##############################################################################
##############################################################################
###
### 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_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 Patched (2026-05-01 r89994)
* 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: 2026-05-23 00:00:04 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      16.799  0.063  17.036
var_imp       16.726  0.073  16.823
corr_plot     16.597  0.086  16.709
pred_ensembel  6.028  0.071   5.434
enrichfindP    0.200  0.036  24.418
* 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-3.24-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 ‘1.19.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
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
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 98.845451 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.570073 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.153486 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.073883 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.783977 
iter  10 value 91.895257
iter  20 value 84.247496
iter  30 value 83.926409
iter  40 value 83.919381
final  value 83.919374 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.020416 
iter  10 value 93.391899
final  value 93.391892 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.028738 
iter  10 value 93.188713
iter  20 value 92.567603
iter  30 value 92.566668
iter  30 value 92.566667
iter  30 value 92.566667
final  value 92.566667 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.161314 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.190810 
iter  10 value 93.284261
iter  20 value 93.283469
final  value 93.283442 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.363918 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.731240 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.040733 
iter  10 value 93.391892
iter  10 value 93.391892
iter  10 value 93.391892
final  value 93.391892 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.622087 
iter  10 value 93.405895
final  value 93.391892 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.194813 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.926177 
iter  10 value 93.496726
final  value 93.391892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.205914 
iter  10 value 94.049689
iter  20 value 93.089474
iter  30 value 92.903680
iter  40 value 92.099397
iter  50 value 86.188718
iter  60 value 82.658897
iter  70 value 81.825584
iter  80 value 81.317450
iter  90 value 80.226676
iter 100 value 80.025851
final  value 80.025851 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.865533 
iter  10 value 93.524236
iter  20 value 85.346232
iter  30 value 84.857253
iter  40 value 84.787080
iter  50 value 84.709258
iter  60 value 84.649986
iter  70 value 84.512981
final  value 84.502942 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.993684 
iter  10 value 94.038397
iter  20 value 91.608344
iter  30 value 91.172655
iter  40 value 90.929364
iter  50 value 90.928304
final  value 90.928276 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.375782 
iter  10 value 94.189296
iter  20 value 94.055259
iter  30 value 85.450716
iter  40 value 84.687336
iter  50 value 84.209449
iter  60 value 82.483125
iter  70 value 82.427668
iter  80 value 82.425783
final  value 82.425755 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.393362 
iter  10 value 94.056684
iter  20 value 93.969596
iter  30 value 89.015777
iter  40 value 85.097592
iter  50 value 84.062684
iter  60 value 83.338673
iter  70 value 83.239438
iter  80 value 83.094648
iter  90 value 81.992819
iter 100 value 81.788245
final  value 81.788245 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.167973 
iter  10 value 94.421255
iter  20 value 94.143303
iter  30 value 90.330058
iter  40 value 86.710896
iter  50 value 85.493309
iter  60 value 84.715922
iter  70 value 84.048380
iter  80 value 82.484876
iter  90 value 81.916744
iter 100 value 81.790670
final  value 81.790670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.944194 
iter  10 value 93.209380
iter  20 value 86.502766
iter  30 value 84.429063
iter  40 value 82.608019
iter  50 value 82.418943
iter  60 value 82.103294
iter  70 value 81.302521
iter  80 value 80.753819
iter  90 value 80.329399
iter 100 value 80.068122
final  value 80.068122 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.914857 
iter  10 value 92.383269
iter  20 value 84.280748
iter  30 value 83.686176
iter  40 value 83.386247
iter  50 value 83.066545
iter  60 value 82.668928
iter  70 value 81.296058
iter  80 value 79.980747
iter  90 value 79.899783
iter 100 value 79.752737
final  value 79.752737 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.001802 
iter  10 value 94.053046
iter  20 value 92.638385
iter  30 value 84.244077
iter  40 value 83.885341
iter  50 value 83.690924
iter  60 value 82.584120
iter  70 value 81.247140
iter  80 value 80.109780
iter  90 value 79.689722
iter 100 value 79.538058
final  value 79.538058 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.218905 
iter  10 value 94.143036
iter  20 value 92.104541
iter  30 value 88.679664
iter  40 value 83.432801
iter  50 value 82.093677
iter  60 value 80.427678
iter  70 value 80.122746
iter  80 value 80.001692
iter  90 value 79.534906
iter 100 value 79.262298
final  value 79.262298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.305186 
iter  10 value 94.161505
iter  20 value 94.016344
iter  30 value 88.168502
iter  40 value 84.765010
iter  50 value 83.389588
iter  60 value 82.078644
iter  70 value 81.628041
iter  80 value 81.345124
iter  90 value 80.534229
iter 100 value 79.563524
final  value 79.563524 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.856045 
iter  10 value 96.890750
iter  20 value 93.326047
iter  30 value 92.019520
iter  40 value 89.477622
iter  50 value 84.818148
iter  60 value 80.744009
iter  70 value 80.102720
iter  80 value 79.466736
iter  90 value 79.156306
