##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.0 RC (2024-04-16 r86468 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.11.0'
* 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 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       31.56   1.30   32.86
FSmethod      29.85   1.80   31.76
corr_plot     29.39   1.44   30.83
pred_ensembel 14.76   0.78   11.25
enrichfindP    0.50   0.45   14.62
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'runTests.R'
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.

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


* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library'
* installing *source* package 'HPiP' ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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

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

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

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

# weights:  103
initial  value 103.451587 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.824002 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.563348 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.765732 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.756100 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.001496 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.884081 
iter  10 value 94.143812
iter  20 value 94.139388
final  value 94.139368 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.340135 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 125.244610 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.100652 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.314181 
iter  10 value 94.467447
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.828073 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.126908 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.814767 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.727057 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.911164 
iter  10 value 94.498203
iter  20 value 94.176663
iter  30 value 94.134171
iter  40 value 89.959858
iter  50 value 88.552581
iter  60 value 86.091065
iter  70 value 85.630487
iter  80 value 85.508223
iter  90 value 85.257140
iter 100 value 84.771020
final  value 84.771020 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.845412 
iter  10 value 94.485771
iter  20 value 89.582994
iter  30 value 86.768394
iter  40 value 84.805360
iter  50 value 84.743150
iter  60 value 84.611406
iter  70 value 84.135436
iter  80 value 83.602868
iter  90 value 83.458001
final  value 83.457836 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.995741 
iter  10 value 94.005866
iter  20 value 88.342020
iter  30 value 87.138890
iter  40 value 86.419704
iter  50 value 85.910587
iter  60 value 85.867739
iter  70 value 85.497879
final  value 85.495439 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.055138 
iter  10 value 94.487248
iter  20 value 89.559663
iter  30 value 86.864399
iter  40 value 86.236986
iter  50 value 85.804188
iter  60 value 85.775488
iter  70 value 85.662826
iter  80 value 85.516561
final  value 85.495440 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.524922 
iter  10 value 94.570722
iter  20 value 93.810169
iter  30 value 88.200470
iter  40 value 87.473516
iter  50 value 87.435878
iter  60 value 87.335752
iter  70 value 86.630168
final  value 86.626961 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.964587 
iter  10 value 94.308639
iter  20 value 91.617645
iter  30 value 89.605363
iter  40 value 88.148057
iter  50 value 85.968055
iter  60 value 84.879007
iter  70 value 84.735466
iter  80 value 84.689710
iter  90 value 84.682275
iter 100 value 84.418038
final  value 84.418038 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.651787 
iter  10 value 94.318792
iter  20 value 89.408496
iter  30 value 87.414821
iter  40 value 86.430273
iter  50 value 83.764601
iter  60 value 83.382542
iter  70 value 82.857145
iter  80 value 82.531207
iter  90 value 82.314764
iter 100 value 82.209582
final  value 82.209582 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.483772 
iter  10 value 94.813012
iter  20 value 94.403481
iter  30 value 92.231735
iter  40 value 90.897544
iter  50 value 87.989601
iter  60 value 87.514634
iter  70 value 87.331845
iter  80 value 85.562181
iter  90 value 85.012014
iter 100 value 83.956961
final  value 83.956961 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.129935 
iter  10 value 94.531157
iter  20 value 89.727679
iter  30 value 88.341641
iter  40 value 87.555853
iter  50 value 85.123878
iter  60 value 84.486520
iter  70 value 84.154062
iter  80 value 83.393470
iter  90 value 83.118969
iter 100 value 82.331209
final  value 82.331209 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.647826 
iter  10 value 94.517094
iter  20 value 94.456693
iter  30 value 91.229770
iter  40 value 88.122585
iter  50 value 87.117791
iter  60 value 86.554243
iter  70 value 86.334109
iter  80 value 85.649635
iter  90 value 84.868730
iter 100 value 84.166523
