##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.3 (2025-02-28 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.3.0
    GNU Fortran (GCC) 13.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.12.0'
* 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 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 ... NOTE
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      35.39   2.00   37.59
var_imp       35.12   1.33   36.45
corr_plot     34.25   1.87   36.12
pred_ensembel 13.83   0.46   12.88
enrichfindP    0.67   0.08   14.31
* 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: 3 NOTEs
See
  'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library'
* installing *source* package 'HPiP' ...
** 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 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 102.195015 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.174175 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.069180 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.872138 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.784104 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.207047 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.521783 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.054973 
iter  10 value 93.601517
final  value 93.601515 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.872282 
final  value 93.731944 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.014016 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 93.406530 
iter  10 value 86.365562
iter  20 value 86.365156
final  value 86.365058 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.100062 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.053903 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.394829 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.764738 
iter  10 value 89.998463
iter  20 value 86.860825
iter  30 value 86.839473
final  value 86.839258 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.417405 
iter  10 value 93.946285
iter  20 value 88.839575
iter  30 value 87.172843
iter  40 value 86.726449
iter  50 value 85.714306
iter  60 value 84.770843
iter  70 value 84.425519
iter  80 value 84.018911
iter  90 value 82.994903
iter 100 value 82.926715
final  value 82.926715 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.043619 
iter  10 value 94.056724
iter  20 value 93.874473
iter  30 value 93.653820
iter  40 value 93.597882
iter  50 value 87.808291
iter  60 value 86.527285
iter  70 value 86.281658
iter  80 value 86.264861
iter  90 value 85.622088
iter 100 value 85.459152
final  value 85.459152 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.198507 
iter  10 value 94.062183
iter  20 value 93.842167
iter  30 value 92.443559
iter  40 value 88.973068
iter  50 value 88.486425
iter  60 value 85.930334
iter  70 value 84.019785
iter  80 value 83.342129
iter  90 value 83.223144
iter 100 value 82.990934
final  value 82.990934 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.627639 
iter  10 value 93.031544
iter  20 value 86.838534
iter  30 value 86.674648
iter  40 value 85.730748
iter  50 value 85.460303
iter  60 value 85.455867
final  value 85.455864 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.121148 
iter  10 value 92.299179
iter  20 value 85.294730
iter  30 value 84.962110
iter  40 value 84.573823
iter  50 value 84.478946
iter  60 value 84.029603
iter  70 value 83.990950
iter  80 value 83.389150
iter  90 value 83.030746
iter 100 value 82.633123
final  value 82.633123 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.548761 
iter  10 value 93.992407
iter  20 value 88.644104
iter  30 value 86.711834
iter  40 value 86.316705
iter  50 value 85.635701
iter  60 value 85.303581
iter  70 value 85.124993
iter  80 value 84.931107
iter  90 value 84.829410
iter 100 value 84.684129
final  value 84.684129 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.628304 
iter  10 value 94.422513
iter  20 value 94.060628
iter  30 value 87.349804
iter  40 value 87.142287
iter  50 value 84.615642
iter  60 value 83.473133
iter  70 value 83.288858
iter  80 value 82.843112
iter  90 value 82.276980
iter 100 value 82.141525
final  value 82.141525 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.815119 
iter  10 value 94.949653
iter  20 value 90.860933
iter  30 value 88.505571
iter  40 value 84.237607
iter  50 value 82.974770
iter  60 value 82.494365
iter  70 value 82.326873
iter  80 value 82.287153
iter  90 value 81.846696
iter 100 value 81.817830
final  value 81.817830 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.290205 
iter  10 value 94.040126
iter  20 value 93.533276
iter  30 value 91.765580
iter  40 value 91.042247
iter  50 value 85.926454
iter  60 value 84.453406
iter  70 value 83.656342
iter  80 value 83.050654
iter  90 value 82.754326
iter 100 value 82.506452
final  value 82.506452 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.500765 
iter  10 value 94.429685
iter  20 value 92.654357
iter  30 value 89.643122
iter  40 value 88.122160
iter  50 value 84.778448
iter  60 value 83.786729
iter  70 value 83.639995
iter  80 value 83.158807
iter  90 value 82.836116
iter 100 value 81.887335
final  value 81.887335 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.736457 
iter  10 value 94.069215
iter  20 value 93.705607
iter  30 value 93.370228
iter  40 value 89.214419
iter  50 value 84.424305
iter  60 value 83.714513
iter  70 value 83.451782
iter  80 value 83.228377
iter  90 value 82.789910
iter 100 value 82.311800
final  value 82.311800 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.158672 
iter  10 value 93.867538
iter  20 value 85.662835
iter  30 value 83.706365
iter  40 value 82.570653
iter  50 value 82.103220
iter  60 value 81.756122
iter  70 value 81.373361
iter  80 value 81.204355
iter  90 value 81.173022
iter 100 value 81.044255
final  value 81.044255 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.178551 
iter  10 value 94.272235
iter  20 value 91.452505
iter  30 value 88.186470
iter  40 value 84.783946
iter  50 value 82.645044
iter  60 value 82.284618
iter  70 value 81.765577
iter  80 value 81.648252
iter  90 value 81.506083
iter 100 value 81.453982
