##############################################################################
##############################################################################
###
### 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: 2026-04-13 00:12:25 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
var_imp       17.177  0.152  17.450
FSmethod      17.189  0.098  17.855
corr_plot     17.151  0.123  17.345
pred_ensembel  6.324  0.197   5.766
enrichfindP    0.200  0.040   8.987
* 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 105.864091 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.056395 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.085920 
iter  10 value 94.275365
final  value 94.275363 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.169749 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.980063 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 124.471775 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.168909 
final  value 94.252920 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.186934 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.354958 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.438293 
iter  10 value 93.846614
iter  20 value 93.557386
iter  30 value 92.342294
iter  40 value 85.165801
iter  50 value 84.164910
iter  60 value 82.621980
iter  70 value 82.620061
iter  80 value 82.489554
iter  90 value 82.483344
final  value 82.483333 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.252048 
iter  10 value 94.479532
iter  10 value 94.479532
iter  10 value 94.479532
final  value 94.479532 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.013143 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.582276 
iter  10 value 94.275364
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.600850 
iter  10 value 92.613983
iter  20 value 89.305116
iter  30 value 87.020773
iter  40 value 86.051878
iter  50 value 80.163180
iter  60 value 80.085818
iter  70 value 79.853783
iter  80 value 79.842116
iter  90 value 79.720658
final  value 79.712864 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.413837 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.375675 
iter  10 value 94.488593
iter  20 value 91.505301
iter  30 value 84.941332
iter  40 value 82.900150
iter  50 value 82.508517
iter  60 value 82.271777
iter  70 value 80.652729
iter  80 value 79.909670
iter  90 value 79.742598
iter 100 value 79.736877
final  value 79.736877 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.137375 
iter  10 value 94.483699
iter  20 value 94.334903
iter  30 value 94.325233
iter  40 value 94.018782
iter  50 value 86.609066
iter  60 value 83.615061
iter  70 value 83.262127
iter  80 value 83.162187
iter  90 value 82.065547
iter 100 value 81.351317
final  value 81.351317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 112.415335 
iter  10 value 93.873811
iter  20 value 87.240381
iter  30 value 85.970569
iter  40 value 84.960754
iter  50 value 84.353741
iter  60 value 84.254114
final  value 84.254057 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.354100 
iter  10 value 94.502360
iter  20 value 94.483741
iter  30 value 93.775108
iter  40 value 85.535742
iter  50 value 83.518263
iter  60 value 81.960530
iter  70 value 81.574495
iter  80 value 81.386474
iter  90 value 81.373479
final  value 81.373440 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.680626 
iter  10 value 94.468842
iter  20 value 93.998699
iter  30 value 86.146623
iter  40 value 81.980379
iter  50 value 81.438251
iter  60 value 81.406642
iter  70 value 81.378783
final  value 81.373437 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.439213 
iter  10 value 94.526399
iter  20 value 91.554217
iter  30 value 90.569840
iter  40 value 83.370615
iter  50 value 82.871134
iter  60 value 81.368132
iter  70 value 80.848250
iter  80 value 80.166777
iter  90 value 79.290319
iter 100 value 79.039881
final  value 79.039881 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.505628 
iter  10 value 94.611950
iter  20 value 94.245570
iter  30 value 91.630606
iter  40 value 91.396783
iter  50 value 90.424566
iter  60 value 86.021764
iter  70 value 83.903616
iter  80 value 83.276502
iter  90 value 81.220830
iter 100 value 79.803311
final  value 79.803311 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.823247 
iter  10 value 94.487992
iter  20 value 91.040600
iter  30 value 88.902464
iter  40 value 82.733359
iter  50 value 80.647474
iter  60 value 79.835941
iter  70 value 79.379786
iter  80 value 78.965362
iter  90 value 78.615936
iter 100 value 78.517644
final  value 78.517644 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.765515 
iter  10 value 92.372407
iter  20 value 89.632962
iter  30 value 83.911447
iter  40 value 82.724810
iter  50 value 82.222247
iter  60 value 81.949606
iter  70 value 81.868056
iter  80 value 81.721833
iter  90 value 81.537657
iter 100 value 80.409943
final  value 80.409943 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.813850 
iter  10 value 94.464667
iter  20 value 94.208143
iter  30 value 92.099180
iter  40 value 84.437658
iter  50 value 83.102979
iter  60 value 81.771969
iter  70 value 81.001340
iter  80 value 80.826974
iter  90 value 80.224929
iter 100 value 79.960914
final  value 79.960914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.434106 
iter  10 value 97.481259
iter  20 value 90.737525
iter  30 value 86.417581
iter  40 value 81.638358
iter  50 value 81.060615
iter  60 value 80.567234
iter  70 value 79.987945
iter  80 value 79.693240
iter  90 value 79.342980
iter 100 value 78.514762
final  value 78.514762 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.662293 
iter  10 value 93.794560
iter  20 value 89.094025
iter  30 value 87.303795
iter  40 value 85.230637
iter  50 value 84.371775
iter  60 value 84.079276
iter  70 value 79.908465
iter  80 value 78.912517
iter  90 value 78.640590
iter 100 value 78.510854
final  value 78.510854 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.328835 
iter  10 value 93.720427
iter  20 value 87.896247
iter  30 value 85.990773
iter  40 value 82.866108
iter  50 value 82.207939
