##############################################################################
##############################################################################
###
### 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 version 4.6.0 alpha (2026-04-08 r89818)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-04-22 00:16:48 UTC
* 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      17.219  0.097  17.423
corr_plot     17.183  0.102  17.375
var_imp       17.063  0.154  17.418
pred_ensembel  6.429  0.165   5.837
enrichfindP    0.202  0.040  10.289
* 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/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 version 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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 97.014906 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.469555 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.297445 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.783418 
final  value 94.323810 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.271172 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.950493 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.310473 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.762076 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.893220 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.094883 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.711044 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.496105 
iter  10 value 94.083971
final  value 94.083671 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.566811 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.618713 
iter  10 value 94.276413
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.231794 
iter  10 value 86.768798
iter  20 value 86.713190
final  value 86.713176 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.770317 
iter  10 value 94.407194
iter  20 value 91.737045
iter  30 value 91.560702
iter  40 value 85.495008
iter  50 value 82.958176
iter  60 value 82.447964
iter  70 value 82.021862
iter  80 value 81.723821
final  value 81.723748 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.364049 
iter  10 value 94.488840
iter  20 value 92.343041
iter  30 value 86.736918
iter  40 value 86.503166
iter  50 value 86.092832
iter  60 value 85.674400
iter  70 value 85.154636
iter  80 value 84.684332
iter  90 value 84.525787
final  value 84.525782 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.240109 
iter  10 value 94.501383
iter  20 value 94.198358
iter  30 value 87.622707
iter  40 value 87.170293
iter  50 value 87.056867
iter  60 value 84.128263
iter  70 value 83.933489
iter  80 value 83.904333
iter  90 value 83.851612
final  value 83.848849 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.298309 
iter  10 value 94.491420
iter  20 value 94.100069
iter  30 value 91.237026
iter  40 value 90.872365
iter  50 value 90.837874
iter  60 value 90.810320
iter  70 value 83.316957
iter  80 value 81.802814
iter  90 value 81.598403
final  value 81.577963 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.470019 
iter  10 value 95.019865
iter  20 value 94.471354
iter  30 value 89.762037
iter  40 value 84.074076
iter  50 value 82.973140
iter  60 value 82.143338
iter  70 value 81.716747
iter  80 value 81.644809
final  value 81.577962 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.164993 
iter  10 value 94.619197
iter  20 value 93.859558
iter  30 value 90.813589
iter  40 value 89.169097
iter  50 value 88.918922
iter  60 value 85.169192
iter  70 value 83.600930
iter  80 value 83.553740
iter  90 value 83.267099
iter 100 value 81.255995
final  value 81.255995 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.469387 
iter  10 value 94.593922
iter  20 value 94.292249
iter  30 value 91.331216
iter  40 value 89.183744
iter  50 value 86.281232
iter  60 value 82.846969
iter  70 value 81.643266
iter  80 value 81.270499
iter  90 value 80.959630
iter 100 value 80.474395
final  value 80.474395 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.653773 
iter  10 value 94.432910
iter  20 value 93.988913
iter  30 value 84.041713
iter  40 value 83.898236
iter  50 value 83.697920
iter  60 value 83.590981
iter  70 value 83.577355
iter  80 value 83.524955
iter  90 value 82.865375
iter 100 value 81.735189
final  value 81.735189 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.074779 
iter  10 value 94.505257
iter  20 value 94.237480
iter  30 value 94.123802
iter  40 value 85.069293
iter  50 value 84.867973
iter  60 value 84.204857
iter  70 value 83.859113
iter  80 value 83.802506
iter  90 value 83.656999
iter 100 value 83.529365
final  value 83.529365 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.065944 
iter  10 value 94.458980
iter  20 value 93.420262
iter  30 value 84.500256
iter  40 value 83.313127
iter  50 value 83.042975
iter  60 value 82.302850
iter  70 value 82.019113
iter  80 value 81.985344
iter  90 value 81.819059
iter 100 value 81.818421
final  value 81.818421 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.096622 
iter  10 value 94.080723
iter  20 value 85.727888
iter  30 value 84.851226
iter  40 value 84.336926
iter  50 value 83.663333
iter  60 value 81.663394
iter  70 value 80.656820
iter  80 value 79.872940
iter  90 value 79.488098
iter 100 value 79.423513
final  value 79.423513 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.718426 
iter  10 value 95.371245
iter  20 value 94.479435
iter  30 value 92.781976
iter  40 value 91.316994
iter  50 value 83.422041
iter  60 value 83.144904
iter  70 value 82.942814
iter  80 value 82.577177
iter  90 value 82.125769
iter 100 value 81.791592
final  value 81.791592 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.260920 
iter  10 value 94.581443
iter  20 value 93.433077
iter  30 value 89.547186
iter  40 value 84.131816
iter  50 value 83.340193
iter  60 value 82.951540
iter  70 value 82.493025
iter  80 value 81.621434
iter  90 value 81.241911
iter 100 value 80.777333
final  value 80.777333 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.618947 