final  value 81.453982 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.578928 
iter  10 value 93.991710
iter  20 value 93.669167
iter  30 value 92.342708
iter  40 value 90.643868
iter  50 value 89.253768
iter  60 value 84.846895
iter  70 value 84.116580
iter  80 value 83.900090
iter  90 value 83.763366
iter 100 value 82.716821
final  value 82.716821 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.941885 
iter  10 value 89.790896
iter  20 value 85.283272
iter  30 value 83.607626
iter  40 value 82.833874
iter  50 value 82.384629
iter  60 value 82.112564
iter  70 value 81.715440
iter  80 value 81.664090
iter  90 value 81.644445
iter 100 value 81.429033
final  value 81.429033 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.690185 
iter  10 value 94.147693
iter  20 value 94.131628
iter  30 value 94.060864
final  value 94.052914 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.735640 
final  value 94.054828 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.339289 
iter  10 value 93.603490
final  value 93.600888 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.645193 
final  value 94.054804 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.233463 
final  value 94.054460 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.011005 
iter  10 value 93.920433
iter  20 value 93.914169
iter  30 value 88.667801
iter  40 value 88.601626
iter  50 value 87.233734
iter  60 value 85.758816
iter  70 value 85.749996
iter  80 value 84.807031
iter  90 value 84.592570
iter 100 value 84.434095
final  value 84.434095 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.053796 
iter  10 value 94.057464
iter  20 value 94.052916
iter  30 value 90.736627
final  value 90.639840 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.431482 
iter  10 value 93.905703
iter  20 value 92.692003
iter  30 value 86.533650
iter  40 value 86.167929
final  value 86.166209 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.472314 
iter  10 value 93.936549
iter  20 value 89.720184
iter  30 value 84.738952
iter  40 value 84.479863
iter  50 value 83.285541
iter  60 value 83.107036
iter  70 value 83.105623
iter  80 value 83.105035
iter  90 value 83.087346
iter 100 value 82.150406
final  value 82.150406 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.764007 
iter  10 value 94.058173
iter  20 value 94.053443
final  value 94.053312 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.360276 
iter  10 value 94.059310
iter  20 value 93.578049
iter  30 value 93.518391
iter  40 value 88.760268
iter  50 value 83.914370
iter  60 value 82.623187
iter  70 value 82.561420
iter  80 value 82.550802
iter  90 value 82.460065
iter 100 value 82.277757
final  value 82.277757 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.324525 
iter  10 value 94.059012
iter  20 value 93.892962
iter  30 value 85.972826
iter  40 value 85.782527
iter  50 value 85.782351
iter  60 value 85.782300
final  value 85.782295 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.077755 
iter  10 value 94.054118
iter  20 value 93.707603
iter  30 value 88.146991
iter  40 value 87.789021
iter  50 value 86.016955
iter  60 value 82.245611
iter  70 value 81.713015
iter  80 value 80.941178
iter  90 value 80.672167
iter 100 value 80.178887
final  value 80.178887 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.187272 
iter  10 value 94.090960
iter  20 value 93.984806
iter  30 value 86.411499
iter  40 value 86.406721
iter  50 value 86.372485
iter  60 value 86.239644
iter  70 value 85.526904
iter  80 value 84.736575
iter  90 value 83.675081
iter 100 value 83.665161
final  value 83.665161 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.489436 
iter  10 value 93.275095
iter  20 value 92.730501
iter  30 value 92.728677
iter  40 value 92.498811
iter  50 value 92.478407
iter  60 value 92.224805
iter  70 value 91.904908
iter  80 value 91.589262
final  value 91.560867 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.691224 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.546092 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.201122 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.304165 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.797211 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.018565 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.408761 
iter  10 value 83.438413
final  value 83.430740 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.930097 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.146528 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.255914 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.923739 
final  value 94.022599 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.593526 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.509236 
iter  10 value 92.811194
final  value 92.809877 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.766999 
iter  10 value 85.573025
iter  20 value 83.770246
iter  30 value 83.313434
iter  40 value 83.125224
iter  50 value 83.096593
iter  60 value 83.073675
final  value 83.073530 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.761046 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.761959 
iter  10 value 94.054746
iter  20 value 89.437476
iter  30 value 86.927356
iter  40 value 85.473744
iter  50 value 84.612342
iter  60 value 84.153806
iter  70 value 84.121831
iter  80 value 84.030744
iter  90 value 83.937477
iter 100 value 83.925134
final  value 83.925134 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.960877 
iter  10 value 94.051738
iter  20 value 92.891817
iter  30 value 92.383166
iter  40 value 92.174863
iter  50 value 91.778272
iter  60 value 91.550358
iter  70 value 91.452005
iter  80 value 91.449201
iter  90 value 90.766494
iter 100 value 88.853004
final  value 88.853004 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.763431 
iter  10 value 93.933571
iter  20 value 92.883132
iter  30 value 87.734603
iter  40 value 86.518244
iter  50 value 85.737012
iter  60 value 83.372303
iter  70 value 82.908305
iter  80 value 82.792095
iter  90 value 82.636459
iter 100 value 82.623523
final  value 82.623523 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.957112 
iter  10 value 92.547174