iter 100 value 78.774451
final  value 78.774451 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.162040 
iter  10 value 97.221553
iter  20 value 95.280014
iter  30 value 89.083394
iter  40 value 84.398474
iter  50 value 83.306566
iter  60 value 81.387726
iter  70 value 80.101389
iter  80 value 79.386900
iter  90 value 79.181416
iter 100 value 79.006057
final  value 79.006057 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.995293 
iter  10 value 100.181927
iter  20 value 93.907809
iter  30 value 93.516120
iter  40 value 93.036859
iter  50 value 86.485998
iter  60 value 82.491667
iter  70 value 81.810481
iter  80 value 81.091492
iter  90 value 80.696056
iter 100 value 79.975742
final  value 79.975742 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.368018 
iter  10 value 94.459620
iter  20 value 93.488098
iter  30 value 87.807368
iter  40 value 82.940479
iter  50 value 81.061717
iter  60 value 80.479824
iter  70 value 79.957704
iter  80 value 79.548292
iter  90 value 79.449084
iter 100 value 79.344763
final  value 79.344763 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.296901 
iter  10 value 94.054655
iter  20 value 93.945818
iter  30 value 90.523059
iter  40 value 89.627457
iter  50 value 89.626470
iter  60 value 89.624306
iter  70 value 89.623463
iter  80 value 89.622670
iter  80 value 89.622670
iter  80 value 89.622670
final  value 89.622670 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.235572 
iter  10 value 94.054520
iter  20 value 94.052995
iter  30 value 93.331855
iter  40 value 84.578003
iter  50 value 82.126905
iter  60 value 82.073307
final  value 82.072979 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.998307 
iter  10 value 94.054337
iter  20 value 94.052863
iter  30 value 92.362170
iter  40 value 85.912842
iter  50 value 85.911672
iter  60 value 85.908335
iter  70 value 85.861372
iter  80 value 85.795782
iter  90 value 85.790797
iter 100 value 85.608640
final  value 85.608640 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.983719 
final  value 94.054617 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.806591 
final  value 94.054828 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.198687 
iter  10 value 86.319152
iter  20 value 86.098547
final  value 86.097452 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.787902 
iter  10 value 93.397397
iter  20 value 93.396370
iter  30 value 93.328409
iter  40 value 90.066600
iter  50 value 87.424541
iter  60 value 87.274986
iter  70 value 87.267900
iter  80 value 87.144997
iter  90 value 87.141296
iter 100 value 87.140266
final  value 87.140266 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.081688 
iter  10 value 93.933981
iter  20 value 93.397018
iter  30 value 93.393086
final  value 93.392338 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.401001 
iter  10 value 94.057724
iter  20 value 93.988689
iter  30 value 92.059396
iter  40 value 87.532636
iter  50 value 87.491190
final  value 87.491169 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.720529 
iter  10 value 86.514299
iter  20 value 85.748557
iter  30 value 85.722300
iter  40 value 85.520497
iter  50 value 85.511371
iter  60 value 85.510616
iter  70 value 85.494776
iter  80 value 85.413162
iter  90 value 85.400045
final  value 85.399951 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.182742 
iter  10 value 93.388498
iter  20 value 93.387250
iter  30 value 93.379877
iter  40 value 93.235064
iter  50 value 90.244327
iter  60 value 89.247398
iter  70 value 88.837138
iter  80 value 88.796852
iter  90 value 88.783035
iter 100 value 88.712833
final  value 88.712833 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.415992 
iter  10 value 92.319387
iter  20 value 92.196350
iter  30 value 91.706452
iter  40 value 91.685314
iter  50 value 91.650686
iter  60 value 91.648142
iter  70 value 91.645446
iter  80 value 91.255302
iter  90 value 89.101583
iter 100 value 82.860948
final  value 82.860948 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.697420 
iter  10 value 94.053415
iter  20 value 93.741699
iter  30 value 91.897243
final  value 91.897146 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.204851 
iter  10 value 93.391245
iter  20 value 93.377087
iter  30 value 93.366990
final  value 93.366893 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.075198 
iter  10 value 93.635747
iter  20 value 93.389102
iter  30 value 93.385370
iter  40 value 93.373263
iter  50 value 92.977964
iter  60 value 92.936474
iter  70 value 92.935779
final  value 92.935334 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.196503 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.065147 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.614689 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.012365 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.280313 
final  value 94.052909 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.136910 
final  value 93.810010 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.353266 
final  value 92.892737 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.160320 
iter  10 value 94.613473
iter  20 value 93.926762
iter  30 value 93.582418
iter  30 value 93.582418
iter  30 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.614028 
iter  10 value 91.540510
iter  20 value 90.829178
iter  30 value 88.719777
iter  40 value 84.779221
iter  50 value 82.699423
final  value 82.640307 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.981984 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.708422 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.329488 
iter  10 value 93.582420
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.229990 
final  value 93.900821 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.532437 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.825952 
iter  10 value 93.183994
final  value 93.183861 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.071360 
iter  10 value 93.318077
iter  20 value 84.460563
iter  30 value 84.379084
iter  40 value 83.491038
