##############################################################################
##############################################################################
###
### 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 4.4.3 (2025-02-28)
* 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 ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       52.417  1.734  59.213
FSmethod      50.602  1.770  54.871
corr_plot     50.508  1.703  55.258
pred_ensembel 25.423  0.392  24.998
calculateTC    4.738  0.478   5.506
enrichfindP    0.889  0.082  13.583
* 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 4.4.3 (2025-02-28) -- "Trophy Case"
Copyright (C) 2025 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 95.133346 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.922085 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.793805 
final  value 94.312038 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.265776 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.665182 
iter  10 value 89.798081
iter  20 value 88.824461
iter  30 value 87.335922
iter  40 value 87.284138
final  value 87.283810 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.806764 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.648612 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.597643 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.251881 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.082389 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.548843 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.010280 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.515447 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.478746 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.010424 
iter  10 value 94.461209
final  value 94.461207 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.906022 
iter  10 value 94.528015
iter  20 value 94.481741
iter  30 value 94.344617
iter  40 value 94.186523
iter  50 value 94.143868
iter  60 value 88.341388
iter  70 value 86.758858
iter  80 value 85.833178
final  value 85.824337 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.371154 
iter  10 value 94.514179
iter  20 value 94.486919
iter  30 value 94.486442
iter  40 value 90.912461
iter  50 value 88.156239
iter  60 value 87.594545
iter  70 value 87.424071
iter  80 value 87.338467
final  value 87.338440 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.447292 
iter  10 value 94.415999
iter  20 value 92.843183
iter  30 value 89.984376
iter  40 value 86.417939
iter  50 value 85.595765
iter  60 value 83.957092
iter  70 value 83.266738
iter  80 value 82.681074
final  value 82.678456 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.452742 
iter  10 value 94.490391
iter  20 value 93.979969
iter  30 value 91.130871
iter  40 value 90.950526
iter  50 value 90.223068
iter  60 value 88.242936
iter  70 value 85.235291
iter  80 value 84.583005
iter  90 value 84.185543
iter 100 value 83.653595
final  value 83.653595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.954569 
iter  10 value 94.493397
iter  20 value 92.747712
iter  30 value 92.558360
iter  40 value 92.527359
iter  50 value 92.521034
iter  60 value 92.510030
iter  70 value 85.985994
iter  80 value 85.580066
iter  90 value 85.462297
iter 100 value 85.186706
final  value 85.186706 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.610495 
iter  10 value 94.444905
iter  20 value 93.838474
iter  30 value 91.149171
iter  40 value 85.897781
iter  50 value 84.547688
iter  60 value 83.255980
iter  70 value 82.544872
iter  80 value 81.943765
iter  90 value 81.746032
iter 100 value 81.510395
final  value 81.510395 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.246657 
iter  10 value 97.344946
iter  20 value 93.406449
iter  30 value 87.265135
iter  40 value 85.013093
iter  50 value 84.639547
iter  60 value 83.798907
iter  70 value 83.081754
iter  80 value 82.711915
iter  90 value 82.449473
iter 100 value 82.282505
final  value 82.282505 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.971984 
iter  10 value 94.495717
iter  20 value 91.832593
iter  30 value 87.616758
iter  40 value 87.494611
iter  50 value 87.401772
iter  60 value 86.223756
iter  70 value 85.996311
iter  80 value 84.473179
iter  90 value 84.097070
iter 100 value 83.928365
final  value 83.928365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.621966 
iter  10 value 94.137731
iter  20 value 89.007932
iter  30 value 88.139568
iter  40 value 87.672952
iter  50 value 86.342973
iter  60 value 84.747901
iter  70 value 83.548796
iter  80 value 83.008204
iter  90 value 82.651968
iter 100 value 82.616368
final  value 82.616368 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.083075 
iter  10 value 94.385438
iter  20 value 90.395758
iter  30 value 87.602653
iter  40 value 84.713658
iter  50 value 82.724089
iter  60 value 82.542181
iter  70 value 82.321162
iter  80 value 82.047954
iter  90 value 82.009671
iter 100 value 81.698160
final  value 81.698160 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.372906 
iter  10 value 94.499018
iter  20 value 94.218840
iter  30 value 89.737783
iter  40 value 87.719725
iter  50 value 84.963267
iter  60 value 82.219780
iter  70 value 81.928203
iter  80 value 81.795204
iter  90 value 81.306401
iter 100 value 81.093187
final  value 81.093187 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.243350 
iter  10 value 93.452968
iter  20 value 88.235889
iter  30 value 84.316933
iter  40 value 82.699266
iter  50 value 81.816776
iter  60 value 81.458751
iter  70 value 81.028235
iter  80 value 80.677578
iter  90 value 80.562258
iter 100 value 80.508911
final  value 80.508911 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.433120 
iter  10 value 94.519815
iter  20 value 86.906284
iter  30 value 85.509535
iter  40 value 84.986418
iter  50 value 83.158428
iter  60 value 82.470781
iter  70 value 81.680391
iter  80 value 81.316395
iter  90 value 81.132124
iter 100 value 80.928237
final  value 80.928237 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.609537 
iter  10 value 91.910362
iter  20 value 87.569210