iter  20 value 86.190868
iter  30 value 84.392791
iter  40 value 83.898813
iter  50 value 83.832057
iter  60 value 83.785948
iter  70 value 83.770951
final  value 83.770950 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.972558 
iter  10 value 93.937888
iter  20 value 91.435962
iter  30 value 88.898798
iter  40 value 86.184697
iter  50 value 85.520494
iter  60 value 83.487071
iter  70 value 83.110022
iter  80 value 82.653809
iter  90 value 82.612602
final  value 82.612600 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.481130 
iter  10 value 94.104722
iter  20 value 91.895846
iter  30 value 88.249987
iter  40 value 87.979090
iter  50 value 87.048758
iter  60 value 86.788798
iter  70 value 85.693050
iter  80 value 84.083342
iter  90 value 82.438519
iter 100 value 81.959664
final  value 81.959664 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.802410 
iter  10 value 94.001677
iter  20 value 85.724665
iter  30 value 84.215657
iter  40 value 84.151370
iter  50 value 83.791767
iter  60 value 83.076242
iter  70 value 82.560322
iter  80 value 82.031860
iter  90 value 81.823567
iter 100 value 81.663619
final  value 81.663619 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.013795 
iter  10 value 89.317037
iter  20 value 87.442570
iter  30 value 85.238847
iter  40 value 84.241051
iter  50 value 83.504899
iter  60 value 82.235813
iter  70 value 81.928166
iter  80 value 81.738167
iter  90 value 81.512935
iter 100 value 81.254839
final  value 81.254839 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.923141 
iter  10 value 94.063769
iter  20 value 93.309408
iter  30 value 86.663194
iter  40 value 86.193693
iter  50 value 85.569113
iter  60 value 84.471136
iter  70 value 83.983242
iter  80 value 83.043676
iter  90 value 82.880460
iter 100 value 82.710683
final  value 82.710683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.756010 
iter  10 value 94.120434
iter  20 value 93.891535
iter  30 value 92.376794
iter  40 value 91.698282
iter  50 value 91.309693
iter  60 value 88.250787
iter  70 value 86.362726
iter  80 value 85.557816
iter  90 value 85.069063
iter 100 value 84.527762
final  value 84.527762 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 150.935212 
iter  10 value 101.784247
iter  20 value 94.445612
iter  30 value 91.630935
iter  40 value 86.347848
iter  50 value 86.180896
iter  60 value 85.877158
iter  70 value 84.218781
iter  80 value 82.106810
iter  90 value 81.494582
iter 100 value 81.251725
final  value 81.251725 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.423380 
iter  10 value 96.205959
iter  20 value 90.172251
iter  30 value 86.325289
iter  40 value 85.872310
iter  50 value 84.019827
iter  60 value 81.710366
iter  70 value 81.557249
iter  80 value 81.479836
iter  90 value 81.180293
iter 100 value 80.938344
final  value 80.938344 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.277616 
iter  10 value 94.013761
iter  20 value 91.982641
iter  30 value 86.637147
iter  40 value 83.982130
iter  50 value 83.153687
iter  60 value 82.744312
iter  70 value 82.518261
iter  80 value 82.497741
iter  90 value 82.465389
iter 100 value 82.459793
final  value 82.459793 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.169499 
iter  10 value 94.234225
iter  20 value 86.738315
iter  30 value 84.476453
iter  40 value 84.111877
iter  50 value 83.289949
iter  60 value 82.894353
iter  70 value 82.200342
iter  80 value 81.933167
iter  90 value 81.533652
iter 100 value 81.369010
final  value 81.369010 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.748722 
iter  10 value 93.714797
iter  20 value 86.174368
iter  30 value 84.879583
iter  40 value 84.515928
iter  50 value 83.722023
iter  60 value 83.550149
iter  70 value 83.430789
iter  80 value 83.262028
iter  90 value 83.106808
iter 100 value 82.992579
final  value 82.992579 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.824196 
final  value 94.054565 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.433820 
final  value 94.054685 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.723007 
iter  10 value 94.054641
iter  20 value 93.746674
iter  30 value 83.340121
final  value 83.318906 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.260259 
final  value 94.054480 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.197335 
final  value 94.054755 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.720966 
iter  10 value 93.095584
iter  20 value 92.897595
iter  30 value 87.029587
iter  40 value 84.585014
iter  50 value 83.300082
iter  60 value 83.226772
final  value 83.175469 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.881066 
iter  10 value 94.057806
iter  20 value 94.007331
iter  30 value 93.745575
iter  40 value 92.682071
iter  50 value 91.779732
iter  60 value 91.645192
iter  70 value 86.759917
iter  80 value 85.955110
iter  90 value 85.914251
final  value 85.914024 
converged
Fitting Repeat 3 

# weights:  305
initial  value 93.884179 
iter  10 value 91.403402
iter  20 value 91.361321
iter  30 value 91.221724
iter  40 value 91.220889
iter  50 value 91.200833
iter  60 value 91.198720
iter  70 value 91.195058
iter  80 value 91.180538
iter  90 value 87.912782
iter 100 value 87.786937
final  value 87.786937 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.120560 
iter  10 value 88.322286
iter  20 value 88.091837
iter  30 value 87.877966
iter  40 value 87.873990
iter  50 value 87.383783
iter  60 value 87.380546
iter  70 value 85.999971
iter  80 value 85.291761
iter  90 value 83.457539
iter 100 value 82.070057
final  value 82.070057 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.377833 
iter  10 value 94.026356
iter  20 value 94.013474
iter  30 value 94.010247
iter  40 value 89.401542
iter  50 value 84.760663
iter  60 value 83.004840
iter  70 value 82.944265
iter  80 value 82.717064
iter  90 value 82.129719
iter 100 value 81.968974
final  value 81.968974 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.197522 
iter  10 value 93.155070
iter  20 value 85.972775
iter  30 value 84.669211
iter  40 value 84.665456
iter  50 value 84.069095
iter  60 value 82.435589
iter  70 value 82.317805
iter  80 value 82.108385
iter  90 value 82.102874
