##############################################################################
##############################################################################
###
### 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_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.0 Patched (2025-04-21 r88169)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.15.0’
* 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 ... INFO
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       17.852  0.743  18.657
FSmethod      17.602  0.717  18.556
corr_plot     17.090  0.666  17.951
pred_ensembel  5.870  0.104   5.372
enrichfindP    0.166  0.030   7.609
* 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: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.22-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/4.5-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** 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 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-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 95.490005 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.099878 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.377824 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.321301 
final  value 93.912644 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.511807 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.467407 
iter  10 value 94.038228
iter  20 value 93.482994
iter  30 value 93.347284
iter  40 value 93.346723
iter  40 value 93.346723
iter  40 value 93.346723
final  value 93.346723 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.195680 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.856135 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.932913 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.789599 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.453847 
iter  10 value 91.454444
iter  20 value 89.169176
iter  30 value 87.343823
iter  40 value 87.328211
iter  50 value 87.234161
final  value 87.231837 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.261919 
iter  10 value 94.038197
iter  20 value 93.983373
final  value 93.902381 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.523792 
iter  10 value 91.579982
final  value 89.759214 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.447991 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.495553 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.016975 
iter  10 value 93.944992
iter  20 value 87.528205
iter  30 value 85.614023
iter  40 value 85.328565
iter  50 value 84.399761
iter  60 value 84.206584
iter  70 value 84.025387
iter  80 value 83.849662
final  value 83.846596 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.457468 
iter  10 value 94.087775
iter  20 value 93.751552
iter  30 value 89.848101
iter  40 value 85.890611
iter  50 value 85.303631
iter  60 value 84.970041
iter  70 value 83.556289
iter  80 value 83.500990
iter  90 value 83.487338
final  value 83.487231 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.695913 
iter  10 value 94.059581
iter  20 value 93.578708
iter  30 value 85.874423
iter  40 value 85.101803
iter  50 value 83.977156
iter  60 value 82.229240
iter  70 value 81.642894
iter  80 value 81.154596
iter  90 value 80.783068
iter 100 value 80.775085
final  value 80.775085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.621719 
iter  10 value 97.139441
iter  20 value 94.032007
iter  30 value 88.750725
iter  40 value 88.259452
iter  50 value 85.011514
iter  60 value 84.298512
iter  70 value 84.158427
iter  80 value 84.079518
iter  90 value 83.789604
iter 100 value 83.531165
final  value 83.531165 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 112.614540 
iter  10 value 93.979475
iter  20 value 93.625466
iter  30 value 88.112153
iter  40 value 85.569831
iter  50 value 84.198739
iter  60 value 83.642855
iter  70 value 83.552238
iter  80 value 83.513788
final  value 83.513591 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.357063 
iter  10 value 94.978944
iter  20 value 90.440949
iter  30 value 89.570139
iter  40 value 89.240508
iter  50 value 84.361931
iter  60 value 83.308788
iter  70 value 83.012819
iter  80 value 80.740897
iter  90 value 80.141306
iter 100 value 79.848372
final  value 79.848372 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.591038 
iter  10 value 94.016093
iter  20 value 89.475492
iter  30 value 87.496100
iter  40 value 84.177529
iter  50 value 81.723270
iter  60 value 80.847430
iter  70 value 80.450340
iter  80 value 80.138268
iter  90 value 79.932002
iter 100 value 79.813390
final  value 79.813390 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.363463 
iter  10 value 94.115262
iter  20 value 86.625145
iter  30 value 84.874641
iter  40 value 83.990547
iter  50 value 83.381959
iter  60 value 83.333791
iter  70 value 83.289734
iter  80 value 83.269565
iter  90 value 83.150196
iter 100 value 81.935411
final  value 81.935411 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.743098 
iter  10 value 93.790941
iter  20 value 93.695591
iter  30 value 89.288319
iter  40 value 84.201535
iter  50 value 82.981320
iter  60 value 82.094210
iter  70 value 80.637621
iter  80 value 80.561964
iter  90 value 80.549921
iter 100 value 80.510045
final  value 80.510045 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.007238 
iter  10 value 94.766338
iter  20 value 93.982677
iter  30 value 88.740743
iter  40 value 85.436818
iter  50 value 84.643164
iter  60 value 83.829416
iter  70 value 82.184203
iter  80 value 81.272576
iter  90 value 81.127242
iter 100 value 80.900031
final  value 80.900031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.326349 
iter  10 value 94.164113
iter  20 value 92.641521
iter  30 value 89.742384
iter  40 value 87.289264
iter  50 value 87.037746
iter  60 value 86.749006
iter  70 value 83.934094
iter  80 value 81.158648
iter  90 value 80.641793
iter 100 value 80.221055
final  value 80.221055 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.953290 
iter  10 value 94.428566
iter  20 value 91.396225
iter  30 value 86.119501
iter  40 value 84.118960
iter  50 value 81.491557
iter  60 value 81.199600
iter  70 value 80.988661
iter  80 value 80.423855
iter  90 value 79.595704
iter 100 value 79.520554