iter  50 value 82.247363
iter  60 value 81.406017
iter  70 value 81.168863
iter  80 value 80.707570
final  value 80.689200 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.043009 
iter  10 value 94.056506
iter  20 value 88.799049
iter  30 value 84.084279
iter  40 value 83.844519
iter  50 value 83.631340
iter  60 value 83.597943
iter  70 value 83.593855
iter  70 value 83.593855
iter  70 value 83.593855
final  value 83.593855 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.124199 
iter  10 value 94.054956
iter  20 value 92.909872
iter  30 value 85.423687
iter  40 value 84.452040
iter  50 value 83.285073
iter  60 value 83.209985
iter  70 value 83.209488
final  value 83.209483 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.841178 
iter  10 value 94.049924
iter  20 value 93.724906
iter  30 value 93.481922
iter  40 value 93.434515
iter  50 value 92.449877
iter  60 value 89.739006
iter  70 value 89.570062
iter  80 value 89.540673
iter  90 value 89.539807
iter 100 value 88.294965
final  value 88.294965 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.894951 
iter  10 value 94.061798
final  value 94.054915 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.499125 
iter  10 value 94.009681
iter  20 value 93.178861
iter  30 value 92.973935
iter  40 value 83.120045
iter  50 value 81.720982
iter  60 value 81.456953
iter  70 value 80.936850
iter  80 value 80.575727
iter  90 value 80.438500
iter 100 value 80.433500
final  value 80.433500 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.100989 
iter  10 value 94.100667
iter  20 value 90.961264
iter  30 value 85.276527
iter  40 value 83.604292
iter  50 value 83.465692
iter  60 value 83.311970
iter  70 value 81.239943
iter  80 value 80.940266
iter  90 value 80.843073
iter 100 value 80.803458
final  value 80.803458 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 122.990323 
iter  10 value 94.270819
iter  20 value 93.221712
iter  30 value 84.476045
iter  40 value 82.689478
iter  50 value 81.798842
iter  60 value 81.247719
iter  70 value 81.023884
iter  80 value 80.881306
iter  90 value 80.802010
iter 100 value 80.779096
final  value 80.779096 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.486369 
iter  10 value 91.459948
iter  20 value 86.829801
iter  30 value 85.266142
iter  40 value 82.309028
iter  50 value 80.921789
iter  60 value 80.298352
iter  70 value 80.213377
iter  80 value 80.093573
iter  90 value 79.850919
iter 100 value 79.737834
final  value 79.737834 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.678233 
iter  10 value 94.067007
iter  20 value 93.196093
iter  30 value 92.984146
iter  40 value 88.480449
iter  50 value 87.558905
iter  60 value 82.064206
iter  70 value 81.490329
iter  80 value 81.408113
iter  90 value 81.184772
iter 100 value 80.782824
final  value 80.782824 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.532522 
iter  10 value 93.870111
iter  20 value 92.905958
iter  30 value 85.877501
iter  40 value 84.447197
iter  50 value 83.458179
iter  60 value 80.751519
iter  70 value 79.647465
iter  80 value 79.209848
iter  90 value 79.052338
iter 100 value 78.980612
final  value 78.980612 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 133.557101 
iter  10 value 94.173595
iter  20 value 93.294498
iter  30 value 91.412167
iter  40 value 86.112049
iter  50 value 85.257682
iter  60 value 83.928260
iter  70 value 81.935752
iter  80 value 81.731236
iter  90 value 81.122853
iter 100 value 80.412018
final  value 80.412018 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.003719 
iter  10 value 89.395308
iter  20 value 83.740588
iter  30 value 82.852938
iter  40 value 81.114818
iter  50 value 80.121989
iter  60 value 79.845395
iter  70 value 79.539214
iter  80 value 79.119989
iter  90 value 78.953432
iter 100 value 78.807250
final  value 78.807250 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.456121 
iter  10 value 94.059033
iter  20 value 90.028869
iter  30 value 82.056848
iter  40 value 80.390335
iter  50 value 79.925167
iter  60 value 79.677094
iter  70 value 79.552797
iter  80 value 79.124863
iter  90 value 79.013554
iter 100 value 78.977740
final  value 78.977740 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.817981 
iter  10 value 94.006944
iter  20 value 87.610899
iter  30 value 86.956229
iter  40 value 85.063151
iter  50 value 82.884266
iter  60 value 81.851612
iter  70 value 81.769528
iter  80 value 81.590069
iter  90 value 81.361838
iter 100 value 80.617527
final  value 80.617527 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.239426 
final  value 94.054528 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.206697 
final  value 94.054371 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.630575 
final  value 94.054309 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.033505 
iter  10 value 94.054499
iter  20 value 94.052939
iter  30 value 86.166030
final  value 85.980300 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.979054 
iter  10 value 94.054570
final  value 94.052914 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.044455 
iter  10 value 94.055680
iter  20 value 89.607568
iter  30 value 88.367315
iter  40 value 82.286786
iter  50 value 80.431210
iter  60 value 79.588065
iter  70 value 79.517980
iter  80 value 79.491015
iter  90 value 79.484329
iter 100 value 79.480203
final  value 79.480203 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.064914 
iter  10 value 93.361558
iter  20 value 93.357187
iter  30 value 93.342550
final  value 93.342534 
converged
Fitting Repeat 3 

# weights:  305
initial  value 117.327472 
iter  10 value 94.057920
iter  20 value 94.052938
iter  30 value 93.330474
iter  40 value 84.813407
iter  50 value 84.794167
iter  60 value 84.781463
iter  70 value 84.697170
iter  80 value 84.694783
iter  90 value 82.724119
iter 100 value 82.581337
final  value 82.581337 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.038497 
iter  10 value 94.057477
iter  20 value 93.997654
iter  30 value 93.542849
iter  40 value 87.816661
final  value 87.810821 
converged