final  value 82.102857 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.525330 
iter  10 value 94.061532
iter  20 value 94.011487
iter  30 value 94.009000
final  value 94.008995 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.298021 
iter  10 value 91.829998
iter  20 value 91.403806
iter  30 value 91.401673
iter  40 value 87.804527
iter  50 value 86.811664
iter  60 value 86.306488
iter  70 value 86.191112
final  value 86.190763 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.077965 
iter  10 value 95.053812
iter  20 value 94.019040
iter  30 value 94.012553
iter  40 value 94.011188
iter  50 value 93.826736
iter  60 value 91.130939
iter  70 value 91.118693
iter  80 value 90.249456
iter  90 value 90.230292
iter 100 value 90.229553
final  value 90.229553 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.686769 
iter  10 value 92.873179
iter  20 value 92.867172
iter  30 value 92.812760
iter  40 value 92.811381
final  value 92.811349 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.319441 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.290584 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.681044 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.232758 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.394179 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.881088 
iter  10 value 87.468415
iter  20 value 86.603767
iter  30 value 85.019359
final  value 85.002841 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.374884 
iter  10 value 94.111062
iter  20 value 94.105281
final  value 94.105264 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.365498 
iter  10 value 94.424077
iter  10 value 94.424077
iter  10 value 94.424077
final  value 94.424077 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.394713 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.646379 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.225495 
iter  10 value 94.484218
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.370129 
iter  10 value 93.104232
iter  20 value 85.554614
iter  30 value 85.284843
iter  40 value 85.215898
iter  50 value 85.199679
iter  60 value 85.199529
final  value 85.199519 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.224295 
final  value 94.427727 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.730997 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.250458 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.866928 
iter  10 value 94.548057
iter  20 value 94.489873
iter  30 value 94.488668
iter  40 value 94.487877
iter  50 value 94.486567
iter  60 value 94.459368
iter  70 value 89.104759
iter  80 value 87.873612
iter  90 value 85.086819
iter 100 value 81.525330
final  value 81.525330 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.940199 
iter  10 value 94.472260
iter  20 value 86.335258
iter  30 value 82.983868
iter  40 value 82.181327
iter  50 value 81.465914
iter  60 value 81.135670
iter  70 value 80.998873
iter  80 value 80.912555
iter  90 value 80.698713
iter 100 value 80.469635
final  value 80.469635 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.823774 
iter  10 value 94.177484
iter  20 value 83.684993
iter  30 value 82.090223
iter  40 value 81.752065
iter  50 value 81.487013
iter  60 value 80.732527
iter  70 value 80.514689
iter  80 value 80.359381
iter  90 value 80.277112
final  value 80.271075 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.383871 
iter  10 value 94.466050
iter  20 value 88.710949
iter  30 value 84.921737
iter  40 value 84.293622
iter  50 value 83.652099
iter  60 value 83.532879
iter  70 value 82.268957
iter  80 value 81.649848
iter  90 value 81.233840
iter 100 value 80.548898
final  value 80.548898 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.941672 
iter  10 value 94.499166
iter  20 value 90.883579
iter  30 value 89.103602
iter  40 value 88.936814
iter  50 value 87.742439
iter  60 value 87.632625
iter  70 value 85.702268
iter  80 value 84.670368
iter  90 value 84.160395
iter 100 value 84.148018
final  value 84.148018 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 127.183010 
iter  10 value 94.071649
iter  20 value 89.580582
iter  30 value 88.490522
iter  40 value 87.595417
iter  50 value 84.883804
iter  60 value 82.182296
iter  70 value 81.333553
iter  80 value 81.025036
iter  90 value 80.552146
iter 100 value 80.490268
final  value 80.490268 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 131.743824 
iter  10 value 94.508218
iter  20 value 86.310490
iter  30 value 84.230941
iter  40 value 81.770035
iter  50 value 81.376824
iter  60 value 80.948567
iter  70 value 80.855446
iter  80 value 80.517953
iter  90 value 80.301121
iter 100 value 80.239131
final  value 80.239131 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.980969 
iter  10 value 94.538500
iter  20 value 88.014599
iter  30 value 84.435330
iter  40 value 82.069841
iter  50 value 81.692090
iter  60 value 81.175731
iter  70 value 80.876246
iter  80 value 80.421209
iter  90 value 79.942846
iter 100 value 79.122176
final  value 79.122176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.242851 
iter  10 value 93.793430
iter  20 value 84.149037
iter  30 value 82.290688
iter  40 value 81.707078
iter  50 value 80.884102
iter  60 value 80.339094
iter  70 value 80.320611
iter  80 value 80.288918
iter  90 value 79.991145
iter 100 value 79.637636
final  value 79.637636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.612317 
iter  10 value 90.823153
iter  20 value 87.375693
iter  30 value 86.873583
iter  40 value 86.353671
iter  50 value 84.770427
iter  60 value 83.010520
iter  70 value 81.179634
iter  80 value 79.756730
iter  90 value 79.523686
iter 100 value 79.292152
final  value 79.292152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.117662 
iter  10 value 94.492803
iter  20 value 86.996626
iter  30 value 83.508781
iter  40 value 81.109878
iter  50 value 80.195617
iter  60 value 79.708953
iter  70 value 79.528163
iter  80 value 78.831569
iter  90 value 78.583439
iter 100 value 78.457722
final  value 78.457722 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.571706 
iter  10 value 95.158664
iter  20 value 87.655364
iter  30 value 84.329883