iter  10 value 94.448452
iter  20 value 93.266388
iter  30 value 89.567979
iter  40 value 87.071537
iter  50 value 84.208048
iter  60 value 83.678227
iter  70 value 83.176758
iter  80 value 82.853803
iter  90 value 82.748886
iter 100 value 82.704912
final  value 82.704912 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.196851 
iter  10 value 94.923900
iter  20 value 93.727798
iter  30 value 85.113029
iter  40 value 84.192230
iter  50 value 83.738957
iter  60 value 83.146023
iter  70 value 81.361417
iter  80 value 81.091726
iter  90 value 80.937740
iter 100 value 80.587500
final  value 80.587500 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.714374 
iter  10 value 94.485889
iter  20 value 94.484041
iter  30 value 94.057691
final  value 94.057666 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.701675 
final  value 94.485908 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.673687 
final  value 94.485913 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.723134 
final  value 93.703280 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.619331 
final  value 94.485740 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.175444 
iter  10 value 94.488801
iter  20 value 94.350325
iter  30 value 92.712259
iter  40 value 83.173432
iter  50 value 82.675159
final  value 82.673705 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.042602 
iter  10 value 94.490313
iter  20 value 93.830980
iter  30 value 84.201249
iter  40 value 84.199820
iter  50 value 84.198612
final  value 84.198516 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.480107 
iter  10 value 92.094443
iter  20 value 92.093459
iter  30 value 92.093048
iter  40 value 92.090991
iter  50 value 84.593254
iter  60 value 82.935323
iter  70 value 82.076369
iter  80 value 82.072124
iter  80 value 82.072124
final  value 82.072124 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.944957 
iter  10 value 94.488893
iter  20 value 92.720925
iter  30 value 92.244175
iter  40 value 92.244016
iter  50 value 92.243744
final  value 92.243614 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.287460 
iter  10 value 87.041790
iter  20 value 83.535265
iter  30 value 82.934799
iter  40 value 82.921203
iter  50 value 82.920108
iter  60 value 82.914601
iter  70 value 82.901983
iter  80 value 82.901721
iter  90 value 82.901602
final  value 82.901586 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.999357 
iter  10 value 94.283417
iter  20 value 94.123250
iter  30 value 84.193636
iter  40 value 84.050444
iter  50 value 84.049053
iter  50 value 84.049053
final  value 84.049053 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.611863 
iter  10 value 94.486957
iter  20 value 93.204171
iter  30 value 85.981847
iter  40 value 84.092823
final  value 83.972313 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.535704 
iter  10 value 94.000179
iter  20 value 93.493788
iter  30 value 89.044351
iter  40 value 87.612205
iter  50 value 87.453017
iter  60 value 87.364739
iter  70 value 87.360879
iter  80 value 85.931080
iter  90 value 83.786642
iter 100 value 83.097840
final  value 83.097840 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.407751 
iter  10 value 94.283282
iter  20 value 94.273205
iter  30 value 93.472873
iter  40 value 86.621849
iter  50 value 85.354516
iter  50 value 85.354515
iter  50 value 85.354515
final  value 85.354515 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.579946 
iter  10 value 94.492245
iter  20 value 94.350160
iter  30 value 84.235109
iter  40 value 84.206104
iter  50 value 84.185812
iter  60 value 83.931213
iter  70 value 80.000118
iter  80 value 79.519001
iter  90 value 79.452552
iter 100 value 79.450015
final  value 79.450015 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.760269 
iter  10 value 94.185036
iter  20 value 94.088893
final  value 94.088890 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.036223 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.010376 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.706482 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.889073 
final  value 94.484137 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.108723 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.623147 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.966460 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.435309 
iter  10 value 87.875211
iter  20 value 87.592036
iter  30 value 85.979124
iter  40 value 85.783444
iter  50 value 85.782042
final  value 85.782038 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.703198 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.073308 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.119397 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.640920 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.046647 
iter  10 value 93.971215
iter  20 value 86.278350
iter  30 value 83.706503
iter  40 value 81.461055
iter  50 value 80.266982
iter  60 value 79.713912
iter  70 value 79.709731
iter  80 value 79.668869
iter  90 value 79.565520
iter 100 value 79.555050
final  value 79.555050 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.749569 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.829441 
iter  10 value 94.489013
iter  20 value 94.396071
iter  30 value 93.001741
iter  40 value 92.069462
iter  50 value 91.543265
iter  60 value 87.684724
iter  70 value 87.300830
iter  80 value 87.138064
iter  90 value 86.798000
iter 100 value 86.293582
final  value 86.293582 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.125254 
iter  10 value 94.223291
iter  20 value 93.527305
iter  30 value 88.000828
iter  40 value 87.652986
iter  50 value 87.022491
iter  60 value 86.803298
iter  70 value 84.996237
iter  80 value 83.852947
iter  90 value 83.830419
iter 100 value 83.128421
final  value 83.128421 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.960856 
iter  10 value 94.490986
iter  20 value 94.472444
iter  30 value 94.110661
iter  40 value 94.088873
iter  50 value 94.080537
final  value 94.077872 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.135856 
