##############################################################################
##############################################################################
###
### 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_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R version 4.5.0 RC (2025-04-04 r88126)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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
var_imp       35.565  1.755  37.785
FSmethod      33.238  1.686  35.232
corr_plot     32.503  1.610  34.328
pred_ensembel 13.190  0.427  11.691
enrichfindP    0.464  0.055   8.893
* 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-3.21-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/4.5-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 96.374213 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.591906 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.464931 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.643263 
iter  10 value 94.057708
final  value 94.052905 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.594642 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.445462 
final  value 94.052912 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.103683 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.905772 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.444537 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.192828 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.280152 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.533854 
final  value 93.869755 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.894362 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.186829 
iter  10 value 93.977232
iter  20 value 93.969048
final  value 93.969041 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.863296 
final  value 93.371808 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.531234 
iter  10 value 89.702460
iter  20 value 85.060402
iter  30 value 84.129306
iter  40 value 84.046785
iter  50 value 84.028305
final  value 84.027676 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.588305 
iter  10 value 94.057246
iter  20 value 91.063061
iter  30 value 87.058203
iter  40 value 85.550955
iter  50 value 84.838689
iter  60 value 84.800968
iter  70 value 84.795789
final  value 84.795779 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.453513 
iter  10 value 94.167451
iter  20 value 94.055076
iter  30 value 93.837029
iter  40 value 93.697291
iter  50 value 93.682364
iter  60 value 89.749056
iter  70 value 86.148659
iter  80 value 84.502271
iter  90 value 84.269500
iter 100 value 83.363996
final  value 83.363996 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.599709 
iter  10 value 94.024970
iter  20 value 93.696414
iter  30 value 93.336917
iter  40 value 87.912385
iter  50 value 85.797846
iter  60 value 85.197758
iter  70 value 83.826887
iter  80 value 82.890462
iter  90 value 82.489875
final  value 82.480678 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.842930 
iter  10 value 93.970657
iter  20 value 93.509393
iter  30 value 90.922978
iter  40 value 86.111131
iter  50 value 83.882581
iter  60 value 83.295577
iter  70 value 82.935624
iter  80 value 82.925023
iter  80 value 82.925023
iter  80 value 82.925023
final  value 82.925023 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.500489 
iter  10 value 94.820314
iter  20 value 91.935936
iter  30 value 88.829834
iter  40 value 87.712353
iter  50 value 86.725070
iter  60 value 86.125802
iter  70 value 86.022084
iter  80 value 85.708960
iter  90 value 85.424013
iter 100 value 85.118833
final  value 85.118833 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.922633 
iter  10 value 94.099402
iter  20 value 89.897221
iter  30 value 88.909177
iter  40 value 88.328847
iter  50 value 86.062317
iter  60 value 84.756691
iter  70 value 84.435140
iter  80 value 84.159787
iter  90 value 82.514683
iter 100 value 82.021997
final  value 82.021997 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.472021 
iter  10 value 93.920240
iter  20 value 87.549792
iter  30 value 86.081336
iter  40 value 85.316524
iter  50 value 84.000436
iter  60 value 83.675240
iter  70 value 82.848061
iter  80 value 82.515058
iter  90 value 82.430807
iter 100 value 82.276131
final  value 82.276131 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.154807 
iter  10 value 93.927971
iter  20 value 87.806112
iter  30 value 85.707107
iter  40 value 83.571700
iter  50 value 81.996208
iter  60 value 81.096136
iter  70 value 80.807904
iter  80 value 80.640558
iter  90 value 80.594297
iter 100 value 80.583504
final  value 80.583504 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.973288 
iter  10 value 90.300443
iter  20 value 85.104680
iter  30 value 84.668836
iter  40 value 84.547997
iter  50 value 84.116934
iter  60 value 83.159245
iter  70 value 82.935612
iter  80 value 82.906010
iter  90 value 82.509968
iter 100 value 81.654694
final  value 81.654694 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.375860 
iter  10 value 88.557209
iter  20 value 87.946134
iter  30 value 87.182174
iter  40 value 83.805335
iter  50 value 83.300539
iter  60 value 83.126156
iter  70 value 82.640806
iter  80 value 81.882911
iter  90 value 81.028673
iter 100 value 80.723049
final  value 80.723049 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.280896 
iter  10 value 94.086369
iter  20 value 88.448716
iter  30 value 85.852052
iter  40 value 84.800714
iter  50 value 83.208169
iter  60 value 82.983757
iter  70 value 82.012781
iter  80 value 81.688294
iter  90 value 81.577639
iter 100 value 81.434365
final  value 81.434365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.454779 
iter  10 value 94.534926
iter  20 value 90.688006
iter  30 value 87.285761
iter  40 value 86.144343
iter  50 value 84.708389
iter  60 value 82.417022
iter  70 value 81.332502
iter  80 value 80.874610
iter  90 value 80.531819
iter 100 value 80.464456
final  value 80.464456 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.765114 
iter  10 value 94.026502
iter  20 value 89.245096
iter  30 value 87.450742
iter  40 value 86.435974
iter  50 value 84.743452
iter  60 value 84.305539
