##############################################################################
##############################################################################
###
### 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_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 Patched (2024-04-24 r86482)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* 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 ... 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
var_imp       54.251  2.380  56.952
corr_plot     53.557  2.485  56.261
FSmethod      43.056  1.630  45.589
pred_ensembel 16.725  0.311  14.372
enrichfindP    0.507  0.074   6.862
* 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
  ‘/Users/biocbuild/bbs-3.20-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/4.4-arm64/Resources/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 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-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 104.906744 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.588295 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.529148 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.794030 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.653137 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.172266 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.475816 
final  value 94.304608 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.105414 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.468599 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.898371 
iter  10 value 92.183582
iter  20 value 91.169804
iter  30 value 83.683408
iter  40 value 83.621539
iter  50 value 83.597693
final  value 83.591261 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.327300 
iter  10 value 92.077099
final  value 92.074748 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.489752 
iter  10 value 84.419201
iter  20 value 83.580295
iter  30 value 83.528294
iter  40 value 83.526332
final  value 83.526317 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.047461 
iter  10 value 94.478108
iter  20 value 94.467415
final  value 94.467392 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.119004 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.480965 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.369195 
iter  10 value 94.303878
iter  20 value 92.352312
iter  30 value 91.844349
iter  40 value 91.578939
iter  50 value 89.154430
iter  60 value 87.440042
iter  70 value 85.934807
iter  80 value 84.730995
iter  90 value 84.229264
iter 100 value 84.210306
final  value 84.210306 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.743163 
iter  10 value 94.488645
iter  20 value 94.138669
iter  30 value 93.603885
iter  40 value 93.504085
iter  50 value 89.353851
iter  60 value 88.703608
iter  70 value 85.383905
iter  80 value 84.389589
iter  90 value 83.847663
iter 100 value 83.279585
final  value 83.279585 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.322296 
iter  10 value 94.474179
iter  20 value 93.360050
iter  30 value 92.551093
iter  40 value 91.945785
iter  50 value 88.796197
iter  60 value 87.242158
iter  70 value 83.947179
iter  80 value 81.839263
iter  90 value 81.776003
final  value 81.775987 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.168223 
iter  10 value 94.530685
iter  20 value 94.463767
iter  30 value 94.064974
iter  40 value 92.949094
iter  50 value 91.566555
iter  60 value 86.864138
iter  70 value 84.070217
iter  80 value 83.404501
iter  90 value 83.170363
iter 100 value 82.693842
final  value 82.693842 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.840428 
iter  10 value 94.488771
iter  20 value 86.379368
iter  30 value 84.880665
iter  40 value 84.137892
iter  50 value 83.784363
iter  60 value 83.231742
iter  70 value 83.162384
final  value 83.162256 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.707223 
iter  10 value 94.417043
iter  20 value 91.595820
iter  30 value 91.306267
iter  40 value 88.269683
iter  50 value 85.246987
iter  60 value 83.930422
iter  70 value 82.891805
iter  80 value 82.437035
iter  90 value 82.380450
iter 100 value 82.064917
final  value 82.064917 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.765522 
iter  10 value 94.855717
iter  20 value 89.850295
iter  30 value 85.862107
iter  40 value 84.743752
iter  50 value 83.583785
iter  60 value 82.265520
iter  70 value 81.864860
iter  80 value 81.772629
iter  90 value 81.486893
iter 100 value 81.129170
final  value 81.129170 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 123.198765 
iter  10 value 94.184306
iter  20 value 92.089438
iter  30 value 84.621665
iter  40 value 84.157234
iter  50 value 83.716380
iter  60 value 82.878736
iter  70 value 82.641751
iter  80 value 82.345894
iter  90 value 82.303386
iter 100 value 81.622404
final  value 81.622404 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.345197 
iter  10 value 88.887469
iter  20 value 87.635407
iter  30 value 85.729399
iter  40 value 83.410836
iter  50 value 82.431956
iter  60 value 82.276765
iter  70 value 82.240941
iter  80 value 82.086014
iter  90 value 81.730931
iter 100 value 81.503256
final  value 81.503256 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.015399 
iter  10 value 94.368062
iter  20 value 92.258209
iter  30 value 91.988213
iter  40 value 85.502451
iter  50 value 84.231309
iter  60 value 83.581915
iter  70 value 81.732245
iter  80 value 81.366887
iter  90 value 80.933513
iter 100 value 80.857791
final  value 80.857791 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.619925 
iter  10 value 96.195806
iter  20 value 94.160904
iter  30 value 87.050846
iter  40 value 84.369851
iter  50 value 84.284443
iter  60 value 83.580710
iter  70 value 82.857495
iter  80 value 82.331235
iter  90 value 81.818244
iter 100 value 81.255676
final  value 81.255676 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.166548 
iter  10 value 94.848982
iter  20 value 92.608753
iter  30 value 84.761091
iter  40 value 83.497940
iter  50 value 81.997971
iter  60 value 81.363639
iter  70 value 80.733598
iter  80 value 80.685252
iter  90 value 80.656107
iter 100 value 80.606043
final  value 80.606043 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.086420 
iter  10 value 94.420426
iter  20 value 90.374978