Fitting Repeat 5 

# weights:  305
initial  value 93.900103 
iter  10 value 93.499433
iter  20 value 93.498321
iter  30 value 91.612707
iter  40 value 91.611463
iter  50 value 91.610530
iter  60 value 91.609659
iter  70 value 91.609055
iter  80 value 91.608738
final  value 91.608627 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.761521 
iter  10 value 94.041090
iter  20 value 93.591530
iter  30 value 89.947337
iter  40 value 82.737205
final  value 82.737185 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.075125 
iter  10 value 88.031828
iter  20 value 85.766068
iter  30 value 85.760060
iter  40 value 85.705287
iter  50 value 85.209442
iter  60 value 82.579664
iter  70 value 82.564674
iter  80 value 82.563977
iter  90 value 82.563236
iter 100 value 82.558678
final  value 82.558678 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.788210 
iter  10 value 87.444661
iter  20 value 83.864737
iter  30 value 83.086430
final  value 83.085663 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.170017 
iter  10 value 93.590811
iter  20 value 89.571921
iter  30 value 80.665422
iter  40 value 80.487736
iter  50 value 80.466057
iter  60 value 80.455431
iter  70 value 80.381075
iter  80 value 79.745315
iter  90 value 78.816483
iter 100 value 78.674804
final  value 78.674804 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.411633 
iter  10 value 92.705210
iter  20 value 87.022801
iter  30 value 85.998669
iter  40 value 85.989482
iter  50 value 85.988310
iter  60 value 85.894781
iter  70 value 85.627090
iter  80 value 80.643182
iter  90 value 79.927754
iter 100 value 78.778529
final  value 78.778529 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.894178 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.816637 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.624898 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.708681 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.343348 
iter  10 value 93.976995
iter  20 value 93.976246
iter  20 value 93.976246
iter  20 value 93.976246
final  value 93.976246 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.111386 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.143192 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.446592 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.848135 
final  value 93.320225 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.659840 
iter  10 value 93.912135
iter  20 value 93.162536
final  value 93.124243 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.997263 
final  value 93.320225 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.841387 
final  value 94.304608 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.900584 
iter  10 value 94.026545
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.386176 
iter  10 value 94.521242
iter  20 value 94.312226
final  value 94.312038 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.553496 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.154819 
iter  10 value 94.203829
iter  20 value 91.148318
iter  30 value 86.045520
iter  40 value 84.872211
iter  50 value 84.602352
final  value 84.598456 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.002201 
iter  10 value 94.486869
iter  20 value 92.532921
iter  30 value 86.265264
iter  40 value 85.974571
iter  50 value 85.676895
iter  60 value 85.457135
iter  70 value 83.255193
iter  80 value 82.645754
iter  90 value 81.946131
iter 100 value 81.880278
final  value 81.880278 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.818514 
iter  10 value 94.518355
iter  20 value 93.752739
iter  30 value 93.163535
iter  40 value 91.026797
iter  50 value 85.037758
iter  60 value 84.374105
iter  70 value 82.537769
iter  80 value 81.755791
iter  90 value 81.588568
iter 100 value 81.566800
final  value 81.566800 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.637589 
iter  10 value 94.422600
iter  20 value 93.545981
iter  30 value 93.267180
iter  40 value 93.259344
iter  50 value 93.154388
iter  60 value 91.440693
iter  70 value 85.030742
iter  80 value 84.945342
iter  90 value 83.883851
iter 100 value 83.133867
final  value 83.133867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.706139 
iter  10 value 94.128192
iter  20 value 93.451797
iter  30 value 88.226399
iter  40 value 87.279782
iter  50 value 86.334444
iter  60 value 83.391407
iter  70 value 82.246624
iter  80 value 82.198730
iter  90 value 82.069351
iter 100 value 81.968981
final  value 81.968981 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.065048 
iter  10 value 94.433663
iter  20 value 92.357711
iter  30 value 87.659702
iter  40 value 83.117093
iter  50 value 82.728822
iter  60 value 81.812954
iter  70 value 81.382580
iter  80 value 81.231190
iter  90 value 80.962838
iter 100 value 80.639847
final  value 80.639847 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.828994 
iter  10 value 94.482523
iter  20 value 93.427254
iter  30 value 93.253693
iter  40 value 92.015018
iter  50 value 85.201925
iter  60 value 84.670043
iter  70 value 84.350737
iter  80 value 83.884195
iter  90 value 82.613943
iter 100 value 81.843941
final  value 81.843941 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.476883 
iter  10 value 95.619543
iter  20 value 93.282845
iter  30 value 85.503142
iter  40 value 84.783724
iter  50 value 82.569888
iter  60 value 82.226696
iter  70 value 81.481302
iter  80 value 80.954853
iter  90 value 80.608914
iter 100 value 80.524845
final  value 80.524845 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.157386 
iter  10 value 94.336348
iter  20 value 87.036433
iter  30 value 85.763094
iter  40 value 82.618356
iter  50 value 81.664711
iter  60 value 81.360389
iter  70 value 80.867974
iter  80 value 80.745152
iter  90 value 80.599064
iter 100 value 80.562786
final  value 80.562786 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.926186 
iter  10 value 94.638316
iter  20 value 88.738030
iter  30 value 84.958446
iter  40 value 82.809813
iter  50 value 82.318979
iter  60 value 82.046426
iter  70 value 81.980109
iter  80 value 81.393707