iter  60 value 80.732542
iter  70 value 79.579390
iter  80 value 79.405089
iter  90 value 79.319533
iter 100 value 79.203535
final  value 79.203535 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.426686 
iter  10 value 93.534438
iter  20 value 83.633959
iter  30 value 81.804967
iter  40 value 81.610019
iter  50 value 81.017676
iter  60 value 80.014372
iter  70 value 79.760869
iter  80 value 79.423522
iter  90 value 78.921618
iter 100 value 78.854338
final  value 78.854338 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.258993 
iter  10 value 94.589581
iter  20 value 85.196857
iter  30 value 83.482716
iter  40 value 83.083765
iter  50 value 81.468002
iter  60 value 81.149582
iter  70 value 79.616347
iter  80 value 78.591604
iter  90 value 78.092479
iter 100 value 78.065383
final  value 78.065383 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.836548 
final  value 94.485861 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.718190 
final  value 94.485923 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.349408 
iter  10 value 93.237681
iter  20 value 93.221775
iter  30 value 93.218927
final  value 93.218925 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.698761 
iter  10 value 94.444920
final  value 94.047359 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.027798 
final  value 94.485924 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.017727 
iter  10 value 94.280210
iter  20 value 94.275985
final  value 94.275735 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.630188 
iter  10 value 94.489364
iter  20 value 94.460027
iter  30 value 83.955567
final  value 83.899680 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.177488 
iter  10 value 94.489201
iter  20 value 94.484280
iter  30 value 93.663289
iter  40 value 89.329753
iter  50 value 86.531695
iter  60 value 86.322666
iter  70 value 86.150155
iter  80 value 82.916330
iter  90 value 82.381058
iter 100 value 82.375399
final  value 82.375399 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.903307 
iter  10 value 94.280406
iter  20 value 94.229215
iter  30 value 94.228841
iter  40 value 88.888509
iter  50 value 82.728604
iter  60 value 82.619201
iter  70 value 82.519231
iter  80 value 82.484362
final  value 82.483973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.417931 
iter  10 value 94.489029
iter  20 value 94.275729
final  value 94.275521 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.428251 
iter  10 value 94.239105
iter  20 value 94.234636
iter  30 value 94.233049
iter  40 value 90.889256
iter  50 value 90.304070
iter  60 value 89.771608
iter  70 value 89.738941
iter  80 value 89.738407
iter  90 value 89.736010
iter 100 value 89.735538
final  value 89.735538 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.393309 
iter  10 value 94.492211
iter  20 value 93.913770
final  value 93.913358 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.321886 
iter  10 value 94.307897
iter  20 value 94.300351
iter  30 value 94.298250
iter  40 value 94.296992
iter  50 value 91.781129
iter  60 value 90.598605
iter  70 value 86.545509
iter  80 value 82.818087
iter  90 value 81.870956
iter 100 value 81.870525
final  value 81.870525 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.350859 
iter  10 value 93.942934
iter  20 value 93.936822
iter  30 value 93.876647
iter  40 value 93.859611
final  value 93.856712 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.635650 
iter  10 value 94.283307
iter  20 value 94.076821
iter  30 value 83.519531
iter  40 value 82.579008
iter  50 value 80.666664
iter  60 value 77.382672
iter  70 value 77.105207
iter  80 value 77.049061
final  value 77.048462 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.299872 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.130780 
iter  10 value 91.627059
iter  20 value 86.142333
iter  30 value 86.118968
final  value 86.118535 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.400389 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.807999 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.055493 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.252483 
iter  10 value 94.395062
iter  10 value 94.395062
iter  10 value 94.395062
final  value 94.395062 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.725573 
iter  10 value 92.993116
iter  20 value 87.947599
final  value 87.947560 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.284233 
iter  10 value 91.183495
iter  20 value 87.259359
iter  30 value 87.252740
iter  40 value 87.252628
final  value 87.252614 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.033165 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.734913 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.070415 
iter  10 value 87.950243
final  value 87.947559 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.038617 
iter  10 value 94.469696
iter  20 value 94.466825
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.450231 
iter  10 value 94.466805
final  value 94.309797 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.813968 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.602175 
iter  10 value 93.935239
iter  10 value 93.935238
iter  10 value 93.935238
final  value 93.935238 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.782288 
iter  10 value 94.420345
iter  20 value 94.093014
iter  30 value 94.032220
iter  40 value 92.191411
iter  50 value 86.343172
iter  60 value 85.294379
iter  70 value 84.554616
iter  80 value 84.349384
iter  90 value 84.345599
iter  90 value 84.345599
iter  90 value 84.345599
final  value 84.345599 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.756521 
iter  10 value 94.491787
iter  20 value 94.468512
iter  30 value 94.014534
iter  40 value 93.116441
iter  50 value 86.705217
iter  60 value 86.024082
iter  70 value 85.842442
iter  80 value 85.352132
iter  90 value 84.954574
iter 100 value 84.588449
final  value 84.588449 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.689463 
iter  10 value 94.445142
iter  20 value 90.517254
iter  30 value 87.187472
iter  40 value 86.741053
iter  50 value 86.106575