iter  10 value 94.488762
iter  20 value 94.442105
iter  30 value 94.247109
iter  40 value 94.228055
iter  50 value 92.147968
iter  60 value 84.453075
iter  70 value 83.922742
iter  80 value 83.871470
iter  90 value 82.983974
iter 100 value 82.524232
final  value 82.524232 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.362139 
iter  10 value 94.490679
iter  20 value 94.359002
iter  30 value 94.215826
iter  40 value 94.212022
iter  50 value 94.072448
iter  60 value 87.502169
iter  70 value 86.532209
iter  80 value 83.261532
iter  90 value 82.411527
iter 100 value 81.950062
final  value 81.950062 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.821511 
iter  10 value 92.287063
iter  20 value 83.554265
iter  30 value 81.684739
iter  40 value 80.630017
iter  50 value 79.813404
iter  60 value 79.798257
iter  70 value 79.676648
iter  80 value 79.167011
iter  90 value 78.989634
iter 100 value 78.895328
final  value 78.895328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.548117 
iter  10 value 95.384119
iter  20 value 94.288197
iter  30 value 90.403507
iter  40 value 84.885486
iter  50 value 84.296297
iter  60 value 83.566807
iter  70 value 83.145249
iter  80 value 80.620456
iter  90 value 79.852970
iter 100 value 78.929254
final  value 78.929254 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.069252 
iter  10 value 94.509708
iter  20 value 94.223471
iter  30 value 92.382225
iter  40 value 89.517248
iter  50 value 85.255133
iter  60 value 82.980932
iter  70 value 82.483973
iter  80 value 81.982647
iter  90 value 79.783429
iter 100 value 79.009404
final  value 79.009404 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.663345 
iter  10 value 94.401819
iter  20 value 93.800974
iter  30 value 92.152029
iter  40 value 91.216441
iter  50 value 88.023420
iter  60 value 84.120465
iter  70 value 82.470761
iter  80 value 81.067553
iter  90 value 80.067004
iter 100 value 79.798164
final  value 79.798164 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.414419 
iter  10 value 94.560326
iter  20 value 94.250352
iter  30 value 89.891837
iter  40 value 83.230441
iter  50 value 82.084784
iter  60 value 81.400361
iter  70 value 81.232771
iter  80 value 81.110670
iter  90 value 80.106308
iter 100 value 78.778906
final  value 78.778906 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.657811 
iter  10 value 97.102856
iter  20 value 95.579543
iter  30 value 94.243706
iter  40 value 89.166700
iter  50 value 88.445130
iter  60 value 87.732900
iter  70 value 86.436470
iter  80 value 82.651044
iter  90 value 80.592044
iter 100 value 80.069612
final  value 80.069612 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.740289 
iter  10 value 94.300625
iter  20 value 85.560069
iter  30 value 84.130230
iter  40 value 84.069110
iter  50 value 83.802634
iter  60 value 82.331533
iter  70 value 79.869471
iter  80 value 79.294899
iter  90 value 79.137923
iter 100 value 79.104650
final  value 79.104650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.731938 
iter  10 value 95.023466
iter  20 value 87.538055
iter  30 value 85.248106
iter  40 value 82.755722
iter  50 value 81.808549
iter  60 value 80.386405
iter  70 value 79.392648
iter  80 value 78.825310
iter  90 value 78.341198
iter 100 value 77.976401
final  value 77.976401 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.674629 
iter  10 value 94.159987
iter  20 value 92.918398
iter  30 value 90.614741
iter  40 value 88.622366
iter  50 value 87.625807
iter  60 value 82.687592
iter  70 value 82.037330
iter  80 value 81.919440
iter  90 value 81.655460
iter 100 value 79.899585
final  value 79.899585 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.974610 
iter  10 value 94.532050
iter  20 value 93.140724
iter  30 value 86.730188
iter  40 value 83.823687
iter  50 value 82.153086
iter  60 value 79.754632
iter  70 value 79.279041
iter  80 value 79.125955
iter  90 value 78.983823
iter 100 value 78.684031
final  value 78.684031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.652179 
final  value 94.485979 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.226458 
iter  10 value 94.028452
iter  20 value 94.027279
final  value 94.027080 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.867476 
final  value 94.485994 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.128269 
final  value 94.485971 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.303388 
final  value 94.486284 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.571046 
iter  10 value 94.209707
iter  20 value 94.205143
iter  30 value 93.384835
iter  40 value 90.657858
iter  50 value 90.645464
iter  60 value 90.643202
iter  70 value 90.636286
iter  80 value 90.633167
iter  90 value 90.628402
iter 100 value 90.619546
final  value 90.619546 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.765985 
iter  10 value 94.488907
iter  20 value 94.337534
iter  30 value 92.769921
iter  40 value 83.834935
iter  50 value 83.441887
iter  60 value 83.260891
final  value 83.260497 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.179314 
iter  10 value 93.984361
iter  20 value 93.980385
iter  30 value 88.995960
iter  40 value 86.763857
iter  50 value 85.955367
iter  60 value 85.015157
iter  70 value 84.990834
final  value 84.990790 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.505566 
iter  10 value 94.489154
iter  20 value 94.438144
final  value 94.027061 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.332978 
iter  10 value 94.488919
iter  20 value 94.484214
iter  30 value 94.052249
iter  40 value 93.979023
iter  50 value 89.698799
iter  60 value 82.875360
iter  70 value 82.371663
final  value 82.369948 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.241633 
iter  10 value 92.693363
iter  20 value 89.066874
iter  30 value 88.450551
iter  40 value 88.435685
iter  50 value 88.433068
iter  60 value 88.431633
iter  70 value 88.429346
iter  80 value 88.428936
iter  90 value 88.156888
iter 100 value 87.023092
final  value 87.023092 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.811750 