iter  30 value 83.903983
iter  40 value 82.189684
iter  50 value 81.413408
iter  60 value 81.360950
iter  70 value 80.933088
iter  80 value 80.897823
iter  90 value 80.829925
iter 100 value 80.680874
final  value 80.680874 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.793990 
iter  10 value 93.337948
iter  20 value 85.131294
iter  30 value 83.984414
iter  40 value 83.812868
iter  50 value 82.982909
iter  60 value 82.136033
iter  70 value 81.218931
iter  80 value 81.027709
iter  90 value 80.571411
iter 100 value 80.409202
final  value 80.409202 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.810861 
iter  10 value 94.651952
iter  20 value 86.244109
iter  30 value 84.982804
iter  40 value 84.102267
iter  50 value 83.461647
iter  60 value 82.852949
iter  70 value 82.625419
iter  80 value 81.733393
iter  90 value 81.291628
iter 100 value 80.978625
final  value 80.978625 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.918720 
iter  10 value 94.485864
iter  20 value 94.484228
iter  30 value 84.603507
iter  40 value 83.580696
final  value 83.580685 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.237844 
final  value 94.485640 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.915716 
final  value 94.485701 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.205244 
final  value 94.485733 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.152726 
final  value 94.486068 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.430768 
iter  10 value 94.472128
iter  20 value 92.242890
iter  30 value 92.157968
iter  40 value 92.153130
iter  50 value 91.553461
final  value 91.553456 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.964363 
iter  10 value 94.489219
iter  20 value 94.136140
iter  30 value 91.662838
iter  40 value 88.931767
iter  50 value 88.914323
iter  60 value 88.816603
iter  70 value 88.337536
iter  80 value 88.030379
iter  90 value 88.026581
iter 100 value 87.629688
final  value 87.629688 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.463045 
iter  10 value 94.487560
iter  20 value 94.446908
iter  30 value 94.444186
iter  40 value 94.345512
iter  50 value 90.771774
iter  60 value 90.529114
iter  70 value 87.556055
iter  80 value 87.429133
iter  90 value 87.396906
iter 100 value 87.396178
final  value 87.396178 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.130214 
iter  10 value 94.488543
iter  20 value 94.484275
iter  30 value 88.684545
iter  40 value 84.223510
iter  50 value 83.867848
iter  60 value 83.860598
iter  70 value 83.733775
iter  80 value 83.580742
iter  80 value 83.580742
final  value 83.580742 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.343656 
iter  10 value 94.285312
iter  20 value 94.150081
iter  30 value 94.144597
iter  40 value 94.116132
iter  50 value 94.114437
iter  60 value 88.271023
iter  70 value 84.599092
iter  80 value 83.587388
iter  90 value 83.171408
iter 100 value 83.091700
final  value 83.091700 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.584668 
iter  10 value 89.319221
iter  20 value 89.048902
iter  30 value 89.034401
final  value 88.808618 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.347703 
iter  10 value 93.947571
iter  20 value 93.930541
iter  30 value 93.924691
iter  40 value 91.814112
iter  50 value 91.660651
iter  60 value 91.493902
iter  70 value 91.260844
final  value 91.260764 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.239566 
iter  10 value 94.491503
iter  20 value 94.485624
iter  30 value 94.351723
iter  40 value 87.756483
iter  50 value 85.346640
iter  60 value 85.136942
iter  70 value 83.319144
iter  80 value 83.060892
iter  90 value 83.037651
iter 100 value 82.977891
final  value 82.977891 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.194445 
iter  10 value 94.096860
iter  20 value 93.644403
iter  30 value 89.406986
iter  40 value 84.104563
iter  50 value 83.444053
iter  60 value 83.440308
iter  70 value 82.541686
iter  80 value 82.511999
iter  90 value 82.511880
iter 100 value 82.506531
final  value 82.506531 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.372853 
iter  10 value 92.080285
iter  20 value 92.067118
iter  30 value 91.232921
iter  40 value 91.082417
iter  50 value 91.037836
iter  60 value 90.989900
iter  70 value 90.989491
iter  80 value 90.523370
iter  90 value 90.255892
iter 100 value 86.683109
final  value 86.683109 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.218477 
iter  10 value 94.112904
iter  10 value 94.112903
iter  10 value 94.112903
final  value 94.112903 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.235680 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.574480 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.079647 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.309002 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.712999 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.875580 
iter  10 value 94.124537
final  value 94.065746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.059941 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 93.461628 
iter  10 value 84.719596
iter  20 value 84.396067
iter  30 value 84.387880
iter  30 value 84.387879
iter  30 value 84.387879
final  value 84.387879 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.108044 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.046016 
iter  10 value 94.070517
iter  20 value 93.940239
iter  30 value 93.938225
final  value 93.938213 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.564450 
iter  10 value 86.233574
iter  20 value 85.822457
iter  30 value 84.848463
iter  40 value 84.569565
iter  40 value 84.569565
iter  40 value 84.569565
final  value 84.569565 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.900949 
iter  10 value 93.743183
final  value 93.743182 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.870916 
iter  10 value 94.165117
iter  10 value 94.165117
iter  10 value 94.165117
final  value 94.165117 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.318320 
iter  10 value 94.112873
iter  20 value 94.045984
final  value 94.045978 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.326251 
iter  10 value 94.096928
iter  20 value 86.828525
iter  30 value 86.644169
iter  40 value 86.543625
iter  50 value 85.846423
iter  60 value 83.311536