iter  90 value 80.595359
iter 100 value 80.157823
final  value 80.157823 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.897603 
iter  10 value 94.646415
iter  20 value 87.919946
iter  30 value 86.670798
iter  40 value 85.003071
iter  50 value 83.195120
iter  60 value 82.223021
iter  70 value 81.411762
iter  80 value 81.122557
iter  90 value 80.903599
iter 100 value 80.660479
final  value 80.660479 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.679141 
iter  10 value 94.398329
iter  20 value 93.129803
iter  30 value 86.837295
iter  40 value 85.343703
iter  50 value 84.701854
iter  60 value 82.146246
iter  70 value 81.516912
iter  80 value 81.173056
iter  90 value 80.841529
iter 100 value 80.395807
final  value 80.395807 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.047619 
iter  10 value 97.417027
iter  20 value 87.945784
iter  30 value 86.589739
iter  40 value 85.423973
iter  50 value 82.252506
iter  60 value 81.592963
iter  70 value 81.136721
iter  80 value 81.007407
iter  90 value 80.833064
iter 100 value 80.585494
final  value 80.585494 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.290798 
iter  10 value 93.891561
iter  20 value 84.859224
iter  30 value 84.190499
iter  40 value 83.437386
iter  50 value 82.004306
iter  60 value 81.185493
iter  70 value 80.668791
iter  80 value 80.489470
iter  90 value 80.327493
iter 100 value 80.266943
final  value 80.266943 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.598929 
iter  10 value 94.385093
iter  20 value 93.461559
iter  30 value 93.292003
iter  40 value 93.215347
iter  50 value 86.920644
iter  60 value 85.391633
iter  70 value 84.050182
iter  80 value 81.807770
iter  90 value 81.229318
iter 100 value 81.096952
final  value 81.096952 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.373363 
iter  10 value 94.486124
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.332633 
final  value 94.485868 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.291180 
final  value 94.486013 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.201235 
iter  10 value 93.171724
iter  20 value 93.112675
iter  30 value 93.110530
iter  40 value 92.903873
iter  50 value 92.898176
iter  60 value 92.898013
iter  60 value 92.898013
iter  60 value 92.898013
final  value 92.898013 
converged
Fitting Repeat 5 

# weights:  103
initial  value 119.661417 
iter  10 value 93.775219
iter  20 value 93.774877
iter  30 value 93.411039
iter  40 value 85.940105
iter  50 value 83.604037
iter  60 value 83.356483
iter  70 value 82.481719
iter  80 value 82.394163
iter  90 value 82.306517
iter 100 value 82.201290
final  value 82.201290 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 98.581766 
iter  10 value 94.031658
iter  20 value 92.799273
iter  30 value 85.184487
iter  40 value 84.846101
iter  50 value 84.627321
iter  60 value 84.621729
final  value 84.621512 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.900604 
iter  10 value 93.778162
iter  20 value 93.775902
iter  30 value 93.261214
iter  40 value 93.008227
iter  50 value 91.253209
iter  60 value 84.523789
iter  70 value 84.016999
iter  80 value 83.686790
iter  90 value 83.439371
iter 100 value 83.337468
final  value 83.337468 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.511715 
iter  10 value 94.488700
iter  20 value 94.039202
final  value 93.823003 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.299214 
iter  10 value 90.408159
iter  20 value 88.527076
final  value 88.524689 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.167540 
iter  10 value 93.812767
iter  20 value 93.696390
iter  30 value 93.694798
final  value 93.692092 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.804801 
iter  10 value 91.351745
iter  20 value 85.123657
iter  30 value 84.800912
iter  40 value 84.750830
iter  50 value 84.745805
iter  60 value 82.883688
iter  70 value 81.601851
iter  80 value 81.054955
iter  90 value 80.641506
iter 100 value 79.933095
final  value 79.933095 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.014053 
iter  10 value 94.266433
iter  20 value 93.790185
iter  30 value 93.783640
iter  40 value 93.470581
iter  50 value 85.633167
iter  60 value 84.300445
iter  70 value 84.064732
iter  80 value 83.978976
iter  90 value 82.727978
iter 100 value 82.582147
final  value 82.582147 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.867958 
iter  10 value 94.037532
iter  20 value 94.034679
iter  30 value 94.025018
iter  40 value 84.515993
iter  50 value 84.260015
iter  60 value 84.026243
iter  70 value 83.022869
iter  80 value 82.996625
final  value 82.996228 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.156033 
iter  10 value 93.920386
iter  20 value 93.866077
iter  30 value 93.829836
iter  40 value 93.046664
iter  50 value 88.394971
iter  60 value 87.118365
iter  70 value 86.733004
iter  80 value 84.078688
iter  90 value 80.420193
iter 100 value 79.152250
final  value 79.152250 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.910826 
iter  10 value 94.034567
iter  20 value 93.838953
iter  30 value 93.363002
iter  40 value 84.717705
iter  50 value 84.481891
final  value 84.481442 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.474666 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.702389 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.998431 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.932740 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.362204 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.082824 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.148737 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.657462 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 130.825185 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.630611 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.382101 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.407258 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.560949 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.172880 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.455350 