final  value 79.520554 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.218522 
iter  10 value 97.067123
iter  20 value 92.942414
iter  30 value 91.050974
iter  40 value 90.721108
iter  50 value 90.523428
iter  60 value 90.206341
iter  70 value 87.006760
iter  80 value 82.511889
iter  90 value 82.319441
iter 100 value 82.148147
final  value 82.148147 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.828643 
iter  10 value 94.018138
iter  20 value 93.567316
iter  30 value 87.055471
iter  40 value 84.821056
iter  50 value 83.523830
iter  60 value 82.407687
iter  70 value 81.941480
iter  80 value 81.494211
iter  90 value 81.211241
iter 100 value 81.066939
final  value 81.066939 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.151912 
iter  10 value 94.251274
iter  20 value 91.354722
iter  30 value 91.019094
iter  40 value 82.808401
iter  50 value 81.066376
iter  60 value 80.418397
iter  70 value 80.342500
iter  80 value 80.164651
iter  90 value 79.867669
iter 100 value 79.371362
final  value 79.371362 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.027052 
final  value 94.054663 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.670245 
final  value 94.054263 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.546421 
iter  10 value 91.818303
iter  20 value 91.376496
iter  30 value 91.329729
iter  40 value 91.329607
iter  50 value 91.328271
final  value 91.328085 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.876305 
iter  10 value 94.040614
iter  20 value 94.039069
iter  30 value 85.825872
iter  40 value 84.444864
final  value 84.444794 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.572135 
final  value 94.039946 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.720247 
iter  10 value 94.058119
iter  20 value 93.849708
iter  30 value 87.380011
iter  40 value 84.999937
iter  50 value 83.992224
iter  60 value 83.468955
iter  70 value 83.465628
iter  80 value 83.183214
iter  90 value 82.495957
iter 100 value 82.211440
final  value 82.211440 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.722913 
iter  10 value 87.909500
iter  20 value 87.115083
iter  30 value 87.092778
iter  40 value 86.633202
iter  50 value 86.615273
iter  60 value 86.614994
final  value 86.614826 
converged
Fitting Repeat 3 

# weights:  305
initial  value 123.595829 
iter  10 value 94.058019
iter  20 value 94.053220
iter  30 value 93.681499
iter  40 value 93.328940
iter  50 value 86.443003
iter  60 value 83.652891
iter  70 value 83.112223
iter  80 value 83.110840
final  value 83.110659 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.302519 
iter  10 value 92.188638
iter  20 value 91.546936
iter  30 value 90.824112
iter  40 value 90.821813
iter  50 value 90.492339
iter  60 value 90.460551
iter  70 value 90.459880
iter  80 value 90.006171
iter  90 value 89.993963
final  value 89.993716 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.228465 
iter  10 value 94.043242
iter  20 value 92.580227
iter  30 value 84.753341
iter  40 value 81.395542
iter  50 value 80.331606
iter  60 value 78.904332
iter  70 value 78.608602
iter  80 value 78.557177
iter  90 value 78.483037
final  value 78.479064 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.020935 
iter  10 value 92.441192
iter  20 value 89.152202
iter  30 value 86.868374
iter  40 value 86.865602
iter  50 value 86.863926
iter  60 value 86.862789
iter  70 value 86.858929
final  value 86.858461 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.655840 
iter  10 value 94.058887
iter  20 value 92.103431
iter  30 value 83.337178
iter  40 value 83.325014
iter  50 value 82.982884
iter  60 value 82.758097
iter  70 value 81.146553
iter  80 value 79.157339
iter  90 value 78.894081
iter 100 value 78.843950
final  value 78.843950 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.852609 
iter  10 value 93.336626
iter  20 value 93.332499
iter  30 value 93.324754
iter  40 value 84.331507
iter  50 value 83.833325
iter  60 value 83.773406
final  value 83.773305 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.053531 
iter  10 value 92.598407
iter  20 value 88.664602
iter  30 value 88.380813
iter  40 value 88.377532
iter  50 value 88.376984
iter  60 value 88.373248
iter  70 value 88.362759
iter  80 value 88.341889
iter  90 value 88.340860
iter 100 value 88.339648
final  value 88.339648 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.089350 
iter  10 value 93.913242
iter  20 value 93.909006
iter  30 value 91.074568
iter  40 value 89.559470
iter  50 value 84.521479
iter  60 value 81.513236
final  value 81.480964 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.553320 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.104007 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.328117 
final  value 94.144482 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.576175 
final  value 94.449438 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.349732 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.795012 
final  value 94.387430 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.276216 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.852244 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.448973 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.150520 
iter  10 value 94.132646
final  value 94.132576 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.083140 
iter  10 value 94.354205
iter  20 value 94.144570
final  value 94.144483 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.088139 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.380945 
iter  10 value 94.484288
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.815872 
iter  10 value 94.354441
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.707201 
final  value 94.144481 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.555938 
iter  10 value 94.486504
iter  20 value 94.197722
iter  30 value 90.862737
iter  40 value 86.942821
iter  50 value 86.414123
iter  60 value 84.963140
iter  70 value 84.502512
iter  80 value 84.198582
iter  90 value 84.010776
iter 100 value 83.800065
final  value 83.800065 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.810356 
iter  10 value 94.486498
iter  20 value 94.404731
iter  30 value 93.856606
iter  40 value 93.311407
iter  50 value 90.268594
