##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* 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 Sonoma 14.8.3
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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
FSmethod      19.130  0.955  20.902
corr_plot     19.023  0.924  20.673
var_imp       18.445  1.012  20.586
pred_ensembel  6.531  0.141   6.255
enrichfindP    0.205  0.043  11.471
* 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-3.23-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/4.6-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** 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 Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 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 102.544684 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.908490 
final  value 93.671508 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.826972 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.910276 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.234455 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.918155 
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.657888 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.839144 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.775911 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.079857 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.714936 
iter  10 value 92.374989
iter  20 value 92.322825
iter  30 value 92.322677
iter  30 value 92.322677
iter  30 value 92.322677
final  value 92.322677 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.446494 
final  value 94.043243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.158061 
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.607235 
iter  10 value 91.038674
iter  20 value 83.011059
iter  30 value 82.934341
final  value 82.934232 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.188941 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.649003 
iter  10 value 94.056933
iter  20 value 93.204179
iter  30 value 86.068704
iter  40 value 85.699133
iter  50 value 84.033548
iter  60 value 81.520041
iter  70 value 81.310646
iter  80 value 80.918241
iter  90 value 80.363529
iter 100 value 80.356120
final  value 80.356120 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.498579 
iter  10 value 91.676530
iter  20 value 82.229116
iter  30 value 81.970991
iter  40 value 81.913540
iter  50 value 81.277677
iter  60 value 81.034059
iter  70 value 81.032808
iter  80 value 81.029818
iter  90 value 81.027260
iter 100 value 80.906267
final  value 80.906267 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.268542 
iter  10 value 93.960055
iter  20 value 91.824426
iter  30 value 89.801958
iter  40 value 82.597571
iter  50 value 81.188726
iter  60 value 81.012667
iter  70 value 80.941721
iter  80 value 80.896674
iter  90 value 80.875433
iter 100 value 80.865778
final  value 80.865778 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.009581 
iter  10 value 94.059964
iter  20 value 93.428054
iter  30 value 85.643038
iter  40 value 81.450965
iter  50 value 80.515918
iter  60 value 79.180017
iter  70 value 78.914047
iter  80 value 78.679970
iter  90 value 78.087122
iter 100 value 78.032019
final  value 78.032019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.123588 
iter  10 value 93.851917
iter  20 value 83.978364
iter  30 value 82.347010
iter  40 value 81.233173
iter  50 value 81.059001
iter  60 value 80.911198
iter  70 value 80.874694
final  value 80.864923 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.688308 
iter  10 value 94.062133
iter  20 value 90.110591
iter  30 value 82.866132
iter  40 value 82.101423
iter  50 value 80.940827
iter  60 value 79.632898
iter  70 value 78.269857
iter  80 value 77.850476
iter  90 value 77.284818
iter 100 value 76.494891
final  value 76.494891 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.719896 
iter  10 value 93.963406
iter  20 value 87.141451
iter  30 value 83.507782
iter  40 value 81.086792
iter  50 value 78.090509
iter  60 value 77.138938
iter  70 value 76.978935
iter  80 value 76.666223
iter  90 value 76.346734
iter 100 value 76.117392
final  value 76.117392 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.908503 
iter  10 value 94.035974
iter  20 value 86.720824
iter  30 value 82.241268
iter  40 value 81.114087
iter  50 value 80.924762
iter  60 value 80.823412
iter  70 value 80.634119
iter  80 value 80.585064
iter  90 value 80.428337
iter 100 value 79.851064
final  value 79.851064 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.938057 
iter  10 value 94.333372
iter  20 value 94.056884
iter  30 value 93.968186
iter  40 value 93.242066
iter  50 value 85.929735
iter  60 value 83.688656
iter  70 value 80.081162
iter  80 value 78.923520
iter  90 value 78.820616
iter 100 value 78.761591
final  value 78.761591 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.362379 
iter  10 value 88.624953
iter  20 value 85.218109
iter  30 value 82.989362
iter  40 value 80.306154
iter  50 value 79.294939
iter  60 value 78.464901
iter  70 value 78.252034
iter  80 value 78.087817
iter  90 value 77.937782
iter 100 value 77.819010
final  value 77.819010 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.047261 
iter  10 value 94.038558
iter  20 value 92.071529
iter  30 value 88.671315
iter  40 value 85.684675
iter  50 value 81.607232
iter  60 value 78.658416
iter  70 value 77.494944
iter  80 value 76.670409
iter  90 value 76.587742
iter 100 value 76.455074
final  value 76.455074 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.074276 
iter  10 value 94.138376
iter  20 value 91.745745
iter  30 value 81.552684
iter  40 value 81.030258
iter  50 value 80.326989
iter  60 value 78.693429
iter  70 value 78.127007
iter  80 value 77.947599
iter  90 value 77.741266
iter 100 value 77.638099
final  value 77.638099 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.350865 
iter  10 value 93.930269
iter  20 value 83.757448
iter  30 value 83.396795
iter  40 value 83.044160
iter  50 value 82.880603
iter  60 value 81.378545