iter  70 value 83.721940
iter  80 value 82.617859
iter  90 value 81.672624
iter 100 value 81.349828
final  value 81.349828 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.898200 
iter  10 value 86.492010
iter  20 value 85.156001
iter  30 value 83.670777
iter  40 value 83.496413
iter  50 value 83.472964
iter  60 value 83.168965
iter  70 value 82.955892
iter  80 value 82.081543
iter  90 value 81.240282
iter 100 value 81.132653
final  value 81.132653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.290529 
iter  10 value 91.137312
iter  20 value 88.955078
iter  30 value 88.943420
iter  40 value 88.411842
iter  50 value 85.779446
final  value 85.736731 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.241417 
iter  10 value 93.498672
iter  20 value 93.492813
iter  30 value 93.059952
iter  40 value 90.917520
iter  50 value 90.560474
iter  60 value 90.560361
final  value 90.560146 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.629136 
iter  10 value 94.039846
iter  20 value 94.038385
final  value 94.038268 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.190976 
final  value 94.054536 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.230299 
iter  10 value 88.442573
iter  20 value 87.253382
iter  30 value 87.250566
final  value 87.250264 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.503997 
iter  10 value 93.876511
iter  20 value 93.873600
iter  30 value 93.858515
iter  40 value 93.232906
final  value 93.232871 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.832135 
iter  10 value 94.057584
iter  20 value 93.957029
iter  30 value 93.654378
final  value 93.654007 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.084158 
iter  10 value 92.054678
iter  20 value 91.143841
iter  30 value 90.991594
iter  40 value 90.990399
iter  50 value 90.988774
final  value 90.988431 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.355594 
iter  10 value 93.864198
iter  20 value 93.862213
iter  30 value 93.859862
iter  40 value 84.746337
iter  50 value 84.115511
iter  60 value 83.534769
iter  70 value 82.737601
iter  80 value 82.327717
iter  90 value 81.177981
iter 100 value 79.847448
final  value 79.847448 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.112614 
iter  10 value 94.043053
iter  20 value 94.039916
iter  30 value 94.033308
iter  40 value 92.204583
iter  50 value 90.789918
final  value 90.787339 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.797748 
iter  10 value 91.708189
iter  20 value 91.665671
iter  30 value 91.228468
iter  40 value 91.226984
iter  50 value 91.171311
iter  60 value 91.166792
iter  70 value 91.165333
iter  80 value 91.163822
iter  90 value 91.155247
final  value 91.155159 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.659996 
iter  10 value 94.060532
iter  20 value 94.052832
iter  30 value 94.038443
iter  40 value 94.038375
final  value 94.038332 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.174040 
iter  10 value 92.206799
iter  20 value 91.142086
iter  30 value 91.140310
iter  40 value 91.134749
iter  50 value 91.134089
iter  60 value 91.133078
iter  70 value 91.132704
iter  80 value 87.518910
iter  90 value 82.527759
iter 100 value 81.924755
final  value 81.924755 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.925421 
iter  10 value 93.833399
iter  20 value 93.827396
iter  30 value 93.620816
iter  40 value 89.867499
iter  50 value 85.962086
iter  60 value 85.950663
final  value 85.950640 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.971677 
iter  10 value 94.046857
iter  20 value 94.037365
iter  30 value 91.699861
iter  40 value 90.988154
final  value 90.852488 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.384796 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.465199 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.536282 
final  value 94.449438 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.990815 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.841870 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.353623 
final  value 94.482932 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.268244 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.854695 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.334197 
final  value 94.449438 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.099402 
iter  10 value 94.326560
final  value 94.326471 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.851547 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.825674 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.224249 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.471281 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.643013 
iter  10 value 87.706449
iter  20 value 87.184693
iter  30 value 87.169583
iter  40 value 87.059752
final  value 87.059441 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.355132 
iter  10 value 87.587684
iter  20 value 84.805997
iter  30 value 81.456345
iter  40 value 81.276660
iter  50 value 80.734191
iter  60 value 80.679911
final  value 80.679894 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.882936 
iter  10 value 94.498419
iter  20 value 90.662009
iter  30 value 90.476199
iter  40 value 90.374960
iter  50 value 90.057377
iter  60 value 87.419197
iter  70 value 85.204060
iter  80 value 84.407659
iter  90 value 84.175096
iter 100 value 83.969324
final  value 83.969324 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.501689 
iter  10 value 94.486324
iter  20 value 94.341289
iter  30 value 90.996796
iter  40 value 83.306119
iter  50 value 82.936598
iter  60 value 82.519970
iter  70 value 82.230118
iter  80 value 81.716745
iter  90 value 81.675066
iter 100 value 81.674667
final  value 81.674667 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.426955 
iter  10 value 94.487050
iter  20 value 94.486550
iter  20 value 94.486550
iter  30 value 90.747998
iter  40 value 85.872749
iter  50 value 83.578537
iter  60 value 83.382065
iter  70 value 82.892895
iter  80 value 82.644430
iter  90 value 82.302290
iter 100 value 82.086292
final  value 82.086292 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.846302 
iter  10 value 94.483986
iter  20 value 92.189792