iter  60 value 88.451987
iter  70 value 86.623361
iter  80 value 85.517605
iter  90 value 85.352722
iter 100 value 85.146408
final  value 85.146408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.501026 
iter  10 value 94.436697
iter  20 value 93.660907
iter  30 value 92.932825
iter  40 value 92.801943
iter  50 value 92.727117
iter  60 value 92.582879
iter  70 value 85.932745
iter  80 value 85.354391
iter  90 value 84.808260
iter 100 value 84.326507
final  value 84.326507 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.097324 
iter  10 value 94.506794
iter  20 value 93.052739
iter  30 value 90.657492
iter  40 value 86.892359
iter  50 value 85.927370
iter  60 value 85.600782
iter  70 value 84.934176
iter  80 value 84.284617
iter  90 value 84.019191
iter 100 value 83.812565
final  value 83.812565 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 117.387830 
iter  10 value 94.404723
iter  20 value 92.825541
iter  30 value 92.684002
iter  40 value 92.666087
final  value 92.666082 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.256736 
iter  10 value 94.453476
iter  20 value 90.817427
iter  30 value 87.079860
iter  40 value 86.413519
iter  50 value 86.072508
iter  60 value 85.782219
iter  70 value 85.589514
iter  80 value 85.414405
iter  90 value 84.277295
iter 100 value 82.795359
final  value 82.795359 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.992886 
iter  10 value 94.883481
iter  20 value 94.533781
iter  30 value 91.907021
iter  40 value 86.565450
iter  50 value 86.506795
iter  60 value 86.178443
iter  70 value 83.612458
iter  80 value 83.299162
iter  90 value 83.057522
iter 100 value 82.890497
final  value 82.890497 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.782435 
iter  10 value 94.548846
iter  20 value 94.413530
iter  30 value 91.815660
iter  40 value 87.288659
iter  50 value 85.653117
iter  60 value 84.289930
iter  70 value 83.232026
iter  80 value 82.834381
iter  90 value 82.758652
iter 100 value 82.545212
final  value 82.545212 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.781918 
iter  10 value 94.488979
iter  20 value 91.238342
iter  30 value 88.537950
iter  40 value 87.497354
iter  50 value 86.767989
iter  60 value 85.864584
iter  70 value 85.449027
iter  80 value 85.230489
iter  90 value 84.445415
iter 100 value 83.465382
final  value 83.465382 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.013659 
iter  10 value 94.237676
iter  20 value 87.954143
iter  30 value 86.275980
iter  40 value 85.635355
iter  50 value 85.311377
iter  60 value 84.628335
iter  70 value 84.347960
iter  80 value 83.878810
iter  90 value 83.394594
iter 100 value 82.887552
final  value 82.887552 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.692807 
iter  10 value 95.220030
iter  20 value 94.089830
iter  30 value 88.441652
iter  40 value 87.672340
iter  50 value 85.204387
iter  60 value 83.991666
iter  70 value 83.447895
iter  80 value 83.019296
iter  90 value 82.806322
iter 100 value 82.225371
final  value 82.225371 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.280989 
iter  10 value 94.490044
iter  20 value 94.297609
iter  30 value 93.087164
iter  40 value 89.395862
iter  50 value 86.714164
iter  60 value 85.824290
iter  70 value 84.198289
iter  80 value 83.137187
iter  90 value 82.712272
iter 100 value 82.156728
final  value 82.156728 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.375623 
iter  10 value 94.080093
iter  20 value 87.721414
iter  30 value 87.388753
iter  40 value 87.284352
iter  50 value 85.890748
iter  60 value 84.519286
iter  70 value 83.654180
iter  80 value 82.587609
iter  90 value 82.058625
iter 100 value 81.771751
final  value 81.771751 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.307197 
iter  10 value 94.582831
iter  20 value 94.360806
iter  30 value 92.747576
iter  40 value 87.606742
iter  50 value 85.153379
iter  60 value 84.280941
iter  70 value 83.222844
iter  80 value 82.710149
iter  90 value 82.641321
iter 100 value 82.362279
final  value 82.362279 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.376238 
iter  10 value 94.406539
iter  20 value 93.338411
iter  30 value 89.106696
iter  40 value 85.641163
iter  50 value 85.020782
iter  60 value 83.847850
iter  70 value 82.726478
iter  80 value 82.522133
iter  90 value 82.295115
iter 100 value 82.089504
final  value 82.089504 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.726468 
final  value 94.485918 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.708391 
final  value 94.485693 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.070916 
final  value 94.485985 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.193177 
iter  10 value 94.485733
iter  20 value 94.484247
iter  30 value 94.366117
iter  40 value 93.298721
iter  50 value 93.089517
iter  60 value 87.603515
iter  70 value 87.290438
iter  80 value 86.475227
iter  90 value 86.460736
iter 100 value 86.457148
final  value 86.457148 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.312686 
final  value 94.485767 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.102440 
iter  10 value 94.488937
iter  20 value 94.484304
final  value 94.484220 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.221353 
iter  10 value 94.149796
iter  20 value 94.101640
iter  30 value 94.096211
iter  40 value 90.396670
iter  50 value 85.755038
iter  60 value 85.753775
final  value 85.753226 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.480359 
iter  10 value 94.359057
iter  20 value 94.355483
final  value 94.354718 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.418688 
iter  10 value 94.358879
iter  20 value 94.163330
iter  30 value 90.641527
final  value 88.422163 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.973667 
iter  10 value 94.454528
iter  20 value 94.449083
iter  30 value 93.984342
iter  40 value 92.510556
iter  50 value 92.370314
iter  60 value 92.299229
final  value 92.299225 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.006160 
iter  10 value 94.491411
iter  20 value 94.429594
iter  30 value 91.348183
iter  40 value 90.983385
iter  50 value 90.981857
iter  60 value 90.881347
iter  70 value 90.878645
iter  80 value 90.330083
iter  90 value 85.392628
iter 100 value 85.162305