iter  70 value 79.757264
iter  80 value 78.886256
iter  90 value 77.672704
iter 100 value 77.339214
final  value 77.339214 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.673530 
iter  10 value 90.493312
iter  20 value 83.902558
iter  30 value 81.470797
iter  40 value 80.684128
iter  50 value 80.225273
iter  60 value 79.227769
iter  70 value 79.121205
iter  80 value 78.407710
iter  90 value 77.659659
iter 100 value 77.209343
final  value 77.209343 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.041979 
iter  10 value 89.931758
iter  20 value 89.209610
iter  30 value 86.390864
iter  40 value 79.442150
iter  50 value 78.659230
iter  60 value 78.109883
iter  70 value 77.316230
iter  80 value 76.591818
iter  90 value 76.319146
iter 100 value 76.273463
final  value 76.273463 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.824306 
final  value 94.054407 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.418737 
iter  10 value 94.054264
iter  20 value 93.953547
iter  30 value 89.893131
iter  40 value 89.863046
final  value 89.863025 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.051628 
final  value 94.054543 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.317364 
final  value 94.054569 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.640414 
iter  10 value 94.054655
iter  20 value 94.050351
iter  30 value 93.968163
iter  40 value 85.887551
iter  50 value 85.833329
iter  60 value 85.595858
iter  70 value 85.286007
iter  80 value 85.252660
iter  90 value 85.170740
iter 100 value 85.101102
final  value 85.101102 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.707191 
iter  10 value 94.058220
iter  20 value 94.053094
iter  30 value 93.308954
iter  40 value 80.889660
iter  50 value 80.808908
iter  60 value 80.205043
iter  70 value 79.462975
iter  80 value 78.971247
iter  90 value 78.789183
iter 100 value 78.788106
final  value 78.788106 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.091510 
iter  10 value 94.048229
iter  20 value 94.045403
iter  30 value 94.043328
final  value 94.043318 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.574295 
iter  10 value 94.058353
iter  20 value 94.053491
iter  30 value 85.600693
iter  40 value 85.406866
final  value 85.406842 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.854783 
iter  10 value 94.059777
iter  20 value 93.902652
iter  30 value 85.981451
iter  40 value 85.978924
iter  50 value 80.790415
iter  60 value 80.636875
iter  70 value 80.636514
iter  80 value 80.636409
final  value 80.636369 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.438039 
iter  10 value 94.081764
iter  20 value 94.033415
iter  30 value 91.969724
iter  40 value 91.910958
iter  50 value 90.328096
iter  60 value 90.049352
iter  70 value 88.781588
iter  80 value 88.740102
iter  90 value 88.736818
iter 100 value 88.389326
final  value 88.389326 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.416532 
iter  10 value 93.824573
iter  20 value 93.819291
iter  30 value 92.981914
iter  40 value 92.519165
iter  50 value 92.518005
iter  60 value 90.796594
iter  70 value 90.656769
iter  80 value 90.640676
iter  90 value 90.638368
iter 100 value 90.637349
final  value 90.637349 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.886952 
iter  10 value 94.050818
iter  20 value 85.839117
iter  30 value 82.369697
iter  40 value 82.256091
iter  50 value 81.874897
iter  60 value 81.166872
iter  70 value 76.976933
iter  80 value 76.659781
iter  90 value 76.427608
iter 100 value 76.269257
final  value 76.269257 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.483081 
iter  10 value 90.039585
iter  20 value 87.345797
iter  30 value 84.763793
iter  40 value 84.701709
iter  50 value 84.671056
iter  60 value 84.669541
final  value 84.668326 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.634570 
iter  10 value 94.061204
iter  20 value 94.049620
iter  30 value 91.492991
iter  40 value 88.744021
iter  50 value 88.704652
iter  60 value 88.675035
iter  70 value 88.673647
iter  80 value 88.629314
iter  90 value 88.439867
iter 100 value 86.567411
final  value 86.567411 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.675533 
iter  10 value 92.166746
iter  20 value 92.162974
iter  30 value 90.421170
iter  40 value 88.893818
iter  50 value 88.890128
final  value 88.889938 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.703208 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.819261 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.692472 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.496273 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.921455 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.573699 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.790835 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.394311 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.085565 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.918245 
iter  10 value 94.453678
final  value 94.453333 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.233277 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.823506 
iter  10 value 94.440765
iter  20 value 94.358725
iter  30 value 94.356343
final  value 94.356334 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.801797 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.434593 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.834550 
iter  10 value 93.592908
final  value 93.567525 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.882313 
iter  10 value 94.432445
iter  20 value 93.395981
iter  30 value 88.100304
iter  40 value 87.721120
iter  50 value 87.044355
iter  60 value 85.862593
iter  70 value 85.180981
iter  80 value 84.651849
iter  90 value 84.427756
final  value 84.426207 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.615335 
iter  10 value 93.893131
iter  20 value 93.772370
iter  30 value 93.751648
iter  40 value 83.787304
iter  50 value 83.360797
iter  60 value 83.038523
iter  70 value 82.697517
iter  80 value 82.614616
iter  90 value 82.575839
iter 100 value 82.551153