iter  10 value 94.491784
iter  20 value 93.997333
iter  30 value 93.980383
iter  40 value 93.976950
iter  50 value 93.974947
iter  60 value 93.973432
final  value 93.973293 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.342778 
iter  10 value 94.034478
iter  20 value 94.027264
iter  30 value 92.529089
iter  40 value 87.065612
iter  50 value 84.759560
iter  60 value 84.758133
iter  70 value 84.671470
iter  80 value 82.885778
iter  90 value 82.709214
iter 100 value 82.472596
final  value 82.472596 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 92.505423 
iter  10 value 85.248276
iter  20 value 84.609880
iter  30 value 84.385004
final  value 84.384395 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.730060 
iter  10 value 94.035179
iter  20 value 94.028810
final  value 94.025383 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.824826 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.738912 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.566453 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.223579 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.203838 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.077031 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.808296 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.599395 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.516080 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.412685 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.980531 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.446113 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.645819 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.165323 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.878678 
iter  10 value 92.915735
iter  20 value 92.700778
iter  30 value 92.535649
final  value 92.535641 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.108338 
iter  10 value 94.053766
iter  20 value 93.899860
iter  30 value 93.892196
iter  40 value 93.853975
iter  50 value 89.752684
iter  60 value 86.689315
iter  70 value 86.016560
iter  80 value 84.342032
iter  90 value 83.479570
iter 100 value 83.113848
final  value 83.113848 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 114.592660 
iter  10 value 94.032160
iter  20 value 91.234895
iter  30 value 87.036642
iter  40 value 84.054081
iter  50 value 83.496517
iter  60 value 83.298207
iter  70 value 83.256519
final  value 83.250585 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.743783 
iter  10 value 94.043062
iter  20 value 93.624341
iter  30 value 91.977334
iter  40 value 86.193347
iter  50 value 83.725793
iter  60 value 83.277531
iter  70 value 83.250592
final  value 83.250585 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.369443 
iter  10 value 94.056600
iter  10 value 94.056599
iter  20 value 93.971244
iter  30 value 85.172920
iter  40 value 84.296449
iter  50 value 82.754551
iter  60 value 82.438921
iter  70 value 82.396287
final  value 82.395915 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.427035 
iter  10 value 94.085384
iter  20 value 94.010926
iter  30 value 92.392002
iter  40 value 91.701028
iter  50 value 85.527890
iter  60 value 81.525892
iter  70 value 81.265822
iter  80 value 80.736990
iter  90 value 80.607442
iter 100 value 80.538487
final  value 80.538487 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.973264 
iter  10 value 94.055304
iter  20 value 93.748513
iter  30 value 93.082517
iter  40 value 89.453148
iter  50 value 85.605110
iter  60 value 84.694625
iter  70 value 84.632299
iter  80 value 82.851009
iter  90 value 82.779386
iter 100 value 82.705103
final  value 82.705103 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.440981 
iter  10 value 94.123132
iter  20 value 93.722383
iter  30 value 92.468438
iter  40 value 85.698124
iter  50 value 84.687773
iter  60 value 83.397318
iter  70 value 83.017974
iter  80 value 82.933139
iter  90 value 82.920155
iter 100 value 82.875951
final  value 82.875951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.209647 
iter  10 value 93.885568
iter  20 value 85.898584
iter  30 value 83.914848
iter  40 value 83.710056
iter  50 value 83.053121
iter  60 value 82.683823
iter  70 value 81.864124
iter  80 value 80.972665
iter  90 value 80.348948
iter 100 value 79.787768
final  value 79.787768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.561380 
iter  10 value 94.086581
iter  20 value 88.095664
iter  30 value 87.399249
iter  40 value 86.780892
iter  50 value 84.655293
iter  60 value 83.601012
iter  70 value 83.239600
iter  80 value 82.995642
iter  90 value 82.547928
iter 100 value 81.151522
final  value 81.151522 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.356515 
iter  10 value 97.310965
iter  20 value 86.691399
iter  30 value 84.807170
iter  40 value 84.584671
iter  50 value 83.390232
iter  60 value 82.999194
iter  70 value 82.681463
iter  80 value 82.635371
iter  90 value 82.234862
iter 100 value 80.597285
final  value 80.597285 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.950156 
iter  10 value 93.923934
iter  20 value 87.160396
iter  30 value 83.083963
iter  40 value 80.466393
iter  50 value 79.383805
iter  60 value 79.152194
iter  70 value 79.118595
iter  80 value 79.049030
iter  90 value 78.975272
iter 100 value 78.870935
final  value 78.870935 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.925150 
iter  10 value 93.550451
iter  20 value 91.727280
iter  30 value 88.385807
iter  40 value 85.516437
iter  50 value 83.433858
iter  60 value 81.678693
iter  70 value 80.219390
iter  80 value 79.646707
iter  90 value 79.570158
iter 100 value 79.522425
final  value 79.522425 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.564906 
iter  10 value 91.041711
iter  20 value 86.067244
iter  30 value 84.832484
iter  40 value 84.315924
iter  50 value 83.370151
iter  60 value 81.779940
iter  70 value 81.155184
iter  80 value 80.608989
iter  90 value 80.046966
iter 100 value 79.652041
final  value 79.652041 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.186431 
iter  10 value 93.962259
iter  20 value 92.305584