final  value 85.162305 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.334134 
iter  10 value 94.495714
iter  20 value 94.459218
iter  30 value 92.544791
iter  40 value 90.623861
iter  50 value 90.614119
iter  60 value 90.367768
iter  70 value 90.323859
iter  80 value 90.255124
iter  90 value 90.218312
iter 100 value 89.521352
final  value 89.521352 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.770929 
iter  10 value 93.352894
iter  20 value 92.977014
iter  30 value 91.271533
iter  40 value 90.157859
iter  50 value 90.099309
iter  60 value 88.961797
iter  70 value 88.894893
iter  80 value 88.890094
iter  90 value 88.888616
iter 100 value 87.920201
final  value 87.920201 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.123484 
iter  10 value 89.221073
iter  20 value 86.900072
iter  30 value 86.863259
iter  40 value 86.584327
iter  50 value 86.239435
iter  60 value 86.238484
iter  70 value 86.211554
iter  80 value 86.153409
iter  90 value 86.152905
iter 100 value 86.152790
final  value 86.152790 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.139405 
iter  10 value 94.457106
iter  20 value 93.489212
iter  30 value 93.485226
iter  40 value 92.607400
iter  50 value 92.607050
iter  60 value 92.604131
final  value 92.534520 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.352201 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.770389 
iter  10 value 93.294329
iter  20 value 92.321991
iter  30 value 91.182959
iter  40 value 90.161522
iter  50 value 90.104234
iter  60 value 90.081006
final  value 90.069606 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.458809 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.041226 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.455836 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.073528 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.029393 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.462917 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.725769 
iter  10 value 92.287414
iter  20 value 92.281087
final  value 92.281082 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.067859 
iter  10 value 94.179774
final  value 94.179348 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.862619 
iter  10 value 92.292466
iter  20 value 92.281092
final  value 92.281082 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.433359 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.516255 
iter  10 value 91.868606
iter  20 value 91.865306
iter  30 value 91.864642
iter  30 value 91.864642
iter  30 value 91.864642
final  value 91.864642 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.797379 
iter  10 value 92.292155
iter  20 value 92.281091
final  value 92.281082 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.745745 
iter  10 value 90.560678
iter  20 value 88.022110
iter  30 value 88.019416
iter  40 value 86.215892
iter  50 value 85.020201
final  value 85.019364 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.607303 
iter  10 value 94.481149
iter  20 value 93.877468
iter  30 value 92.843266
iter  40 value 92.347093
iter  50 value 83.844920
iter  60 value 83.437966
iter  70 value 81.902034
iter  80 value 79.902986
iter  90 value 79.398041
iter 100 value 79.320367
final  value 79.320367 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.188784 
iter  10 value 94.387906
iter  20 value 92.660730
iter  30 value 92.612396
iter  40 value 92.545534
iter  50 value 92.042309
iter  60 value 86.421002
iter  70 value 85.786071
iter  80 value 84.043552
iter  90 value 83.001682
iter 100 value 81.237513
final  value 81.237513 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.097364 
iter  10 value 94.342206
iter  20 value 91.973468
iter  30 value 87.660605
iter  40 value 86.115383
iter  50 value 85.267333
iter  60 value 81.558486
iter  70 value 81.338450
iter  80 value 81.102808
iter  90 value 79.850368
iter 100 value 79.390671
final  value 79.390671 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.512214 
iter  10 value 86.314419
iter  20 value 85.868698
iter  30 value 85.577750
final  value 85.573764 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.917579 
iter  10 value 94.397986
iter  20 value 93.052445
iter  30 value 93.023087
iter  40 value 92.702540
iter  50 value 86.788366
iter  60 value 86.527867
iter  70 value 86.518095
iter  80 value 85.470766
iter  90 value 83.649948
iter 100 value 82.612245
final  value 82.612245 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.092291 
iter  10 value 94.493812
iter  20 value 93.095034
iter  30 value 92.530284
iter  40 value 86.043467
iter  50 value 82.783759
iter  60 value 80.438459
iter  70 value 79.785190
iter  80 value 79.552418
iter  90 value 79.301059
iter 100 value 79.205853
final  value 79.205853 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.874498 
iter  10 value 93.851766
iter  20 value 92.980484
iter  30 value 92.500312
iter  40 value 92.392352
iter  50 value 84.741584
iter  60 value 83.328806
iter  70 value 80.464631
iter  80 value 78.664506
iter  90 value 77.927280
iter 100 value 77.650121
final  value 77.650121 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.819142 
iter  10 value 95.227394
iter  20 value 93.824073
iter  30 value 92.689502
iter  40 value 91.799032
iter  50 value 87.637810
iter  60 value 86.771518
iter  70 value 85.861484
iter  80 value 84.383881
iter  90 value 81.128246
iter 100 value 78.927023
final  value 78.927023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.824352 
iter  10 value 94.257411
iter  20 value 92.447835
iter  30 value 92.069403
iter  40 value 84.502490
iter  50 value 83.287067
iter  60 value 79.730512
iter  70 value 78.357774
iter  80 value 78.104157
iter  90 value 77.873909
iter 100 value 77.845376
final  value 77.845376 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.788402 
iter  10 value 92.973667
iter  20 value 85.234416
iter  30 value 81.435538
iter  40 value 80.416778
iter  50 value 79.129065
iter  60 value 78.593971
iter  70 value 78.041085
iter  80 value 77.729651
iter  90 value 77.626512
iter 100 value 77.540405
final  value 77.540405 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.013050 
iter  10 value 94.661437
iter  20 value 93.013516
iter  30 value 92.850571
iter  40 value 92.151440
iter  50 value 89.481223
iter  60 value 82.717993