iter  30 value 85.469761
iter  40 value 84.453437
iter  50 value 84.180029
iter  60 value 84.163900
iter  70 value 83.959176
iter  80 value 83.906234
iter  90 value 83.806991
final  value 83.805239 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.036250 
iter  10 value 94.459164
iter  20 value 85.523815
iter  30 value 84.466396
iter  40 value 83.268376
iter  50 value 82.438519
iter  60 value 82.163118
iter  70 value 81.424616
iter  80 value 80.540767
iter  90 value 80.221015
iter 100 value 80.106450
final  value 80.106450 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.619589 
iter  10 value 94.420748
iter  20 value 93.719368
iter  30 value 89.495224
iter  40 value 89.270254
iter  50 value 86.604888
iter  60 value 84.566601
iter  70 value 82.166614
iter  80 value 81.303356
iter  90 value 80.886489
iter 100 value 79.668912
final  value 79.668912 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.014034 
iter  10 value 93.962401
iter  20 value 88.539924
iter  30 value 85.302693
iter  40 value 84.867030
iter  50 value 84.390637
iter  60 value 83.902192
iter  70 value 82.697284
iter  80 value 81.365775
iter  90 value 81.202414
iter 100 value 80.627414
final  value 80.627414 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.856225 
iter  10 value 94.796305
iter  20 value 94.710060
iter  30 value 94.481913
iter  40 value 93.441410
iter  50 value 86.233847
iter  60 value 85.782253
iter  70 value 82.947499
iter  80 value 81.509388
iter  90 value 79.754860
iter 100 value 79.339275
final  value 79.339275 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.922286 
iter  10 value 90.052311
iter  20 value 83.804766
iter  30 value 83.283599
iter  40 value 82.652565
iter  50 value 82.192568
iter  60 value 80.825770
iter  70 value 80.501929
iter  80 value 80.377117
iter  90 value 80.154444
iter 100 value 79.460607
final  value 79.460607 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.656010 
iter  10 value 94.815963
iter  20 value 84.653311
iter  30 value 83.041322
iter  40 value 82.983328
iter  50 value 82.719270
iter  60 value 82.327187
iter  70 value 82.090339
iter  80 value 81.803234
iter  90 value 81.651168
iter 100 value 80.548253
final  value 80.548253 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 155.125860 
iter  10 value 96.226130
iter  20 value 95.187135
iter  30 value 92.893762
iter  40 value 90.334349
iter  50 value 87.118330
iter  60 value 84.419978
iter  70 value 81.784397
iter  80 value 80.228593
iter  90 value 79.761332
iter 100 value 79.477712
final  value 79.477712 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.477877 
iter  10 value 94.433639
iter  20 value 93.297852
iter  30 value 85.729012
iter  40 value 83.569223
iter  50 value 80.371283
iter  60 value 79.577112
iter  70 value 79.276756
iter  80 value 79.089156
iter  90 value 78.893716
iter 100 value 78.667763
final  value 78.667763 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.854994 
iter  10 value 89.489529
iter  20 value 87.955360
iter  30 value 87.762112
iter  40 value 87.477037
iter  50 value 84.077212
iter  60 value 81.675434
iter  70 value 81.040872
iter  80 value 80.574819
iter  90 value 79.774460
iter 100 value 79.638232
final  value 79.638232 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.209937 
iter  10 value 92.682894
iter  20 value 86.174309
iter  30 value 81.470145
iter  40 value 80.373377
iter  50 value 80.059707
iter  60 value 79.838537
iter  70 value 79.291491
iter  80 value 78.839411
iter  90 value 78.742318
iter 100 value 78.639510
final  value 78.639510 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.824176 
final  value 94.485959 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.667541 
final  value 94.485814 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.739857 
final  value 94.485757 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.257836 
final  value 94.485854 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.397724 
final  value 94.487217 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.558698 
iter  10 value 94.488516
iter  20 value 94.355058
iter  30 value 94.277453
iter  40 value 89.350011
iter  50 value 88.460606
iter  60 value 86.415436
iter  70 value 82.435989
iter  80 value 77.535675
iter  90 value 77.321059
iter 100 value 77.277921
final  value 77.277921 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.263176 
iter  10 value 94.488631
iter  20 value 93.721466
iter  30 value 87.457267
iter  40 value 83.197370
iter  50 value 82.683816
iter  60 value 82.489261
iter  70 value 82.439959
final  value 82.438722 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.331321 
iter  10 value 94.451961
iter  20 value 93.601736
iter  30 value 93.210295
final  value 93.210216 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.333948 
iter  10 value 94.488979
iter  20 value 94.484423
iter  30 value 91.637761
iter  40 value 91.081508
iter  50 value 89.869421
final  value 89.868485 
converged
Fitting Repeat 5 

# weights:  305
initial  value 125.399952 
iter  10 value 94.489156
iter  20 value 94.452986
iter  30 value 87.891673
iter  40 value 87.580245
iter  50 value 85.535560
iter  60 value 82.671270
iter  70 value 82.314241
iter  80 value 82.070736
final  value 82.068638 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.901177 
iter  10 value 94.334612
iter  20 value 94.026183
iter  30 value 88.225471
iter  40 value 84.198213
iter  50 value 84.137432
iter  60 value 84.042092
iter  70 value 83.627020
iter  80 value 83.624973
final  value 83.624844 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.083386 
iter  10 value 89.513447
iter  20 value 88.380496
iter  30 value 87.818922
iter  40 value 87.815139
iter  50 value 87.813297
iter  60 value 85.887630
iter  70 value 85.551197
iter  80 value 85.485201
iter  90 value 85.445363
iter 100 value 85.444113
final  value 85.444113 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.453436 
iter  10 value 94.487254
iter  20 value 94.479523
iter  30 value 94.453042
iter  40 value 91.822547
iter  50 value 90.384352
iter  60 value 90.301843
iter  70 value 90.301403
iter  80 value 89.744851
iter  90 value 89.611516
iter 100 value 88.395650