final  value 84.166523 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.572962 
iter  10 value 91.439208
iter  20 value 87.709139
iter  30 value 85.651760
iter  40 value 85.214908
iter  50 value 84.775633
iter  60 value 83.702988
iter  70 value 83.157816
iter  80 value 82.541326
iter  90 value 82.328524
iter 100 value 82.030062
final  value 82.030062 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.945437 
iter  10 value 94.440346
iter  20 value 88.702187
iter  30 value 87.141927
iter  40 value 85.138715
iter  50 value 84.403706
iter  60 value 84.181167
iter  70 value 83.653428
iter  80 value 83.068682
iter  90 value 82.323643
iter 100 value 82.245034
final  value 82.245034 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.027511 
iter  10 value 94.516554
iter  20 value 89.795833
iter  30 value 85.085887
iter  40 value 84.750138
iter  50 value 84.077758
iter  60 value 83.360559
iter  70 value 83.111656
iter  80 value 82.898204
iter  90 value 82.723140
iter 100 value 82.615025
final  value 82.615025 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.044408 
iter  10 value 95.940368
iter  20 value 94.845974
iter  30 value 94.268959
iter  40 value 93.131329
iter  50 value 87.698249
iter  60 value 85.870877
iter  70 value 85.364294
iter  80 value 85.166231
iter  90 value 85.039982
iter 100 value 84.581636
final  value 84.581636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.930089 
iter  10 value 93.889693
iter  20 value 89.414552
iter  30 value 86.794488
iter  40 value 85.857290
iter  50 value 84.762868
iter  60 value 84.050824
iter  70 value 83.573172
iter  80 value 82.490336
iter  90 value 82.406583
iter 100 value 82.026784
final  value 82.026784 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.677121 
final  value 94.485839 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.035584 
iter  10 value 94.485887
iter  20 value 94.482265
iter  30 value 94.454560
iter  40 value 87.645412
iter  50 value 87.291899
iter  60 value 87.286908
final  value 87.286880 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.555693 
final  value 94.486143 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.785489 
iter  10 value 94.485880
final  value 94.484432 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.175622 
final  value 94.485664 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.327776 
iter  10 value 94.488938
iter  20 value 94.484227
iter  30 value 88.731919
iter  40 value 88.178483
iter  50 value 86.349294
iter  60 value 86.121089
iter  70 value 86.064954
iter  80 value 86.058813
final  value 86.058739 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.977078 
iter  10 value 94.489538
iter  20 value 94.393480
iter  30 value 85.757546
iter  40 value 85.217793
iter  50 value 85.200712
final  value 85.200327 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.791136 
iter  10 value 94.472139
iter  20 value 94.467860
iter  30 value 87.505136
iter  40 value 85.933267
iter  50 value 83.558276
iter  60 value 83.311687
iter  70 value 82.950678
iter  80 value 82.806901
iter  90 value 82.461146
iter 100 value 81.886547
final  value 81.886547 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.767096 
iter  10 value 94.192527
iter  20 value 94.107519
iter  30 value 94.097439
iter  40 value 94.096265
iter  50 value 89.873236
iter  60 value 89.756775
iter  70 value 89.756326
iter  80 value 89.753834
iter  90 value 89.742399
final  value 89.742333 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.134427 
iter  10 value 94.489428
iter  20 value 94.480380
iter  30 value 88.478164
iter  40 value 86.880284
final  value 86.879402 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.098856 
iter  10 value 94.270376
iter  20 value 94.262869
iter  30 value 94.224863
iter  40 value 91.446460
iter  50 value 86.347319
iter  60 value 85.368243
iter  70 value 83.994438
iter  80 value 83.935794
iter  90 value 83.935237
final  value 83.935202 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.274620 
iter  10 value 94.492246
iter  20 value 93.625683
iter  30 value 87.383300
iter  40 value 87.215148
iter  50 value 87.034038
iter  60 value 86.971368
final  value 86.970489 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.404726 
iter  10 value 94.492689
iter  20 value 91.699401
iter  30 value 89.216878
iter  40 value 88.806717
iter  50 value 88.051621
iter  60 value 84.727793
iter  70 value 83.239367
iter  80 value 82.911190
iter  90 value 82.820530
iter 100 value 82.738696
final  value 82.738696 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.070602 
iter  10 value 94.475491
iter  20 value 94.467517
iter  30 value 94.463608
iter  40 value 87.651742
iter  50 value 85.541705
iter  60 value 84.637739
iter  70 value 84.637046
iter  80 value 84.414320
iter  90 value 83.426015
iter 100 value 82.044534
final  value 82.044534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.696620 
iter  10 value 94.366958
iter  20 value 94.283124
iter  30 value 93.781344
iter  40 value 90.512689
iter  50 value 88.699104
iter  60 value 88.637009
iter  70 value 88.636346
iter  80 value 88.576849
iter  90 value 85.600212