iter  70 value 83.162886
iter  80 value 83.127861
iter  90 value 83.101940
final  value 83.098705 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.022900 
iter  10 value 94.487946
iter  20 value 94.281960
iter  30 value 94.237419
iter  40 value 94.235278
iter  50 value 93.840713
iter  60 value 91.436075
iter  70 value 88.996484
iter  80 value 88.217690
iter  90 value 84.566880
iter 100 value 84.012076
final  value 84.012076 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.916643 
iter  10 value 94.469311
iter  20 value 90.070205
iter  30 value 87.032816
iter  40 value 86.409290
iter  50 value 86.332347
iter  60 value 83.738161
iter  70 value 83.631208
final  value 83.630112 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.120244 
iter  10 value 94.467429
iter  20 value 94.202774
iter  30 value 92.464409
iter  40 value 87.355830
iter  50 value 87.117017
iter  60 value 85.532260
iter  70 value 83.130061
iter  80 value 82.766407
iter  90 value 82.672131
iter 100 value 82.498836
final  value 82.498836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.583436 
iter  10 value 94.441667
iter  20 value 87.929551
iter  30 value 86.926307
iter  40 value 84.008738
iter  50 value 83.698397
iter  60 value 83.680371
iter  70 value 83.666902
iter  70 value 83.666901
final  value 83.666901 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.492092 
iter  10 value 94.562275
iter  20 value 93.723242
iter  30 value 84.989330
iter  40 value 84.511471
iter  50 value 82.454206
iter  60 value 81.791436
iter  70 value 81.107327
iter  80 value 80.720694
iter  90 value 80.440653
iter 100 value 80.336583
final  value 80.336583 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.760348 
iter  10 value 97.000455
iter  20 value 88.131728
iter  30 value 84.331138
iter  40 value 83.343248
iter  50 value 82.146940
iter  60 value 81.274897
iter  70 value 80.882445
iter  80 value 80.648916
iter  90 value 80.420477
iter 100 value 80.357170
final  value 80.357170 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.865503 
iter  10 value 94.532797
iter  20 value 89.276332
iter  30 value 88.431938
iter  40 value 87.180566
iter  50 value 83.996911
iter  60 value 82.393225
iter  70 value 81.041382
iter  80 value 80.339648
iter  90 value 80.266848
iter 100 value 80.197185
final  value 80.197185 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.023130 
iter  10 value 96.406998
iter  20 value 90.588869
iter  30 value 87.042517
iter  40 value 86.636052
iter  50 value 86.550611
iter  60 value 83.178420
iter  70 value 81.765768
iter  80 value 81.226637
iter  90 value 81.183114
iter 100 value 81.119147
final  value 81.119147 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.276963 
iter  10 value 94.492747
iter  20 value 87.998891
iter  30 value 87.479241
iter  40 value 82.846336
iter  50 value 82.187317
iter  60 value 81.509832
iter  70 value 81.000633
iter  80 value 80.794493
iter  90 value 80.761149
final  value 80.759637 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.434875 
iter  10 value 93.996979
iter  20 value 84.796911
iter  30 value 83.501391
iter  40 value 81.882454
iter  50 value 81.649185
iter  60 value 81.489013
iter  70 value 81.293353
iter  80 value 81.228539
iter  90 value 80.785502
iter 100 value 80.426542
final  value 80.426542 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.947214 
iter  10 value 94.245525
iter  20 value 86.620452
iter  30 value 86.313355
iter  40 value 84.748297
iter  50 value 83.296491
iter  60 value 83.012235
iter  70 value 82.856003
iter  80 value 82.656158
iter  90 value 82.624319
iter 100 value 82.614318
final  value 82.614318 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.893885 
iter  10 value 94.661907
iter  20 value 89.199839
iter  30 value 88.605972
iter  40 value 86.155230
iter  50 value 82.752557
iter  60 value 82.137302
iter  70 value 81.689237
iter  80 value 81.520160
iter  90 value 81.388826
iter 100 value 81.206160
final  value 81.206160 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 151.530822 
iter  10 value 98.017851
iter  20 value 97.188791
iter  30 value 92.291399
iter  40 value 86.974945
iter  50 value 84.507692
iter  60 value 83.912499
iter  70 value 82.726058
iter  80 value 81.402087
iter  90 value 80.846991
iter 100 value 80.714044
final  value 80.714044 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.578173 
iter  10 value 94.604708
iter  20 value 91.754691
iter  30 value 83.665558
iter  40 value 81.338582
iter  50 value 81.007802
iter  60 value 80.812724
iter  70 value 80.537643
iter  80 value 80.469712
iter  90 value 80.376737
iter 100 value 80.097418
final  value 80.097418 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.099232 
iter  10 value 94.485946
iter  20 value 94.484224
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.956186 
iter  10 value 94.114720
iter  20 value 94.103428
iter  30 value 93.849166
iter  40 value 87.481640
iter  50 value 87.247061
iter  60 value 87.246457
iter  70 value 87.245990
iter  80 value 86.343749
iter  90 value 85.400049
iter 100 value 84.697299
final  value 84.697299 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 94.884384 
final  value 94.485845 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.300995 
final  value 94.485857 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.524353 
final  value 94.485891 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.812650 
iter  10 value 94.492904
iter  20 value 94.333652
iter  30 value 94.117986
iter  40 value 92.293515
iter  50 value 86.043063
iter  60 value 85.932626
iter  70 value 85.931174
final  value 85.931102 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.885058 
iter  10 value 94.117659
iter  20 value 94.113567
iter  30 value 94.003498
iter  40 value 93.993936
iter  40 value 93.993936
final  value 93.993936 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.046162 
iter  10 value 94.489605
iter  20 value 94.471031
iter  30 value 92.665494
iter  40 value 92.529587
iter  50 value 86.295405
iter  60 value 84.113659
iter  60 value 84.113659
final  value 82.746871 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.954516 
iter  10 value 94.217668
iter  20 value 94.212820
iter  30 value 94.074609
final  value 94.046277 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.229774 