iter  60 value 85.432510
iter  70 value 85.255049
final  value 85.243080 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.356350 
iter  10 value 94.509072
iter  20 value 93.672638
iter  30 value 89.051613
iter  40 value 87.482295
iter  50 value 84.100974
iter  60 value 83.900234
final  value 83.898671 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.167659 
iter  10 value 94.488512
iter  20 value 88.343292
iter  30 value 88.117212
iter  40 value 87.758231
iter  50 value 84.412662
iter  60 value 84.345609
final  value 84.345599 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.652864 
iter  10 value 94.611777
iter  20 value 91.616648
iter  30 value 85.643292
iter  40 value 84.980148
iter  50 value 82.987465
iter  60 value 82.325820
iter  70 value 80.197927
iter  80 value 79.705357
iter  90 value 79.543348
iter 100 value 79.483091
final  value 79.483091 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.021127 
iter  10 value 94.291117
iter  20 value 87.054365
iter  30 value 86.619493
iter  40 value 86.250669
iter  50 value 85.947666
iter  60 value 84.831884
iter  70 value 81.419452
iter  80 value 79.913464
iter  90 value 79.669810
iter 100 value 79.471547
final  value 79.471547 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.778707 
iter  10 value 94.441976
iter  20 value 88.190301
iter  30 value 86.647246
iter  40 value 82.066257
iter  50 value 80.511234
iter  60 value 80.278354
iter  70 value 79.988532
iter  80 value 79.145338
iter  90 value 79.097378
iter 100 value 79.072623
final  value 79.072623 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.855486 
iter  10 value 94.108042
iter  20 value 86.826001
iter  30 value 85.234277
iter  40 value 84.415439
iter  50 value 83.499501
iter  60 value 82.133284
iter  70 value 81.763974
iter  80 value 80.727625
iter  90 value 80.373748
iter 100 value 79.705007
final  value 79.705007 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.289064 
iter  10 value 94.354415
iter  20 value 85.758685
iter  30 value 83.296732
iter  40 value 82.595818
iter  50 value 81.550664
iter  60 value 79.652697
iter  70 value 79.358926
iter  80 value 79.033295
iter  90 value 78.888364
iter 100 value 78.837802
final  value 78.837802 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.505726 
iter  10 value 94.564824
iter  20 value 88.723803
iter  30 value 88.336294
iter  40 value 87.402264
iter  50 value 86.171774
iter  60 value 83.436611
iter  70 value 81.519309
iter  80 value 80.852400
iter  90 value 80.759164
iter 100 value 80.092181
final  value 80.092181 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.882872 
iter  10 value 94.524774
iter  20 value 94.283125
iter  30 value 87.546386
iter  40 value 83.441012
iter  50 value 82.652108
iter  60 value 81.076163
iter  70 value 80.085862
iter  80 value 79.073286
iter  90 value 78.858522
iter 100 value 78.681664
final  value 78.681664 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.070202 
iter  10 value 94.383714
iter  20 value 91.531326
iter  30 value 86.339362
iter  40 value 83.907672
iter  50 value 82.951512
iter  60 value 82.559194
iter  70 value 82.383210
iter  80 value 81.939020
iter  90 value 81.818841
iter 100 value 79.618047
final  value 79.618047 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.845341 
iter  10 value 92.800621
iter  20 value 89.199612
iter  30 value 85.264608
iter  40 value 83.731426
iter  50 value 82.143879
iter  60 value 81.626601
iter  70 value 81.385207
iter  80 value 81.109709
iter  90 value 80.928984
iter 100 value 80.920900
final  value 80.920900 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.039736 
iter  10 value 93.263067
iter  20 value 85.415260
iter  30 value 83.299545
iter  40 value 82.045399
iter  50 value 80.487693
iter  60 value 79.995459
iter  70 value 79.692137
iter  80 value 79.410363
iter  90 value 79.014366
iter 100 value 78.865530
final  value 78.865530 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.535569 
final  value 94.485680 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.311249 
iter  10 value 94.485799
iter  20 value 94.478786
iter  30 value 92.630262
iter  40 value 92.629892
final  value 92.629382 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.013185 
final  value 94.485793 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.217476 
final  value 94.468268 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.664717 
iter  10 value 94.485940
iter  20 value 94.484226
final  value 94.484216 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.486158 
iter  10 value 94.485726
iter  20 value 93.965454
iter  30 value 88.660011
iter  40 value 88.611078
iter  50 value 88.585473
iter  60 value 88.576876
iter  70 value 88.565341
iter  80 value 88.563319
iter  90 value 87.199199
iter 100 value 86.631324
final  value 86.631324 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.250807 
iter  10 value 94.407244
iter  20 value 90.573853
iter  30 value 89.460009
iter  40 value 89.341638
iter  50 value 86.686595
iter  60 value 86.469515
iter  70 value 85.531403
iter  80 value 85.524922
final  value 85.524888 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.863135 
iter  10 value 93.927383
iter  20 value 93.899633
iter  30 value 93.897872
final  value 93.894586 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.879886 
iter  10 value 94.489072
iter  20 value 94.005102
final  value 93.974633 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.394404 
iter  10 value 94.488986
iter  20 value 94.478373
iter  30 value 85.483195
iter  40 value 85.467437
final  value 85.467404 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.430273 
iter  10 value 94.501773
iter  20 value 94.492938
iter  30 value 94.015414
iter  40 value 94.000560
iter  50 value 93.998175
iter  60 value 93.991979
iter  70 value 93.974587
final  value 93.974374 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.130119 
iter  10 value 94.491968
iter  20 value 94.257294
iter  30 value 89.361330
iter  40 value 89.353851
iter  50 value 86.332047
iter  60 value 85.468437
final  value 85.468395 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.660419 