iter 100 value 85.557271
final  value 85.557271 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.250538 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.046491 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.387134 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.671486 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.574637 
iter  10 value 87.839048
iter  20 value 87.794740
iter  30 value 87.781739
final  value 87.781417 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.731891 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.982134 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.010531 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.991171 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.234267 
iter  10 value 93.540711
final  value 93.540410 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.551140 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.376596 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.440281 
iter  10 value 90.920786
final  value 90.913016 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.320064 
iter  10 value 89.610970
iter  20 value 87.424164
iter  30 value 87.057384
iter  40 value 87.047998
final  value 87.047931 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.688707 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.105987 
iter  10 value 94.486034
iter  20 value 93.936335
iter  30 value 93.901601
iter  40 value 93.892832
iter  50 value 93.878200
iter  60 value 92.426644
iter  70 value 87.253678
iter  80 value 84.701899
iter  90 value 83.676351
iter 100 value 83.119079
final  value 83.119079 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.187265 
iter  10 value 94.369402
iter  20 value 94.334940
iter  30 value 94.328914
iter  40 value 93.528892
iter  50 value 89.034540
iter  60 value 86.405211
iter  70 value 85.626012
iter  80 value 85.564232
iter  90 value 84.952589
iter 100 value 84.666995
final  value 84.666995 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.914714 
iter  10 value 94.489383
iter  20 value 94.430862
iter  30 value 93.772598
iter  40 value 91.640303
iter  50 value 87.719887
iter  60 value 86.592290
iter  70 value 86.536481
iter  80 value 86.256699
iter  90 value 85.745878
iter 100 value 85.255013
final  value 85.255013 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.533623 
iter  10 value 94.488866
iter  20 value 94.356065
iter  30 value 94.220969
iter  40 value 88.056199
iter  50 value 87.784654
iter  60 value 87.590791
iter  70 value 86.894340
iter  80 value 85.118385
iter  90 value 84.699386
iter 100 value 84.648409
final  value 84.648409 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.683473 
iter  10 value 94.398808
iter  20 value 91.822724
iter  30 value 86.949582
iter  40 value 85.495608
iter  50 value 85.229852
iter  60 value 84.880964
iter  70 value 83.401329
iter  80 value 82.839653
iter  90 value 82.762541
final  value 82.762004 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.151754 
iter  10 value 94.247631
iter  20 value 93.599921
iter  30 value 89.442327
iter  40 value 86.624350
iter  50 value 85.861118
iter  60 value 85.621893
iter  70 value 84.006100
iter  80 value 83.288114
iter  90 value 82.997983
iter 100 value 82.661678
final  value 82.661678 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.141494 
iter  10 value 93.687495
iter  20 value 85.546640
iter  30 value 84.497369
iter  40 value 84.254843
iter  50 value 83.419732
iter  60 value 83.040037
iter  70 value 82.709705
iter  80 value 82.469488
iter  90 value 82.043958
iter 100 value 81.858494
final  value 81.858494 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.365486 
iter  10 value 93.742725
iter  20 value 89.710114
iter  30 value 87.191453
iter  40 value 87.067626
iter  50 value 85.735547
iter  60 value 83.094945
iter  70 value 82.361372
iter  80 value 81.877367
iter  90 value 81.723855
iter 100 value 81.646442
final  value 81.646442 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.271320 
iter  10 value 94.550446
iter  20 value 93.165841
iter  30 value 88.487273
iter  40 value 85.912852
iter  50 value 85.093686
iter  60 value 83.108761
iter  70 value 82.490783
iter  80 value 81.758171
iter  90 value 81.627882
iter 100 value 81.603100
final  value 81.603100 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.026016 
iter  10 value 94.615318
iter  20 value 86.377634
iter  30 value 83.099747
iter  40 value 82.171948
iter  50 value 81.881637
iter  60 value 81.796633
iter  70 value 81.723897
iter  80 value 81.641189
iter  90 value 81.376980
iter 100 value 81.216393
final  value 81.216393 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.897971 
iter  10 value 94.465833
iter  20 value 86.217627
iter  30 value 85.599897
iter  40 value 83.707999
iter  50 value 83.402312
iter  60 value 82.846351
iter  70 value 82.119266
iter  80 value 81.710266
iter  90 value 81.314489
iter 100 value 81.123232
final  value 81.123232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.391608 
iter  10 value 98.333411
iter  20 value 89.653016
iter  30 value 86.171371
iter  40 value 85.862204