final  value 82.551153 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.840318 
iter  10 value 94.483602
iter  20 value 88.805166
iter  30 value 85.605670
iter  40 value 83.992673
iter  50 value 83.043309
iter  60 value 83.031248
iter  70 value 83.028492
final  value 83.028297 
converged
Fitting Repeat 4 

# weights:  103
initial  value 126.199903 
iter  10 value 94.004964
iter  20 value 86.515758
iter  30 value 83.467010
iter  40 value 83.264073
iter  50 value 83.073854
iter  60 value 83.038214
iter  70 value 82.934828
final  value 82.933889 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.296210 
iter  10 value 94.355789
iter  20 value 87.291969
iter  30 value 87.020466
iter  40 value 84.669683
iter  50 value 83.115093
iter  60 value 83.028342
final  value 83.028297 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.039816 
iter  10 value 94.616263
iter  20 value 86.418604
iter  30 value 85.871396
iter  40 value 83.390133
iter  50 value 82.976841
iter  60 value 82.645299
iter  70 value 82.595778
iter  80 value 82.542783
iter  90 value 82.342944
iter 100 value 82.158300
final  value 82.158300 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.312333 
iter  10 value 94.370867
iter  20 value 84.582007
iter  30 value 83.747830
iter  40 value 83.105760
iter  50 value 82.799616
iter  60 value 82.735021
iter  70 value 82.731734
iter  80 value 82.471741
iter  90 value 81.592455
iter 100 value 81.360477
final  value 81.360477 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.811592 
iter  10 value 88.773393
iter  20 value 86.134037
iter  30 value 85.642322
iter  40 value 82.884964
iter  50 value 82.394827
iter  60 value 81.761593
iter  70 value 81.134932
iter  80 value 80.885039
iter  90 value 80.687694
iter 100 value 80.627029
final  value 80.627029 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.317217 
iter  10 value 94.466229
iter  20 value 88.382794
iter  30 value 84.228237
iter  40 value 83.154919
iter  50 value 82.627935
iter  60 value 82.463601
iter  70 value 82.054772
iter  80 value 81.626465
iter  90 value 81.014276
iter 100 value 80.826498
final  value 80.826498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.352824 
iter  10 value 95.083495
iter  20 value 87.612734
iter  30 value 86.946158
iter  40 value 86.634264
iter  50 value 85.704504
iter  60 value 82.867983
iter  70 value 82.581335
iter  80 value 82.056952
iter  90 value 81.436916
iter 100 value 81.267649
final  value 81.267649 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.899332 
iter  10 value 91.927320
iter  20 value 83.659228
iter  30 value 82.166631
iter  40 value 81.548679
iter  50 value 81.066442
iter  60 value 80.840560
iter  70 value 80.778486
iter  80 value 80.729002
iter  90 value 80.656387
iter 100 value 80.647400
final  value 80.647400 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.813903 
iter  10 value 94.784267
iter  20 value 84.406505
iter  30 value 83.739419
iter  40 value 83.167836
iter  50 value 82.925731
iter  60 value 82.416860
iter  70 value 81.203242
iter  80 value 80.768669
iter  90 value 80.666584
iter 100 value 80.623878
final  value 80.623878 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.759636 
iter  10 value 94.521787
iter  20 value 93.206081
iter  30 value 91.478713
iter  40 value 88.469976
iter  50 value 86.849064
iter  60 value 84.110940
iter  70 value 82.977930
iter  80 value 82.808563
iter  90 value 81.479527
iter 100 value 81.169599
final  value 81.169599 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.171056 
iter  10 value 94.623997
iter  20 value 93.504375
iter  30 value 89.190219
iter  40 value 82.858689
iter  50 value 81.740572
iter  60 value 81.270071
iter  70 value 80.753503
iter  80 value 80.685432
iter  90 value 80.519900
iter 100 value 80.371883
final  value 80.371883 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.794061 
iter  10 value 97.538376
iter  20 value 94.911909
iter  30 value 90.790322
iter  40 value 88.717829
iter  50 value 86.273678
iter  60 value 84.643936
iter  70 value 83.101546
iter  80 value 81.837464
iter  90 value 81.274118
iter 100 value 81.057892
final  value 81.057892 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 117.459582 
final  value 94.485700 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.842622 
final  value 94.485829 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.294890 
final  value 94.485895 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.656117 
final  value 94.486056 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.318255 
iter  10 value 87.820867
iter  20 value 85.955477
iter  30 value 85.954677
iter  40 value 84.658372
iter  50 value 84.658154
iter  60 value 84.657363
final  value 84.657180 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.680685 
iter  10 value 94.488859
iter  20 value 94.396739
iter  30 value 86.009833
iter  40 value 85.965144
iter  50 value 85.960755
iter  60 value 85.324928
iter  70 value 85.268244
iter  80 value 85.237330
iter  90 value 85.113389
iter 100 value 85.112914
final  value 85.112914 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.356787 
iter  10 value 94.472067
iter  20 value 94.376824
iter  30 value 93.152475
iter  40 value 92.162574
iter  50 value 92.151776
iter  60 value 92.129563
final  value 92.129530 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.681686 
iter  10 value 94.472014
iter  20 value 94.469707
iter  30 value 94.441124
iter  40 value 85.169968
iter  40 value 85.169968
final  value 85.169963 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.590277 
iter  10 value 93.546032
iter  20 value 91.648476
iter  30 value 83.847313
iter  40 value 82.632019
iter  50 value 82.629131
iter  60 value 82.515313
iter  70 value 82.504622
iter  80 value 82.503151
iter  80 value 82.503151
final  value 82.503151 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.499257 
final  value 94.488885 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.217112 
iter  10 value 86.804159
iter  20 value 85.194523
iter  30 value 85.174509
iter  40 value 84.691501