iter  30 value 86.518565
iter  40 value 85.455700
iter  50 value 85.039196
iter  60 value 84.816345
iter  70 value 82.543294
iter  80 value 81.609373
iter  90 value 81.466731
iter 100 value 81.001541
final  value 81.001541 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.093106 
iter  10 value 94.549566
iter  20 value 92.766630
iter  30 value 92.454253
iter  40 value 92.325468
iter  50 value 92.104885
iter  60 value 90.810810
iter  70 value 85.541945
iter  80 value 84.421388
iter  90 value 83.603608
iter 100 value 83.481279
final  value 83.481279 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.512945 
final  value 94.486023 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.881632 
final  value 93.703607 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.283169 
final  value 94.485662 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.583093 
final  value 94.486033 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.628987 
final  value 94.485837 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.510549 
iter  10 value 94.471839
iter  20 value 89.230035
iter  30 value 84.725344
iter  40 value 84.725073
iter  50 value 84.724675
iter  60 value 84.669799
iter  70 value 82.274048
iter  80 value 82.074882
iter  90 value 81.903377
iter 100 value 81.856883
final  value 81.856883 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.062570 
iter  10 value 94.471405
iter  20 value 94.466917
iter  30 value 91.140196
iter  40 value 87.296475
iter  50 value 87.289058
iter  60 value 86.178878
final  value 86.158678 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.840420 
iter  10 value 93.712626
iter  20 value 93.710433
iter  30 value 93.709573
iter  40 value 87.047464
final  value 86.957384 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.759118 
iter  10 value 94.489562
iter  20 value 94.466192
iter  30 value 87.201702
iter  40 value 87.097252
iter  50 value 87.095636
final  value 87.095537 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.740745 
iter  10 value 94.486891
iter  20 value 89.576669
iter  30 value 87.191156
iter  40 value 87.190202
iter  40 value 87.190202
final  value 87.190202 
converged
Fitting Repeat 1 

# weights:  507
initial  value 92.415581 
iter  10 value 88.342975
iter  20 value 86.541207
iter  30 value 86.495809
iter  40 value 86.491792
iter  50 value 86.489618
iter  60 value 86.488149
iter  70 value 86.487685
iter  80 value 86.487186
iter  90 value 84.691618
final  value 84.627462 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.150367 
iter  10 value 94.469307
iter  20 value 93.902532
iter  30 value 89.291776
iter  40 value 87.440568
iter  50 value 86.588057
iter  60 value 85.213371
iter  70 value 84.403773
iter  80 value 84.059486
iter  90 value 83.946469
final  value 83.945751 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.546206 
iter  10 value 94.254275
iter  20 value 94.243858
iter  30 value 94.242955
iter  40 value 94.238937
iter  50 value 94.176093
iter  60 value 94.169006
iter  70 value 87.796940
iter  80 value 84.746929
iter  80 value 84.746928
iter  90 value 84.280585
final  value 84.280581 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.733992 
iter  10 value 93.711766
iter  20 value 91.489388
iter  30 value 87.985386
iter  40 value 84.531708
iter  50 value 81.950174
iter  60 value 81.871004
iter  70 value 81.825469
final  value 81.824271 
converged
Fitting Repeat 5 

# weights:  507
initial  value 133.829609 
iter  10 value 94.562441
iter  20 value 94.451056
iter  30 value 94.443252
iter  40 value 94.267341
iter  50 value 94.250062
iter  60 value 94.151329
iter  70 value 94.150739
iter  80 value 94.150524
final  value 94.150049 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.054443 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.547410 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.515928 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.097586 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.763803 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.211214 
iter  10 value 93.869431
final  value 93.867974 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.788415 
iter  10 value 93.817685
final  value 93.810010 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.111085 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.029861 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.953820 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.152758 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.661642 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.430260 
iter  10 value 93.773505
iter  20 value 92.906778
iter  30 value 92.892555
iter  40 value 88.069604
iter  50 value 87.389253
final  value 87.389148 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.867436 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.806822 
iter  10 value 93.571534
final  value 93.571529 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.620574 
iter  10 value 94.056724
iter  20 value 92.719109
iter  30 value 87.362938
iter  40 value 86.340996
iter  50 value 85.876376
iter  60 value 85.823707
iter  70 value 85.818387
final  value 85.817530 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.627027 
iter  10 value 94.055008
iter  20 value 93.789881
iter  30 value 93.523225
iter  40 value 93.510401
iter  50 value 89.943314
iter  60 value 89.290539
iter  70 value 89.118302
iter  80 value 88.495096
iter  90 value 87.554005
iter 100 value 87.514303
final  value 87.514303 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.742646 
iter  10 value 93.778398
iter  20 value 90.087637
iter  30 value 89.285195
iter  40 value 86.497183
iter  50 value 85.823933
iter  60 value 85.817645
final  value 85.817530 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.618090 
iter  10 value 94.069762
iter  20 value 93.625882
iter  30 value 93.573982
iter  40 value 93.571722
iter  50 value 93.569798
iter  60 value 87.939333
iter  70 value 86.718117
iter  80 value 85.743414
iter  90 value 85.533560
iter 100 value 85.504843
final  value 85.504843 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.517674 