iter  70 value 80.829309
iter  80 value 79.312092
iter  90 value 79.161896
iter 100 value 78.769482
final  value 78.769482 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.301392 
iter  10 value 94.366300
iter  20 value 93.274869
iter  30 value 92.335551
iter  40 value 91.882483
iter  50 value 87.441754
iter  60 value 85.457427
iter  70 value 84.850072
iter  80 value 81.948622
iter  90 value 79.475442
iter 100 value 77.759823
final  value 77.759823 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.421184 
iter  10 value 94.487124
iter  20 value 90.845808
iter  30 value 84.623407
iter  40 value 81.710272
iter  50 value 81.508468
iter  60 value 81.356350
iter  70 value 81.248384
iter  80 value 80.788195
iter  90 value 79.686344
iter 100 value 78.961980
final  value 78.961980 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.163937 
iter  10 value 94.072566
iter  20 value 88.850172
iter  30 value 84.785514
iter  40 value 81.987658
iter  50 value 80.465874
iter  60 value 79.171125
iter  70 value 78.504832
iter  80 value 78.233343
iter  90 value 77.755899
iter 100 value 77.662449
final  value 77.662449 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.077952 
iter  10 value 94.217573
iter  20 value 92.302509
iter  30 value 87.444815
iter  40 value 84.723255
iter  50 value 81.471304
iter  60 value 79.212276
iter  70 value 78.561754
iter  80 value 78.034490
iter  90 value 77.831017
iter 100 value 77.745387
final  value 77.745387 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.079876 
final  value 94.485638 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.447465 
final  value 94.485882 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.588138 
iter  10 value 93.475517
iter  20 value 92.340528
iter  30 value 91.988075
iter  40 value 91.764075
iter  50 value 91.669572
iter  50 value 91.669571
iter  50 value 91.669571
final  value 91.669571 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.487931 
final  value 94.485989 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.607881 
final  value 94.485701 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.983686 
iter  10 value 94.488098
iter  20 value 94.229715
iter  30 value 92.293226
iter  40 value 92.292357
iter  50 value 92.145220
iter  60 value 86.670801
iter  70 value 84.584720
iter  80 value 84.340415
iter  90 value 84.189667
iter 100 value 84.043561
final  value 84.043561 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.596530 
iter  10 value 92.378111
iter  20 value 92.297585
iter  30 value 91.888723
iter  40 value 91.876996
iter  50 value 91.875249
final  value 91.875152 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.039655 
iter  10 value 93.789199
iter  20 value 93.786628
iter  30 value 90.169524
iter  40 value 85.722238
iter  50 value 85.660938
final  value 85.659268 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.319247 
iter  10 value 94.315591
iter  20 value 93.788771
iter  30 value 93.784754
iter  40 value 93.575528
iter  50 value 90.481241
iter  60 value 90.479660
iter  70 value 87.596858
iter  80 value 86.641940
iter  90 value 86.639640
iter 100 value 84.879907
final  value 84.879907 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.498979 
iter  10 value 94.492680
iter  20 value 94.469508
iter  30 value 92.289619
iter  40 value 92.288423
iter  50 value 92.182741
iter  60 value 86.068517
iter  70 value 85.973044
iter  80 value 85.972732
iter  90 value 85.972440
iter 100 value 85.972406
final  value 85.972406 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.317728 
iter  10 value 92.313720
iter  20 value 92.294308
iter  30 value 92.243314
iter  40 value 92.236661
iter  50 value 91.757681
iter  60 value 88.671317
iter  70 value 80.413362
iter  80 value 77.472450
iter  90 value 77.172313
iter 100 value 77.115167
final  value 77.115167 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.004799 
iter  10 value 83.795005
iter  20 value 83.358958
iter  30 value 83.314878
iter  40 value 83.313959
iter  50 value 83.308799
iter  60 value 83.305556
iter  70 value 82.836536
iter  80 value 81.823710
iter  90 value 79.470911
iter 100 value 77.869053
final  value 77.869053 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.348754 
iter  10 value 92.295403
iter  20 value 92.292183
iter  30 value 91.797311
iter  40 value 91.684542
iter  50 value 91.657492
final  value 91.654788 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.662104 
iter  10 value 92.307879
iter  20 value 92.294325
iter  30 value 92.290364
iter  40 value 92.284973
iter  50 value 91.514918
iter  60 value 90.102080
iter  70 value 82.943965
iter  80 value 78.453063
iter  90 value 78.099918
iter 100 value 78.011173
final  value 78.011173 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.329583 
iter  10 value 92.332263
iter  20 value 92.306728
iter  30 value 92.299214
iter  40 value 92.123087
iter  50 value 90.995587
iter  60 value 82.491909
iter  70 value 79.854755
iter  80 value 78.132270
iter  90 value 78.094222
iter 100 value 78.088329
final  value 78.088329 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.996338 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.317233 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.004112 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.401876 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.661465 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 92.233828 
iter  10 value 85.889659
final  value 85.889610 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.519998 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.291531 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.775553 
iter  10 value 92.636058
iter  20 value 85.968836
final  value 85.951718 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.270187 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.423237 
final  value 94.315789 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.311925 
iter  10 value 92.678657
iter  20 value 91.609035
iter  30 value 91.597908
iter  40 value 91.597734
iter  40 value 91.597734
iter  40 value 91.597734
final  value 91.597734 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.738869 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.499070 
iter  10 value 94.466838