iter  10 value 94.489041
iter  20 value 94.389551
iter  30 value 88.421839
iter  40 value 87.508953
iter  50 value 84.696166
iter  60 value 84.673017
iter  70 value 84.587361
iter  80 value 82.448859
iter  90 value 81.267387
iter 100 value 81.263853
final  value 81.263853 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.388584 
iter  10 value 94.492632
iter  20 value 94.484379
iter  30 value 94.306455
iter  40 value 87.249524
iter  50 value 86.829808
iter  60 value 84.076513
final  value 84.076262 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.604948 
iter  10 value 94.121479
iter  20 value 94.096457
iter  30 value 93.779382
iter  40 value 93.712307
iter  50 value 93.712043
iter  50 value 93.712043
iter  50 value 93.712043
final  value 93.712043 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.734050 
iter  10 value 93.384958
iter  20 value 92.623118
iter  30 value 92.366798
iter  40 value 92.123966
iter  50 value 92.123338
final  value 92.123319 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.799541 
iter  10 value 94.121829
iter  20 value 94.032580
iter  30 value 87.747051
iter  40 value 85.479459
iter  50 value 83.788714
iter  60 value 81.862850
iter  70 value 80.348646
iter  80 value 80.085416
iter  90 value 80.054562
final  value 80.053925 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.322581 
iter  10 value 94.492423
iter  20 value 94.431462
iter  30 value 94.130229
final  value 94.066132 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.785140 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.683959 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.099586 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.071532 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.290402 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.698826 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.981225 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.641759 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.135198 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.671772 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.453449 
iter  10 value 85.071614
iter  20 value 83.686926
iter  30 value 83.361222
iter  40 value 82.706810
iter  50 value 82.210020
final  value 82.209775 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.494793 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 136.818698 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.523093 
iter  10 value 93.672976
final  value 93.672974 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.283997 
iter  10 value 93.095201
iter  20 value 92.940609
final  value 92.935232 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.021425 
iter  10 value 93.639092
iter  20 value 88.896629
iter  30 value 85.451703
iter  40 value 85.238158
iter  50 value 85.076903
iter  60 value 84.986677
iter  70 value 83.495604
final  value 83.494475 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.254996 
iter  10 value 94.047906
iter  20 value 93.050823
iter  30 value 89.528362
iter  40 value 83.878413
iter  50 value 80.799554
iter  60 value 80.014342
iter  70 value 79.793445
iter  80 value 79.735602
iter  90 value 79.638675
final  value 79.634724 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.596284 
iter  10 value 94.012076
iter  20 value 93.183305
iter  30 value 90.832596
iter  40 value 82.187059
iter  50 value 81.924603
iter  60 value 80.620826
iter  70 value 79.792912
iter  80 value 79.646105
iter  90 value 79.634760
final  value 79.634724 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.977174 
iter  10 value 93.980456
iter  20 value 93.208195
iter  30 value 93.105259
iter  40 value 90.302005
iter  50 value 87.447678
iter  60 value 87.382671
iter  70 value 85.026533
iter  80 value 84.986368
iter  90 value 84.967755
iter 100 value 84.802857
final  value 84.802857 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.664917 
iter  10 value 94.055261
iter  20 value 93.812748
iter  30 value 93.684448
iter  40 value 93.204260
iter  50 value 85.066074
iter  60 value 84.586445
iter  70 value 84.512920
iter  80 value 84.496826
iter  90 value 84.476967
iter 100 value 83.907860
final  value 83.907860 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.074715 
iter  10 value 88.018768
iter  20 value 82.205097
iter  30 value 81.911495
iter  40 value 81.851937
iter  50 value 80.906158
iter  60 value 79.441788
iter  70 value 78.830213
iter  80 value 78.575773
iter  90 value 78.273880
iter 100 value 78.142792
final  value 78.142792 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.830115 
iter  10 value 93.375740
iter  20 value 86.725394
iter  30 value 85.226234
iter  40 value 84.935107
iter  50 value 84.736515
iter  60 value 82.203697
iter  70 value 81.465877
iter  80 value 80.712152
iter  90 value 80.531009
iter 100 value 80.414548
final  value 80.414548 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.741596 
iter  10 value 93.517989
iter  20 value 84.661563
iter  30 value 82.043686
iter  40 value 80.566552
iter  50 value 79.289838
iter  60 value 78.973765
iter  70 value 78.853734
iter  80 value 78.709974
iter  90 value 78.659060
iter 100 value 78.630740
final  value 78.630740 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.419362 
iter  10 value 93.971786
iter  20 value 88.295145
iter  30 value 85.210985
iter  40 value 82.782439
iter  50 value 80.435143
iter  60 value 79.819759
iter  70 value 79.484456
iter  80 value 79.110574
iter  90 value 78.754935
iter 100 value 78.591492
final  value 78.591492 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.320065 
iter  10 value 93.549412
iter  20 value 91.101932
iter  30 value 84.624878
iter  40 value 84.280130
iter  50 value 83.435859
iter  60 value 81.888786
iter  70 value 80.026833
iter  80 value 79.440224
iter  90 value 78.563712
iter 100 value 78.348855
final  value 78.348855 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.339625 
iter  10 value 94.837325
iter  20 value 90.853184
iter  30 value 85.387430
iter  40 value 84.284628
iter  50 value 83.306925
iter  60 value 81.602951
iter  70 value 80.513619
iter  80 value 79.602768
iter  90 value 78.656787
iter 100 value 78.311689
final  value 78.311689 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 132.141077 