iter  10 value 85.145489
iter  20 value 85.099451
iter  30 value 85.002213
iter  40 value 83.249254
iter  50 value 79.761831
iter  60 value 79.518296
iter  70 value 79.444315
iter  80 value 79.373520
iter  90 value 79.334742
iter 100 value 79.280120
final  value 79.280120 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.445432 
iter  10 value 94.312656
iter  20 value 94.221114
iter  30 value 94.215574
iter  40 value 94.210761
iter  50 value 94.182900
iter  60 value 89.656820
iter  70 value 82.891208
iter  80 value 82.859699
iter  90 value 82.800140
iter 100 value 82.065208
final  value 82.065208 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.455449 
iter  10 value 94.475022
iter  20 value 94.009139
iter  30 value 90.794028
iter  40 value 90.331697
iter  50 value 90.301933
iter  60 value 90.301658
final  value 90.301499 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.688593 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.491120 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.961415 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.209651 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.059887 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.978562 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.408236 
final  value 93.900001 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.898535 
iter  10 value 93.991537
final  value 93.991526 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.929148 
iter  10 value 93.886149
iter  20 value 93.884583
final  value 93.884578 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.186027 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.827289 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.896259 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.709646 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.771907 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.145088 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.821103 
iter  10 value 90.755976
iter  20 value 84.330162
iter  30 value 83.532925
iter  40 value 81.908857
iter  50 value 81.662118
iter  60 value 81.533065
iter  70 value 81.429280
iter  80 value 81.407108
final  value 81.407095 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.611912 
iter  10 value 94.057553
iter  20 value 93.942176
iter  30 value 91.811548
iter  40 value 89.092018
iter  50 value 84.777670
iter  60 value 84.609432
iter  70 value 84.248201
iter  80 value 82.316066
iter  90 value 81.647239
iter 100 value 81.455652
final  value 81.455652 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.138890 
iter  10 value 94.067906
iter  20 value 93.879497
iter  30 value 88.239144
iter  40 value 85.190042
iter  50 value 82.713986
iter  60 value 82.072637
iter  70 value 81.824770
iter  80 value 81.421158
iter  90 value 81.198752
iter 100 value 80.553742
final  value 80.553742 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.295618 
iter  10 value 94.023266
iter  20 value 89.630874
iter  30 value 85.822105
iter  40 value 84.988635
iter  50 value 84.682023
iter  60 value 81.587718
iter  70 value 80.715792
iter  80 value 80.681351
iter  90 value 80.434553
iter 100 value 80.209118
final  value 80.209118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.570711 
iter  10 value 93.747586
iter  20 value 92.979022
iter  30 value 92.191049
iter  40 value 92.130326
iter  50 value 92.012328
iter  60 value 91.685121
iter  70 value 91.683838
iter  80 value 91.682256
iter  80 value 91.682255
iter  80 value 91.682255
final  value 91.682255 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.842064 
iter  10 value 93.345095
iter  20 value 86.718969
iter  30 value 85.432424
iter  40 value 84.137701
iter  50 value 83.535474
iter  60 value 82.720312
iter  70 value 81.105799
iter  80 value 80.658911
iter  90 value 80.196566
iter 100 value 79.571175
final  value 79.571175 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.333421 
iter  10 value 93.872375
iter  20 value 93.629202
iter  30 value 85.771358
iter  40 value 85.549541
iter  50 value 85.091811
iter  60 value 83.118877
iter  70 value 82.877054
iter  80 value 82.323444
iter  90 value 80.299339
iter 100 value 79.348381
final  value 79.348381 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.715076 
iter  10 value 94.051083
iter  20 value 88.967596
iter  30 value 85.826763
iter  40 value 85.341178
iter  50 value 84.050962
iter  60 value 81.320433
iter  70 value 80.919199
iter  80 value 80.494328
iter  90 value 80.443561
iter 100 value 80.389573
final  value 80.389573 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.640874 
iter  10 value 94.065178
iter  20 value 93.543752
iter  30 value 85.824879
iter  40 value 84.515329
iter  50 value 82.140068
iter  60 value 82.034367
iter  70 value 81.581356
iter  80 value 81.396804
iter  90 value 80.933103
iter 100 value 80.629308
final  value 80.629308 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.793076 
iter  10 value 93.928458
iter  20 value 87.194368
iter  30 value 82.538200
iter  40 value 81.224790
iter  50 value 79.309018
iter  60 value 79.231084
iter  70 value 79.200668
iter  80 value 79.090974
iter  90 value 78.850718
iter 100 value 78.760407
final  value 78.760407 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.011083 
iter  10 value 93.054705
iter  20 value 85.536083
iter  30 value 85.214681
iter  40 value 84.835251
iter  50 value 83.151469
iter  60 value 82.336908
iter  70 value 82.161846
iter  80 value 81.148328
iter  90 value 79.568251
iter 100 value 79.031048
final  value 79.031048 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.569491 
iter  10 value 93.822782
iter  20 value 93.527214
iter  30 value 92.142659
iter  40 value 90.574573
iter  50 value 87.407261
iter  60 value 85.086327
iter  70 value 84.556660
iter  80 value 84.382963
iter  90 value 83.062446
iter 100 value 80.894427
final  value 80.894427 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.111293 
iter  10 value 94.444208
iter  20 value 93.094898
iter  30 value 86.475827
iter  40 value 84.130171
iter  50 value 83.771021
iter  60 value 83.450858