iter  30 value 83.804708
iter  40 value 83.218854
iter  50 value 80.908238
iter  60 value 80.008716
iter  70 value 79.722624
iter  80 value 79.580795
iter  90 value 79.426614
iter 100 value 79.288815
final  value 79.288815 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.116592 
iter  10 value 94.019769
iter  20 value 84.848374
iter  30 value 84.028492
iter  40 value 83.483447
iter  50 value 82.526073
iter  60 value 81.360972
iter  70 value 80.106424
iter  80 value 79.996892
iter  90 value 79.762991
iter 100 value 79.655316
final  value 79.655316 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.336454 
final  value 94.060378 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.343691 
final  value 94.054526 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.196631 
iter  10 value 94.018881
iter  20 value 93.459326
final  value 91.608258 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.801479 
iter  10 value 94.054824
iter  20 value 94.030956
iter  30 value 83.486563
iter  40 value 82.356204
iter  50 value 82.196487
iter  60 value 82.165074
iter  70 value 82.137417
iter  80 value 82.045618
final  value 82.033980 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.873117 
final  value 94.054529 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.821114 
iter  10 value 93.841094
iter  20 value 93.487657
iter  30 value 93.474878
iter  40 value 93.324648
iter  50 value 92.195265
iter  60 value 89.691660
iter  70 value 88.930871
iter  80 value 86.233043
iter  90 value 86.128715
iter 100 value 86.126237
final  value 86.126237 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.921730 
iter  10 value 92.271317
iter  20 value 91.611886
iter  30 value 91.611478
iter  40 value 91.609954
iter  50 value 91.607152
iter  60 value 91.606832
final  value 91.606828 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.535558 
iter  10 value 91.335504
iter  20 value 91.334042
iter  30 value 87.379793
iter  40 value 83.664304
iter  50 value 82.620894
iter  60 value 82.542346
final  value 82.541778 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.890847 
iter  10 value 94.021889
iter  20 value 87.149305
iter  30 value 83.682686
iter  40 value 82.171396
iter  50 value 81.834630
iter  60 value 81.686364
iter  70 value 81.685920
iter  80 value 81.654123
iter  90 value 81.626933
final  value 81.626849 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.131108 
iter  10 value 94.057753
iter  20 value 94.022286
iter  30 value 93.461251
iter  40 value 90.037355
iter  50 value 87.075057
iter  60 value 87.061618
iter  70 value 87.059983
iter  80 value 87.059861
iter  90 value 87.058583
iter 100 value 87.046745
final  value 87.046745 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.526737 
iter  10 value 93.844801
iter  20 value 93.030795
iter  30 value 84.861961
iter  40 value 84.845933
iter  50 value 84.780664
iter  60 value 84.416987
iter  70 value 84.269558
iter  80 value 84.269144
iter  90 value 84.193439
iter 100 value 81.611042
final  value 81.611042 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.916092 
iter  10 value 91.118214
iter  20 value 86.899918
iter  30 value 86.844536
iter  40 value 86.448783
iter  50 value 86.417630
iter  60 value 85.352293
iter  70 value 85.088715
iter  80 value 85.083303
iter  90 value 84.241864
iter 100 value 83.224038
final  value 83.224038 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.146396 
iter  10 value 94.056985
iter  20 value 93.182150
iter  30 value 91.439543
iter  40 value 91.435987
iter  50 value 90.538316
iter  60 value 90.466673
iter  70 value 90.465489
iter  80 value 90.388652
iter  90 value 90.249619
iter 100 value 90.248152
final  value 90.248152 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.578289 
iter  10 value 94.061378
iter  20 value 92.902065
iter  30 value 92.552253
iter  40 value 92.550344
iter  50 value 92.550202
final  value 92.550025 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.755465 
iter  10 value 91.607899
iter  20 value 91.396377
iter  30 value 91.392780
final  value 91.390601 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.910432 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.647091 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.493290 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.231692 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.220449 
iter  10 value 93.674889
final  value 93.671508 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.470406 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.830382 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.521922 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.370533 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.012370 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.678151 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.970909 
iter  10 value 93.936341
iter  20 value 93.018237
iter  30 value 90.310320
iter  40 value 85.791275
iter  50 value 83.526086
iter  60 value 82.901917
iter  70 value 82.862153
iter  80 value 82.834332
iter  90 value 81.637333
final  value 81.420794 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.118638 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.776197 
final  value 94.027933 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.015145 
iter  10 value 94.000000
iter  10 value 94.000000
iter  10 value 94.000000
final  value 94.000000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.534996 
iter  10 value 93.986191
iter  20 value 90.800389
iter  30 value 85.482631
iter  40 value 81.274019
iter  50 value 79.642535
iter  60 value 79.305292
iter  70 value 78.882620
iter  80 value 78.836111
final  value 78.835138 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.365224 
iter  10 value 93.973989
iter  20 value 92.528198
iter  30 value 91.509711
iter  40 value 91.236423
iter  50 value 91.021015
iter  60 value 90.594241
iter  70 value 85.846228
iter  80 value 84.077841
iter  90 value 83.681612
iter 100 value 83.025335
final  value 83.025335 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.735543 