iter  40 value 82.796572
iter  50 value 81.340296
iter  60 value 80.603886
iter  70 value 80.583777
iter  80 value 80.337288
iter  90 value 79.567364
iter 100 value 79.081405
final  value 79.081405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.100697 
iter  10 value 94.521999
iter  20 value 94.460331
iter  30 value 88.324020
iter  40 value 83.434210
iter  50 value 82.826273
iter  60 value 82.480080
iter  70 value 81.001965
iter  80 value 80.636685
iter  90 value 80.069785
iter 100 value 79.407834
final  value 79.407834 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.206593 
iter  10 value 94.666274
iter  20 value 93.094493
iter  30 value 88.019929
iter  40 value 87.630290
iter  50 value 85.444131
iter  60 value 84.502326
iter  70 value 84.074745
iter  80 value 83.825573
iter  90 value 83.660361
iter 100 value 82.041045
final  value 82.041045 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.562871 
iter  10 value 94.898762
iter  20 value 94.465278
iter  30 value 90.845301
iter  40 value 89.347624
iter  50 value 83.782400
iter  60 value 82.529796
iter  70 value 81.774749
iter  80 value 80.689464
iter  90 value 79.560913
iter 100 value 78.947398
final  value 78.947398 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.064043 
final  value 94.485745 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.469716 
final  value 94.485746 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.729584 
final  value 94.485778 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.277872 
final  value 94.485738 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.613846 
final  value 94.486028 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.521135 
iter  10 value 94.471533
iter  20 value 94.467407
final  value 94.466992 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.803600 
iter  10 value 94.471512
iter  20 value 94.372007
iter  30 value 93.566004
iter  40 value 93.515407
iter  50 value 91.978041
iter  60 value 88.739410
iter  70 value 88.564779
iter  80 value 86.728041
iter  90 value 83.589417
iter 100 value 81.833344
final  value 81.833344 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.722554 
iter  10 value 93.542116
iter  20 value 91.203372
iter  30 value 91.065019
iter  40 value 91.059861
iter  50 value 91.058170
iter  60 value 91.045982
iter  70 value 91.045792
iter  80 value 91.045147
iter  90 value 91.044958
iter 100 value 91.044593
final  value 91.044593 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.105921 
iter  10 value 94.489068
iter  20 value 94.399081
iter  30 value 85.308706
iter  40 value 84.227299
iter  50 value 84.225198
iter  60 value 84.198980
iter  70 value 84.075876
iter  80 value 84.073679
iter  90 value 83.905606
iter 100 value 83.904864
final  value 83.904864 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.011945 
iter  10 value 94.488912
iter  20 value 94.484306
iter  30 value 94.373086
iter  40 value 90.026128
iter  50 value 88.687274
iter  60 value 88.612007
iter  70 value 83.691703
iter  80 value 82.186707
iter  90 value 81.947038
iter 100 value 81.279243
final  value 81.279243 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.392768 
iter  10 value 94.474560
iter  20 value 93.974965
iter  30 value 93.607842
iter  40 value 85.406577
iter  50 value 83.184587
iter  60 value 82.967540
iter  70 value 80.448665
iter  80 value 80.346041
iter  90 value 80.322737
iter 100 value 79.401822
final  value 79.401822 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.308856 
iter  10 value 94.481325
iter  20 value 94.453689
iter  30 value 94.376431
iter  40 value 92.698687
iter  50 value 92.559613
iter  60 value 92.475595
iter  70 value 92.470830
iter  80 value 92.215032
iter  90 value 92.081642
iter 100 value 92.077056
final  value 92.077056 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.768874 
iter  10 value 91.958046
iter  20 value 87.859815
iter  30 value 87.827954
iter  40 value 87.823010
iter  50 value 87.819963
iter  60 value 86.496234
iter  70 value 84.805514
iter  80 value 84.123812
iter  90 value 78.138586
iter 100 value 77.839583
final  value 77.839583 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.430641 
iter  10 value 94.436568
iter  20 value 94.238104
iter  30 value 84.918176
iter  40 value 79.396798
iter  50 value 78.709577
iter  60 value 78.696446
iter  70 value 78.691051
iter  80 value 78.688156
iter  90 value 78.684621
iter 100 value 78.679825
final  value 78.679825 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.976705 
iter  10 value 94.474928
iter  20 value 94.467688
iter  30 value 90.998009
iter  40 value 90.974110
iter  50 value 84.405718
iter  60 value 83.251811
iter  70 value 83.247717
iter  80 value 83.243201
iter  90 value 82.889154
iter 100 value 81.153925
final  value 81.153925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.711129 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.066589 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.044660 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.318411 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.378723 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.861192 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.935809 
iter  10 value 94.409648
final  value 94.409639 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.800173 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.915938 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.753756 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.544085 
iter  10 value 94.448923
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.228758 
iter  10 value 94.383623
iter  10 value 94.383623
iter  10 value 94.383623
final  value 94.383623 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.226228 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.149548 
iter  10 value 94.354513
iter  20 value 94.315162
final  value 94.315116 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.968829 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.354453 
iter  10 value 94.415059
iter  20 value 87.345974
iter  30 value 85.550658
iter  40 value 83.530477
iter  50 value 82.104243
iter  60 value 81.841562
iter  70 value 81.728495