iter  70 value 82.833778
iter  80 value 81.132381
iter  90 value 80.447068
iter 100 value 79.995228
final  value 79.995228 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.737428 
iter  10 value 93.985742
iter  20 value 92.858845
iter  30 value 87.459972
iter  40 value 83.814753
iter  50 value 81.436229
iter  60 value 79.368218
iter  70 value 78.887485
iter  80 value 78.631126
iter  90 value 78.412250
iter 100 value 78.296507
final  value 78.296507 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.108362 
iter  10 value 93.886803
iter  20 value 86.563544
iter  30 value 81.922808
iter  40 value 81.581346
iter  50 value 81.492020
iter  60 value 81.451508
iter  70 value 81.278497
iter  80 value 80.851325
iter  90 value 80.796626
iter 100 value 80.590552
final  value 80.590552 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 112.308072 
final  value 94.054755 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.838049 
iter  10 value 94.054331
iter  20 value 94.052457
iter  30 value 86.838214
iter  40 value 82.763408
iter  50 value 82.741164
iter  60 value 81.748456
iter  70 value 80.546212
iter  80 value 80.362483
iter  90 value 80.361327
final  value 80.360372 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.079835 
final  value 94.054393 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.640369 
iter  10 value 93.676804
iter  20 value 93.606091
iter  30 value 93.518293
final  value 93.518289 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.871712 
final  value 94.054663 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.752626 
iter  10 value 94.057744
iter  20 value 94.053077
iter  30 value 93.690381
iter  40 value 91.327193
iter  50 value 90.287668
iter  60 value 88.843386
iter  70 value 85.404533
iter  80 value 81.885048
iter  90 value 79.548089
iter 100 value 79.138099
final  value 79.138099 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.110984 
iter  10 value 94.037642
iter  20 value 94.033532
iter  30 value 93.931501
iter  40 value 93.601648
final  value 93.601615 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.775866 
iter  10 value 94.058283
iter  20 value 93.997198
iter  30 value 93.590861
iter  40 value 93.587790
final  value 93.587788 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.292309 
iter  10 value 94.057696
iter  20 value 94.051123
iter  30 value 92.456198
iter  40 value 92.443078
iter  50 value 92.002457
iter  60 value 92.001472
final  value 92.000769 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.367149 
iter  10 value 93.803969
iter  20 value 93.524222
iter  30 value 93.285679
iter  40 value 93.221939
iter  50 value 93.220179
iter  60 value 93.217415
iter  70 value 93.216499
iter  80 value 93.211554
iter  90 value 91.763568
iter 100 value 91.191622
final  value 91.191622 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.794281 
iter  10 value 92.861834
iter  20 value 92.843381
iter  30 value 92.837536
final  value 92.837212 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.698234 
iter  10 value 94.040983
iter  20 value 94.034263
iter  30 value 86.548854
iter  40 value 86.543874
iter  50 value 86.535861
iter  60 value 86.524075
iter  70 value 86.498664
iter  80 value 86.429895
iter  90 value 85.974807
iter 100 value 85.442572
final  value 85.442572 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.794154 
iter  10 value 94.060568
iter  20 value 94.054302
iter  30 value 91.024866
iter  40 value 84.483581
iter  50 value 84.419788
iter  60 value 84.402422
iter  70 value 84.399910
iter  80 value 84.375615
iter  90 value 84.352024
iter 100 value 84.340178
final  value 84.340178 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.697743 
iter  10 value 94.057862
iter  20 value 93.817466
iter  30 value 93.598594
iter  40 value 87.462955
iter  50 value 85.190427
iter  60 value 85.159148
iter  70 value 84.709144
iter  80 value 82.079581
iter  90 value 81.079122
iter 100 value 80.709455
final  value 80.709455 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.251266 
iter  10 value 93.612882
iter  20 value 93.518729
iter  30 value 93.300327
iter  40 value 93.214221
final  value 93.214219 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.097084 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.731524 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.446171 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.669830 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.660420 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.156727 
iter  10 value 93.924032
iter  20 value 93.908609
final  value 93.907602 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.514339 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.252916 
final  value 94.275345 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.683529 
iter  10 value 94.275763
final  value 94.275345 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.403658 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 93.376126 
iter  10 value 85.560183
iter  20 value 85.290310
final  value 85.289851 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.174025 
iter  10 value 94.275400
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.107701 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.535850 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.807118 
iter  10 value 93.993779
iter  20 value 88.360533
iter  30 value 85.093058
iter  40 value 85.074629
iter  50 value 85.074524
final  value 85.074519 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.061273 
iter  10 value 94.488418
iter  20 value 92.683932
iter  30 value 92.509806
iter  40 value 85.368335
iter  50 value 84.450118
iter  60 value 84.230686
iter  70 value 84.184742
iter  80 value 83.943621
iter  90 value 83.788205
final  value 83.774299 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.727855 
iter  10 value 94.489171
iter  20 value 94.146698
iter  30 value 92.982245
iter  40 value 86.424012
iter  50 value 85.965881
iter  60 value 84.107614
iter  70 value 83.792512
iter  80 value 83.790067
iter  90 value 83.048653
iter 100 value 81.893814