final  value 94.466829 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.696682 
iter  10 value 94.452876
iter  10 value 94.452875
iter  10 value 94.452875
final  value 94.452875 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.994700 
iter  10 value 94.464569
iter  20 value 94.213840
iter  30 value 91.321029
iter  40 value 87.110272
iter  50 value 85.034494
iter  60 value 84.760729
iter  70 value 84.314722
iter  80 value 84.282970
iter  90 value 84.275956
final  value 84.275953 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.633271 
iter  10 value 94.486688
iter  20 value 94.230386
iter  30 value 89.125676
iter  40 value 85.690116
iter  50 value 84.435215
iter  60 value 84.371130
iter  70 value 84.335421
iter  80 value 84.281643
iter  90 value 84.275990
final  value 84.275953 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.633876 
iter  10 value 94.502144
iter  20 value 94.483752
iter  30 value 94.291184
iter  40 value 94.212566
iter  50 value 94.165677
iter  60 value 94.074463
iter  70 value 94.052979
iter  80 value 90.516603
iter  90 value 85.065944
iter 100 value 83.126855
final  value 83.126855 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.299831 
iter  10 value 94.487917
iter  20 value 94.456830
iter  30 value 91.677005
iter  40 value 88.392696
iter  50 value 87.642824
iter  60 value 86.942887
iter  70 value 86.406731
iter  80 value 86.356507
final  value 86.355854 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.187778 
iter  10 value 94.469264
iter  20 value 91.604438
iter  30 value 90.261543
iter  40 value 90.023304
iter  50 value 85.461353
iter  60 value 84.866727
iter  70 value 82.497033
iter  80 value 80.863633
iter  90 value 80.789342
iter 100 value 80.670936
final  value 80.670936 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.694431 
iter  10 value 95.413342
iter  20 value 94.371562
iter  30 value 91.695049
iter  40 value 86.489236
iter  50 value 86.316409
iter  60 value 86.133005
iter  70 value 86.002299
iter  80 value 84.629960
iter  90 value 83.387819
iter 100 value 83.118072
final  value 83.118072 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.759658 
iter  10 value 95.967549
iter  20 value 92.875288
iter  30 value 88.450938
iter  40 value 87.334540
iter  50 value 85.939289
iter  60 value 85.824411
iter  70 value 83.729746
iter  80 value 81.547843
iter  90 value 80.837647
iter 100 value 80.676473
final  value 80.676473 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.897045 
iter  10 value 94.470825
iter  20 value 93.656560
iter  30 value 91.688319
iter  40 value 91.032442
iter  50 value 90.959433
iter  60 value 90.531447
iter  70 value 81.680270
iter  80 value 81.507574
iter  90 value 81.199744
iter 100 value 80.339261
final  value 80.339261 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.394032 
iter  10 value 94.344987
iter  20 value 90.628692
iter  30 value 86.946195
iter  40 value 84.098534
iter  50 value 82.917539
iter  60 value 82.804020
iter  70 value 82.465294
iter  80 value 81.934042
iter  90 value 81.063404
iter 100 value 80.848334
final  value 80.848334 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.199141 
iter  10 value 94.596034
iter  20 value 94.102395
iter  30 value 90.875711
iter  40 value 89.297394
iter  50 value 83.927336
iter  60 value 83.110390
iter  70 value 82.802269
iter  80 value 82.765049
iter  90 value 80.495624
iter 100 value 80.272174
final  value 80.272174 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.975190 
iter  10 value 94.417408
iter  20 value 88.799168
iter  30 value 87.724240
iter  40 value 86.439327
iter  50 value 84.151554
iter  60 value 81.297885
iter  70 value 80.759861
iter  80 value 79.478505
iter  90 value 78.971274
iter 100 value 78.938103
final  value 78.938103 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.774720 
iter  10 value 94.529226
iter  20 value 93.606226
iter  30 value 86.427860
iter  40 value 82.752705
iter  50 value 80.539316
iter  60 value 79.346681
iter  70 value 78.703793
iter  80 value 78.347930
iter  90 value 78.207591
iter 100 value 78.159704
final  value 78.159704 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.154021 
iter  10 value 94.683711
iter  20 value 93.939923
iter  30 value 90.363906
iter  40 value 89.218445
iter  50 value 86.624663
iter  60 value 82.827155
iter  70 value 81.802822
iter  80 value 80.828098
iter  90 value 80.049404
iter 100 value 79.052228
final  value 79.052228 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.024827 
iter  10 value 94.579050
iter  20 value 94.446325
iter  30 value 86.082171
iter  40 value 83.257816
iter  50 value 82.934701
iter  60 value 82.775028
iter  70 value 80.408775
iter  80 value 79.827688
iter  90 value 79.293046
iter 100 value 78.840010
final  value 78.840010 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.237463 
iter  10 value 94.816624
iter  20 value 90.455434
iter  30 value 87.452274
iter  40 value 87.033494
iter  50 value 85.063178
iter  60 value 80.301898
iter  70 value 79.465955
iter  80 value 79.069187
iter  90 value 78.413620
iter 100 value 78.006142
final  value 78.006142 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.118903 
final  value 94.485709 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.838962 
final  value 94.486071 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.357544 
iter  10 value 91.240013
iter  20 value 91.211605
final  value 91.211531 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.332770 
final  value 94.486043 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.678561 
final  value 94.485644 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.267798 
iter  10 value 94.149644
iter  20 value 93.666797
iter  30 value 85.296023
final  value 84.008135 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.689400 
iter  10 value 94.489391
iter  20 value 94.484258
iter  30 value 94.475001
iter  40 value 93.998311
iter  50 value 93.993061
iter  60 value 93.992970
iter  60 value 93.992970
iter  60 value 93.992970
final  value 93.992970 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.584146 
iter  10 value 94.471876
iter  20 value 94.321068
iter  30 value 94.062423
iter  40 value 94.051094
final  value 94.050995 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.764044 