iter  10 value 94.214382
iter  20 value 94.056140
iter  30 value 93.245252
iter  40 value 91.675342
iter  50 value 87.758888
iter  60 value 87.284328
iter  70 value 85.305994
iter  80 value 83.345128
iter  90 value 83.013010
iter 100 value 82.959091
final  value 82.959091 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.304875 
iter  10 value 93.897412
iter  20 value 86.306268
iter  30 value 84.656763
iter  40 value 83.758681
iter  50 value 83.303843
iter  60 value 82.676542
iter  70 value 81.115302
iter  80 value 79.781879
iter  90 value 79.674700
iter 100 value 79.673174
final  value 79.673174 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.549313 
iter  10 value 94.055147
iter  20 value 93.201668
iter  30 value 91.473889
iter  40 value 91.068844
iter  50 value 91.061629
final  value 91.061622 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.531547 
iter  10 value 93.019804
iter  20 value 83.552923
iter  30 value 82.822996
iter  40 value 82.175282
iter  50 value 81.383145
iter  60 value 80.069904
iter  70 value 78.374034
iter  80 value 78.131498
iter  90 value 77.990130
iter 100 value 77.760129
final  value 77.760129 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.306018 
iter  10 value 88.571626
iter  20 value 84.754380
iter  30 value 83.813731
iter  40 value 83.107420
iter  50 value 82.999860
iter  60 value 82.513706
iter  70 value 79.908121
iter  80 value 79.012501
iter  90 value 78.403379
iter 100 value 78.212999
final  value 78.212999 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.721712 
iter  10 value 94.000916
iter  20 value 89.905272
iter  30 value 89.119503
iter  40 value 86.142303
iter  50 value 82.542222
iter  60 value 79.073130
iter  70 value 78.032376
iter  80 value 77.701858
iter  90 value 77.624038
iter 100 value 77.530792
final  value 77.530792 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.608901 
iter  10 value 90.833091
iter  20 value 84.649490
iter  30 value 84.254268
iter  40 value 82.095088
iter  50 value 81.654044
iter  60 value 81.051605
iter  70 value 78.857692
iter  80 value 77.953639
iter  90 value 77.791109
iter 100 value 77.718682
final  value 77.718682 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.712199 
iter  10 value 93.955986
iter  20 value 84.072819
iter  30 value 83.230522
iter  40 value 82.565794
iter  50 value 81.349095
iter  60 value 79.782502
iter  70 value 79.540253
iter  80 value 79.405434
iter  90 value 79.159328
iter 100 value 78.856583
final  value 78.856583 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.629288 
iter  10 value 94.169489
iter  20 value 90.237610
iter  30 value 85.271935
iter  40 value 82.587318
iter  50 value 79.069647
iter  60 value 78.631071
iter  70 value 77.866100
iter  80 value 77.767998
iter  90 value 77.732985
iter 100 value 77.548933
final  value 77.548933 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.355910 
iter  10 value 93.923053
iter  20 value 88.377268
iter  30 value 83.217279
iter  40 value 82.271253
iter  50 value 80.301977
iter  60 value 78.873348
iter  70 value 77.717910
iter  80 value 77.622042
iter  90 value 77.549232
iter 100 value 77.340271
final  value 77.340271 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.873965 
iter  10 value 95.662878
iter  20 value 94.085634
iter  30 value 84.343920
iter  40 value 83.270395
iter  50 value 82.346179
iter  60 value 81.651519
iter  70 value 81.383809
iter  80 value 80.694830
iter  90 value 79.098186
iter 100 value 78.227920
final  value 78.227920 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.676466 
iter  10 value 93.701898
iter  20 value 85.487551
iter  30 value 83.780177
iter  40 value 83.399424
iter  50 value 81.874441
iter  60 value 81.266181
iter  70 value 80.871063
iter  80 value 80.580941
iter  90 value 80.002852
iter 100 value 79.700479
final  value 79.700479 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.877447 
iter  10 value 93.970335
iter  20 value 87.131082
iter  30 value 84.249275
iter  40 value 81.692355
iter  50 value 80.314345
iter  60 value 79.679777
iter  70 value 78.850004
iter  80 value 78.373362
iter  90 value 77.984442
iter 100 value 77.811472
final  value 77.811472 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.545870 
final  value 94.054536 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.965031 
iter  10 value 94.054632
iter  20 value 94.047757
iter  30 value 93.928063
iter  40 value 89.525856
iter  50 value 81.786892
iter  60 value 81.076477
iter  70 value 81.033353
iter  80 value 80.899953
iter  90 value 80.898319
final  value 80.897371 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.147222 
iter  10 value 94.001657
iter  20 value 93.768576
iter  30 value 93.726254
final  value 93.726149 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.503462 
final  value 94.039845 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.698124 
iter  10 value 94.054068
final  value 94.052912 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.698322 
iter  10 value 94.043010
iter  20 value 91.375955
iter  30 value 87.612968
final  value 87.612961 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.548313 
iter  10 value 94.043053
iter  20 value 93.961803
iter  30 value 88.544458
iter  40 value 85.223419
iter  50 value 85.221540
iter  60 value 85.220592
final  value 85.219762 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.943764 
iter  10 value 94.042953
iter  20 value 93.995121
iter  30 value 84.814697
iter  40 value 84.780352
iter  50 value 84.779773
iter  60 value 83.438157
iter  70 value 80.890896
iter  80 value 79.668357
iter  90 value 78.691199
iter 100 value 76.719009
final  value 76.719009 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.884566 
iter  10 value 94.043069
iter  20 value 93.733491
iter  30 value 93.715008
iter  40 value 93.682343
final  value 93.681549 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.942134 
iter  10 value 94.057516
iter  20 value 85.364030
iter  30 value 85.158506
iter  40 value 85.157538
iter  40 value 85.157538