iter  10 value 93.180677
iter  20 value 89.325976
iter  30 value 85.566262
iter  40 value 84.317291
iter  50 value 80.783617
iter  60 value 79.899729
iter  70 value 78.944933
iter  80 value 78.814571
iter  90 value 78.676920
iter 100 value 78.506073
final  value 78.506073 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.847356 
iter  10 value 95.266962
iter  20 value 85.426563
iter  30 value 84.262794
iter  40 value 82.824344
iter  50 value 81.980186
iter  60 value 81.580717
iter  70 value 81.311396
iter  80 value 80.894106
iter  90 value 79.768547
iter 100 value 79.493708
final  value 79.493708 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.113357 
iter  10 value 94.463494
iter  20 value 89.265606
iter  30 value 82.910554
iter  40 value 79.653209
iter  50 value 79.242665
iter  60 value 78.925405
iter  70 value 78.454623
iter  80 value 78.351565
iter  90 value 78.100897
iter 100 value 78.044573
final  value 78.044573 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.386929 
iter  10 value 94.057962
iter  20 value 91.071366
iter  30 value 86.382205
iter  40 value 83.806953
iter  50 value 82.502612
iter  60 value 80.836826
iter  70 value 79.592806
iter  80 value 79.399137
iter  90 value 78.823535
iter 100 value 78.681670
final  value 78.681670 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.672998 
final  value 94.054597 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.456538 
final  value 94.054553 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.502196 
iter  10 value 94.054663
iter  20 value 94.052977
iter  30 value 93.587565
final  value 93.582786 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.680273 
iter  10 value 94.054803
iter  20 value 94.052920
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 116.442226 
iter  10 value 93.944473
iter  20 value 92.823750
iter  30 value 88.561640
iter  40 value 85.293759
iter  50 value 84.938753
iter  60 value 82.690843
final  value 82.689097 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.350520 
iter  10 value 93.370687
iter  20 value 93.367566
iter  30 value 88.296462
iter  40 value 82.807055
iter  50 value 82.795322
iter  60 value 82.790079
iter  70 value 81.737935
iter  80 value 81.378349
iter  90 value 81.309999
iter 100 value 81.300860
final  value 81.300860 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.080605 
iter  10 value 94.057515
iter  20 value 93.986832
iter  30 value 91.812513
iter  40 value 85.138818
iter  50 value 84.450063
iter  60 value 84.401788
iter  70 value 84.391969
iter  80 value 84.390077
iter  90 value 84.389902
iter 100 value 84.389590
final  value 84.389590 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.159303 
iter  10 value 94.057657
iter  20 value 94.041335
iter  30 value 93.160945
iter  40 value 93.116098
iter  50 value 93.114449
iter  60 value 93.114317
iter  70 value 93.113920
final  value 93.113801 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.489631 
iter  10 value 93.459745
iter  20 value 93.425356
iter  30 value 93.370614
iter  40 value 92.080484
iter  50 value 91.386361
iter  60 value 91.339606
iter  70 value 91.216427
iter  80 value 91.125264
iter  90 value 91.112658
iter 100 value 91.109228
final  value 91.109228 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.150761 
iter  10 value 94.058129
iter  20 value 93.304183
iter  30 value 89.594752
iter  30 value 89.594752
iter  30 value 89.594752
final  value 89.594752 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.591417 
iter  10 value 92.376446
iter  20 value 92.260448
iter  30 value 91.788388
iter  40 value 91.477721
iter  50 value 91.476887
iter  60 value 91.475639
final  value 91.475636 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.775003 
iter  10 value 93.878463
iter  20 value 93.877634
iter  30 value 93.876444
iter  40 value 93.873053
final  value 93.872938 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.765147 
iter  10 value 94.060883
iter  20 value 93.972328
iter  30 value 90.938040
iter  40 value 90.932959
iter  50 value 90.928123
iter  60 value 90.727138
iter  70 value 89.874139
iter  80 value 89.672902
iter  90 value 89.645960
final  value 89.645614 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.973072 
iter  10 value 93.591415
iter  20 value 93.583387
iter  30 value 86.196560
iter  40 value 84.265826
iter  50 value 79.872214
iter  60 value 79.522036
iter  70 value 79.073768
iter  80 value 78.913269
iter  90 value 78.619119
iter 100 value 78.606507
final  value 78.606507 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.476669 
iter  10 value 94.054670
iter  20 value 92.250628
iter  30 value 85.266980
iter  40 value 83.225057
final  value 83.203426 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.394281 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.621980 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.397550 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.136712 
final  value 93.356643 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.208708 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.210965 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.396984 
iter  10 value 93.915749
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.063685 
final  value 93.893849 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.448790 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.752347 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.302140 
iter  10 value 90.088968
iter  20 value 89.593720
final  value 89.593238 
converged
Fitting Repeat 2 

# weights:  507
initial  value 93.739553 
iter  10 value 89.607230
iter  20 value 89.550611
final  value 89.550509 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.920833 
iter  10 value 93.390766
iter  20 value 93.273675
iter  30 value 93.273394
final  value 93.273392 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.833385 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.433655 
iter  10 value 93.409697
iter  20 value 93.284593
final  value 93.284494 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.633227 
iter  10 value 94.054918
iter  20 value 93.771227
iter  30 value 93.517326
iter  40 value 93.363331
iter  50 value 93.225392
iter  60 value 88.327703
iter  70 value 87.641833
iter  80 value 87.217560
iter  90 value 85.357549