iter  50 value 82.394685
iter  60 value 81.054570
iter  70 value 80.891621
iter  80 value 80.864626
iter  90 value 80.630323
iter 100 value 80.577662
final  value 80.577662 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.825970 
iter  10 value 94.492379
iter  20 value 94.096914
iter  30 value 89.955401
iter  40 value 89.635566
iter  50 value 89.272373
iter  60 value 89.050608
iter  70 value 88.947833
iter  80 value 88.946239
iter  90 value 84.819146
iter 100 value 84.567076
final  value 84.567076 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.649278 
iter  10 value 93.575423
iter  20 value 86.683767
iter  30 value 85.167901
iter  40 value 82.018928
iter  50 value 81.968044
iter  60 value 81.967354
iter  70 value 81.967128
iter  80 value 81.946203
iter  90 value 81.822516
iter 100 value 81.214159
final  value 81.214159 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.897509 
iter  10 value 94.491619
iter  20 value 94.435908
iter  30 value 87.291500
iter  40 value 82.700691
final  value 82.626991 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.632337 
iter  10 value 94.491275
iter  20 value 94.475257
iter  30 value 94.470774
iter  40 value 84.516906
iter  50 value 82.079438
iter  60 value 81.961897
final  value 81.961895 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.468055 
iter  10 value 89.998104
iter  20 value 89.517508
final  value 89.514642 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.176632 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.524703 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.533542 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.368223 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.610638 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.707189 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.389841 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.387909 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.180072 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.823993 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.518497 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.687735 
iter  10 value 94.338744
iter  10 value 94.338744
iter  10 value 94.338744
final  value 94.338744 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.803869 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.993135 
iter  10 value 94.025798
iter  20 value 94.015484
final  value 94.015335 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.129972 
iter  10 value 94.479505
iter  20 value 91.810642
iter  30 value 90.385613
iter  40 value 90.193376
iter  50 value 89.888528
iter  60 value 88.852791
iter  70 value 86.265343
iter  80 value 85.694024
iter  90 value 83.868798
iter 100 value 83.559071
final  value 83.559071 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.160613 
iter  10 value 94.490003
iter  20 value 94.252569
iter  30 value 94.222076
iter  40 value 94.168232
iter  50 value 91.673940
iter  60 value 91.103008
iter  70 value 91.004881
iter  80 value 88.227724
iter  90 value 86.733569
iter 100 value 86.197076
final  value 86.197076 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.430495 
iter  10 value 93.519938
iter  20 value 88.214196
iter  30 value 88.078130
iter  40 value 87.474052
iter  50 value 87.156474
iter  60 value 86.340920
iter  70 value 85.448461
iter  80 value 85.392941
final  value 85.392287 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.200178 
iter  10 value 94.110020
iter  20 value 87.651484
iter  30 value 86.394456
iter  40 value 86.205870
iter  50 value 85.993152
iter  60 value 85.977005
final  value 85.977003 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.169508 
iter  10 value 94.487012
iter  20 value 89.228502
iter  30 value 87.584026
iter  40 value 85.863399
iter  50 value 85.602629
iter  60 value 85.549660
final  value 85.548024 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.428607 
iter  10 value 94.184485
iter  20 value 87.639571
iter  30 value 87.322396
iter  40 value 86.961483
iter  50 value 85.409779
iter  60 value 84.275708
iter  70 value 83.698393
iter  80 value 83.492939
iter  90 value 83.278547
iter 100 value 82.651503
final  value 82.651503 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.503906 
iter  10 value 94.006777
iter  20 value 86.952720
iter  30 value 86.177180
iter  40 value 84.809524
iter  50 value 84.022706
iter  60 value 83.583267
iter  70 value 82.973907
iter  80 value 82.942450
iter  90 value 82.702109
iter 100 value 82.552733
final  value 82.552733 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 122.975541 
iter  10 value 94.479498
iter  20 value 94.190577
iter  30 value 87.894289
iter  40 value 87.642503
iter  50 value 87.578127
iter  60 value 85.924878
iter  70 value 85.595836
iter  80 value 85.526835
iter  90 value 85.487732
iter 100 value 84.843712
final  value 84.843712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.347417 
iter  10 value 94.470501
iter  20 value 94.183216
iter  30 value 93.742346
iter  40 value 86.889365
iter  50 value 86.317820
iter  60 value 85.951981
iter  70 value 85.517852
iter  80 value 83.756444
iter  90 value 83.523611
iter 100 value 83.370017
final  value 83.370017 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.509981 
iter  10 value 94.569133
iter  20 value 87.881125
iter  30 value 85.501326
iter  40 value 83.820112
iter  50 value 83.748799
iter  60 value 83.683465
iter  70 value 83.416458
iter  80 value 83.012563
iter  90 value 82.600676
iter 100 value 82.413564
final  value 82.413564 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.115164 
iter  10 value 93.953954
iter  20 value 90.054211
iter  30 value 87.881651
iter  40 value 86.121192
iter  50 value 84.931707
iter  60 value 84.119838
iter  70 value 83.792835
iter  80 value 83.346692
iter  90 value 82.834962
iter 100 value 82.283500
final  value 82.283500 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.470889 
iter  10 value 94.847237
iter  20 value 91.149115
iter  30 value 87.297036
iter  40 value 86.423074
iter  50 value 85.873985