iter  50 value 84.962490
iter  60 value 84.366414
iter  70 value 83.540097
iter  80 value 83.177451
iter  90 value 82.127232
iter 100 value 81.528601
final  value 81.528601 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.493954 
iter  10 value 95.004534
iter  20 value 86.181178
iter  30 value 83.999617
iter  40 value 82.630106
iter  50 value 82.471269
iter  60 value 82.161647
iter  70 value 81.748730
iter  80 value 81.174688
iter  90 value 81.071962
iter 100 value 81.031214
final  value 81.031214 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.256744 
iter  10 value 94.220550
iter  20 value 88.113000
iter  30 value 85.440496
iter  40 value 84.735822
iter  50 value 84.576592
iter  60 value 84.417293
iter  70 value 84.369468
iter  80 value 84.341888
iter  90 value 84.233989
iter 100 value 83.889988
final  value 83.889988 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.417850 
iter  10 value 94.522109
iter  20 value 90.047621
iter  30 value 89.385042
iter  40 value 86.476440
iter  50 value 85.186821
iter  60 value 84.469842
iter  70 value 83.624171
iter  80 value 83.542480
iter  90 value 82.148294
iter 100 value 81.650306
final  value 81.650306 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.759373 
final  value 94.485963 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.500768 
final  value 94.486105 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.906556 
iter  10 value 94.485823
iter  20 value 94.475579
iter  30 value 90.976435
final  value 90.974165 
converged
Fitting Repeat 4 

# weights:  103
initial  value 116.703132 
final  value 94.485612 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.153029 
final  value 94.485943 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.054320 
iter  10 value 94.489261
iter  20 value 94.484218
iter  30 value 93.638098
final  value 93.637674 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.310129 
iter  10 value 94.484763
iter  20 value 93.913431
iter  30 value 86.555176
iter  40 value 86.463630
iter  50 value 84.711983
iter  60 value 84.153806
final  value 84.153538 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.869957 
iter  10 value 94.414344
iter  20 value 94.306359
iter  30 value 94.275865
iter  40 value 94.268766
iter  50 value 93.744140
iter  60 value 93.683330
iter  70 value 93.683251
final  value 93.683216 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.950360 
iter  10 value 94.280587
iter  20 value 94.053081
iter  30 value 94.029878
iter  30 value 94.029878
iter  30 value 94.029878
final  value 94.029878 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.998997 
iter  10 value 94.489472
iter  20 value 94.473700
iter  30 value 93.639558
final  value 93.639541 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.109936 
iter  10 value 93.845878
iter  20 value 93.838643
iter  30 value 93.835514
iter  40 value 93.834630
iter  50 value 93.833208
iter  60 value 93.832487
iter  70 value 91.935101
iter  80 value 90.025835
iter  90 value 85.479530
iter 100 value 84.183618
final  value 84.183618 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.031770 
iter  10 value 94.493386
iter  20 value 94.455363
iter  30 value 91.092154
iter  40 value 91.091149
iter  50 value 86.945982
iter  60 value 86.945673
iter  70 value 86.475730
iter  80 value 86.324615
iter  90 value 84.420870
iter 100 value 83.132055
final  value 83.132055 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.196105 
iter  10 value 94.282848
iter  20 value 94.276411
iter  30 value 86.783889
iter  40 value 86.636507
iter  50 value 86.541835
iter  60 value 85.298671
iter  70 value 84.451388
iter  80 value 83.938579
iter  90 value 83.899980
iter 100 value 83.846754
final  value 83.846754 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.980615 
iter  10 value 94.284116
iter  20 value 94.277475
iter  30 value 90.685062
iter  40 value 88.364076
iter  50 value 88.342590
final  value 88.342585 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.822939 
iter  10 value 94.282868
iter  20 value 93.895238
iter  30 value 86.126589
iter  40 value 83.656849
iter  50 value 83.645125
iter  60 value 83.640514
iter  70 value 83.638943
iter  80 value 83.504654
iter  90 value 81.623660
iter 100 value 80.762031
final  value 80.762031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.883187 
iter  10 value 93.996832
final  value 93.991528 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.002238 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.494260 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.069921 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.990640 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.496250 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.770850 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.849465 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.183109 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.416069 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.188849 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.979724 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.417916 