iter  10 value 93.725339
iter  20 value 93.080591
iter  30 value 92.211392
iter  40 value 92.210115
final  value 92.210099 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.063041 
iter  10 value 88.988976
iter  20 value 87.778068
iter  30 value 87.615384
iter  40 value 86.211340
final  value 85.891622 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.676393 
iter  10 value 93.686029
iter  20 value 92.600635
iter  30 value 92.306375
iter  40 value 92.301981
final  value 92.301845 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.782370 
iter  10 value 93.784150
iter  20 value 93.657351
iter  30 value 86.667884
iter  40 value 86.610563
iter  50 value 86.609136
iter  60 value 86.608967
iter  70 value 86.607565
iter  80 value 86.373308
iter  90 value 86.277885
iter 100 value 85.794260
final  value 85.794260 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.780402 
iter  10 value 94.492391
iter  20 value 94.457944
iter  30 value 85.106374
iter  40 value 83.165007
final  value 83.164975 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.495925 
iter  10 value 94.492349
iter  20 value 94.484013
iter  30 value 91.767655
iter  40 value 83.894062
iter  50 value 81.745770
iter  60 value 81.079673
iter  70 value 80.741410
iter  80 value 79.694524
iter  90 value 78.903213
iter 100 value 77.601250
final  value 77.601250 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.811194 
iter  10 value 94.474344
iter  20 value 94.468131
iter  30 value 94.467907
iter  40 value 93.969424
iter  50 value 84.077131
iter  60 value 84.014030
iter  70 value 83.738078
iter  80 value 78.826286
iter  90 value 78.588789
iter 100 value 77.876613
final  value 77.876613 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.519520 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.114283 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.483315 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.707326 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.188958 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.581135 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.570238 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.169291 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.090197 
final  value 94.052448 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.918518 
iter  10 value 94.052911
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.459562 
iter  10 value 94.038255
final  value 94.038250 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.936365 
iter  10 value 94.038251
iter  10 value 94.038251
iter  10 value 94.038251
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.732093 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.598090 
iter  10 value 94.038253
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.140388 
iter  10 value 91.725914
iter  20 value 91.450384
final  value 91.448719 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.523770 
iter  10 value 94.019331
iter  20 value 85.376204
iter  30 value 82.785722
iter  40 value 82.660032
iter  50 value 82.614533
iter  60 value 82.290166
iter  70 value 81.946680
iter  80 value 81.912227
final  value 81.912218 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.222727 
iter  10 value 93.461048
iter  20 value 83.825792
iter  30 value 83.479651
iter  40 value 82.571831
iter  50 value 82.085401
iter  60 value 82.058207
iter  70 value 82.023601
iter  80 value 81.941429
final  value 81.932199 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.543044 
iter  10 value 94.056589
iter  20 value 93.069371
iter  30 value 91.789285
iter  40 value 85.190358
iter  50 value 83.908576
iter  60 value 81.669860
iter  70 value 80.938031
iter  80 value 80.623464
iter  90 value 80.353079
iter 100 value 80.330798
final  value 80.330798 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 107.573178 
iter  10 value 93.763467
iter  20 value 89.220119
iter  30 value 83.818291
iter  40 value 82.904279
iter  50 value 82.682975
iter  60 value 82.170203
iter  70 value 81.932260
final  value 81.932199 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.052770 
iter  10 value 89.692197
iter  20 value 88.209104
iter  30 value 86.627548
iter  40 value 86.144981
iter  50 value 84.787240
iter  60 value 82.832647
iter  70 value 82.136694
iter  80 value 81.785323
iter  90 value 81.506972
final  value 81.494191 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.405223 
iter  10 value 94.071711
iter  20 value 91.708658
iter  30 value 86.814928
iter  40 value 82.330116
iter  50 value 80.275276
iter  60 value 79.488274
iter  70 value 79.218069
iter  80 value 78.850619
iter  90 value 78.782777
iter 100 value 78.767944
final  value 78.767944 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.897882 
iter  10 value 93.902151
iter  20 value 86.872162
iter  30 value 83.869581
iter  40 value 82.214547
iter  50 value 81.850435
iter  60 value 80.770113
iter  70 value 80.477023
iter  80 value 80.315480
iter  90 value 80.250002
iter 100 value 80.127355
final  value 80.127355 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.221451 
iter  10 value 94.047665
iter  20 value 86.394474
iter  30 value 82.942153
iter  40 value 80.632473
iter  50 value 80.220571
iter  60 value 80.143581
iter  70 value 80.028789
iter  80 value 79.785742
iter  90 value 79.624165
iter 100 value 79.553745
final  value 79.553745 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.562612 
iter  10 value 94.013938
iter  20 value 90.793592
iter  30 value 86.796436
iter  40 value 85.601635
iter  50 value 85.255034
iter  60 value 84.955152
iter  70 value 83.741496
iter  80 value 82.023869
iter  90 value 79.752445
iter 100 value 78.854774
final  value 78.854774 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.889853 
iter  10 value 94.106387
iter  20 value 91.914246
iter  30 value 91.299138
iter  40 value 84.890139
iter  50 value 80.634559
iter  60 value 79.158854
iter  70 value 78.847780
iter  80 value 78.782884
iter  90 value 78.709930
iter 100 value 78.590294
final  value 78.590294 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.924286 
iter  10 value 97.129019
iter  20 value 94.016677
iter  30 value 84.833705
iter  40 value 83.710709
iter  50 value 83.445861
iter  60 value 82.627460
iter  70 value 82.220629