final  value 88.395650 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.382836 
iter  10 value 94.362364
iter  20 value 92.391171
iter  30 value 90.692323
iter  40 value 90.596408
iter  50 value 90.577469
iter  60 value 90.577294
iter  70 value 90.511458
iter  80 value 88.800396
iter  90 value 84.876091
iter 100 value 84.104896
final  value 84.104896 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.049855 
iter  10 value 94.362513
iter  20 value 94.362016
iter  30 value 94.354023
iter  40 value 92.772044
iter  50 value 83.596891
iter  60 value 80.898439
iter  70 value 80.894323
iter  80 value 80.892183
iter  90 value 80.876147
iter 100 value 80.773723
final  value 80.773723 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.541217 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.795340 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.022108 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.870561 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.800578 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.160379 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.822827 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.942091 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.761058 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.671266 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.371261 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.246480 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.130868 
iter  10 value 93.962475
iter  20 value 93.943880
final  value 93.943842 
converged
Fitting Repeat 4 

# weights:  507
initial  value 93.238060 
iter  10 value 84.165878
iter  20 value 83.836808
iter  30 value 83.436573
iter  40 value 83.337450
iter  50 value 83.185978
iter  60 value 83.067341
iter  70 value 83.059876
iter  80 value 83.059498
iter  90 value 83.059454
final  value 83.059450 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.669368 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.315726 
iter  10 value 94.052037
iter  20 value 93.968814
iter  30 value 86.338434
iter  40 value 84.359852
iter  50 value 83.947727
iter  60 value 83.658343
iter  70 value 83.377181
iter  80 value 83.375594
final  value 83.375012 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.036803 
iter  10 value 94.056635
iter  20 value 89.855462
iter  30 value 85.787118
iter  40 value 82.713167
iter  50 value 82.274123
iter  60 value 81.851908
iter  70 value 81.443260
iter  80 value 81.254378
final  value 81.211204 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.607240 
iter  10 value 94.020824
iter  20 value 90.157963
iter  30 value 87.247776
iter  40 value 85.838118
iter  50 value 84.960268
iter  60 value 84.373419
iter  70 value 84.138242
iter  80 value 83.996188
final  value 83.987670 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.164529 
iter  10 value 94.124484
iter  20 value 94.056387
iter  30 value 94.052952
iter  40 value 85.120896
iter  50 value 84.113433
iter  60 value 83.478327
iter  70 value 83.387941
iter  80 value 83.367740
final  value 83.367635 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.865752 
iter  10 value 94.052471
iter  20 value 88.681194
iter  30 value 86.421247
iter  40 value 85.953023
iter  50 value 85.296289
iter  60 value 85.008319
iter  70 value 84.223887
iter  80 value 84.043930
final  value 83.987670 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.101914 
iter  10 value 93.869160
iter  20 value 89.684474
iter  30 value 85.993266
iter  40 value 85.429381
iter  50 value 81.696188
iter  60 value 81.030874
iter  70 value 80.709449
iter  80 value 80.605288
iter  90 value 80.569986
iter 100 value 80.516792
final  value 80.516792 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.881969 
iter  10 value 94.032314
iter  20 value 90.247285
iter  30 value 88.286112
iter  40 value 88.093474
iter  50 value 85.144210
iter  60 value 81.056473
iter  70 value 80.841330
iter  80 value 80.716842
iter  90 value 80.508529
iter 100 value 80.215834
final  value 80.215834 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.615596 
iter  10 value 94.275507
iter  20 value 93.920161
iter  30 value 93.313958
iter  40 value 87.939923
iter  50 value 86.508521
iter  60 value 84.611390
iter  70 value 83.118632
iter  80 value 82.674132
iter  90 value 82.173851
iter 100 value 81.416514
final  value 81.416514 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.813883 
iter  10 value 93.443515
iter  20 value 87.421131
iter  30 value 85.811426
iter  40 value 84.707153
iter  50 value 84.076539
iter  60 value 83.972554
iter  70 value 83.867112
iter  80 value 83.618018
iter  90 value 83.561758
iter 100 value 83.494096
final  value 83.494096 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.285336 
iter  10 value 94.163234
iter  20 value 93.341014
iter  30 value 88.708640
iter  40 value 85.955374
iter  50 value 83.319943
iter  60 value 82.427655
iter  70 value 81.933731
iter  80 value 81.574893
iter  90 value 81.444579
iter 100 value 81.047259
final  value 81.047259 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.036366 
iter  10 value 94.044109
iter  20 value 89.997634
iter  30 value 85.727101
iter  40 value 83.473758
iter  50 value 82.537851
iter  60 value 81.722771
iter  70 value 81.363975
iter  80 value 80.435430
iter  90 value 80.181371
iter 100 value 79.860422
final  value 79.860422 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.990515 
iter  10 value 93.090815
iter  20 value 88.492460
iter  30 value 84.929831
iter  40 value 84.007413
iter  50 value 83.638458
iter  60 value 82.179113
iter  70 value 81.333464
iter  80 value 80.723722
iter  90 value 80.240728
iter 100 value 79.772021
final  value 79.772021 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.013681 
iter  10 value 94.628705
iter  20 value 93.274962
iter  30 value 85.563883
iter  40 value 84.092895
iter  50 value 83.092097
iter  60 value 81.288073
iter  70 value 80.791081
iter  80 value 80.509091
iter  90 value 80.250930
iter 100 value 80.194891
final  value 80.194891 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.761543 
iter  10 value 97.967981
iter  20 value 90.850617