final  value 81.893814 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.623557 
iter  10 value 94.481269
iter  20 value 92.140318
iter  30 value 86.119248
iter  40 value 85.675610
iter  50 value 83.934007
iter  60 value 82.670984
iter  70 value 81.948698
iter  80 value 81.749399
iter  90 value 81.742222
final  value 81.742216 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.077104 
iter  10 value 94.443274
iter  20 value 91.273281
iter  30 value 90.096863
iter  40 value 89.794713
iter  50 value 84.191311
iter  60 value 83.969993
iter  70 value 83.799096
iter  80 value 83.774341
final  value 83.774298 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.226718 
iter  10 value 94.473673
iter  20 value 94.335710
iter  30 value 94.034053
iter  40 value 94.018892
iter  50 value 93.710588
iter  60 value 88.542011
iter  70 value 86.738394
iter  80 value 85.964463
iter  90 value 85.737415
iter 100 value 84.644551
final  value 84.644551 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.104247 
iter  10 value 94.591730
iter  20 value 88.982484
iter  30 value 86.049064
iter  40 value 82.274830
iter  50 value 81.549749
iter  60 value 81.108784
iter  70 value 80.643179
iter  80 value 80.404498
iter  90 value 80.306214
iter 100 value 80.208822
final  value 80.208822 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 128.403232 
iter  10 value 94.441720
iter  20 value 85.272176
iter  30 value 84.399283
iter  40 value 84.248788
iter  50 value 83.889868
iter  60 value 83.534490
iter  70 value 83.081361
iter  80 value 82.016113
iter  90 value 81.368611
iter 100 value 80.998069
final  value 80.998069 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.027586 
iter  10 value 94.500195
iter  20 value 87.410674
iter  30 value 85.306812
iter  40 value 83.931000
iter  50 value 83.812708
iter  60 value 83.637441
iter  70 value 83.509467
iter  80 value 83.226664
iter  90 value 81.607940
iter 100 value 80.845818
final  value 80.845818 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.683400 
iter  10 value 94.512982
iter  20 value 91.222075
iter  30 value 86.521356
iter  40 value 83.739356
iter  50 value 83.039972
iter  60 value 82.571295
iter  70 value 82.133415
iter  80 value 81.537182
iter  90 value 81.058780
iter 100 value 80.912069
final  value 80.912069 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.793249 
iter  10 value 95.055070
iter  20 value 86.096731
iter  30 value 85.600030
iter  40 value 84.029322
iter  50 value 83.484499
iter  60 value 83.463817
iter  70 value 83.200633
iter  80 value 82.664661
iter  90 value 81.153642
iter 100 value 80.933568
final  value 80.933568 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.864079 
iter  10 value 94.478079
iter  20 value 93.430312
iter  30 value 84.971270
iter  40 value 83.284997
iter  50 value 81.416466
iter  60 value 80.769400
iter  70 value 80.430569
iter  80 value 80.355818
iter  90 value 80.210010
iter 100 value 80.126864
final  value 80.126864 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.595065 
iter  10 value 94.691711
iter  20 value 89.962566
iter  30 value 85.945648
iter  40 value 83.892844
iter  50 value 83.531341
iter  60 value 83.468394
iter  70 value 82.182783
iter  80 value 81.168542
iter  90 value 80.722549
iter 100 value 80.624592
final  value 80.624592 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.898478 
iter  10 value 92.978642
iter  20 value 85.401028
iter  30 value 82.851980
iter  40 value 82.343226
iter  50 value 81.824284
iter  60 value 80.887182
iter  70 value 80.547622
iter  80 value 80.417632
iter  90 value 80.231678
iter 100 value 80.130580
final  value 80.130580 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.406107 
iter  10 value 95.049363
iter  20 value 93.487627
iter  30 value 89.634925
iter  40 value 85.527484
iter  50 value 83.670735
iter  60 value 82.130572
iter  70 value 81.084304
iter  80 value 80.789761
iter  90 value 80.748338
iter 100 value 80.669690
final  value 80.669690 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.271715 
iter  10 value 94.847249
iter  20 value 94.507512
iter  30 value 93.339327
iter  40 value 86.113936
iter  50 value 83.913667
iter  60 value 83.695622
iter  70 value 82.863593
iter  80 value 81.623724
iter  90 value 81.035257
iter 100 value 80.791905
final  value 80.791905 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.299555 
iter  10 value 94.276901
iter  20 value 94.139009
final  value 91.654096 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.266069 
final  value 94.485566 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.032218 
iter  10 value 94.277110
iter  20 value 94.209450
iter  30 value 82.934488
iter  40 value 82.895206
iter  50 value 82.886248
final  value 82.886137 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.393047 
final  value 94.486034 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.754465 
iter  10 value 94.485933
iter  20 value 94.474521
iter  30 value 93.921400
final  value 93.921366 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.380435 
iter  10 value 94.489184
iter  20 value 94.450868
iter  30 value 93.949491
iter  40 value 89.976852
iter  50 value 85.278775
iter  60 value 85.268252
iter  70 value 84.787665
iter  80 value 82.014910
iter  90 value 81.030275
iter 100 value 80.300596
final  value 80.300596 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.505142 
iter  10 value 94.489058
iter  20 value 94.476453
iter  30 value 91.390332
final  value 91.269849 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.435065 
iter  10 value 94.280829
iter  20 value 94.277038
iter  30 value 85.332652
iter  40 value 85.064464
iter  40 value 85.064464
iter  40 value 85.064464
final  value 85.064464 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.235874 
iter  10 value 94.488833
iter  20 value 92.063721
iter  30 value 91.655129
iter  40 value 91.652960
iter  50 value 90.385278
iter  60 value 82.967482
iter  70 value 82.820466
iter  80 value 82.819272
iter  90 value 82.819147
final  value 82.818803 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.537968 
iter  10 value 94.489175
iter  20 value 94.014848