final  value 94.427726 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.122783 
iter  10 value 94.488635
iter  20 value 94.486552
iter  30 value 90.392218
iter  40 value 87.041498
iter  50 value 86.649437
iter  60 value 86.508415
iter  70 value 86.331633
iter  80 value 85.464972
iter  90 value 84.136676
iter 100 value 83.859256
final  value 83.859256 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.412777 
iter  10 value 94.486617
iter  20 value 94.403727
iter  30 value 94.000946
iter  40 value 93.982255
iter  50 value 93.958472
iter  60 value 92.978253
iter  70 value 88.242526
iter  80 value 87.554208
iter  90 value 87.073572
iter 100 value 87.007687
final  value 87.007687 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.775346 
iter  10 value 94.488720
iter  20 value 94.396948
iter  30 value 94.143395
iter  40 value 93.717958
iter  50 value 87.800144
iter  60 value 85.714756
iter  70 value 85.184375
iter  80 value 85.055273
iter  90 value 84.942091
iter 100 value 84.437552
final  value 84.437552 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 110.793602 
iter  10 value 94.490600
iter  20 value 91.427167
iter  30 value 87.205925
iter  40 value 86.408813
iter  50 value 85.955279
iter  60 value 85.132546
iter  70 value 83.868435
iter  80 value 83.857728
iter  80 value 83.857727
iter  80 value 83.857727
final  value 83.857727 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.193283 
iter  10 value 91.122014
iter  20 value 88.484101
iter  30 value 86.479829
iter  40 value 86.016939
iter  50 value 84.780770
iter  60 value 84.398245
iter  70 value 83.876729
final  value 83.857726 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.428459 
iter  10 value 94.319887
iter  20 value 88.202507
iter  30 value 87.244914
iter  40 value 85.576668
iter  50 value 85.056757
iter  60 value 84.400719
iter  70 value 84.120770
iter  80 value 83.841642
iter  90 value 83.692310
iter 100 value 83.440332
final  value 83.440332 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.073462 
iter  10 value 93.689760
iter  20 value 92.739001
iter  30 value 89.521347
iter  40 value 88.481492
iter  50 value 87.559999
iter  60 value 85.370476
iter  70 value 84.589101
iter  80 value 83.554389
iter  90 value 83.269453
iter 100 value 82.921434
final  value 82.921434 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.768350 
iter  10 value 94.493279
iter  20 value 94.479236
iter  30 value 94.099905
iter  40 value 94.071598
iter  50 value 93.102849
iter  60 value 92.226663
iter  70 value 90.968231
iter  80 value 89.323566
iter  90 value 87.074785
iter 100 value 83.922197
final  value 83.922197 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.960312 
iter  10 value 94.610053
iter  20 value 92.775071
iter  30 value 88.607500
iter  40 value 88.495281
iter  50 value 88.415973
iter  60 value 87.812534
iter  70 value 87.338294
iter  80 value 85.909161
iter  90 value 84.151863
iter 100 value 83.360524
final  value 83.360524 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.594378 
iter  10 value 95.631021
iter  20 value 87.547496
iter  30 value 86.276217
iter  40 value 85.208366
iter  50 value 84.807159
iter  60 value 84.436361
iter  70 value 83.700114
iter  80 value 83.266829
iter  90 value 82.767319
iter 100 value 82.570458
final  value 82.570458 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.100210 
iter  10 value 94.698912
iter  20 value 93.082784
iter  30 value 89.632893
iter  40 value 87.930755
iter  50 value 86.882404
iter  60 value 85.526285
iter  70 value 85.281895
iter  80 value 84.906948
iter  90 value 84.465963
iter 100 value 84.204888
final  value 84.204888 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.586539 
iter  10 value 94.428218
iter  20 value 88.847061
iter  30 value 88.542099
iter  40 value 88.292410
iter  50 value 87.677328
iter  60 value 85.940527
iter  70 value 85.670859
iter  80 value 84.679819
iter  90 value 83.486447
iter 100 value 82.931511
final  value 82.931511 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.460960 
iter  10 value 94.450439
iter  20 value 92.011118
iter  30 value 88.315902
iter  40 value 86.828548
iter  50 value 86.435394
iter  60 value 85.653612
iter  70 value 85.079103
iter  80 value 84.331537
iter  90 value 83.776063
iter 100 value 83.329289
final  value 83.329289 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 135.583770 
iter  10 value 94.412984
iter  20 value 93.168220
iter  30 value 88.309139
iter  40 value 86.031361
iter  50 value 84.808364
iter  60 value 83.398096
iter  70 value 83.007160
iter  80 value 82.814841
iter  90 value 82.667845
iter 100 value 82.492752
final  value 82.492752 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.658233 
iter  10 value 95.845928
iter  20 value 86.954241
iter  30 value 86.729719
iter  40 value 85.876174
iter  50 value 85.561711
iter  60 value 84.976068
iter  70 value 84.350693
iter  80 value 84.244220
iter  90 value 84.087489
iter 100 value 83.817864
final  value 83.817864 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.351982 
iter  10 value 94.485883
iter  20 value 94.484230
final  value 94.484219 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.989249 
final  value 94.486084 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.137447 
final  value 94.485691 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.255975 
final  value 94.485782 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.734294 
final  value 94.485905 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.748707 
iter  10 value 92.647005
iter  20 value 90.508533
iter  30 value 90.444575
iter  40 value 90.430694
final  value 90.430427 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.257127 
iter  10 value 94.489076
iter  20 value 94.466629
iter  30 value 92.767776
iter  40 value 90.793093
iter  50 value 90.791663
iter  60 value 90.790947
final  value 90.790730 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.843689 
iter  10 value 94.471795
iter  20 value 94.364288
iter  30 value 90.273059
iter  40 value 87.216293