iter  80 value 81.881789
iter  90 value 80.917496
iter 100 value 79.639673
final  value 79.639673 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.874729 
iter  10 value 95.201535
iter  20 value 91.313026
iter  30 value 88.777469
iter  40 value 83.273618
iter  50 value 81.259901
iter  60 value 79.285376
iter  70 value 78.918067
iter  80 value 78.804097
iter  90 value 78.636800
iter 100 value 78.474730
final  value 78.474730 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.695894 
iter  10 value 93.257398
iter  20 value 83.648574
iter  30 value 81.627823
iter  40 value 79.991241
iter  50 value 79.202542
iter  60 value 78.696449
iter  70 value 78.349523
iter  80 value 78.053607
iter  90 value 77.980288
iter 100 value 77.819790
final  value 77.819790 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.021259 
iter  10 value 92.239643
iter  20 value 91.885139
iter  30 value 90.904650
iter  40 value 87.368861
iter  50 value 80.757639
iter  60 value 79.356869
iter  70 value 78.932502
iter  80 value 78.295219
iter  90 value 77.981721
iter 100 value 77.859491
final  value 77.859491 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.183345 
iter  10 value 85.929189
iter  20 value 83.768168
iter  30 value 80.902007
iter  40 value 80.008583
iter  50 value 79.458490
iter  60 value 78.874908
iter  70 value 78.492387
iter  80 value 78.403755
iter  90 value 78.174051
iter 100 value 78.124692
final  value 78.124692 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.671605 
final  value 94.054548 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.329789 
final  value 94.054565 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.614683 
iter  10 value 93.876519
final  value 93.272914 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.408289 
iter  10 value 94.051904
iter  20 value 91.584351
iter  30 value 91.255676
iter  40 value 91.253385
iter  50 value 91.252996
iter  60 value 91.252150
final  value 91.252011 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.415104 
final  value 94.054547 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.016255 
iter  10 value 88.417540
iter  20 value 84.121874
iter  30 value 84.087461
iter  40 value 84.083226
iter  50 value 79.736760
iter  60 value 79.131505
iter  70 value 79.073694
iter  80 value 79.072668
iter  90 value 79.072520
iter 100 value 78.350216
final  value 78.350216 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.106331 
iter  10 value 94.057686
iter  20 value 93.907199
iter  30 value 89.713260
iter  40 value 84.468295
iter  50 value 83.738251
iter  60 value 83.727920
iter  70 value 81.207367
iter  80 value 79.300453
iter  90 value 79.208941
iter 100 value 79.112742
final  value 79.112742 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.647793 
iter  10 value 93.904926
iter  20 value 93.871062
iter  30 value 93.791505
final  value 93.789607 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.867320 
iter  10 value 93.522606
iter  20 value 93.310450
iter  30 value 93.299145
iter  40 value 91.242501
iter  50 value 91.242325
iter  60 value 91.139315
iter  70 value 87.719539
iter  80 value 86.257123
iter  90 value 86.256933
iter 100 value 86.256004
final  value 86.256004 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.326312 
iter  10 value 94.056589
iter  20 value 93.318436
iter  30 value 85.290831
iter  40 value 82.236822
iter  50 value 82.143186
iter  60 value 82.140069
final  value 82.139819 
converged
Fitting Repeat 1 

# weights:  507
initial  value 92.972587 
iter  10 value 83.244206
iter  20 value 81.712181
iter  30 value 80.319522
iter  40 value 80.286128
iter  50 value 80.284562
final  value 80.281614 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.305310 
iter  10 value 93.908023
iter  20 value 89.035576
iter  30 value 85.103901
iter  40 value 84.723230
iter  50 value 82.557562
iter  60 value 82.557035
iter  70 value 82.550353
iter  80 value 82.544637
iter  90 value 82.543543
iter 100 value 81.906071
final  value 81.906071 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.487385 
iter  10 value 94.060756
iter  20 value 94.033658
iter  30 value 89.309811
iter  40 value 84.709416
iter  50 value 84.697864
iter  60 value 83.806198
iter  70 value 83.367404
iter  80 value 83.271077
iter  90 value 83.270787
final  value 83.270590 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.145305 
iter  10 value 94.061355
iter  20 value 94.053875
iter  30 value 93.816301
iter  40 value 88.106674
iter  50 value 87.346885
iter  60 value 87.336536
iter  70 value 87.335920
iter  80 value 87.335109
iter  90 value 87.334267
final  value 87.333604 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.935574 
iter  10 value 94.046507
iter  20 value 93.986505
iter  30 value 88.517584
iter  40 value 82.914445
iter  50 value 82.323387
iter  60 value 82.321234
iter  70 value 82.321091
iter  80 value 82.320566
iter  90 value 82.320147
iter 100 value 82.015348
final  value 82.015348 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.210573 
final  value 117.874568 
converged
Fitting Repeat 2 

# weights:  507
initial  value 132.862548 
iter  10 value 116.450581
iter  20 value 115.018542
iter  30 value 115.016314
iter  40 value 115.012091
iter  50 value 114.917756
iter  60 value 114.916503
final  value 114.915918 
converged
Fitting Repeat 3 

# weights:  507
initial  value 127.460054 
iter  10 value 117.896524
iter  20 value 117.680141
iter  30 value 107.033905
iter  40 value 107.011178
iter  50 value 107.010089
iter  60 value 106.909547
iter  70 value 106.757151
iter  80 value 106.648401
iter  90 value 106.624525
iter 100 value 106.344855
final  value 106.344855 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.918906 
iter  10 value 115.257430
iter  20 value 114.919427
iter  30 value 110.151285
iter  40 value 109.187871
iter  50 value 108.999415
iter  60 value 103.376774
iter  70 value 102.368579
iter  80 value 102.329875
iter  90 value 102.155074
iter 100 value 102.154079
final  value 102.154079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.600229 
iter  10 value 117.748898
iter  20 value 117.731015
final  value 117.731009 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Jun 18 19:44:04 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 
 18.817   0.429  74.725