iter  10 value 93.909492
iter  20 value 90.291848
iter  30 value 89.247847
iter  40 value 88.047692
iter  50 value 87.519719
iter  60 value 87.514296
final  value 87.514288 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.576648 
iter  10 value 89.131667
iter  20 value 87.062559
iter  30 value 86.488882
iter  40 value 85.488968
iter  50 value 85.261637
iter  60 value 85.092776
iter  70 value 85.007514
iter  80 value 84.991521
iter  90 value 84.974645
iter 100 value 84.871290
final  value 84.871290 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.690558 
iter  10 value 91.762153
iter  20 value 89.656116
iter  30 value 85.862996
iter  40 value 85.631821
iter  50 value 85.219020
iter  60 value 84.131707
iter  70 value 83.977746
iter  80 value 83.739165
iter  90 value 83.516643
iter 100 value 83.240274
final  value 83.240274 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.782745 
iter  10 value 93.614713
iter  20 value 92.435391
iter  30 value 91.999299
iter  40 value 91.515698
iter  50 value 91.352279
iter  60 value 84.153149
iter  70 value 83.660877
iter  80 value 83.576660
iter  90 value 83.466115
iter 100 value 83.359682
final  value 83.359682 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.458311 
iter  10 value 94.094677
iter  20 value 88.760275
iter  30 value 87.649736
iter  40 value 85.415895
iter  50 value 83.955318
iter  60 value 83.761707
iter  70 value 83.671816
iter  80 value 83.429515
iter  90 value 83.319399
iter 100 value 83.306734
final  value 83.306734 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.251410 
iter  10 value 94.014251
iter  20 value 88.981785
iter  30 value 88.003515
iter  40 value 87.234056
iter  50 value 86.542941
iter  60 value 86.436170
iter  70 value 86.222972
iter  80 value 84.229696
iter  90 value 83.939989
iter 100 value 83.907091
final  value 83.907091 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.342796 
iter  10 value 94.425865
iter  20 value 90.363586
iter  30 value 87.920301
iter  40 value 87.456305
iter  50 value 87.219073
iter  60 value 85.930359
iter  70 value 85.289635
iter  80 value 85.070260
iter  90 value 84.890161
iter 100 value 84.863947
final  value 84.863947 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.385699 
iter  10 value 94.176217
iter  20 value 94.045810
iter  30 value 93.510274
iter  40 value 90.259189
iter  50 value 87.798316
iter  60 value 84.759119
iter  70 value 84.065816
iter  80 value 83.732421
iter  90 value 83.422537
iter 100 value 83.335176
final  value 83.335176 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.284491 
iter  10 value 94.423400
iter  20 value 93.742474
iter  30 value 89.092836
iter  40 value 85.837787
iter  50 value 84.646490
iter  60 value 84.134533
iter  70 value 83.817943
iter  80 value 83.563701
iter  90 value 83.470364
iter 100 value 83.434202
final  value 83.434202 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.267439 
iter  10 value 93.793936
iter  20 value 92.224860
iter  30 value 87.458383
iter  40 value 86.902676
iter  50 value 85.391617
iter  60 value 84.424788
iter  70 value 83.874538
iter  80 value 83.678363
iter  90 value 83.580570
iter 100 value 83.493092
final  value 83.493092 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.167208 
iter  10 value 93.765386
iter  20 value 92.321993
iter  30 value 89.523785
iter  40 value 85.831683
iter  50 value 84.599648
iter  60 value 84.457301
iter  70 value 84.262151
iter  80 value 83.464175
iter  90 value 83.277720
iter 100 value 83.182117
final  value 83.182117 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.174878 
final  value 94.054379 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.646888 
iter  10 value 93.456828
final  value 93.456688 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.874084 
iter  10 value 94.054701
iter  20 value 94.052596
iter  30 value 87.483297
iter  40 value 87.377455
iter  50 value 87.375038
iter  60 value 86.172112
iter  70 value 86.169570
final  value 86.169506 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.634376 
final  value 94.054456 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.364124 
final  value 94.055095 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.022610 
iter  10 value 90.086845
iter  20 value 89.300005
iter  30 value 88.220858
iter  40 value 88.218991
iter  50 value 88.158099
iter  60 value 88.157200
iter  70 value 88.153777
final  value 88.153596 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.140800 
iter  10 value 94.057965
iter  20 value 94.053239
iter  30 value 93.459328
iter  40 value 90.104247
iter  50 value 86.172962
final  value 86.169879 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.003009 
iter  10 value 93.841162
iter  20 value 93.693823
iter  30 value 88.200057
iter  40 value 88.157234
iter  50 value 88.156733
iter  60 value 88.155224
iter  70 value 87.887548
iter  80 value 87.648365
iter  90 value 86.119068
iter 100 value 84.519872
final  value 84.519872 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.367487 
iter  10 value 94.057686
iter  20 value 94.052924
iter  30 value 93.460088
final  value 93.455259 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.796915 
iter  10 value 94.057063
iter  20 value 92.856777
iter  30 value 87.377717
iter  40 value 86.201240
iter  50 value 86.171072
iter  60 value 86.170926
iter  70 value 86.098050
iter  80 value 85.951581
iter  80 value 85.951581
final  value 85.951581 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.693226 
iter  10 value 94.079509
iter  20 value 93.059401
iter  30 value 92.779116
iter  40 value 92.717949
iter  50 value 92.511769
iter  60 value 91.461071
iter  70 value 90.409573
iter  80 value 90.368420
iter  90 value 84.042222
iter 100 value 83.301631
final  value 83.301631 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.695393 
iter  10 value 91.035995
iter  20 value 90.537239
iter  30 value 90.533534
iter  40 value 88.655369
iter  50 value 87.915837
iter  60 value 87.752717
final  value 87.752710 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.468169 