iter  30 value 91.653857
final  value 91.653434 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.914343 
iter  10 value 94.283987
iter  20 value 94.215534
iter  30 value 93.722306
iter  40 value 91.906027
iter  50 value 91.569479
iter  60 value 91.462992
iter  70 value 91.453503
iter  80 value 91.453123
iter  90 value 86.147013
iter 100 value 85.282089
final  value 85.282089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.017569 
iter  10 value 93.383906
iter  20 value 93.376640
iter  30 value 93.306545
iter  40 value 90.199702
iter  50 value 82.704226
iter  60 value 82.689611
iter  70 value 82.689326
iter  80 value 82.688793
iter  90 value 82.688553
iter 100 value 82.342798
final  value 82.342798 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.196504 
iter  10 value 94.310013
iter  20 value 94.284666
iter  30 value 94.280089
iter  40 value 94.276867
iter  50 value 93.847967
iter  60 value 90.433318
iter  70 value 88.267212
iter  80 value 88.252181
iter  90 value 88.251596
iter 100 value 88.251077
final  value 88.251077 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.305396 
iter  10 value 94.283668
iter  20 value 93.946394
iter  30 value 89.473667
iter  40 value 89.079764
iter  50 value 87.074502
iter  60 value 86.432842
iter  70 value 86.256374
iter  80 value 86.147697
iter  90 value 86.147255
iter 100 value 86.126147
final  value 86.126147 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.338613 
iter  10 value 94.492090
iter  20 value 94.408222
iter  30 value 87.047627
final  value 87.047625 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.943190 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.470729 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.171683 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.534568 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.890759 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.086594 
iter  10 value 94.011438
final  value 94.011429 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.800322 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.182435 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.187296 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.208387 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.122379 
iter  10 value 93.791151
final  value 93.790891 
converged
Fitting Repeat 2 

# weights:  507
initial  value 131.858854 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.324855 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.812346 
iter  10 value 93.770696
final  value 93.734703 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.315458 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.878017 
iter  10 value 94.052639
iter  20 value 93.499868
iter  30 value 92.502147
iter  40 value 92.244482
iter  50 value 92.169909
iter  60 value 86.483621
iter  70 value 85.479630
iter  80 value 85.217117
iter  90 value 85.093044
final  value 85.092660 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.546125 
iter  10 value 94.036941
iter  20 value 91.438455
iter  30 value 87.140960
iter  40 value 85.184789
iter  50 value 84.794346
iter  60 value 84.703290
iter  70 value 84.679224
iter  80 value 84.676198
final  value 84.676195 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.902602 
iter  10 value 93.888686
iter  20 value 92.496318
iter  30 value 88.165107
iter  40 value 86.959711
iter  50 value 85.790582
iter  60 value 85.234256
iter  70 value 83.795501
iter  80 value 83.551274
iter  90 value 83.494223
iter 100 value 83.430631
final  value 83.430631 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.433097 
iter  10 value 94.054951
iter  20 value 93.963717
iter  30 value 92.006235
iter  40 value 87.256085
iter  50 value 85.910491
iter  60 value 85.211655
iter  70 value 85.132288
iter  80 value 84.830105
iter  90 value 84.684617
final  value 84.676195 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.503037 
iter  10 value 94.055054
iter  20 value 92.303675
iter  30 value 87.040942
iter  40 value 85.690419
iter  50 value 84.823763
iter  60 value 84.696112
iter  70 value 84.681799
iter  80 value 84.677004
iter  90 value 84.676199
final  value 84.676195 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.825376 
iter  10 value 94.022752
iter  20 value 87.370691
iter  30 value 86.440190
iter  40 value 85.137119
iter  50 value 83.953269
iter  60 value 82.679208
iter  70 value 82.445307
iter  80 value 82.361712
iter  90 value 82.315320
iter 100 value 82.301328
final  value 82.301328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.799124 
iter  10 value 93.943363
iter  20 value 86.177363
iter  30 value 85.867620
iter  40 value 85.698876
iter  50 value 84.216843
iter  60 value 83.654782
iter  70 value 83.370782
iter  80 value 83.171448
iter  90 value 83.037747
iter 100 value 82.559357
final  value 82.559357 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.071796 
iter  10 value 94.432679
iter  20 value 94.103293
iter  30 value 91.176154
iter  40 value 90.142608
iter  50 value 87.982495
iter  60 value 86.255727
iter  70 value 85.255690
iter  80 value 84.915794
iter  90 value 84.787127
iter 100 value 84.573511
final  value 84.573511 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.450796 
iter  10 value 93.914660
iter  20 value 89.167710
iter  30 value 87.476623
iter  40 value 85.168424
iter  50 value 84.413675
iter  60 value 83.649114
iter  70 value 83.127090
iter  80 value 82.800670
iter  90 value 82.568584
iter 100 value 82.553830
final  value 82.553830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.175177 
iter  10 value 93.654823
iter  20 value 91.058599
iter  30 value 87.729463
iter  40 value 87.301140
iter  50 value 86.031094
iter  60 value 85.781227
iter  70 value 84.758312
iter  80 value 83.024793
iter  90 value 82.843743
iter 100 value 82.787879
final  value 82.787879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.822418 
iter  10 value 94.207581
iter  20 value 93.910950
iter  30 value 93.845145
iter  40 value 89.587438
iter  50 value 87.457608
iter  60 value 85.735853
iter  70 value 84.771914
iter  80 value 84.432897