iter 100 value 85.060257
final  value 85.060257 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.604333 
iter  10 value 93.965230
iter  20 value 93.445076
iter  30 value 92.833320
iter  40 value 89.415732
iter  50 value 86.526676
iter  60 value 86.395435
iter  70 value 86.269517
iter  80 value 85.534459
iter  90 value 84.873607
final  value 84.870573 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.343123 
iter  10 value 94.072484
iter  20 value 90.368660
iter  30 value 85.431278
iter  40 value 85.210583
iter  50 value 85.049462
iter  60 value 84.909160
iter  70 value 84.871144
final  value 84.870573 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.439709 
iter  10 value 93.901405
iter  20 value 89.110859
iter  30 value 85.869326
iter  40 value 85.457596
iter  50 value 85.155825
final  value 85.134374 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.302051 
iter  10 value 94.141025
iter  20 value 90.262861
iter  30 value 85.555506
iter  40 value 85.385031
iter  50 value 85.182675
iter  60 value 85.136385
final  value 85.136312 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.481869 
iter  10 value 94.220726
iter  20 value 89.092638
iter  30 value 87.216935
iter  40 value 86.689280
iter  50 value 85.451451
iter  60 value 84.392665
iter  70 value 83.380184
iter  80 value 82.979145
iter  90 value 82.039222
iter 100 value 81.629849
final  value 81.629849 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.277371 
iter  10 value 93.965182
iter  20 value 92.390097
iter  30 value 90.053197
iter  40 value 87.778792
iter  50 value 83.751542
iter  60 value 83.232247
iter  70 value 81.876815
iter  80 value 81.268452
iter  90 value 80.928232
iter 100 value 80.796776
final  value 80.796776 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.850842 
iter  10 value 94.086840
iter  20 value 90.227104
iter  30 value 89.049373
iter  40 value 87.418884
iter  50 value 84.910258
iter  60 value 84.395490
iter  70 value 83.530163
iter  80 value 81.851134
iter  90 value 81.744947
iter 100 value 81.654676
final  value 81.654676 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 138.431875 
iter  10 value 94.148221
iter  20 value 94.005629
iter  30 value 93.529310
iter  40 value 93.312351
iter  50 value 88.271014
iter  60 value 88.090613
iter  70 value 87.723566
iter  80 value 85.566981
iter  90 value 84.857421
iter 100 value 83.795462
final  value 83.795462 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.649159 
iter  10 value 94.832549
iter  20 value 94.061781
iter  30 value 91.617617
iter  40 value 87.182617
iter  50 value 85.241428
iter  60 value 83.241069
iter  70 value 82.162419
iter  80 value 81.766227
iter  90 value 81.597611
iter 100 value 81.374506
final  value 81.374506 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.269343 
iter  10 value 94.262095
iter  20 value 92.946340
iter  30 value 88.303799
iter  40 value 83.944061
iter  50 value 82.613302
iter  60 value 81.812318
iter  70 value 81.269314
iter  80 value 81.071221
iter  90 value 81.031511
iter 100 value 80.806779
final  value 80.806779 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.841331 
iter  10 value 95.330422
iter  20 value 90.621535
iter  30 value 88.658803
iter  40 value 84.238138
iter  50 value 82.674467
iter  60 value 82.009917
iter  70 value 81.666510
iter  80 value 81.510155
iter  90 value 81.293568
iter 100 value 80.912975
final  value 80.912975 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.046631 
iter  10 value 93.130655
iter  20 value 92.522647
iter  30 value 88.008116
iter  40 value 85.621481
iter  50 value 84.562065
iter  60 value 83.486653
iter  70 value 83.097462
iter  80 value 82.941108
iter  90 value 82.547966
iter 100 value 81.983137
final  value 81.983137 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.558789 
iter  10 value 94.339416
iter  20 value 93.789439
iter  30 value 90.566003
iter  40 value 85.531895
iter  50 value 83.876330
iter  60 value 83.668390
iter  70 value 83.220899
iter  80 value 82.732681
iter  90 value 81.783821
iter 100 value 81.600534
final  value 81.600534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.295714 
iter  10 value 95.035568
iter  20 value 94.186121
iter  30 value 93.359979
iter  40 value 91.981785
iter  50 value 86.984454
iter  60 value 85.342919
iter  70 value 85.074492
iter  80 value 84.679093
iter  90 value 83.545620
iter 100 value 82.014451
final  value 82.014451 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.473476 
final  value 94.054633 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.550799 
final  value 94.054394 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.031205 
iter  10 value 94.053893
iter  20 value 93.866364
iter  30 value 93.865649
iter  40 value 93.268935
iter  50 value 93.259075
iter  60 value 93.258833
iter  60 value 93.258832
iter  60 value 93.258832
final  value 93.258832 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.813137 
final  value 94.054550 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.901660 
final  value 94.054488 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.670871 
iter  10 value 94.057908
iter  20 value 92.361863
final  value 92.274164 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.929339 
iter  10 value 93.184946
iter  20 value 93.183658
final  value 93.180669 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.305400 
iter  10 value 94.058086
iter  20 value 94.053000
iter  30 value 93.486796
iter  40 value 88.617394
iter  50 value 88.498619
iter  60 value 88.496552
iter  70 value 85.913944
iter  80 value 85.881857
iter  90 value 85.868704
iter 100 value 84.572146
final  value 84.572146 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.513794 
iter  10 value 93.495496
iter  20 value 93.290835
iter  30 value 93.289512
iter  40 value 91.549049
iter  50 value 87.108010
iter  60 value 85.294964
iter  70 value 84.284614
iter  80 value 84.260468
iter  90 value 84.202914
iter 100 value 83.801795
final  value 83.801795 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.969467 
iter  10 value 94.057741
iter  20 value 94.053441
iter  30 value 94.002863
iter  40 value 84.523856
iter  50 value 84.448272
iter  60 value 83.683796
iter  70 value 82.337523
iter  80 value 81.742758
iter  90 value 81.728387