iter  10 value 93.950721
iter  20 value 93.438567
iter  30 value 93.398781
iter  40 value 93.390064
iter  50 value 93.385725
iter  60 value 93.382386
iter  70 value 93.381417
iter  80 value 92.472527
iter  90 value 90.475633
iter 100 value 87.582535
final  value 87.582535 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.700599 
iter  10 value 93.818151
iter  20 value 93.752883
iter  30 value 93.450889
iter  30 value 93.450888
iter  30 value 93.450888
final  value 93.450888 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.445620 
iter  10 value 93.844231
iter  20 value 93.837970
final  value 93.836843 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.492009 
final  value 94.472273 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.631288 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.128717 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.817078 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.423799 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.575998 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.979629 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.526122 
iter  10 value 94.354715
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.076408 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.885511 
final  value 94.206005 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.120885 
iter  10 value 94.448052
iter  10 value 94.448052
iter  10 value 94.448052
final  value 94.448052 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.759310 
iter  10 value 94.309525
iter  10 value 94.309524
iter  10 value 94.309524
final  value 94.309524 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.311945 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.230034 
iter  10 value 91.839528
final  value 91.834445 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.960497 
final  value 94.322896 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.292115 
iter  10 value 94.488662
iter  20 value 94.392483
iter  30 value 94.382309
iter  40 value 93.687592
iter  50 value 85.284412
iter  60 value 83.921627
iter  70 value 82.976303
iter  80 value 82.223279
iter  90 value 82.124034
iter 100 value 81.523161
final  value 81.523161 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.190452 
iter  10 value 94.467315
iter  20 value 91.702642
iter  30 value 87.300244
iter  40 value 87.154999
iter  50 value 87.123601
iter  60 value 87.105411
iter  70 value 85.281053
iter  80 value 85.250415
iter  90 value 85.204327
iter 100 value 85.189528
final  value 85.189528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 113.842040 
iter  10 value 94.490464
iter  20 value 94.481759
iter  30 value 90.987087
iter  40 value 88.540258
iter  50 value 86.418767
iter  60 value 85.922618
iter  70 value 85.038844
iter  80 value 84.680981
iter  90 value 83.894287
iter 100 value 83.871774
final  value 83.871774 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.064401 
iter  10 value 94.490683
iter  20 value 89.190755
iter  30 value 86.024734
iter  40 value 85.111967
iter  50 value 82.830561
iter  60 value 82.215851
iter  70 value 81.302685
iter  80 value 80.773726
iter  90 value 80.745616
final  value 80.745568 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.506122 
iter  10 value 92.957426
iter  20 value 91.099616
iter  30 value 91.064491
iter  40 value 91.058814
iter  50 value 91.057738
iter  50 value 91.057738
iter  50 value 91.057738
final  value 91.057738 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.723805 
iter  10 value 94.444221
iter  20 value 90.818582
iter  30 value 87.510142
iter  40 value 86.645251
iter  50 value 85.402490
iter  60 value 82.402295
iter  70 value 80.734463
iter  80 value 80.277065
iter  90 value 80.042104
iter 100 value 79.841207
final  value 79.841207 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.427018 
iter  10 value 94.473307
iter  20 value 92.996836
iter  30 value 86.838609
iter  40 value 85.895265
iter  50 value 84.380682
iter  60 value 82.933614
iter  70 value 81.114865
iter  80 value 80.333167
iter  90 value 80.142194
iter 100 value 80.035982
final  value 80.035982 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.401448 
iter  10 value 94.526490
iter  20 value 91.825129
iter  30 value 87.004611
iter  40 value 83.500241
iter  50 value 81.720416
iter  60 value 80.752086
iter  70 value 79.978420
iter  80 value 79.242759
iter  90 value 79.137875
iter 100 value 79.036367
final  value 79.036367 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.932630 
iter  10 value 94.523846
iter  20 value 94.491401
iter  30 value 94.381861
iter  40 value 93.550046
iter  50 value 86.777060
iter  60 value 85.122775
iter  70 value 84.906216
iter  80 value 84.416259
iter  90 value 83.449878
iter 100 value 81.965926
final  value 81.965926 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.413034 
iter  10 value 94.426305
iter  20 value 90.347740
iter  30 value 87.767218
iter  40 value 83.626992
iter  50 value 82.106614
iter  60 value 80.949586
iter  70 value 80.211824
iter  80 value 79.968542
iter  90 value 79.825041
iter 100 value 79.785256
final  value 79.785256 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.461882 
iter  10 value 91.509224
iter  20 value 85.642852
iter  30 value 82.816077
iter  40 value 81.915673
iter  50 value 81.051230
iter  60 value 80.491529
iter  70 value 80.400771
iter  80 value 79.905214
iter  90 value 79.606199
iter 100 value 79.538053
final  value 79.538053 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.588419 
iter  10 value 94.953371
iter  20 value 94.538584
iter  30 value 88.147747
iter  40 value 87.790731
iter  50 value 86.204471
iter  60 value 83.741354
iter  70 value 81.187724
iter  80 value 80.026615
iter  90 value 79.481094
iter 100 value 79.269050
final  value 79.269050 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.632088 
iter  10 value 94.798923
iter  20 value 92.255506
iter  30 value 84.524506
iter  40 value 84.255061
iter  50 value 82.928317
iter  60 value 81.312449
iter  70 value 81.152461
iter  80 value 80.795055
iter  90 value 80.301476
iter 100 value 79.861535