iter  50 value 86.837057
final  value 86.836126 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.753434 
iter  10 value 92.006068
iter  20 value 86.142822
iter  30 value 84.992436
iter  40 value 84.963221
iter  50 value 84.962931
iter  60 value 84.956100
iter  70 value 84.950698
iter  80 value 84.945547
iter  90 value 84.931608
iter 100 value 84.931402
final  value 84.931402 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.587766 
iter  10 value 94.488898
iter  20 value 94.214981
iter  30 value 93.817716
iter  40 value 93.692066
iter  50 value 93.691175
final  value 93.691159 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.460388 
iter  10 value 94.489680
iter  20 value 93.149833
iter  30 value 92.615912
iter  40 value 92.615723
iter  50 value 92.402533
iter  60 value 90.824373
iter  70 value 90.807245
iter  80 value 90.568833
final  value 90.390958 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.244346 
iter  10 value 94.492332
iter  20 value 92.983556
iter  30 value 90.284557
iter  40 value 90.271465
final  value 90.271404 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.049610 
iter  10 value 92.823012
iter  20 value 91.423122
iter  30 value 91.150809
iter  40 value 91.144333
final  value 91.143559 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.543118 
iter  10 value 94.491309
iter  20 value 94.481365
iter  30 value 90.603906
iter  40 value 87.869498
iter  50 value 87.815192
iter  60 value 87.814153
iter  70 value 87.488852
iter  80 value 83.487065
iter  90 value 82.115047
iter 100 value 81.897678
final  value 81.897678 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.229701 
iter  10 value 94.435484
iter  20 value 93.698618
iter  30 value 91.455745
iter  40 value 91.270686
iter  50 value 91.266082
final  value 91.264799 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.051923 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.059015 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.128778 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.576372 
final  value 94.144481 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.948101 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.755566 
iter  10 value 94.019156
final  value 94.019154 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.894488 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.132155 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.587641 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.934262 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.002305 
iter  10 value 94.019425
final  value 94.019154 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.216519 
iter  10 value 94.484215
iter  10 value 94.484214
iter  10 value 94.484214
final  value 94.484214 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.596523 
iter  10 value 92.832471
iter  20 value 92.809144
final  value 92.807486 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.974720 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.758174 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.630499 
iter  10 value 92.848777
iter  20 value 83.213310
iter  30 value 82.340665
iter  40 value 81.854435
iter  50 value 81.165881
iter  60 value 80.401130
iter  70 value 79.473312
iter  80 value 78.781950
iter  90 value 78.740989
final  value 78.740987 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.917139 
iter  10 value 94.496492
iter  20 value 94.450511
iter  30 value 90.346455
iter  40 value 86.226496
iter  50 value 85.336518
iter  60 value 84.951324
iter  70 value 81.984556
iter  80 value 81.047902
iter  90 value 80.040256
iter 100 value 79.419678
final  value 79.419678 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.693743 
iter  10 value 94.402981
iter  20 value 85.595597
iter  30 value 82.461152
iter  40 value 81.292203
iter  50 value 80.710548
iter  60 value 80.566920
iter  70 value 80.536462
iter  80 value 80.512692
final  value 80.512542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.430466 
iter  10 value 93.812123
iter  20 value 81.772256
iter  30 value 80.428849
iter  40 value 80.010553
iter  50 value 79.834070
iter  60 value 79.723333
iter  70 value 79.699171
final  value 79.696052 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.365038 
iter  10 value 93.424475
iter  20 value 91.259666
iter  30 value 91.169686
iter  40 value 86.301654
iter  50 value 84.555892
iter  60 value 84.149890
iter  70 value 81.060595
iter  80 value 79.344443
iter  90 value 78.980682
iter 100 value 78.951440
final  value 78.951440 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.711366 
iter  10 value 94.489128
iter  20 value 94.224892
iter  30 value 94.128161
iter  40 value 93.065114
iter  50 value 81.533554
iter  60 value 79.996091
iter  70 value 78.834609
iter  80 value 78.020743
iter  90 value 77.594212
iter 100 value 77.490551
final  value 77.490551 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.069428 
iter  10 value 94.417846
iter  20 value 92.162307
iter  30 value 88.698769
iter  40 value 85.790333
iter  50 value 82.629970
iter  60 value 80.900713
iter  70 value 80.456301
iter  80 value 79.534934
iter  90 value 79.109672
iter 100 value 78.803060
final  value 78.803060 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.116495 
iter  10 value 95.128269
iter  20 value 93.321130
iter  30 value 88.179563
iter  40 value 85.415536
iter  50 value 83.945321
iter  60 value 83.512722
iter  70 value 82.467057
iter  80 value 80.094697
iter  90 value 78.543768
iter 100 value 77.836308
final  value 77.836308 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.433716 
iter  10 value 94.204268
iter  20 value 93.620277
iter  30 value 91.567778
iter  40 value 82.422166
iter  50 value 81.795528
iter  60 value 81.307884
iter  70 value 80.992508
iter  80 value 79.279223
iter  90 value 77.699339
iter 100 value 77.500469
final  value 77.500469 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.225317 
iter  10 value 94.521621
iter  20 value 85.912087
iter  30 value 82.607214
iter  40 value 81.046001
iter  50 value 80.390531