final  value 85.157538 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.971056 
iter  10 value 94.025544
iter  20 value 94.018958
final  value 94.018854 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.111033 
iter  10 value 93.336880
iter  20 value 93.332196
iter  30 value 93.328729
iter  40 value 91.903258
iter  50 value 82.739939
iter  60 value 82.101005
iter  70 value 82.069956
iter  80 value 82.055255
iter  90 value 82.054984
final  value 82.054948 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.165449 
iter  10 value 93.901084
iter  20 value 93.760645
iter  30 value 90.713508
final  value 90.713311 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.144941 
iter  10 value 94.046772
iter  20 value 93.898340
iter  30 value 84.393470
iter  40 value 83.225615
iter  50 value 79.912633
iter  60 value 79.843610
iter  70 value 79.740385
iter  80 value 79.728918
iter  90 value 79.163424
iter 100 value 77.070732
final  value 77.070732 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 135.837942 
iter  10 value 94.049057
iter  20 value 94.042568
iter  30 value 94.041190
iter  40 value 90.390585
iter  50 value 88.646866
iter  60 value 88.570465
final  value 88.570220 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.301948 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 119.510621 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.882299 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.953269 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.799553 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.012834 
iter  10 value 94.364119
final  value 94.104010 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.555412 
iter  10 value 94.390339
iter  20 value 89.143716
iter  30 value 89.143455
final  value 89.143454 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.251062 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.041044 
final  value 94.428839 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.320327 
final  value 94.436784 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.586312 
iter  10 value 91.619218
iter  20 value 87.653284
final  value 87.617659 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.773395 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.790046 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.044499 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.867351 
iter  10 value 88.099207
iter  20 value 87.794955
final  value 87.794643 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.375404 
iter  10 value 93.848766
iter  20 value 89.675225
iter  30 value 88.277250
iter  40 value 87.707864
iter  50 value 87.655750
iter  60 value 86.919782
iter  70 value 86.417785
iter  80 value 86.279734
iter  90 value 85.827367
iter 100 value 85.665431
final  value 85.665431 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.146193 
iter  10 value 94.487507
iter  20 value 94.297013
iter  30 value 94.065279
iter  40 value 93.958145
iter  50 value 88.858756
iter  60 value 88.650487
iter  70 value 88.071703
iter  80 value 86.500309
iter  90 value 86.160407
iter 100 value 86.088939
final  value 86.088939 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.261953 
iter  10 value 94.486836
iter  20 value 94.118716
iter  30 value 89.559225
iter  40 value 87.071813
iter  50 value 86.980181
iter  60 value 86.942818
iter  70 value 86.786036
iter  80 value 86.700227
iter  90 value 86.699336
iter  90 value 86.699336
iter  90 value 86.699336
final  value 86.699336 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.379995 
iter  10 value 93.247468
iter  20 value 92.747093
iter  30 value 92.724813
final  value 92.724718 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.186888 
iter  10 value 94.496291
iter  20 value 94.416593
iter  30 value 93.991762
iter  40 value 93.968286
iter  50 value 93.967495
iter  60 value 92.855915
iter  70 value 88.563974
iter  80 value 88.082346
iter  90 value 87.809204
iter 100 value 86.565081
final  value 86.565081 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.155240 
iter  10 value 94.931798
iter  20 value 88.308760
iter  30 value 87.014280
iter  40 value 86.685242
iter  50 value 86.541658
iter  60 value 86.036055
iter  70 value 85.332245
iter  80 value 84.886050
iter  90 value 84.662994
iter 100 value 84.583909
final  value 84.583909 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.655486 
iter  10 value 94.444563
iter  20 value 90.029604
iter  30 value 87.953224
iter  40 value 87.666612
iter  50 value 86.772799
iter  60 value 85.202135
iter  70 value 84.862138
iter  80 value 84.815599
iter  90 value 84.776859
iter 100 value 84.770231
final  value 84.770231 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.167160 
iter  10 value 95.094498
iter  20 value 94.434874
iter  30 value 91.228447
iter  40 value 89.338554
iter  50 value 88.754911
iter  60 value 86.626779
iter  70 value 85.873905
iter  80 value 85.536467
iter  90 value 85.390834
iter 100 value 85.097714
final  value 85.097714 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.204411 
iter  10 value 94.050304
iter  20 value 88.842198
iter  30 value 88.168703
iter  40 value 87.772298
iter  50 value 86.808027
iter  60 value 85.668178
iter  70 value 85.328159
iter  80 value 84.924699
iter  90 value 84.876669
iter 100 value 84.830394
final  value 84.830394 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 134.182099 
iter  10 value 94.632813
iter  20 value 94.438756
iter  30 value 93.952358
iter  40 value 93.395433
iter  50 value 92.999654
iter  60 value 92.735537
iter  70 value 92.674978
iter  80 value 92.582657
iter  90 value 92.359822
iter 100 value 91.632073
final  value 91.632073 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.802906 
iter  10 value 95.125645
iter  20 value 91.064149
iter  30 value 88.622313
iter  40 value 87.348296
iter  50 value 87.092934
iter  60 value 86.689511
iter  70 value 86.153151
iter  80 value 85.942743
iter  90 value 85.851711
iter 100 value 85.549584
final  value 85.549584 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.898223 
iter  10 value 94.492275
iter  20 value 92.141166