iter  90 value 83.970359
iter 100 value 83.247121
final  value 83.247121 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.462651 
iter  10 value 94.312074
iter  20 value 93.583918
iter  30 value 92.125962
iter  40 value 90.871921
iter  50 value 90.621509
iter  60 value 88.366476
iter  70 value 85.711295
iter  80 value 84.993186
iter  90 value 84.120641
iter 100 value 83.810825
final  value 83.810825 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.897300 
iter  10 value 96.543600
iter  20 value 94.077642
iter  30 value 93.305582
iter  40 value 85.494440
iter  50 value 84.265623
iter  60 value 83.656033
iter  70 value 82.977389
iter  80 value 82.532256
iter  90 value 82.333533
iter 100 value 81.948085
final  value 81.948085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.473103 
iter  10 value 91.888778
iter  20 value 86.289451
iter  30 value 85.755812
iter  40 value 84.175083
iter  50 value 83.102567
iter  60 value 82.854595
iter  70 value 82.704583
iter  80 value 82.669055
iter  90 value 82.648581
iter 100 value 82.625506
final  value 82.625506 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.134961 
iter  10 value 95.161939
iter  20 value 93.056420
iter  30 value 92.839158
iter  40 value 92.644151
iter  50 value 87.306792
iter  60 value 84.409633
iter  70 value 83.661247
iter  80 value 82.865332
iter  90 value 82.175998
iter 100 value 82.042474
final  value 82.042474 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.880041 
final  value 94.054760 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.208842 
final  value 94.055142 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.057642 
iter  10 value 94.054560
iter  20 value 94.019276
iter  30 value 86.471137
final  value 86.469585 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.534973 
final  value 94.054535 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.767800 
final  value 94.054551 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.058736 
iter  10 value 93.704516
iter  20 value 93.702128
iter  30 value 93.694694
iter  40 value 91.950977
iter  50 value 87.003908
iter  60 value 84.820186
iter  70 value 84.413888
iter  80 value 84.303165
iter  90 value 84.302681
final  value 84.302385 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.987117 
iter  10 value 93.814894
iter  20 value 93.791334
iter  30 value 93.787741
iter  40 value 93.741683
iter  50 value 89.902834
iter  60 value 85.775495
final  value 85.750161 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.137907 
iter  10 value 94.057902
iter  20 value 94.052772
iter  30 value 86.505809
iter  40 value 85.449650
iter  50 value 85.436145
iter  60 value 85.435939
iter  60 value 85.435938
final  value 85.435938 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.789014 
iter  10 value 94.016533
iter  20 value 93.815353
iter  30 value 93.765041
final  value 93.728929 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.928928 
iter  10 value 93.841062
iter  20 value 93.839585
iter  30 value 93.752285
iter  40 value 92.145177
iter  50 value 86.997777
iter  60 value 84.604297
iter  70 value 84.579002
iter  80 value 84.555564
iter  90 value 84.351198
iter 100 value 81.589483
final  value 81.589483 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.197666 
iter  10 value 93.844308
iter  20 value 93.791552
final  value 93.786568 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.940543 
iter  10 value 86.936212
iter  20 value 86.806836
iter  30 value 86.799621
iter  40 value 86.733623
final  value 86.731182 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.275903 
iter  10 value 93.946721
iter  20 value 87.681170
iter  30 value 87.573209
iter  40 value 87.506544
final  value 87.504947 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.928926 
iter  10 value 93.844638
iter  20 value 93.837229
iter  30 value 93.771847
iter  40 value 89.813608
iter  50 value 86.842271
iter  60 value 86.836250
iter  70 value 86.836145
iter  80 value 85.998459
iter  90 value 84.427237
iter 100 value 83.438130
final  value 83.438130 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.805560 
iter  10 value 93.844361
iter  20 value 93.600134
iter  30 value 88.384649
iter  40 value 84.863064
iter  50 value 84.780250
final  value 84.780033 
converged
Fitting Repeat 1 

# weights:  103
initial  value 122.218602 
iter  10 value 117.635160
iter  20 value 117.604194
iter  30 value 110.046940
iter  40 value 107.305496
iter  50 value 107.061511
iter  60 value 104.801766
iter  70 value 102.933539
iter  80 value 102.369598
iter  90 value 102.100011
final  value 102.094538 
converged
Fitting Repeat 2 

# weights:  103
initial  value 121.087332 
iter  10 value 117.534034
iter  20 value 110.303014
iter  30 value 109.670790
iter  40 value 107.721600
iter  50 value 107.458286
iter  60 value 106.231398
iter  70 value 105.850038
iter  80 value 105.646535
iter  90 value 105.262609
iter 100 value 105.258656
final  value 105.258656 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 120.481147 
iter  10 value 117.831046
iter  20 value 117.242088
iter  30 value 109.193552
iter  40 value 107.032534
iter  50 value 105.291369
iter  60 value 103.559951
iter  70 value 103.539018
final  value 103.538053 
converged
Fitting Repeat 4 

# weights:  103
initial  value 123.910030 
iter  10 value 117.892722
iter  20 value 117.635048
iter  30 value 115.557632
iter  40 value 113.341626
iter  50 value 109.788099
iter  60 value 106.925749
iter  70 value 106.272778
iter  80 value 105.643076
iter  90 value 105.566340
iter  90 value 105.566339
iter  90 value 105.566339
final  value 105.566339 
converged
Fitting Repeat 5 

# weights:  103
initial  value 125.755205 
iter  10 value 117.894182
iter  20 value 117.803508
iter  30 value 116.872017
iter  40 value 110.343700
iter  50 value 104.817024
iter  60 value 103.905588
iter  70 value 103.481011
iter  80 value 103.229133
iter  90 value 102.849596
iter 100 value 102.692735
final  value 102.692735 
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 -- Sun Apr 12 20:15:38 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 
 19.427   0.683  78.044