iter 100 value 81.592332
final  value 81.592332 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.457152 
iter  10 value 94.061032
iter  20 value 94.053118
iter  30 value 93.395059
iter  40 value 88.046324
iter  50 value 85.340111
iter  60 value 84.831319
iter  70 value 83.815553
iter  80 value 81.099816
iter  90 value 80.427117
iter 100 value 80.362595
final  value 80.362595 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.792446 
iter  10 value 94.060919
iter  20 value 94.053260
iter  30 value 93.164691
iter  40 value 86.459504
iter  50 value 84.675213
iter  60 value 83.827691
iter  70 value 83.817650
iter  80 value 83.816667
iter  90 value 83.466765
iter 100 value 81.483458
final  value 81.483458 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.016313 
iter  10 value 94.061049
iter  20 value 93.431178
iter  30 value 86.304012
iter  40 value 86.034662
iter  50 value 86.018387
iter  60 value 85.366120
iter  70 value 83.968239
final  value 83.924733 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.194940 
iter  10 value 93.924426
iter  20 value 93.025390
iter  30 value 86.612310
iter  40 value 85.050806
iter  50 value 83.608154
iter  60 value 82.343046
iter  70 value 82.163064
iter  80 value 81.939237
iter  90 value 81.938270
iter 100 value 81.934478
final  value 81.934478 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.453122 
iter  10 value 93.340117
iter  20 value 93.291809
iter  30 value 93.289844
iter  40 value 93.173205
iter  50 value 84.463103
iter  60 value 82.619672
iter  70 value 81.008177
iter  80 value 80.527837
final  value 80.514744 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.534857 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.947602 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.374618 
iter  10 value 94.427051
final  value 94.424077 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.819812 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.828373 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.879127 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.841623 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.120111 
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.700161 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.206582 
iter  10 value 94.323810
iter  10 value 94.323810
iter  10 value 94.323810
final  value 94.323810 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.324226 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.857264 
final  value 94.046703 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.701384 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.357684 
iter  10 value 89.733148
iter  20 value 89.656169
iter  30 value 89.633118
iter  30 value 89.633117
iter  30 value 89.633117
final  value 89.633117 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.569585 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.025815 
iter  10 value 94.131107
iter  20 value 85.590474
iter  30 value 84.536518
iter  40 value 84.314503
iter  50 value 84.137540
iter  60 value 83.451161
iter  70 value 83.327898
final  value 83.327696 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.529851 
iter  10 value 94.480980
iter  20 value 91.674609
iter  30 value 85.931849
iter  40 value 83.935400
iter  50 value 82.707376
iter  60 value 82.546791
iter  70 value 82.104043
iter  80 value 81.886080
iter  90 value 81.574259
iter 100 value 81.528958
final  value 81.528958 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.681082 
iter  10 value 94.483931
iter  20 value 92.539066
iter  30 value 90.965190
iter  40 value 90.341363
iter  50 value 86.891565
iter  60 value 82.919678
iter  70 value 82.812855
iter  80 value 81.663756
iter  90 value 81.349505
iter 100 value 81.166483
final  value 81.166483 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 113.055810 
iter  10 value 94.402880
iter  20 value 91.780671
iter  30 value 90.241716
iter  40 value 85.486214
iter  50 value 84.693886
iter  60 value 84.270278
iter  70 value 83.826521
iter  80 value 83.806906
final  value 83.805711 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.309286 
iter  10 value 94.424876
iter  20 value 85.490048
iter  30 value 85.105710
iter  40 value 83.909056
iter  50 value 83.362875
iter  60 value 83.337349
iter  70 value 83.327709
final  value 83.327607 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.534526 
iter  10 value 94.690270
iter  20 value 87.806307
iter  30 value 86.525644
iter  40 value 84.703351
iter  50 value 83.496926
iter  60 value 82.847974
iter  70 value 82.601399
iter  80 value 82.419980
iter  90 value 82.305354
iter 100 value 82.175409
final  value 82.175409 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.568766 
iter  10 value 94.532255
iter  20 value 94.490870
iter  30 value 86.748441
iter  40 value 85.489383
iter  50 value 84.729421
iter  60 value 82.780673
iter  70 value 82.371048
iter  80 value 82.011457
iter  90 value 81.817365
iter 100 value 81.689489
final  value 81.689489 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.561506 
iter  10 value 94.603054
iter  20 value 88.861997
iter  30 value 84.651212
iter  40 value 82.544945
iter  50 value 81.805679
iter  60 value 81.367735
iter  70 value 81.190345
iter  80 value 80.667144
iter  90 value 79.971939
iter 100 value 79.590911
final  value 79.590911 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.581320 
iter  10 value 94.614611
iter  20 value 94.467556
iter  30 value 89.338983
iter  40 value 88.809612
iter  50 value 87.995495
iter  60 value 86.549137
iter  70 value 84.671690
iter  80 value 84.330055
iter  90 value 81.667443
iter 100 value 80.797860
final  value 80.797860 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.939163 
iter  10 value 94.696745
iter  20 value 85.436728
iter  30 value 84.641536
iter  40 value 84.066614
iter  50 value 83.925911
iter  60 value 82.726440
iter  70 value 80.873109
iter  80 value 79.916839
iter  90 value 79.353627
iter 100 value 79.231295
final  value 79.231295 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.717078 
iter  10 value 94.571209
iter  20 value 91.930794
iter  30 value 90.731536
iter  40 value 84.406231
iter  50 value 84.031151
iter  60 value 83.575154
iter  70 value 83.341510
iter  80 value 83.143346
iter  90 value 82.279361
iter 100 value 82.079358