final  value 79.861535 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.698256 
iter  10 value 92.645876
iter  20 value 88.277579
iter  30 value 84.516534
iter  40 value 82.512553
iter  50 value 81.408828
iter  60 value 80.296442
iter  70 value 79.849746
iter  80 value 79.619141
iter  90 value 79.481723
iter 100 value 79.467467
final  value 79.467467 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.497358 
iter  10 value 94.568741
iter  20 value 91.621754
iter  30 value 86.246688
iter  40 value 84.966986
iter  50 value 82.956576
iter  60 value 81.864994
iter  70 value 81.602367
iter  80 value 81.480578
iter  90 value 81.009209
iter 100 value 80.268981
final  value 80.268981 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.090771 
final  value 94.485677 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.179187 
final  value 94.485853 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.153852 
final  value 94.485919 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.331675 
final  value 94.485984 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.258538 
iter  10 value 94.485962
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.128450 
iter  10 value 94.343897
iter  20 value 93.491950
iter  30 value 89.730695
iter  40 value 83.604455
iter  50 value 79.714178
iter  60 value 79.663599
iter  70 value 79.357646
iter  80 value 79.328490
final  value 79.328106 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.764073 
iter  10 value 94.488476
iter  20 value 94.442447
final  value 94.354434 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.144973 
iter  10 value 94.489272
iter  20 value 94.484227
iter  30 value 94.128959
iter  40 value 93.179710
iter  50 value 86.751240
iter  60 value 86.293783
iter  70 value 84.734420
iter  80 value 84.075760
iter  90 value 83.968388
iter 100 value 83.967017
final  value 83.967017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.041815 
iter  10 value 94.489092
iter  20 value 89.587509
iter  30 value 88.771924
iter  40 value 88.249406
iter  50 value 85.813085
iter  60 value 85.775257
iter  70 value 84.537180
iter  80 value 79.730831
iter  90 value 78.639977
iter 100 value 78.300690
final  value 78.300690 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.017686 
iter  10 value 93.651676
iter  20 value 92.927548
iter  30 value 92.851169
iter  40 value 92.621309
iter  50 value 92.619716
iter  60 value 92.619258
final  value 92.619133 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.258068 
iter  10 value 94.363283
iter  20 value 94.357768
iter  30 value 94.351223
iter  40 value 88.516620
iter  50 value 85.916983
iter  60 value 85.585121
final  value 85.585117 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.909596 
iter  10 value 94.397027
iter  20 value 93.599570
iter  30 value 93.050971
iter  40 value 92.403688
iter  50 value 92.376855
iter  60 value 92.242448
iter  70 value 90.962231
iter  80 value 89.438392
iter  90 value 89.413660
iter 100 value 87.693767
final  value 87.693767 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.780427 
iter  10 value 94.390985
iter  20 value 94.313674
iter  30 value 94.210378
iter  40 value 93.309178
iter  50 value 88.968088
iter  60 value 87.465814
iter  70 value 87.337935
iter  80 value 87.329487
iter  90 value 87.183550
iter 100 value 84.888499
final  value 84.888499 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.743238 
iter  10 value 94.362330
iter  20 value 94.355311
iter  30 value 94.306731
iter  40 value 91.486662
iter  50 value 89.402892
iter  60 value 89.140676
iter  70 value 89.119687
iter  80 value 89.118622
iter  90 value 89.114020
final  value 89.112716 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.290149 
iter  10 value 94.238444
iter  20 value 93.827200
iter  30 value 87.332533
iter  40 value 87.327153
iter  50 value 87.321754
iter  60 value 86.920699
iter  70 value 86.909232
iter  80 value 86.879502
iter  90 value 85.896395
iter 100 value 83.747936
final  value 83.747936 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.326405 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.808063 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.010651 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.206664 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.333859 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.683314 
iter  10 value 94.053305
final  value 94.052436 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.525349 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.648342 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.538703 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.645912 
iter  10 value 84.819024
iter  20 value 82.218401
iter  30 value 82.052278
iter  40 value 82.015678
final  value 81.944321 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.862761 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.123842 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.322743 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.382029 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.176162 
iter  10 value 94.061133
iter  20 value 83.968403
final  value 83.952465 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.666704 
iter  10 value 93.352929
iter  20 value 89.659683
iter  30 value 84.437554
iter  40 value 83.931837
iter  50 value 82.871648
iter  60 value 79.565139
iter  70 value 78.854900
iter  80 value 78.756752
final  value 78.736768 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.676805 
iter  10 value 94.333595
iter  20 value 92.907778
iter  30 value 91.841124
iter  40 value 91.384297
iter  50 value 90.546706
iter  60 value 83.734866
iter  70 value 82.081677
iter  80 value 81.319236
iter  90 value 81.225736
final  value 81.224330 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.700432 
iter  10 value 93.796945
iter  20 value 84.678729
iter  30 value 82.806828
iter  40 value 82.109191
iter  50 value 81.390235
iter  60 value 80.768885
iter  70 value 80.628155
iter  80 value 80.610377
final  value 80.610374 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.864565 