iter  60 value 85.671015
iter  70 value 85.622660
iter  80 value 84.948409
iter  90 value 83.892363
iter 100 value 83.430493
final  value 83.430493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.033757 
iter  10 value 93.686971
iter  20 value 90.745826
iter  30 value 87.175118
iter  40 value 86.033183
iter  50 value 85.103381
iter  60 value 84.518341
iter  70 value 83.958500
iter  80 value 83.473338
iter  90 value 82.648453
iter 100 value 82.470231
final  value 82.470231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 144.733708 
iter  10 value 94.705462
iter  20 value 88.183497
iter  30 value 86.902820
iter  40 value 85.784980
iter  50 value 84.769611
iter  60 value 84.054494
iter  70 value 83.357582
iter  80 value 83.113001
iter  90 value 82.878973
iter 100 value 82.698097
final  value 82.698097 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.590757 
iter  10 value 94.268531
iter  20 value 90.712792
iter  30 value 86.426342
iter  40 value 84.684849
iter  50 value 84.046875
iter  60 value 83.340838
iter  70 value 82.579901
iter  80 value 81.819020
iter  90 value 81.571699
iter 100 value 81.454434
final  value 81.454434 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.533171 
final  value 94.486034 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.148584 
final  value 94.485877 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.710743 
final  value 94.486010 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.056843 
final  value 94.485814 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.895659 
final  value 94.485751 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.281910 
iter  10 value 93.997943
iter  20 value 93.981182
iter  30 value 93.976715
iter  40 value 92.843836
iter  50 value 89.611271
iter  60 value 86.432668
iter  70 value 86.426416
iter  80 value 86.426206
iter  90 value 86.372355
iter 100 value 85.076311
final  value 85.076311 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.223582 
iter  10 value 94.489071
iter  20 value 94.432865
iter  30 value 89.268250
iter  40 value 89.252002
iter  50 value 89.249178
iter  60 value 89.017165
iter  70 value 87.541782
iter  80 value 87.440319
iter  90 value 87.022448
iter 100 value 86.959732
final  value 86.959732 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.492431 
iter  10 value 94.488788
iter  20 value 94.393735
iter  30 value 93.813178
iter  40 value 93.297308
iter  50 value 93.295431
iter  60 value 93.294814
iter  70 value 90.505766
iter  80 value 86.574735
iter  90 value 86.397977
iter 100 value 86.397437
final  value 86.397437 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.510425 
iter  10 value 94.036148
iter  20 value 94.030817
iter  30 value 94.023938
iter  40 value 93.977339
iter  50 value 93.976518
iter  60 value 93.833065
iter  70 value 93.590465
iter  80 value 89.243515
iter  90 value 85.084657
iter 100 value 84.823228
final  value 84.823228 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.463756 
iter  10 value 94.489591
iter  20 value 94.484765
iter  30 value 94.044397
iter  40 value 90.993027
iter  50 value 87.366365
iter  60 value 87.136372
iter  70 value 87.041249
final  value 87.041207 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.058574 
iter  10 value 94.475669
iter  20 value 94.467790
final  value 94.467739 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.421192 
iter  10 value 94.492284
iter  20 value 93.627687
iter  30 value 87.100791
iter  40 value 87.074149
iter  50 value 87.073752
final  value 87.073548 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.426724 
iter  10 value 94.034754
iter  20 value 94.020832
iter  30 value 92.435667
iter  40 value 88.569910
iter  50 value 85.794651
iter  60 value 85.530017
final  value 85.526953 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.369197 
iter  10 value 94.492110
iter  20 value 94.443122
iter  30 value 93.228997
iter  40 value 93.080462
iter  50 value 85.852453
iter  60 value 84.679332
final  value 84.679330 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.983774 
iter  10 value 94.491672
iter  20 value 94.150977
iter  30 value 90.680683
iter  40 value 90.679195
iter  50 value 90.678971
iter  60 value 87.328278
iter  70 value 87.327871
iter  80 value 87.327292
iter  90 value 86.142097
iter 100 value 85.766353
final  value 85.766353 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.095012 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.226913 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.284064 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.216663 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.977038 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.961911 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.165362 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.892532 
iter  10 value 93.191653
iter  20 value 85.791909
iter  30 value 85.785812
final  value 85.785715 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.221404 
iter  10 value 93.937873
final  value 93.937870 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.835248 
iter  10 value 92.182859
iter  10 value 92.182859
iter  10 value 92.182859
final  value 92.182859 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.512514 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.054778 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.560593 
iter  10 value 92.013790
iter  20 value 90.779618
iter  30 value 89.828045
iter  40 value 89.044759
iter  50 value 89.043879
final  value 89.043872 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.273285 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.364921 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.995103 
iter  10 value 94.051511
iter  20 value 93.871564
iter  30 value 93.841187
iter  40 value 91.669794
iter  50 value 87.794480
iter  60 value 87.461528
iter  70 value 85.061127
iter  80 value 82.882110
iter  90 value 82.086473
iter 100 value 81.876591
final  value 81.876591 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.682409 
iter  10 value 94.315709