iter  30 value 87.301501
iter  40 value 86.284163
iter  50 value 85.836413
iter  60 value 85.257497
iter  70 value 84.618099
iter  80 value 84.599447
iter  90 value 84.566666
iter 100 value 84.559298
final  value 84.559298 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.749814 
iter  10 value 95.589719
iter  20 value 90.326239
iter  30 value 88.038776
iter  40 value 86.239802
iter  50 value 85.588012
iter  60 value 85.455854
iter  70 value 85.192234
iter  80 value 84.847883
iter  90 value 84.645303
iter 100 value 84.490784
final  value 84.490784 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.791567 
iter  10 value 94.505063
iter  20 value 92.108765
iter  30 value 91.084225
iter  40 value 89.839196
iter  50 value 89.696296
iter  60 value 87.999320
iter  70 value 87.481319
iter  80 value 85.967150
iter  90 value 85.038207
iter 100 value 84.659840
final  value 84.659840 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.103718 
iter  10 value 94.813358
iter  20 value 91.219249
iter  30 value 90.156152
iter  40 value 89.805037
iter  50 value 89.431893
iter  60 value 88.943461
iter  70 value 87.276771
iter  80 value 86.043117
iter  90 value 85.776889
iter 100 value 85.719491
final  value 85.719491 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.801110 
final  value 94.485681 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.156030 
iter  10 value 93.247598
iter  20 value 92.642508
final  value 92.639657 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.799209 
final  value 94.485639 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.273332 
final  value 94.485865 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.135888 
final  value 94.485813 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.558326 
iter  10 value 94.495272
iter  20 value 94.459930
iter  30 value 93.980264
iter  40 value 93.975847
iter  50 value 93.969594
iter  60 value 93.400069
iter  70 value 89.911750
iter  80 value 87.861509
iter  90 value 85.272618
iter 100 value 84.776330
final  value 84.776330 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.636770 
iter  10 value 94.489823
iter  20 value 94.484475
final  value 94.484470 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.590732 
iter  10 value 94.489142
iter  20 value 93.983133
iter  30 value 88.175921
iter  40 value 87.953422
iter  50 value 87.650318
iter  60 value 87.632202
iter  70 value 87.626509
iter  80 value 87.622398
iter  90 value 87.613115
iter 100 value 86.955012
final  value 86.955012 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.868482 
iter  10 value 94.471290
iter  20 value 94.433416
final  value 94.430866 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.567481 
iter  10 value 94.488863
iter  20 value 94.484173
iter  30 value 92.132004
iter  40 value 87.517322
iter  50 value 86.627256
iter  60 value 86.486079
iter  70 value 86.484328
iter  70 value 86.484328
iter  80 value 86.478342
iter  90 value 86.477851
iter 100 value 86.476025
final  value 86.476025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.090524 
iter  10 value 94.038440
iter  20 value 93.977530
iter  30 value 93.974085
iter  40 value 93.586885
iter  50 value 87.304874
iter  60 value 87.114478
iter  70 value 87.099328
iter  80 value 87.080094
iter  90 value 87.076270
final  value 87.076257 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.219318 
iter  10 value 94.038422
iter  20 value 94.031112
iter  30 value 93.948447
iter  40 value 93.845093
iter  50 value 93.330498
iter  60 value 90.358790
iter  70 value 86.777917
iter  80 value 86.404747
iter  80 value 86.404746
final  value 86.404746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 140.854491 
iter  10 value 94.463775
iter  20 value 94.048494
iter  30 value 89.425389
iter  40 value 87.304854
iter  50 value 84.745245
iter  60 value 84.700552
iter  70 value 84.406560
iter  80 value 84.288305
iter  90 value 84.283431
iter 100 value 84.282812
final  value 84.282812 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.722462 
iter  10 value 94.491389
iter  20 value 94.237366
iter  30 value 87.973726
final  value 87.939139 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.079989 
iter  10 value 93.996485
iter  20 value 93.983289
iter  30 value 93.980502
iter  40 value 93.977041
iter  50 value 93.976524
iter  60 value 93.974846
final  value 93.974492 
converged
Fitting Repeat 1 

# weights:  507
initial  value 151.367716 
iter  10 value 117.766737
iter  20 value 117.563677
iter  30 value 117.551676
final  value 117.551306 
converged
Fitting Repeat 2 

# weights:  507
initial  value 135.373744 
iter  10 value 117.747596
iter  20 value 117.743500
iter  30 value 111.544903
iter  40 value 107.429578
iter  50 value 103.884973
iter  60 value 103.752904
iter  70 value 103.404494
iter  80 value 102.882144
iter  90 value 102.388278
final  value 102.383901 
converged
Fitting Repeat 3 

# weights:  507
initial  value 147.618058 
iter  10 value 117.899978
iter  20 value 117.891210
iter  30 value 116.465405
iter  40 value 105.572624
iter  50 value 105.159941
iter  60 value 105.140378
iter  70 value 105.028348
iter  80 value 105.000483
iter  90 value 104.934780
iter 100 value 103.599836
final  value 103.599836 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 133.044235 
iter  10 value 117.899283
iter  20 value 117.607096
iter  30 value 107.794108
iter  40 value 105.377590
iter  50 value 105.360346
iter  60 value 104.223920
iter  70 value 103.290245
iter  80 value 103.287484
iter  90 value 103.280434
iter 100 value 103.256534
final  value 103.256534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.444924 
iter  10 value 117.898441
iter  20 value 117.885168
iter  30 value 117.065148
iter  40 value 106.765497
iter  50 value 106.601232
iter  60 value 106.038306
iter  70 value 102.278995
iter  80 value 101.679387
iter  90 value 101.674136
iter 100 value 101.670307
final  value 101.670307 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Apr 21 20:20:07 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 
 20.073   0.702  83.503