iter  10 value 94.240228
iter  20 value 90.820367
iter  30 value 90.179786
iter  40 value 89.599330
iter  50 value 89.142148
iter  60 value 85.879452
iter  70 value 85.508304
iter  80 value 83.130124
iter  90 value 82.476700
iter 100 value 80.402247
final  value 80.402247 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.422199 
iter  10 value 94.488713
iter  20 value 93.645150
iter  30 value 91.761610
iter  40 value 84.494093
iter  50 value 84.283163
iter  60 value 81.730570
iter  70 value 81.256497
iter  80 value 81.225419
final  value 81.224330 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.277028 
iter  10 value 94.467276
iter  20 value 93.274856
iter  30 value 85.020839
iter  40 value 83.456155
iter  50 value 83.218405
iter  60 value 81.586524
iter  70 value 80.998657
iter  80 value 79.094051
iter  90 value 78.297012
iter 100 value 77.933628
final  value 77.933628 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.329602 
iter  10 value 94.474691
iter  20 value 92.077895
iter  30 value 81.462571
iter  40 value 79.933801
iter  50 value 79.459959
iter  60 value 78.689314
iter  70 value 77.904410
iter  80 value 77.178709
iter  90 value 76.947508
iter 100 value 76.830353
final  value 76.830353 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.740583 
iter  10 value 92.308457
iter  20 value 87.630280
iter  30 value 84.548028
iter  40 value 83.481016
iter  50 value 82.588782
iter  60 value 79.330209
iter  70 value 78.066887
iter  80 value 77.766770
iter  90 value 77.694068
iter 100 value 77.421672
final  value 77.421672 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.848008 
iter  10 value 93.422951
iter  20 value 83.670846
iter  30 value 82.677836
iter  40 value 81.799946
iter  50 value 81.307023
iter  60 value 81.209333
iter  70 value 81.182590
iter  80 value 80.842044
iter  90 value 80.540945
iter 100 value 80.099687
final  value 80.099687 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.419615 
iter  10 value 94.307839
iter  20 value 90.717120
iter  30 value 87.684351
iter  40 value 85.490672
iter  50 value 84.620376
iter  60 value 82.667853
iter  70 value 82.287481
iter  80 value 80.238128
iter  90 value 79.877977
iter 100 value 78.196311
final  value 78.196311 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.722024 
iter  10 value 95.185644
iter  20 value 88.756434
iter  30 value 85.767677
iter  40 value 85.156874
iter  50 value 84.778472
iter  60 value 80.364166
iter  70 value 79.356204
iter  80 value 77.622908
iter  90 value 77.216753
iter 100 value 77.028219
final  value 77.028219 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.900925 
iter  10 value 95.205791
iter  20 value 89.024272
iter  30 value 80.589705
iter  40 value 77.711645
iter  50 value 77.305798
iter  60 value 77.176224
iter  70 value 76.830920
iter  80 value 76.762779
iter  90 value 76.745528
iter 100 value 76.612201
final  value 76.612201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.907488 
iter  10 value 94.366749
iter  20 value 90.966703
iter  30 value 90.110813
iter  40 value 89.360336
iter  50 value 81.350017
iter  60 value 80.500009
iter  70 value 78.607520
iter  80 value 78.000068
iter  90 value 77.372726
iter 100 value 77.315179
final  value 77.315179 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.271643 
iter  10 value 88.740884
iter  20 value 80.883026
iter  30 value 78.888153
iter  40 value 78.363653
iter  50 value 77.875416
iter  60 value 77.744776
iter  70 value 77.131800
iter  80 value 76.899922
iter  90 value 76.530678
iter 100 value 76.428696
final  value 76.428696 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.056296 
iter  10 value 93.986446
iter  20 value 86.997826
iter  30 value 81.306351
iter  40 value 79.173303
iter  50 value 78.041202
iter  60 value 77.012881
iter  70 value 76.900573
iter  80 value 76.826646
iter  90 value 76.749375
iter 100 value 76.735529
final  value 76.735529 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.617938 
final  value 94.485678 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.992714 
final  value 94.485781 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.816493 
final  value 94.486045 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.819799 
final  value 94.485974 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.018715 
final  value 94.485695 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.399324 
iter  10 value 94.489203
iter  20 value 94.282450
iter  30 value 81.072685
iter  40 value 80.046060
final  value 80.032725 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.797744 
iter  10 value 94.280725
iter  20 value 86.843355
iter  30 value 80.885445
iter  40 value 80.877468
iter  50 value 80.144188
iter  60 value 80.026753
final  value 80.025456 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.697128 
iter  10 value 94.489274
iter  20 value 94.478126
iter  30 value 84.609342
final  value 84.591578 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.687224 
iter  10 value 94.464488
iter  20 value 94.280061
iter  30 value 94.275846
iter  40 value 91.302100
iter  50 value 81.765136
iter  60 value 79.884267
iter  70 value 79.561037
final  value 79.560007 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.428969 
iter  10 value 94.381103
iter  20 value 94.281107
iter  30 value 93.772377
iter  40 value 90.221985
final  value 90.221828 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.515412 
iter  10 value 94.282916
iter  20 value 94.279378
iter  30 value 94.278480
iter  40 value 94.071921
iter  50 value 91.998573
iter  60 value 85.925845
final  value 85.925830 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.010888 
iter  10 value 94.490738
iter  20 value 90.503488
iter  30 value 90.118957
iter  40 value 90.117531
iter  40 value 90.117530
final  value 90.117530 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.889448 
iter  10 value 94.492966
iter  20 value 91.707417
iter  30 value 85.885721
iter  40 value 84.155242
iter  50 value 79.245445
iter  60 value 78.995911
iter  70 value 78.985126
iter  80 value 78.973930
iter  90 value 78.971251