iter  20 value 94.006925
iter  30 value 93.714968
iter  40 value 93.684528
iter  50 value 93.655637
iter  60 value 87.074364
iter  70 value 82.561661
iter  80 value 82.520809
iter  90 value 82.003870
iter 100 value 81.943940
final  value 81.943940 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.067738 
iter  10 value 94.051827
iter  20 value 93.092622
iter  30 value 89.840185
iter  40 value 85.381461
iter  50 value 85.090902
iter  60 value 84.934649
iter  70 value 82.573450
iter  80 value 82.278973
iter  90 value 82.254381
final  value 82.251774 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.297752 
iter  10 value 94.047906
iter  20 value 85.980411
iter  30 value 83.145109
iter  40 value 82.393928
iter  50 value 82.344621
iter  60 value 82.026418
iter  70 value 81.853525
iter  80 value 81.851525
final  value 81.851522 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.980124 
iter  10 value 93.987069
iter  20 value 83.355118
iter  30 value 82.449662
iter  40 value 82.042489
iter  50 value 81.866192
iter  60 value 81.851539
final  value 81.851522 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.307105 
iter  10 value 94.025622
iter  20 value 89.437193
iter  30 value 80.401590
iter  40 value 80.043614
iter  50 value 79.401972
iter  60 value 78.823964
iter  70 value 78.722164
iter  80 value 78.516179
iter  90 value 77.895424
iter 100 value 77.382084
final  value 77.382084 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.621525 
iter  10 value 93.908689
iter  20 value 85.756791
iter  30 value 84.777174
iter  40 value 83.225879
iter  50 value 81.044905
iter  60 value 79.794664
iter  70 value 79.411807
iter  80 value 78.704044
iter  90 value 78.378158
iter 100 value 77.945831
final  value 77.945831 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.191843 
iter  10 value 94.127854
iter  20 value 91.988338
iter  30 value 87.454783
iter  40 value 86.592281
iter  50 value 82.206647
iter  60 value 80.460833
iter  70 value 79.699163
iter  80 value 79.662687
iter  90 value 79.634259
iter 100 value 79.523165
final  value 79.523165 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.153138 
iter  10 value 93.976727
iter  20 value 85.537688
iter  30 value 82.891115
iter  40 value 82.571914
iter  50 value 82.515984
iter  60 value 82.326991
iter  70 value 82.100206
iter  80 value 81.822692
iter  90 value 81.071544
iter 100 value 80.364513
final  value 80.364513 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.246927 
iter  10 value 94.065396
iter  20 value 92.634921
iter  30 value 85.009525
iter  40 value 84.639855
iter  50 value 83.294420
iter  60 value 80.594171
iter  70 value 79.198973
iter  80 value 77.923268
iter  90 value 77.650402
iter 100 value 77.629940
final  value 77.629940 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.979561 
iter  10 value 94.038835
iter  20 value 92.502895
iter  30 value 86.625512
iter  40 value 82.286732
iter  50 value 82.112457
iter  60 value 81.965481
iter  70 value 81.257118
iter  80 value 80.045516
iter  90 value 79.085073
iter 100 value 78.098908
final  value 78.098908 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.534519 
iter  10 value 94.017118
iter  20 value 88.418216
iter  30 value 85.388484
iter  40 value 84.665563
iter  50 value 83.851134
iter  60 value 80.641585
iter  70 value 77.970960
iter  80 value 77.662033
iter  90 value 77.383009
iter 100 value 77.199068
final  value 77.199068 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.128203 
iter  10 value 89.413732
iter  20 value 84.068679
iter  30 value 82.452236
iter  40 value 81.074245
iter  50 value 80.008857
iter  60 value 79.261815
iter  70 value 79.055499
iter  80 value 78.850769
iter  90 value 78.802262
iter 100 value 78.737663
final  value 78.737663 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.693296 
iter  10 value 89.925691
iter  20 value 82.161292
iter  30 value 80.583486
iter  40 value 79.553761
iter  50 value 79.129812
iter  60 value 78.900591
iter  70 value 78.764855
iter  80 value 78.075482
iter  90 value 77.815957
iter 100 value 77.662773
final  value 77.662773 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.265106 
iter  10 value 94.179388
iter  20 value 87.292994
iter  30 value 83.090308
iter  40 value 82.884258
iter  50 value 82.792930
iter  60 value 81.622457
iter  70 value 81.051623
iter  80 value 80.742915
iter  90 value 80.444564
iter 100 value 79.559156
final  value 79.559156 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.922116 
final  value 94.054480 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.146980 
final  value 94.054771 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.447318 
final  value 94.054757 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.724386 
final  value 94.034683 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.100450 
iter  10 value 94.054517
iter  20 value 94.009614
iter  30 value 87.404270
iter  40 value 86.993856
iter  50 value 86.643105
iter  60 value 86.631257
iter  70 value 86.622689
final  value 86.621885 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.749595 
iter  10 value 94.037764
iter  20 value 93.996488
iter  30 value 92.679471
iter  40 value 87.010497
iter  50 value 83.700476
iter  60 value 83.540227
iter  70 value 83.538732
iter  80 value 83.481132
iter  90 value 83.137549
iter 100 value 82.774383
final  value 82.774383 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.651509 
iter  10 value 94.038174
iter  20 value 94.033825
iter  30 value 90.329491
final  value 90.176055 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.512625 
iter  10 value 94.057385
iter  20 value 94.053062
final  value 94.033113 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.102252 
iter  10 value 94.056390
final  value 94.052906 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.340106 
iter  10 value 94.053859
final  value 94.052923 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.006161 
iter  10 value 94.060618
iter  20 value 93.638095
iter  30 value 84.626106
iter  40 value 81.557372