iter  30 value 89.675230
iter  40 value 84.101364
iter  50 value 82.380493
iter  60 value 81.508130
iter  70 value 80.470844
iter  80 value 80.062755
iter  90 value 79.912634
iter 100 value 79.699920
final  value 79.699920 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.142208 
iter  10 value 91.376120
iter  20 value 85.948172
iter  30 value 84.261012
iter  40 value 81.691925
iter  50 value 81.031135
iter  60 value 80.719547
iter  70 value 79.995297
iter  80 value 79.657708
iter  90 value 79.572500
iter 100 value 79.450148
final  value 79.450148 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.280829 
final  value 94.054226 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.563846 
final  value 94.054428 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.639466 
iter  10 value 86.832906
iter  20 value 84.242444
iter  30 value 83.966681
iter  40 value 83.935219
iter  50 value 83.934484
final  value 83.933129 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.710884 
final  value 94.054495 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.628314 
final  value 94.054623 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.700433 
iter  10 value 94.038025
iter  20 value 93.982830
iter  30 value 93.810410
final  value 93.809460 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.225467 
iter  10 value 93.730020
iter  20 value 93.715773
iter  30 value 85.544544
iter  40 value 85.177521
iter  50 value 85.176581
iter  60 value 83.912763
iter  70 value 82.851502
iter  80 value 82.687729
iter  90 value 82.640883
iter 100 value 82.637639
final  value 82.637639 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.632661 
iter  10 value 94.056975
iter  20 value 93.381221
iter  30 value 92.878118
iter  40 value 92.736868
iter  50 value 92.723930
iter  60 value 91.681993
iter  70 value 91.678497
final  value 91.678352 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.301627 
iter  10 value 94.058100
iter  20 value 94.052918
iter  30 value 92.876378
iter  40 value 85.929772
iter  50 value 82.942896
iter  60 value 82.625302
iter  70 value 82.620918
iter  80 value 82.546089
iter  90 value 82.104971
iter 100 value 82.049168
final  value 82.049168 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.071943 
iter  10 value 94.057903
iter  20 value 94.053059
iter  30 value 87.532723
iter  40 value 85.331353
iter  50 value 85.321059
iter  60 value 85.318751
iter  70 value 84.447321
iter  80 value 83.214196
iter  90 value 80.306947
iter 100 value 80.097892
final  value 80.097892 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.376628 
iter  10 value 94.061074
iter  20 value 94.018338
iter  30 value 87.779302
iter  40 value 84.350125
iter  50 value 84.318339
iter  60 value 84.301053
iter  70 value 83.336806
iter  80 value 81.373731
iter  90 value 80.479816
iter 100 value 80.339043
final  value 80.339043 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.873321 
iter  10 value 93.286482
iter  20 value 93.246335
iter  30 value 92.638808
iter  40 value 92.499853
iter  50 value 92.498516
iter  50 value 92.498515
iter  60 value 92.498116
iter  70 value 92.496696
iter  80 value 92.494079
iter  90 value 91.899976
iter 100 value 85.661498
final  value 85.661498 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.906414 
iter  10 value 94.040870
iter  20 value 93.626259
iter  30 value 92.738502
iter  40 value 92.577145
iter  50 value 92.547832
iter  60 value 92.546397
final  value 92.545240 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.531071 
iter  10 value 94.060090
iter  20 value 90.804213
iter  30 value 85.385043
iter  40 value 85.314914
iter  50 value 83.947289
iter  60 value 82.705469
iter  70 value 82.300157
iter  80 value 82.021240
final  value 82.021135 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.535878 
iter  10 value 94.044927
iter  20 value 94.040059
iter  30 value 86.304493
iter  40 value 84.561654
iter  50 value 84.508150
iter  60 value 84.364053
iter  70 value 84.352102
iter  80 value 84.161712
iter  90 value 81.174652
iter 100 value 80.820932
final  value 80.820932 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.938168 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.195002 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.542125 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.159591 
iter  10 value 93.772973
iter  10 value 93.772973
iter  10 value 93.772973
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.461517 
iter  10 value 92.597607
iter  20 value 88.847252
iter  30 value 87.324243
iter  40 value 86.747756
iter  50 value 86.747308
iter  50 value 86.747308
iter  50 value 86.747308
final  value 86.747308 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.922530 
iter  10 value 93.772994
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.885430 
iter  10 value 93.773441
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.781021 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.567847 
final  value 93.691092 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.266449 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.900328 
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.481847 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.524562 
iter  10 value 92.137006
final  value 92.019542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.944518 
iter  10 value 93.772974
iter  10 value 93.772974
iter  10 value 93.772974
final  value 93.772974 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.810481 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.597760 
iter  10 value 94.488405
iter  20 value 94.221520
iter  30 value 92.359760
iter  40 value 84.394353
iter  50 value 81.855957
iter  60 value 81.785798
iter  70 value 81.778707
iter  80 value 81.775890
iter  90 value 81.775668
iter 100 value 81.774824
final  value 81.774824 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 110.885703 
iter  10 value 93.605408
iter  20 value 87.228318
iter  30 value 84.367965
iter  40 value 83.116849
iter  50 value 82.625283
iter  60 value 82.086047
iter  70 value 82.070504
iter  80 value 82.058214
final  value 82.058182 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.757680 