final  value 81.728459 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.918067 
iter  10 value 94.482597
iter  20 value 93.499021
iter  30 value 92.182175
iter  40 value 91.657952
iter  50 value 91.526393
final  value 91.526112 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.339500 
iter  10 value 94.509798
iter  20 value 94.425279
iter  30 value 93.326367
iter  40 value 89.378717
iter  50 value 86.127938
iter  60 value 85.594857
iter  70 value 85.505083
final  value 85.504814 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.463787 
iter  10 value 92.551874
iter  20 value 86.836982
iter  30 value 85.843150
iter  40 value 85.377458
final  value 85.375208 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.581089 
iter  10 value 94.434354
iter  20 value 94.020384
iter  30 value 93.835775
iter  40 value 92.315492
iter  50 value 89.673804
iter  60 value 86.021054
iter  70 value 84.790776
iter  80 value 84.080833
iter  90 value 82.631184
iter 100 value 82.473653
final  value 82.473653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.973933 
iter  10 value 94.140488
iter  20 value 88.743714
iter  30 value 87.720117
iter  40 value 86.497061
iter  50 value 86.255954
iter  60 value 85.709686
iter  70 value 85.345679
iter  80 value 84.454899
iter  90 value 81.223888
iter 100 value 80.628291
final  value 80.628291 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 126.824592 
iter  10 value 94.437364
iter  20 value 93.070109
iter  30 value 91.082974
iter  40 value 90.323596
iter  50 value 89.836554
iter  60 value 85.394556
iter  70 value 81.729829
iter  80 value 80.293662
iter  90 value 79.902704
iter 100 value 79.656942
final  value 79.656942 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.841807 
iter  10 value 94.394305
iter  20 value 89.791516
iter  30 value 87.906467
iter  40 value 87.650409
iter  50 value 83.323963
iter  60 value 82.723761
iter  70 value 82.578280
iter  80 value 82.517041
iter  90 value 82.453284
iter 100 value 81.614061
final  value 81.614061 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.106296 
iter  10 value 94.121380
iter  20 value 89.298257
iter  30 value 88.203480
iter  40 value 86.032861
iter  50 value 84.382721
iter  60 value 82.552288
iter  70 value 81.047596
iter  80 value 80.065577
iter  90 value 79.937469
iter 100 value 79.687973
final  value 79.687973 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.707793 
iter  10 value 94.105394
iter  20 value 92.819762
iter  30 value 84.604580
iter  40 value 84.041584
iter  50 value 82.778508
iter  60 value 82.591826
iter  70 value 82.426625
iter  80 value 81.603440
iter  90 value 81.468970
iter 100 value 81.449569
final  value 81.449569 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.188765 
iter  10 value 94.511217
iter  20 value 92.200956
iter  30 value 85.232796
iter  40 value 83.954208
iter  50 value 82.437466
iter  60 value 81.752458
iter  70 value 80.546952
iter  80 value 80.167225
iter  90 value 80.034952
iter 100 value 79.937343
final  value 79.937343 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.904018 
iter  10 value 87.136395
iter  20 value 85.052059
iter  30 value 82.842252
iter  40 value 82.141235
iter  50 value 81.799920
iter  60 value 81.652129
iter  70 value 81.459727
iter  80 value 81.348904
iter  90 value 81.048274
iter 100 value 80.248233
final  value 80.248233 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.541704 
iter  10 value 94.659863
iter  20 value 93.740657
iter  30 value 90.271737
iter  40 value 89.156863
iter  50 value 86.572708
iter  60 value 85.664350
iter  70 value 81.990599
iter  80 value 81.172361
iter  90 value 80.936660
iter 100 value 80.096451
final  value 80.096451 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.549539 
iter  10 value 94.959431
iter  20 value 89.981880
iter  30 value 87.275273
iter  40 value 86.686728
iter  50 value 85.577974
iter  60 value 85.454529
iter  70 value 85.039866
iter  80 value 81.953214
iter  90 value 80.459628
iter 100 value 80.322808
final  value 80.322808 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.068852 
iter  10 value 90.446647
iter  20 value 88.920716
iter  30 value 87.870147
iter  40 value 86.951552
iter  50 value 81.339936
iter  60 value 80.515664
iter  70 value 80.074641
iter  80 value 79.826086
iter  90 value 79.650651
iter 100 value 79.628893
final  value 79.628893 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.271380 
final  value 94.485720 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.666417 
final  value 94.485896 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.178109 
iter  10 value 94.485628
final  value 94.484219 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.699810 
iter  10 value 94.444808
iter  20 value 94.350637
iter  30 value 93.467671
iter  40 value 92.914653
iter  50 value 92.912568
iter  60 value 92.911840
final  value 92.911804 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.863309 
iter  10 value 94.438664
iter  20 value 92.806279
iter  30 value 88.075634
iter  40 value 88.000141
iter  50 value 87.999874
final  value 87.999821 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.254727 
iter  10 value 94.489406
iter  20 value 94.402382
iter  30 value 91.761563
iter  40 value 90.258603
iter  50 value 90.153059
iter  60 value 90.152923
iter  70 value 90.152651
final  value 90.152243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.270189 
iter  10 value 94.487560
iter  20 value 92.721032
iter  30 value 86.629578
final  value 86.624764 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.444369 
iter  10 value 94.325149
iter  20 value 93.728136
iter  30 value 93.716547
iter  40 value 93.711737
iter  50 value 93.704225
final  value 93.704121 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.635128 
iter  10 value 94.489095
iter  20 value 87.972938
iter  30 value 86.625537
iter  40 value 86.621689
iter  50 value 86.621441
iter  60 value 86.620999
iter  70 value 86.286554
iter  80 value 86.286482
iter  90 value 86.286114
iter 100 value 86.283623
final  value 86.283623 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.019957 
iter  10 value 94.448712
iter  20 value 89.793907
iter  30 value 86.629365
iter  40 value 86.626329