iter  50 value 81.231697
iter  60 value 81.125358
iter  70 value 80.506553
iter  80 value 80.433413
iter  90 value 80.428363
iter 100 value 80.427693
final  value 80.427693 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 93.119504 
iter  10 value 83.753442
iter  20 value 83.590605
iter  30 value 83.584467
iter  40 value 83.354042
iter  50 value 82.850483
iter  60 value 80.517737
iter  70 value 80.353864
final  value 80.353168 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.350018 
iter  10 value 93.900006
iter  20 value 93.771463
iter  30 value 93.763887
iter  40 value 92.112816
iter  50 value 86.784800
iter  60 value 85.416008
iter  70 value 85.412816
iter  80 value 84.696524
iter  90 value 80.812193
iter 100 value 78.094926
final  value 78.094926 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.091572 
iter  10 value 94.040941
iter  20 value 94.034554
iter  30 value 82.444455
iter  40 value 82.348989
iter  50 value 82.327459
final  value 82.327394 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.414308 
iter  10 value 94.041672
iter  20 value 94.021205
iter  30 value 93.942144
iter  40 value 93.758407
iter  50 value 85.200069
iter  60 value 81.448773
iter  70 value 81.059674
iter  80 value 80.970071
iter  90 value 80.231076
iter 100 value 77.871235
final  value 77.871235 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.504644 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.143743 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.581875 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.658378 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.222300 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.186584 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.525495 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.119902 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.523576 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.818636 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.021465 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.242826 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.964177 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.265345 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.520541 
iter  10 value 94.033646
iter  20 value 94.024582
final  value 94.024564 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.492757 
iter  10 value 94.092266
iter  20 value 93.275249
iter  30 value 90.438186
iter  40 value 89.421123
iter  50 value 88.695209
iter  60 value 83.645611
iter  70 value 83.096596
iter  80 value 82.768000
iter  90 value 82.652143
iter 100 value 82.596526
final  value 82.596526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.942416 
iter  10 value 94.268721
iter  20 value 92.755714
iter  30 value 90.151606
iter  40 value 88.816761
iter  50 value 86.395002
iter  60 value 85.852541
iter  70 value 85.789036
iter  80 value 85.756817
final  value 85.751111 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.195043 
iter  10 value 94.471800
iter  20 value 93.997913
iter  30 value 93.921590
iter  40 value 88.378053
iter  50 value 88.059684
iter  60 value 86.262795
iter  70 value 85.956056
iter  80 value 85.812670
iter  90 value 85.756690
final  value 85.751110 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.450976 
iter  10 value 93.821042
iter  20 value 86.289171
iter  30 value 84.297485
iter  40 value 83.798776
iter  50 value 82.780415
iter  60 value 82.699353
iter  70 value 82.594059
final  value 82.592470 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.779183 
iter  10 value 93.625511
iter  20 value 87.802153
iter  30 value 86.418523
iter  40 value 86.252765
iter  50 value 86.245984
iter  60 value 86.237413
iter  70 value 85.959179
iter  80 value 85.919637
iter  90 value 85.797194
iter 100 value 85.751183
final  value 85.751183 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.303630 
iter  10 value 93.877128
iter  20 value 87.414558
iter  30 value 84.907328
iter  40 value 83.076222
iter  50 value 82.360078
iter  60 value 81.958574
iter  70 value 81.694898
iter  80 value 81.648246
iter  90 value 81.613772
iter 100 value 81.549217
final  value 81.549217 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.387978 
iter  10 value 93.340284
iter  20 value 90.901366
iter  30 value 86.302309
iter  40 value 85.628620
iter  50 value 84.246999
iter  60 value 83.973544
iter  70 value 83.845351
iter  80 value 82.778794
iter  90 value 82.121438
iter 100 value 81.656483
final  value 81.656483 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.956130 
iter  10 value 94.387168
iter  20 value 94.127641
iter  30 value 90.768646
iter  40 value 86.693038
iter  50 value 85.377216
iter  60 value 82.818787
iter  70 value 82.633190
iter  80 value 82.275999
iter  90 value 81.990110
iter 100 value 81.548630
final  value 81.548630 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.638169 
iter  10 value 94.127658
iter  20 value 88.696747
iter  30 value 87.572529
iter  40 value 85.728051
iter  50 value 84.341321
iter  60 value 82.969253
iter  70 value 82.269743
iter  80 value 81.748952
iter  90 value 81.676924
iter 100 value 81.671971
final  value 81.671971 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.229944 
iter  10 value 94.049704
iter  20 value 87.911101
iter  30 value 85.270457
iter  40 value 84.558469
iter  50 value 81.913336
iter  60 value 81.584916
iter  70 value 81.525256
iter  80 value 81.483935
iter  90 value 81.460699
iter 100 value 81.419311
final  value 81.419311 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.893665 
iter  10 value 94.241752
iter  20 value 89.082405
iter  30 value 86.505347
iter  40 value 85.839430
iter  50 value 83.622473
iter  60 value 82.674482
iter  70 value 82.455802
iter  80 value 82.404548
iter  90 value 82.263150
iter 100 value 82.051466
final  value 82.051466 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.476414 
iter  10 value 94.561026
iter  20 value 94.134532
iter  30 value 92.336142
iter  40 value 85.953824
iter  50 value 82.894944
iter  60 value 81.958693
iter  70 value 81.740199