iter  10 value 94.483829
iter  20 value 93.420294
iter  30 value 93.153041
iter  40 value 89.503993
iter  50 value 87.306048
iter  60 value 86.806548
iter  70 value 86.572361
iter  80 value 85.583267
iter  90 value 84.578668
iter 100 value 84.556220
final  value 84.556220 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.099082 
iter  10 value 93.421692
iter  20 value 87.425302
iter  30 value 85.718018
iter  40 value 84.618827
iter  50 value 84.591399
iter  60 value 84.587891
iter  60 value 84.587891
iter  60 value 84.587891
final  value 84.587891 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.151634 
iter  10 value 94.244327
iter  20 value 89.088795
iter  30 value 87.740661
iter  40 value 86.320899
iter  50 value 85.703498
iter  60 value 85.468604
iter  70 value 85.353813
iter  80 value 84.197912
iter  90 value 82.289991
iter 100 value 82.227633
final  value 82.227633 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.121155 
iter  10 value 94.464684
iter  20 value 90.257033
iter  30 value 86.904175
iter  40 value 84.160341
iter  50 value 82.767054
iter  60 value 81.927579
iter  70 value 81.386983
iter  80 value 81.037455
iter  90 value 80.826124
iter 100 value 80.727901
final  value 80.727901 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.414355 
iter  10 value 94.933912
iter  20 value 92.710450
iter  30 value 89.505455
iter  40 value 87.353307
iter  50 value 85.394515
iter  60 value 82.708021
iter  70 value 81.987977
iter  80 value 81.781002
iter  90 value 81.678688
iter 100 value 81.667909
final  value 81.667909 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.014346 
iter  10 value 95.203584
iter  20 value 94.492177
iter  30 value 94.161169
iter  40 value 91.044030
iter  50 value 90.713618
iter  60 value 90.473873
iter  70 value 90.448862
iter  80 value 89.856638
iter  90 value 84.714721
iter 100 value 82.461063
final  value 82.461063 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.872088 
iter  10 value 93.942400
iter  20 value 89.242739
iter  30 value 86.414916
iter  40 value 85.953645
iter  50 value 85.777201
iter  60 value 85.570627
iter  70 value 85.547661
iter  80 value 85.527217
iter  90 value 85.381430
iter 100 value 83.586846
final  value 83.586846 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.943785 
iter  10 value 94.218687
iter  20 value 85.462847
iter  30 value 84.023546
iter  40 value 82.886914
iter  50 value 82.295001
iter  60 value 82.040888
iter  70 value 81.770290
iter  80 value 81.389115
iter  90 value 80.932511
iter 100 value 80.772557
final  value 80.772557 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.053903 
iter  10 value 96.568631
iter  20 value 94.490511
iter  30 value 87.610338
iter  40 value 86.120614
iter  50 value 84.578683
iter  60 value 82.113320
iter  70 value 81.833922
iter  80 value 81.173764
iter  90 value 80.756869
iter 100 value 80.584301
final  value 80.584301 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.252841 
iter  10 value 95.631882
iter  20 value 94.741109
iter  30 value 92.834821
iter  40 value 86.248666
iter  50 value 85.706463
iter  60 value 85.173880
iter  70 value 83.171118
iter  80 value 82.151982
iter  90 value 81.490629
iter 100 value 80.951829
final  value 80.951829 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.062022 
iter  10 value 94.920520
iter  20 value 93.333143
iter  30 value 87.298084
iter  40 value 84.929945
iter  50 value 83.904963
iter  60 value 82.796643
iter  70 value 81.023977
iter  80 value 80.265854
iter  90 value 80.062218
iter 100 value 79.962483
final  value 79.962483 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.266515 
iter  10 value 94.526166
iter  20 value 93.382770
iter  30 value 87.590471
iter  40 value 87.113126
iter  50 value 85.510221
iter  60 value 85.207943
iter  70 value 84.763216
iter  80 value 83.887581
iter  90 value 82.623723
iter 100 value 81.368584
final  value 81.368584 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 137.316064 
iter  10 value 94.490101
iter  20 value 93.892015
iter  30 value 93.359744
iter  40 value 88.289556
iter  50 value 84.429234
iter  60 value 83.148643
iter  70 value 83.003481
iter  80 value 82.950210
iter  90 value 82.753028
iter 100 value 82.051546
final  value 82.051546 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.380789 
final  value 94.485837 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.036084 
iter  10 value 94.485904
iter  20 value 94.484252
final  value 94.484215 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.600812 
iter  10 value 94.485794
iter  20 value 94.484214
iter  20 value 94.484214
iter  20 value 94.484214
final  value 94.484214 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.201579 
final  value 94.254801 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.070934 
final  value 94.486015 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.615177 
iter  10 value 94.215373
iter  20 value 93.777994
iter  30 value 93.511166
iter  40 value 93.475857
iter  50 value 93.008859
iter  60 value 93.007116
iter  70 value 88.258007
iter  80 value 86.246723
iter  90 value 84.556439
iter 100 value 84.216654
final  value 84.216654 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.259374 
iter  10 value 93.778650
iter  20 value 93.776532
iter  30 value 93.435625
iter  40 value 92.057237
iter  50 value 86.531019
iter  60 value 82.632446
iter  70 value 80.780124
iter  80 value 80.014889
iter  90 value 80.005827
final  value 80.005107 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.348733 
iter  10 value 94.488930
iter  20 value 94.483843
iter  30 value 94.291987
final  value 93.773421 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.900534 
iter  10 value 94.489121
iter  20 value 94.477932
iter  30 value 92.347971
iter  40 value 85.391004
iter  50 value 85.095540
final  value 85.093744 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.870979 
iter  10 value 94.489654
iter  20 value 93.312304
iter  30 value 93.302509
iter  40 value 93.262478
iter  50 value 84.221628
iter  60 value 82.629614
iter  70 value 81.102885
iter  80 value 80.007350
final  value 80.007129 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.525597 