iter  50 value 86.622266
iter  60 value 83.358393
iter  70 value 82.996374
iter  80 value 82.994340
iter  90 value 82.993797
iter 100 value 82.992973
final  value 82.992973 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.786384 
iter  10 value 94.451177
iter  20 value 94.355318
iter  30 value 93.678065
iter  40 value 92.627445
iter  50 value 88.766408
iter  60 value 86.754705
iter  70 value 86.748501
final  value 86.748483 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.130181 
iter  10 value 92.579482
iter  20 value 87.635726
iter  30 value 87.145766
iter  40 value 87.137175
iter  50 value 86.999020
iter  60 value 86.781540
iter  70 value 86.773292
iter  80 value 86.769156
iter  90 value 86.767850
iter 100 value 84.996531
final  value 84.996531 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.137015 
iter  10 value 94.451135
iter  20 value 94.405111
iter  30 value 94.400494
iter  40 value 94.400396
iter  50 value 94.382947
iter  60 value 86.261054
iter  70 value 85.397969
iter  80 value 85.397851
iter  90 value 85.028056
iter 100 value 83.277025
final  value 83.277025 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.726046 
iter  10 value 94.393622
iter  20 value 94.367362
iter  30 value 94.366969
iter  40 value 94.366801
iter  50 value 94.362052
final  value 94.361641 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.378772 
iter  10 value 94.437306
iter  20 value 94.430540
iter  20 value 94.430540
iter  20 value 94.430540
final  value 94.430540 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.702601 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.354466 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.098428 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.454333 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.560583 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.167382 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.295133 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.507177 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.237502 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.609139 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.559242 
iter  10 value 94.025344
iter  20 value 93.893414
iter  30 value 85.493070
iter  40 value 82.687075
iter  50 value 82.597195
iter  60 value 82.386526
iter  60 value 82.386526
iter  60 value 82.386526
final  value 82.386526 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.167424 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.688768 
iter  10 value 93.975298
final  value 93.974641 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.131329 
iter  10 value 93.834017
iter  20 value 93.764385
final  value 93.764219 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.607341 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.149668 
iter  10 value 97.173524
iter  20 value 94.469289
iter  30 value 91.945628
iter  40 value 90.565675
iter  50 value 90.251349
iter  60 value 90.228680
final  value 90.227846 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.064629 
iter  10 value 94.528952
iter  20 value 94.488302
iter  30 value 94.205004
iter  40 value 93.788034
iter  50 value 93.006040
iter  60 value 85.780746
iter  70 value 85.224898
iter  80 value 85.008407
iter  90 value 83.297990
iter 100 value 82.114974
final  value 82.114974 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.916351 
iter  10 value 94.409091
iter  20 value 86.230290
iter  30 value 82.105741
iter  40 value 82.074142
iter  50 value 82.045985
iter  60 value 81.987597
iter  70 value 81.894165
iter  80 value 81.884163
iter  90 value 81.883817
final  value 81.882832 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.289571 
iter  10 value 94.482894
iter  20 value 90.294642
iter  30 value 87.369221
iter  40 value 84.666202
iter  50 value 81.929526
iter  60 value 81.893131
final  value 81.882832 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.314200 
iter  10 value 94.154708
iter  20 value 90.990767
iter  30 value 89.495858
iter  40 value 88.730359
iter  50 value 86.070089
iter  60 value 80.743885
iter  70 value 79.872405
iter  80 value 79.764842
iter  90 value 79.619139
iter 100 value 79.421348
final  value 79.421348 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 141.592952 
iter  10 value 94.500643
iter  20 value 94.178798
iter  30 value 93.754523
iter  40 value 91.902200
iter  50 value 85.277168
iter  60 value 83.277966
iter  70 value 81.341244
iter  80 value 81.052864
iter  90 value 80.352933
iter 100 value 79.944762
final  value 79.944762 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.257110 
iter  10 value 94.575112
iter  20 value 91.629207
iter  30 value 85.659578
iter  40 value 83.792246
iter  50 value 82.532075
iter  60 value 80.953222
iter  70 value 80.383676
iter  80 value 79.451531
iter  90 value 78.667451
iter 100 value 78.497693
final  value 78.497693 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.813611 
iter  10 value 94.552812
iter  20 value 94.507697
iter  30 value 94.328991
iter  40 value 91.806324
iter  50 value 87.638130
iter  60 value 84.100824
iter  70 value 81.814619
iter  80 value 81.219303
iter  90 value 80.657547
iter 100 value 80.391781
final  value 80.391781 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.287063 
iter  10 value 87.892968
iter  20 value 84.823733
iter  30 value 84.497800
iter  40 value 81.374652
iter  50 value 79.809597
iter  60 value 79.666075
iter  70 value 79.525724
iter  80 value 79.006886
iter  90 value 78.787623
iter 100 value 78.729944
final  value 78.729944 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.065206 
iter  10 value 94.274579
iter  20 value 93.201025
iter  30 value 84.971957
iter  40 value 81.658955
iter  50 value 79.979292
iter  60 value 79.434668
iter  70 value 78.829108
iter  80 value 78.650381
iter  90 value 78.632516
iter 100 value 78.594298
final  value 78.594298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.435002 
iter  10 value 94.506909
iter  20 value 94.445662
iter  30 value 86.654870
iter  40 value 82.432406
iter  50 value 81.931176
iter  60 value 81.690664
iter  70 value 81.531425
iter  80 value 81.078101
iter  90 value 79.333807