iter  80 value 81.702755
iter  90 value 81.623726
iter 100 value 81.489845
final  value 81.489845 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.260372 
iter  10 value 94.540400
iter  20 value 93.394367
iter  30 value 92.918155
iter  40 value 90.419139
iter  50 value 90.295128
iter  60 value 89.841885
iter  70 value 86.873110
iter  80 value 85.055102
iter  90 value 84.303388
iter 100 value 83.016502
final  value 83.016502 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.033915 
iter  10 value 95.515799
iter  20 value 94.540992
iter  30 value 93.468351
iter  40 value 90.472225
iter  50 value 87.377193
iter  60 value 83.577663
iter  70 value 82.220200
iter  80 value 81.762382
iter  90 value 81.518194
iter 100 value 81.309365
final  value 81.309365 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.058153 
iter  10 value 94.267274
iter  20 value 91.479856
iter  30 value 88.953690
iter  40 value 86.396834
iter  50 value 84.240066
iter  60 value 83.441397
iter  70 value 82.604644
iter  80 value 81.863273
iter  90 value 81.508610
iter 100 value 81.229092
final  value 81.229092 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.486458 
final  value 94.485870 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.150356 
iter  10 value 94.028377
iter  20 value 94.026916
final  value 94.026897 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.633690 
iter  10 value 94.486024
iter  20 value 94.477915
iter  30 value 92.985800
iter  40 value 92.977497
iter  50 value 92.895823
final  value 92.895502 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.769769 
final  value 94.486044 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.258926 
final  value 94.486049 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.448970 
iter  10 value 94.031417
iter  20 value 94.027746
iter  30 value 93.225670
iter  40 value 93.016840
iter  50 value 84.945722
iter  60 value 83.830333
iter  70 value 83.600546
iter  80 value 83.598137
final  value 83.598070 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.050140 
iter  10 value 94.031850
iter  20 value 94.027159
iter  30 value 93.923531
iter  40 value 93.782562
iter  50 value 87.661682
iter  60 value 87.602381
iter  70 value 87.413447
iter  80 value 87.326283
iter  90 value 87.319890
iter 100 value 87.292064
final  value 87.292064 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.920434 
final  value 94.489415 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.265193 
iter  10 value 94.488499
iter  20 value 88.196016
iter  30 value 86.894833
iter  40 value 86.863766
iter  50 value 86.858787
iter  60 value 86.282309
iter  70 value 84.863960
iter  80 value 81.210158
iter  90 value 80.720268
iter 100 value 80.326796
final  value 80.326796 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.190748 
iter  10 value 94.031973
iter  20 value 94.029865
iter  30 value 93.368581
iter  40 value 90.418520
iter  50 value 83.468506
iter  60 value 82.935136
iter  70 value 82.636033
iter  80 value 82.537827
iter  90 value 82.536106
iter 100 value 82.508100
final  value 82.508100 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.778766 
iter  10 value 94.492758
iter  20 value 94.463384
iter  30 value 93.021772
iter  40 value 92.867558
iter  50 value 92.684389
iter  60 value 92.679059
iter  70 value 92.677460
iter  80 value 90.368154
iter  90 value 85.735709
iter 100 value 84.884948
final  value 84.884948 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.672610 
iter  10 value 93.031825
iter  20 value 91.571406
iter  30 value 86.214076
iter  40 value 84.166714
iter  50 value 84.060103
iter  60 value 83.968639
final  value 83.863313 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.287996 
iter  10 value 94.492195
iter  20 value 93.825601
iter  30 value 88.763674
iter  40 value 88.428752
iter  50 value 88.428676
iter  60 value 87.533651
iter  70 value 86.831908
iter  80 value 86.796916
iter  90 value 85.362731
iter 100 value 82.657414
final  value 82.657414 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.758010 
iter  10 value 94.330957
iter  20 value 94.312233
iter  30 value 93.037874
iter  40 value 87.038552
iter  50 value 84.985536
iter  60 value 84.896815
iter  70 value 84.612362
iter  80 value 84.606273
iter  90 value 84.604523
final  value 84.603621 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.634375 
iter  10 value 94.034575
iter  20 value 89.833656
iter  30 value 87.090441
iter  40 value 86.356771
iter  50 value 85.579600
iter  60 value 85.155242
iter  70 value 83.553551
iter  80 value 83.546511
iter  90 value 83.109530
iter 100 value 82.841184
final  value 82.841184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 130.129182 
iter  10 value 117.102596
iter  20 value 116.995146
iter  30 value 107.095581
iter  40 value 104.938654
iter  50 value 104.698745
iter  60 value 104.670939
final  value 104.670932 
converged
Fitting Repeat 2 

# weights:  305
initial  value 127.291994 
iter  10 value 116.410974
iter  20 value 105.163633
iter  30 value 104.098159
iter  40 value 104.085965
iter  50 value 103.753368
iter  60 value 103.752891
final  value 103.750244 
converged
Fitting Repeat 3 

# weights:  305
initial  value 133.257473 
iter  10 value 117.895077
iter  20 value 117.890605
final  value 117.890584 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.806710 
iter  10 value 117.763031
iter  20 value 117.758690
iter  30 value 111.980920
iter  40 value 108.508206
iter  50 value 108.486481
iter  60 value 108.486211
iter  70 value 108.472493
iter  80 value 108.157720
iter  90 value 106.848287
iter 100 value 104.951922
final  value 104.951922 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 127.060562 
iter  10 value 117.894820
iter  20 value 117.890253
iter  30 value 117.572116
iter  40 value 117.511395
iter  50 value 107.257024
final  value 107.222975 
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 Mar  4 20:24:13 2026 
*********************************************** 
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 
 20.833   0.521  70.198