final  value 82.079358 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.519707 
iter  10 value 89.749306
iter  20 value 83.436525
iter  30 value 81.540071
iter  40 value 81.063858
iter  50 value 80.887988
iter  60 value 80.063532
iter  70 value 79.920884
iter  80 value 79.768190
iter  90 value 79.683611
iter 100 value 79.501653
final  value 79.501653 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.574831 
iter  10 value 94.433264
iter  20 value 86.232901
iter  30 value 83.307266
iter  40 value 82.473691
iter  50 value 82.287693
iter  60 value 81.123962
iter  70 value 80.395241
iter  80 value 79.911281
iter  90 value 79.598156
iter 100 value 79.337704
final  value 79.337704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.817632 
iter  10 value 94.849298
iter  20 value 94.318521
iter  30 value 89.947082
iter  40 value 87.333366
iter  50 value 84.280433
iter  60 value 82.817850
iter  70 value 81.640330
iter  80 value 80.413570
iter  90 value 80.166267
iter 100 value 80.051554
final  value 80.051554 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.436854 
iter  10 value 94.458711
iter  20 value 85.562798
iter  30 value 83.299704
iter  40 value 83.173265
iter  50 value 82.083342
iter  60 value 81.809783
iter  70 value 81.636075
iter  80 value 81.403061
iter  90 value 80.618491
iter 100 value 80.154158
final  value 80.154158 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.972495 
iter  10 value 94.486095
final  value 94.484218 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.714039 
final  value 94.485763 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.728913 
final  value 94.485997 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.434283 
final  value 94.485599 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.840618 
final  value 94.485891 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.589608 
iter  10 value 85.709618
iter  20 value 84.902603
iter  30 value 83.690999
iter  40 value 83.358042
iter  50 value 83.112755
iter  60 value 83.106991
iter  70 value 83.106251
final  value 83.105601 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.566910 
iter  10 value 94.432667
iter  20 value 94.428491
iter  30 value 94.268434
iter  40 value 94.025200
iter  50 value 94.020706
final  value 94.019666 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.773110 
iter  10 value 94.471820
iter  20 value 94.420177
iter  30 value 83.690675
iter  40 value 83.686504
final  value 83.686495 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.621587 
iter  10 value 94.471731
iter  20 value 93.397633
iter  30 value 90.354273
iter  40 value 90.329297
iter  50 value 90.144661
iter  60 value 85.676577
iter  70 value 84.816095
iter  80 value 84.778292
iter  90 value 84.775082
iter 100 value 84.769522
final  value 84.769522 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.836252 
iter  10 value 94.490793
iter  20 value 94.486073
iter  30 value 94.218196
iter  40 value 94.025661
iter  50 value 89.342424
iter  60 value 87.421661
iter  70 value 87.308389
iter  80 value 87.307610
final  value 87.307582 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.035726 
iter  10 value 94.492183
iter  20 value 94.447468
iter  30 value 83.296251
iter  40 value 83.107117
final  value 83.107088 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.985302 
iter  10 value 95.009969
iter  20 value 94.108874
iter  30 value 94.105260
iter  40 value 94.017033
iter  50 value 93.925633
iter  60 value 93.213355
iter  70 value 92.670867
iter  80 value 92.662186
final  value 92.661557 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.677231 
iter  10 value 94.475406
iter  20 value 93.759441
iter  30 value 86.200544
iter  40 value 85.844336
iter  50 value 85.705395
final  value 85.693644 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.045034 
iter  10 value 94.475468
iter  20 value 94.452926
iter  30 value 94.432070
iter  40 value 94.257691
iter  50 value 94.256480
iter  60 value 94.241089
iter  70 value 94.239627
iter  80 value 87.233875
iter  90 value 86.630078
iter 100 value 81.170142
final  value 81.170142 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.694248 
iter  10 value 94.481881
iter  20 value 94.474296
iter  30 value 94.431290
iter  30 value 94.431290
iter  40 value 83.798255
final  value 83.687621 
converged
Fitting Repeat 1 

# weights:  305
initial  value 134.582375 
iter  10 value 117.826124
iter  20 value 109.184603
iter  30 value 105.459857
iter  40 value 105.149999
iter  50 value 104.669635
iter  60 value 103.416120
iter  70 value 102.720303
iter  80 value 102.430564
iter  90 value 102.314594
iter 100 value 101.989649
final  value 101.989649 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 151.360436 
iter  10 value 117.764421
iter  20 value 107.314260
iter  30 value 105.484880
iter  40 value 105.160561
iter  50 value 104.062216
iter  60 value 103.190219
iter  70 value 103.021909
iter  80 value 102.727041
iter  90 value 101.844567
iter 100 value 101.050155
final  value 101.050155 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 137.773787 
iter  10 value 117.812305
iter  20 value 113.000559
iter  30 value 106.284928
iter  40 value 105.773070
iter  50 value 103.901248
iter  60 value 102.592869
iter  70 value 102.207108
iter  80 value 101.942905
iter  90 value 101.758178
iter 100 value 101.511886
final  value 101.511886 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 141.385759 
iter  10 value 117.655007
iter  20 value 117.581960
iter  30 value 115.535715
iter  40 value 112.244490
iter  50 value 110.684130
iter  60 value 106.992988
iter  70 value 103.921612
iter  80 value 103.278216
iter  90 value 102.634503
iter 100 value 102.267267
final  value 102.267267 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 143.718345 
iter  10 value 117.934471
iter  20 value 117.784704
iter  30 value 116.370957
iter  40 value 108.084450
iter  50 value 107.558925
iter  60 value 106.418442
iter  70 value 105.686435
iter  80 value 105.075612
iter  90 value 102.498660
iter 100 value 101.333548
final  value 101.333548 
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 Jun 10 22:29:09 2024 
*********************************************** 
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 
 49.445   1.198  50.666