iter 100 value 78.969465
final  value 78.969465 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.441151 
iter  10 value 94.283392
iter  20 value 94.279828
iter  30 value 85.142040
iter  40 value 83.926285
iter  50 value 83.876916
iter  60 value 82.252576
iter  70 value 81.578903
iter  80 value 81.574777
iter  90 value 81.574169
iter 100 value 81.571930
final  value 81.571930 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.792935 
iter  10 value 94.151836
iter  20 value 91.595848
iter  30 value 80.964327
iter  40 value 80.528705
iter  50 value 80.521289
iter  60 value 80.514331
iter  70 value 80.511406
iter  80 value 80.328309
iter  90 value 79.469424
iter 100 value 77.690239
final  value 77.690239 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.436306 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.416495 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.749301 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.594425 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.618909 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.380517 
final  value 93.890110 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.152670 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.965684 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.275388 
final  value 93.890110 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.726149 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.085546 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.336152 
iter  10 value 85.209237
iter  20 value 83.068497
iter  30 value 82.984952
iter  30 value 82.984952
iter  30 value 82.984952
final  value 82.984952 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.799569 
iter  10 value 93.286498
final  value 93.093311 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.287547 
iter  10 value 94.008697
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.590505 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.075408 
iter  10 value 94.055649
iter  20 value 90.788394
iter  30 value 87.117077
iter  40 value 86.248713
iter  50 value 84.914378
iter  60 value 83.207115
iter  70 value 83.045091
iter  80 value 83.002417
iter  90 value 82.822826
iter 100 value 82.555022
final  value 82.555022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.568490 
iter  10 value 93.823737
iter  20 value 83.277672
iter  30 value 82.301766
iter  40 value 81.865800
iter  50 value 81.360092
iter  60 value 80.657570
iter  70 value 80.581620
iter  80 value 80.522586
iter  80 value 80.522585
iter  80 value 80.522585
final  value 80.522585 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.485697 
iter  10 value 93.996677
iter  20 value 93.452412
iter  30 value 91.754008
iter  40 value 90.693204
iter  50 value 90.537277
iter  60 value 90.477925
final  value 90.477622 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.039110 
iter  10 value 94.013517
iter  20 value 84.928464
iter  30 value 83.605440
iter  40 value 83.043380
iter  50 value 82.353888
iter  60 value 82.113530
iter  70 value 82.081206
iter  80 value 82.076742
final  value 82.076725 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.489647 
iter  10 value 94.077277
iter  20 value 94.010091
iter  30 value 90.257261
iter  40 value 84.678263
iter  50 value 82.361215
iter  60 value 81.150576
iter  70 value 80.957913
iter  80 value 80.714823
iter  90 value 80.658261
iter 100 value 80.603158
final  value 80.603158 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.716020 
iter  10 value 93.936677
iter  20 value 91.994272
iter  30 value 89.251860
iter  40 value 88.165639
iter  50 value 87.710388
iter  60 value 83.120740
iter  70 value 81.205901
iter  80 value 80.333975
iter  90 value 79.902215
iter 100 value 79.837899
final  value 79.837899 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.207586 
iter  10 value 92.100712
iter  20 value 85.234884
iter  30 value 82.292606
iter  40 value 81.536040
iter  50 value 80.738615
iter  60 value 80.160153
iter  70 value 79.852206
iter  80 value 79.574573
iter  90 value 79.446550
iter 100 value 79.330258
final  value 79.330258 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.592440 
iter  10 value 93.956300
iter  20 value 85.882024
iter  30 value 84.672072
iter  40 value 83.407898
iter  50 value 81.249285
iter  60 value 80.123310
iter  70 value 79.862579
iter  80 value 79.636045
iter  90 value 79.604401
iter 100 value 79.594720
final  value 79.594720 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.679571 
iter  10 value 94.134998
iter  20 value 90.764876
iter  30 value 89.413111
iter  40 value 87.568170
iter  50 value 86.836848
iter  60 value 81.907819
iter  70 value 80.403675
iter  80 value 80.125806
iter  90 value 80.003908
iter 100 value 79.789084
final  value 79.789084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.132051 
iter  10 value 94.144355
iter  20 value 94.073385
iter  30 value 92.625552
iter  40 value 85.340128
iter  50 value 84.068405
iter  60 value 81.826235
iter  70 value 81.006916
iter  80 value 80.761392
iter  90 value 80.281674
iter 100 value 79.897269
final  value 79.897269 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.727612 
iter  10 value 94.241088
iter  20 value 92.712928
iter  30 value 83.899191
iter  40 value 82.923812
iter  50 value 81.694476
iter  60 value 81.130462
iter  70 value 80.636864
iter  80 value 80.550899
iter  90 value 80.499582
iter 100 value 80.429327
final  value 80.429327 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.889731 
iter  10 value 94.054898
iter  20 value 86.176519
iter  30 value 84.688948
iter  40 value 84.062527
iter  50 value 82.842560
iter  60 value 82.577449
iter  70 value 81.636939
iter  80 value 80.220229
iter  90 value 79.445940
iter 100 value 79.210557
final  value 79.210557 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.232499 
iter  10 value 94.193889
iter  20 value 89.793671
iter  30 value 86.724031
iter  40 value 83.909743
iter  50 value 81.633088
iter  60 value 80.790065
iter  70 value 80.571671
iter  80 value 80.450392
iter  90 value 80.417012
iter 100 value 80.334425
