.891043
iter  60 value 81.328142
iter  70 value 80.913059
final  value 80.912864 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.740570 
iter  10 value 94.475517
iter  20 value 94.467620
iter  30 value 93.110351
iter  40 value 88.520227
iter  50 value 85.614577
iter  60 value 82.973898
iter  70 value 82.919181
iter  80 value 82.535342
iter  90 value 82.487849
iter 100 value 82.475344
final  value 82.475344 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.024296 
iter  10 value 94.450371
iter  20 value 94.439760
iter  30 value 92.352426
iter  40 value 90.987887
iter  50 value 90.967392
iter  60 value 81.668250
iter  70 value 81.444582
iter  80 value 81.444471
iter  90 value 81.444322
iter 100 value 81.335231
final  value 81.335231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.399497 
iter  10 value 94.473578
iter  20 value 94.467867
iter  20 value 94.467866
iter  20 value 94.467866
final  value 94.467866 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.252727 
iter  10 value 94.492882
iter  20 value 94.140496
iter  30 value 86.525384
iter  40 value 84.910083
iter  50 value 84.774540
iter  60 value 84.773005
iter  70 value 84.772685
iter  80 value 84.772625
iter  90 value 84.771685
iter 100 value 82.247197
final  value 82.247197 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.045096 
iter  10 value 119.318337
iter  20 value 112.517704
iter  30 value 107.111858
iter  40 value 106.886431
iter  50 value 105.170324
iter  60 value 103.493373
iter  70 value 101.738473
iter  80 value 101.053764
iter  90 value 100.715306
iter 100 value 100.623824
final  value 100.623824 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 132.310609 
iter  10 value 117.688807
iter  20 value 113.806933
iter  30 value 108.709086
iter  40 value 107.232142
iter  50 value 105.868755
iter  60 value 105.407471
iter  70 value 105.059853
iter  80 value 104.442289
iter  90 value 103.541601
iter 100 value 103.286352
final  value 103.286352 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 134.149584 
iter  10 value 118.084674
iter  20 value 116.443514
iter  30 value 109.539637
iter  40 value 105.915938
iter  50 value 105.625930
iter  60 value 105.285221
iter  70 value 104.587349
iter  80 value 103.368274
iter  90 value 102.394141
iter 100 value 101.877655
final  value 101.877655 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.842323 
iter  10 value 117.837858
iter  20 value 115.952294
iter  30 value 106.537026
iter  40 value 102.365941
iter  50 value 101.909274
iter  60 value 101.301356
iter  70 value 100.816051
iter  80 value 100.564026
iter  90 value 100.399059
iter 100 value 100.323839
final  value 100.323839 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 134.974967 
iter  10 value 118.182237
iter  20 value 117.505432
iter  30 value 109.700323
iter  40 value 108.798836
iter  50 value 108.608025
iter  60 value 104.858658
iter  70 value 104.431303
iter  80 value 103.898754
iter  90 value 102.308565
iter 100 value 101.997607
final  value 101.997607 
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 -- Tue Nov 19 23:14:47 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 
 32.545   1.276  50.595