iter 100 value 79.065439
final  value 79.065439 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 141.916825 
iter  10 value 95.510137
iter  20 value 93.828166
iter  30 value 91.208576
iter  40 value 84.648027
iter  50 value 83.281984
iter  60 value 80.245103
iter  70 value 78.763517
iter  80 value 78.647694
iter  90 value 78.257466
iter 100 value 78.166778
final  value 78.166778 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.982267 
iter  10 value 94.563926
iter  20 value 89.528473
iter  30 value 85.062893
iter  40 value 84.719504
iter  50 value 82.667955
iter  60 value 82.050576
iter  70 value 81.502449
iter  80 value 80.193590
iter  90 value 80.073991
iter 100 value 80.021449
final  value 80.021449 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.819622 
iter  10 value 94.369531
iter  20 value 87.909019
iter  30 value 86.086991
iter  40 value 85.187821
iter  50 value 81.788452
iter  60 value 81.132959
iter  70 value 79.555956
iter  80 value 79.127780
iter  90 value 78.860383
iter 100 value 78.545976
final  value 78.545976 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.192373 
iter  10 value 94.179462
iter  20 value 92.416950
iter  30 value 84.802364
iter  40 value 82.340052
iter  50 value 80.612026
iter  60 value 80.009878
iter  70 value 79.477932
iter  80 value 78.858838
iter  90 value 78.647728
iter 100 value 78.565352
final  value 78.565352 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.824870 
final  value 94.485718 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.802662 
iter  10 value 94.166822
iter  20 value 94.166473
iter  30 value 93.872074
final  value 93.872042 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.732291 
final  value 94.486030 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.345301 
final  value 94.485805 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.758369 
final  value 94.485716 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.952736 
iter  10 value 94.489421
iter  20 value 94.480745
iter  30 value 93.637858
iter  40 value 89.462085
iter  50 value 81.067242
iter  60 value 81.029042
iter  70 value 81.016550
iter  80 value 80.662208
iter  90 value 80.395876
iter 100 value 80.262361
final  value 80.262361 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.942908 
iter  10 value 94.489032
iter  20 value 94.478922
iter  30 value 93.573641
final  value 93.573429 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.879830 
iter  10 value 94.031453
iter  20 value 94.022365
iter  30 value 93.519231
iter  40 value 92.456392
iter  50 value 85.172235
iter  60 value 84.961594
iter  70 value 84.960303
final  value 84.959148 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.651667 
iter  10 value 94.488853
iter  20 value 92.034570
iter  30 value 83.784138
iter  40 value 83.354296
final  value 83.353696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.343186 
iter  10 value 94.489214
iter  20 value 93.416304
iter  30 value 92.617040
iter  40 value 92.615426
final  value 92.615342 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.887431 
iter  10 value 94.037249
iter  20 value 93.782949
iter  30 value 93.575666
iter  40 value 93.206014
iter  50 value 87.593182
iter  60 value 83.648389
iter  70 value 83.239345
iter  80 value 83.233881
iter  90 value 83.091977
iter 100 value 82.845130
final  value 82.845130 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.158492 
iter  10 value 88.848906
iter  20 value 85.961963
iter  30 value 85.959652
iter  40 value 83.787195
iter  50 value 83.785802
iter  60 value 83.370821
iter  70 value 80.801863
iter  80 value 80.704130
iter  90 value 80.703706
iter 100 value 80.703178
final  value 80.703178 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 133.079460 
iter  10 value 94.034437
iter  20 value 94.028646
iter  30 value 94.027402
final  value 94.027366 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.679574 
iter  10 value 94.468450
iter  20 value 91.402279
iter  30 value 81.208617
iter  40 value 81.171556
iter  50 value 81.162806
iter  60 value 81.011772
iter  70 value 81.010103
iter  80 value 81.007881
iter  90 value 80.745137
iter 100 value 80.694068
final  value 80.694068 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.546352 
iter  10 value 94.491995
iter  20 value 87.448395
iter  30 value 85.963496
iter  40 value 85.960663
iter  50 value 85.957678
iter  60 value 84.543239
iter  70 value 83.784677
iter  80 value 83.481160
iter  90 value 83.472801
iter 100 value 83.471639
final  value 83.471639 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.587297 
iter  10 value 117.767012
iter  20 value 117.758793
iter  30 value 116.120691
iter  40 value 111.755156
iter  50 value 105.711496
iter  60 value 103.044381
iter  70 value 102.448065
iter  80 value 101.611247
iter  90 value 101.147430
iter 100 value 101.028381
final  value 101.028381 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.326240 
iter  10 value 117.281432
iter  20 value 117.215552
iter  30 value 117.212087
iter  40 value 117.208414
iter  50 value 107.508027
iter  60 value 104.656708
iter  70 value 104.417749
iter  80 value 104.417242
iter  90 value 104.415214
iter 100 value 103.756784
final  value 103.756784 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.123969 
iter  10 value 117.767096
iter  20 value 117.554580
iter  30 value 117.364654
iter  40 value 112.107522
iter  50 value 111.896619
final  value 111.896421 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.286087 
iter  10 value 117.615523
iter  20 value 117.519111
iter  30 value 117.371942
iter  40 value 105.364863
iter  50 value 105.359729
iter  60 value 104.952699
iter  70 value 103.924063
iter  80 value 102.844248
iter  90 value 102.603496
iter 100 value 102.562342
final  value 102.562342 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.139455 
iter  10 value 116.395235
iter  20 value 115.918962
iter  30 value 115.903859
iter  40 value 115.441614
iter  50 value 115.281055
iter  60 value 115.223846
iter  70 value 115.223354
final  value 115.223285 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Mar 14 02:12:35 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
  44.95    1.37  108.98