final  value 80.334425 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.174865 
iter  10 value 94.211686
iter  20 value 90.735734
iter  30 value 84.572909
iter  40 value 81.909480
iter  50 value 80.556973
iter  60 value 80.171974
iter  70 value 79.776710
iter  80 value 79.556845
iter  90 value 79.443377
iter 100 value 79.382407
final  value 79.382407 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.675814 
iter  10 value 95.196140
iter  20 value 92.247439
iter  30 value 87.741398
iter  40 value 85.810243
iter  50 value 85.302041
iter  60 value 83.505833
iter  70 value 82.245372
iter  80 value 81.724843
iter  90 value 81.061540
iter 100 value 80.545784
final  value 80.545784 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.768918 
final  value 94.055081 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.741103 
iter  10 value 93.895667
iter  20 value 93.894791
iter  30 value 93.810851
iter  30 value 93.810851
iter  30 value 93.810851
final  value 93.810851 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.541702 
iter  10 value 94.055248
final  value 94.053622 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.840786 
final  value 94.054667 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.343513 
iter  10 value 94.054583
iter  20 value 94.053005
iter  30 value 92.805235
iter  40 value 92.301780
iter  50 value 92.289686
final  value 92.289679 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.156038 
iter  10 value 94.057658
iter  20 value 93.768193
iter  30 value 91.406288
iter  40 value 91.241641
final  value 91.176655 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.163089 
iter  10 value 94.057992
iter  20 value 93.912693
iter  30 value 91.499330
iter  40 value 87.828561
iter  50 value 85.974065
iter  60 value 84.836739
iter  70 value 84.835273
iter  80 value 84.835019
iter  90 value 84.382265
iter 100 value 82.730617
final  value 82.730617 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.450382 
iter  10 value 87.826995
iter  20 value 83.002017
iter  30 value 82.214721
iter  40 value 82.214072
iter  50 value 82.163213
iter  60 value 82.151023
iter  70 value 82.147984
final  value 82.146395 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.466153 
iter  10 value 93.790567
iter  20 value 93.788133
iter  30 value 93.787005
iter  40 value 93.786820
iter  50 value 93.786225
final  value 93.786205 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.671490 
iter  10 value 94.057765
iter  20 value 92.471460
iter  30 value 84.786747
final  value 84.746058 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.337452 
iter  10 value 94.017129
iter  20 value 91.991518
iter  30 value 85.752895
iter  40 value 85.750105
iter  50 value 85.211636
iter  60 value 84.917838
iter  70 value 84.743401
final  value 84.739548 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.603412 
iter  10 value 94.020676
iter  20 value 93.853462
iter  30 value 93.806196
iter  40 value 93.781918
iter  50 value 93.781526
iter  60 value 91.586948
iter  70 value 91.380075
iter  80 value 91.033001
iter  90 value 90.743160
iter 100 value 90.732287
final  value 90.732287 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.928648 
iter  10 value 94.016304
iter  20 value 94.010447
iter  30 value 93.965528
iter  40 value 84.150223
iter  50 value 83.144915
iter  60 value 83.144634
iter  70 value 83.008987
iter  80 value 81.180154
iter  90 value 81.114308
iter 100 value 81.095331
final  value 81.095331 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.220990 
iter  10 value 93.722632
iter  20 value 93.391838
iter  30 value 84.404631
iter  40 value 82.746630
iter  50 value 82.724234
iter  60 value 82.557372
iter  70 value 81.285835
iter  80 value 81.277214
iter  90 value 81.277168
iter 100 value 80.709065
final  value 80.709065 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.287616 
iter  10 value 94.017420
iter  20 value 94.008598
iter  30 value 93.675368
iter  40 value 88.504821
iter  50 value 85.861730
iter  60 value 85.858290
iter  70 value 85.694955
iter  80 value 85.691422
iter  90 value 85.687373
iter 100 value 85.184969
final  value 85.184969 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 177.625295 
iter  10 value 119.811723
iter  20 value 114.654343
iter  30 value 110.344871
iter  40 value 110.108281
iter  50 value 109.255143
iter  60 value 105.291778
iter  70 value 103.905918
iter  80 value 102.921033
iter  90 value 102.355942
iter 100 value 101.809372
final  value 101.809372 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 159.933225 
iter  10 value 118.311454
iter  20 value 117.901536
iter  30 value 117.669746
iter  40 value 112.865977
iter  50 value 105.829992
iter  60 value 105.581327
iter  70 value 104.502682
iter  80 value 103.202125
iter  90 value 102.155682
iter 100 value 101.866970
final  value 101.866970 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 133.599541 
iter  10 value 114.969007
iter  20 value 107.858431
iter  30 value 106.435964
iter  40 value 104.300090
iter  50 value 103.049683
iter  60 value 102.726754
iter  70 value 101.588851
iter  80 value 101.540931
iter  90 value 101.390280
iter 100 value 101.339081
final  value 101.339081 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 156.683575 
iter  10 value 117.803552
iter  20 value 117.378828
iter  30 value 107.132492
iter  40 value 104.966974
iter  50 value 102.662864
iter  60 value 101.963056
iter  70 value 101.646635
iter  80 value 101.414985
iter  90 value 101.143830
iter 100 value 101.046851
final  value 101.046851 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 138.069745 
iter  10 value 117.580006
iter  20 value 117.205672
iter  30 value 106.271345
iter  40 value 106.119751
iter  50 value 105.505184
iter  60 value 103.173090
iter  70 value 102.144635
iter  80 value 101.429116
iter  90 value 101.151370
iter 100 value 101.063117
final  value 101.063117 
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 Apr  1 04:29:55 2025 
*********************************************** 
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 
 76.887   2.048 153.930