iter  10 value 94.493145
iter  20 value 94.485130
iter  30 value 93.412690
iter  40 value 88.053075
iter  50 value 87.401856
iter  60 value 87.391761
iter  70 value 87.391251
final  value 87.387364 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.560902 
iter  10 value 94.492311
iter  20 value 94.431418
iter  30 value 92.983461
iter  40 value 91.800668
iter  50 value 91.467813
iter  60 value 91.466045
iter  70 value 91.465076
iter  80 value 91.464513
iter  80 value 91.464513
final  value 91.464513 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.379592 
iter  10 value 93.781665
iter  20 value 93.779072
iter  30 value 91.081940
iter  40 value 91.011845
iter  50 value 90.703142
iter  60 value 90.501526
iter  70 value 90.446539
final  value 90.444447 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.043078 
iter  10 value 93.515587
iter  20 value 93.508579
iter  30 value 93.139729
final  value 93.085679 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.066638 
iter  10 value 94.334646
iter  20 value 90.675825
iter  30 value 84.025893
iter  40 value 83.986560
iter  50 value 83.986323
iter  50 value 83.986323
iter  50 value 83.986323
final  value 83.986323 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.644988 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.052226 
iter  10 value 93.996119
final  value 93.994891 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.594727 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.062522 
iter  10 value 92.929142
iter  20 value 92.923556
final  value 92.923530 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.310569 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.670672 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.692397 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.637298 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.006993 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.039120 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.513985 
iter  10 value 94.276223
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.937186 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.754009 
final  value 94.274404 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.490400 
iter  10 value 94.307530
iter  20 value 94.274445
final  value 94.274405 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.324329 
iter  10 value 93.286594
final  value 93.286550 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.887608 
iter  10 value 94.440802
iter  20 value 92.830547
iter  30 value 87.782987
iter  40 value 83.880196
iter  50 value 82.446399
iter  60 value 82.367485
iter  70 value 82.315505
iter  80 value 82.148531
iter  90 value 81.999379
final  value 81.992302 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.868626 
iter  10 value 94.439876
iter  20 value 94.117562
iter  30 value 93.669313
iter  40 value 93.655860
iter  50 value 92.988252
iter  60 value 90.656743
iter  70 value 88.694614
iter  80 value 86.396836
iter  90 value 86.246725
iter 100 value 82.384225
final  value 82.384225 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.195172 
iter  10 value 94.490208
iter  20 value 91.434970
iter  30 value 87.845934
final  value 86.399884 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.107977 
iter  10 value 94.497333
iter  20 value 94.332052
iter  30 value 93.490485
iter  40 value 90.669631
iter  50 value 89.320943
iter  60 value 82.186748
iter  70 value 81.799461
iter  80 value 81.663638
iter  90 value 81.504081
iter 100 value 81.453771
final  value 81.453771 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.564593 
iter  10 value 92.498124
iter  20 value 82.189223
iter  30 value 81.789849
iter  40 value 81.547881
iter  50 value 81.455754
final  value 81.453729 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.820290 
iter  10 value 94.373590
iter  20 value 89.384907
iter  30 value 85.357090
iter  40 value 81.919632
iter  50 value 81.674592
iter  60 value 81.089621
iter  70 value 79.961273
iter  80 value 79.659350
iter  90 value 79.042625
iter 100 value 78.949815
final  value 78.949815 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.393740 
iter  10 value 94.382274
iter  20 value 88.957419
iter  30 value 87.408522
iter  40 value 86.671652
iter  50 value 85.417718
iter  60 value 84.641976
iter  70 value 82.850355
iter  80 value 81.292986
iter  90 value 80.686825
iter 100 value 80.518350
final  value 80.518350 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.025402 
iter  10 value 94.515293
iter  20 value 86.978046
iter  30 value 86.261918
iter  40 value 84.034468
iter  50 value 83.051405
iter  60 value 82.043703
iter  70 value 80.517882
iter  80 value 80.376736
iter  90 value 80.105537
iter 100 value 79.858753
final  value 79.858753 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.538577 
iter  10 value 93.945451
iter  20 value 85.894749
iter  30 value 85.765661
iter  40 value 84.596303
iter  50 value 82.227562
iter  60 value 80.609929
iter  70 value 80.415219
final  value 80.347898 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.264935 
iter  10 value 94.312307
iter  20 value 92.478943
iter  30 value 84.313824
iter  40 value 82.775417
iter  50 value 82.424531
iter  60 value 81.576502
iter  70 value 80.619949
iter  80 value 79.662022
iter  90 value 79.220819
iter 100 value 79.110906
final  value 79.110906 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.992862 
iter  10 value 92.507850
iter  20 value 87.390201
iter  30 value 86.454474
iter  40 value 85.547081
iter  50 value 84.189758
iter  60 value 80.644485
iter  70 value 80.470875
iter  80 value 80.157452
iter  90 value 79.372316
iter 100 value 79.058714
final  value 79.058714 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.608405 
iter  10 value 94.992133
iter  20 value 87.821214
iter  30 value 84.367979
iter  40 value 82.705241
iter  50 value 82.270013
iter  60 value 81.225934
iter  70 value 80.890564
iter  80 value 80.399630
iter  90 value 79.916049
iter 100 value 79.550830
final  value 79.550830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.806860 
iter  10 value 95.103841
iter  20 value 85.101120
iter  30 value 82.227711