iter  60 value 80.134555
iter  70 value 79.944718
iter  80 value 79.576201
iter  90 value 79.413283
iter 100 value 78.915432
final  value 78.915432 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.004239 
iter  10 value 95.976822
iter  20 value 93.955173
iter  30 value 91.995972
iter  40 value 81.888901
iter  50 value 81.304146
iter  60 value 81.092583
iter  70 value 81.029147
iter  80 value 80.922351
iter  90 value 80.471612
iter 100 value 80.150029
final  value 80.150029 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 135.164757 
iter  10 value 94.478887
iter  20 value 85.631128
iter  30 value 81.282337
iter  40 value 81.055686
iter  50 value 79.230910
iter  60 value 77.835603
iter  70 value 77.589968
iter  80 value 77.347573
iter  90 value 77.150631
iter 100 value 77.094482
final  value 77.094482 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.156027 
iter  10 value 97.757868
iter  20 value 94.325054
iter  30 value 91.366067
iter  40 value 87.914675
iter  50 value 83.752746
iter  60 value 82.038428
iter  70 value 81.251274
iter  80 value 79.758083
iter  90 value 77.970232
iter 100 value 77.684553
final  value 77.684553 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.634009 
iter  10 value 94.490413
iter  20 value 92.840344
iter  30 value 82.535760
iter  40 value 81.598727
iter  50 value 79.550350
iter  60 value 78.140754
iter  70 value 77.767937
iter  80 value 77.212266
iter  90 value 77.072680
iter 100 value 77.021112
final  value 77.021112 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.870229 
iter  10 value 94.024694
iter  20 value 88.351848
iter  30 value 82.562158
iter  40 value 79.453270
iter  50 value 78.104538
iter  60 value 77.423942
iter  70 value 77.178668
iter  80 value 76.926790
iter  90 value 76.853461
iter 100 value 76.829072
final  value 76.829072 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.874309 
final  value 94.485907 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.312716 
final  value 94.486926 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.611135 
final  value 94.473755 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.331482 
iter  10 value 94.031006
iter  20 value 93.915974
iter  30 value 93.914018
final  value 93.913828 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.670841 
final  value 94.485848 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.865769 
iter  10 value 94.031592
iter  20 value 92.231402
iter  30 value 83.944325
iter  40 value 82.602833
iter  50 value 82.460648
iter  60 value 79.929186
iter  70 value 79.898973
iter  80 value 79.897498
iter  90 value 79.873673
iter 100 value 78.115867
final  value 78.115867 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.127880 
iter  10 value 94.119323
iter  20 value 94.118561
iter  30 value 94.115819
iter  40 value 93.735428
iter  50 value 93.697109
iter  60 value 93.449276
iter  70 value 93.322356
iter  80 value 93.316942
final  value 93.316940 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.171535 
iter  10 value 94.489301
iter  20 value 94.484494
iter  30 value 94.446668
iter  40 value 91.684495
iter  50 value 91.675567
final  value 91.674289 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.357346 
iter  10 value 94.488425
iter  20 value 92.156712
iter  30 value 82.275368
final  value 82.275285 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.115884 
iter  10 value 94.484418
iter  20 value 94.042413
iter  30 value 94.028791
iter  40 value 94.026874
final  value 94.026739 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.256702 
iter  10 value 94.491677
iter  20 value 92.799340
iter  30 value 91.753429
final  value 91.753336 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.111396 
iter  10 value 94.034805
iter  20 value 93.941290
iter  30 value 81.943991
iter  40 value 81.932657
iter  50 value 81.931289
final  value 81.931222 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.171110 
iter  10 value 94.492024
iter  20 value 94.484201
iter  30 value 84.615343
iter  40 value 83.297554
iter  50 value 80.974915
iter  60 value 78.994525
iter  70 value 78.870723
iter  80 value 78.766601
iter  90 value 77.045411
iter 100 value 76.776251
final  value 76.776251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.033850 
iter  10 value 94.491473
iter  20 value 94.416144
iter  30 value 81.223378
iter  40 value 78.750700
iter  50 value 78.678365
iter  60 value 78.298345
iter  70 value 77.987538
iter  80 value 77.955014
iter  90 value 77.922898
iter 100 value 77.588116
final  value 77.588116 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.630875 
iter  10 value 94.491869
iter  20 value 94.484807
iter  30 value 94.484683
final  value 94.484681 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.899822 
iter  10 value 117.898937
iter  20 value 114.331949
iter  30 value 105.359856
iter  30 value 105.359855
iter  30 value 105.359855
final  value 105.359855 
converged
Fitting Repeat 2 

# weights:  507
initial  value 132.949848 
iter  10 value 112.418644
iter  20 value 108.504923
iter  30 value 106.250776
iter  40 value 106.243637
iter  50 value 104.936891
iter  60 value 104.834272
iter  70 value 104.820834
iter  80 value 104.814317
final  value 104.811606 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.972808 
iter  10 value 117.550973
iter  20 value 117.547522
iter  30 value 117.541937
iter  40 value 117.449402
final  value 117.446344 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.871719 
iter  10 value 117.766903
iter  20 value 117.759035
final  value 117.758896 
converged
Fitting Repeat 5 

# weights:  507
initial  value 138.142538 
iter  10 value 117.901122
iter  20 value 115.587047
iter  30 value 106.375590
iter  40 value 103.600197
iter  50 value 100.931885
iter  60 value 99.330358
iter  70 value 98.914385
iter  80 value 98.809231
iter  90 value 98.768117
iter 100 value 98.764731
final  value 98.764731 
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 -- Fri May 22 20:03:41 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 
 18.303   0.444  90.726