iter  40 value 81.879184
iter  50 value 80.750813
iter  60 value 79.972365
iter  70 value 79.563639
iter  80 value 79.511746
iter  90 value 79.364472
iter 100 value 79.214213
final  value 79.214213 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.464627 
iter  10 value 85.485759
iter  20 value 83.250465
iter  30 value 82.037680
iter  40 value 81.404124
iter  50 value 80.421905
iter  60 value 79.719054
iter  70 value 79.560789
iter  80 value 79.468052
iter  90 value 79.295020
iter 100 value 79.192762
final  value 79.192762 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.526589 
iter  10 value 91.247131
iter  20 value 84.988398
iter  30 value 81.754115
iter  40 value 81.423692
iter  50 value 80.795922
iter  60 value 79.946923
iter  70 value 79.710649
iter  80 value 79.687034
iter  90 value 79.653022
iter 100 value 79.538410
final  value 79.538410 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.368250 
final  value 94.486018 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.913501 
iter  10 value 86.663996
iter  20 value 84.943073
iter  30 value 84.872630
iter  40 value 84.871262
iter  50 value 80.894271
iter  60 value 80.890548
iter  70 value 80.886699
final  value 80.886460 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.423700 
final  value 94.485679 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.905608 
final  value 94.485888 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.490092 
final  value 94.485890 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.284544 
iter  10 value 94.280100
iter  20 value 94.230017
iter  30 value 85.170387
iter  40 value 85.169266
iter  50 value 85.081038
iter  60 value 84.657846
iter  70 value 84.657736
final  value 84.657343 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.273031 
iter  10 value 94.489167
iter  20 value 94.475886
iter  30 value 81.401482
iter  40 value 80.903380
iter  50 value 80.891120
iter  60 value 80.236519
iter  70 value 78.759276
iter  80 value 78.087287
iter  90 value 77.987859
iter 100 value 77.922841
final  value 77.922841 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.461442 
iter  10 value 94.488688
iter  20 value 94.479505
iter  30 value 90.988301
iter  40 value 90.590623
iter  50 value 90.212279
iter  60 value 81.908794
iter  70 value 79.829390
iter  80 value 79.643586
iter  90 value 79.071536
iter 100 value 78.966227
final  value 78.966227 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.687312 
iter  10 value 94.280382
iter  20 value 94.097174
iter  30 value 94.000694
iter  40 value 93.322102
iter  50 value 92.607166
iter  60 value 92.604139
iter  70 value 92.494205
iter  80 value 92.492846
final  value 92.492844 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.419867 
iter  10 value 94.489012
iter  20 value 94.401743
iter  30 value 93.512813
final  value 93.512409 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.752872 
iter  10 value 94.491837
iter  20 value 94.484333
iter  30 value 94.424953
iter  40 value 93.549037
iter  50 value 91.919740
iter  60 value 84.366443
iter  70 value 82.088483
iter  80 value 81.589658
iter  90 value 81.562362
iter 100 value 81.486399
final  value 81.486399 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.025595 
iter  10 value 85.343165
iter  20 value 85.029209
iter  30 value 84.673396
iter  40 value 84.637632
iter  50 value 84.475073
iter  60 value 81.960319
iter  70 value 81.508930
iter  80 value 81.245350
iter  90 value 81.115923
iter 100 value 81.112752
final  value 81.112752 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.537593 
iter  10 value 94.417469
iter  20 value 94.261620
iter  30 value 94.258679
iter  40 value 94.201594
iter  50 value 94.200915
final  value 94.200839 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.900967 
iter  10 value 94.283583
iter  20 value 94.278067
iter  30 value 90.529820
iter  40 value 89.250691
iter  50 value 89.250231
final  value 89.250162 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.260558 
iter  10 value 94.284003
iter  20 value 94.276496
iter  30 value 94.010455
iter  40 value 81.785552
iter  50 value 81.760003
iter  60 value 80.943419
iter  70 value 80.699971
iter  80 value 80.459539
iter  90 value 80.410546
iter 100 value 80.407682
final  value 80.407682 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 128.461476 
iter  10 value 115.931822
iter  20 value 108.902929
iter  30 value 106.776232
iter  40 value 106.215554
iter  50 value 106.181481
iter  60 value 105.602640
iter  70 value 105.097079
iter  80 value 104.930519
iter  90 value 104.894980
iter 100 value 103.399607
final  value 103.399607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 147.599776 
iter  10 value 118.269112
iter  20 value 111.033687
iter  30 value 108.384544
iter  40 value 106.235522
iter  50 value 103.257456
iter  60 value 102.704258
iter  70 value 102.073482
iter  80 value 101.975601
iter  90 value 101.620961
iter 100 value 101.409006
final  value 101.409006 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.783917 
iter  10 value 117.399555
iter  20 value 108.981639
iter  30 value 105.782761
iter  40 value 105.109005
iter  50 value 103.754435
iter  60 value 103.394735
iter  70 value 102.464978
iter  80 value 101.701405
iter  90 value 101.640014
iter 100 value 101.595584
final  value 101.595584 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 148.430198 
iter  10 value 117.555166
iter  20 value 116.341361
iter  30 value 108.277063
iter  40 value 107.193950
iter  50 value 105.677732
iter  60 value 105.276287
iter  70 value 104.367916
iter  80 value 103.399914
iter  90 value 102.260248
iter 100 value 101.316455
final  value 101.316455 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 146.991779 
iter  10 value 117.850538
iter  20 value 117.426965
iter  30 value 115.527923
iter  40 value 110.351161
iter  50 value 107.042947
iter  60 value 105.576141
iter  70 value 104.503503
iter  80 value 102.258114
iter  90 value 101.313183
iter 100 value 100.921845
final  value 100.921845 
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 -- Mon Apr 21 21:23:52 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 
 40.175   1.601 119.849