iter  10 value 93.567297
iter  20 value 93.451378
final  value 93.451356 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.134769 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.734454 
iter  10 value 92.211098
iter  20 value 92.184108
final  value 92.182540 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.037124 
iter  10 value 94.052570
iter  20 value 93.935924
iter  30 value 93.848602
iter  40 value 93.839602
iter  50 value 91.000133
iter  60 value 82.428069
iter  70 value 81.986700
iter  80 value 81.783157
iter  90 value 80.906303
iter 100 value 79.998036
final  value 79.998036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.818392 
iter  10 value 88.382704
iter  20 value 83.741541
iter  30 value 83.123359
iter  40 value 81.915718
iter  50 value 81.673871
iter  60 value 81.459733
iter  70 value 81.384820
iter  80 value 81.379857
iter  90 value 81.376913
final  value 81.376897 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.857606 
iter  10 value 94.057131
iter  20 value 93.956565
iter  30 value 93.822840
iter  40 value 93.792845
iter  50 value 90.973865
iter  60 value 87.278651
iter  70 value 85.747425
iter  80 value 83.601148
iter  90 value 83.324194
iter 100 value 83.110941
final  value 83.110941 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.354118 
iter  10 value 93.904702
iter  20 value 83.758064
iter  30 value 82.638416
iter  40 value 82.418017
iter  50 value 82.060845
iter  60 value 81.920265
final  value 81.920163 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.718448 
iter  10 value 94.054858
iter  20 value 93.176914
iter  30 value 88.668299
iter  40 value 83.778243
iter  50 value 82.250533
iter  60 value 82.228948
iter  70 value 82.142952
iter  80 value 82.087353
iter  90 value 81.927126
final  value 81.920163 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.358391 
iter  10 value 93.755454
iter  20 value 88.602166
iter  30 value 84.463261
iter  40 value 83.212301
iter  50 value 82.604861
iter  60 value 81.890756
iter  70 value 81.093237
iter  80 value 79.885692
iter  90 value 78.407890
iter 100 value 77.699117
final  value 77.699117 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.073096 
iter  10 value 94.081941
iter  20 value 93.936377
iter  30 value 92.313448
iter  40 value 88.361509
iter  50 value 85.004650
iter  60 value 83.429324
iter  70 value 80.568756
iter  80 value 79.088196
iter  90 value 78.957352
iter 100 value 78.301555
final  value 78.301555 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.464717 
iter  10 value 94.284775
iter  20 value 92.242085
iter  30 value 91.633218
iter  40 value 90.388988
iter  50 value 83.847590
iter  60 value 82.287186
iter  70 value 82.104147
iter  80 value 81.669711
iter  90 value 81.266488
iter 100 value 80.963495
final  value 80.963495 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.728074 
iter  10 value 87.212595
iter  20 value 84.510943
iter  30 value 82.338050
iter  40 value 82.096675
iter  50 value 81.606795
iter  60 value 81.059634
iter  70 value 80.515093
iter  80 value 80.484032
iter  90 value 80.445145
iter 100 value 80.389150
final  value 80.389150 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.188776 
iter  10 value 94.022146
iter  20 value 92.251494
iter  30 value 91.675639
iter  40 value 91.478274
iter  50 value 91.446752
iter  60 value 82.906969
iter  70 value 81.701181
iter  80 value 81.289754
iter  90 value 80.891826
iter 100 value 80.317360
final  value 80.317360 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.327199 
iter  10 value 92.058687
iter  20 value 86.074656
iter  30 value 84.401846
iter  40 value 81.800889
iter  50 value 80.088101
iter  60 value 79.654675
iter  70 value 79.467174
iter  80 value 79.058949
iter  90 value 78.606581
iter 100 value 78.208640
final  value 78.208640 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.238240 
iter  10 value 94.094285
iter  20 value 91.066894
iter  30 value 86.935110
iter  40 value 83.785896
iter  50 value 80.022833
iter  60 value 79.048558
iter  70 value 77.943254
iter  80 value 77.815598
iter  90 value 77.652893
iter 100 value 77.541801
final  value 77.541801 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.433439 
iter  10 value 93.642044
iter  20 value 86.644714
iter  30 value 83.735811
iter  40 value 81.780714
iter  50 value 81.441189
iter  60 value 81.238935
iter  70 value 80.821388
iter  80 value 79.915132
iter  90 value 78.959442
iter 100 value 78.012899
final  value 78.012899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.986894 
iter  10 value 90.609165
iter  20 value 81.796755
iter  30 value 80.450171
iter  40 value 79.034722
iter  50 value 78.281014
iter  60 value 78.152306
iter  70 value 78.014607
iter  80 value 77.880091
iter  90 value 77.855638
iter 100 value 77.847684
final  value 77.847684 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.341074 
iter  10 value 94.067991
iter  20 value 88.431463
iter  30 value 85.549626
iter  40 value 83.024829
iter  50 value 80.551656
iter  60 value 79.909465
iter  70 value 79.497764
iter  80 value 79.169144
iter  90 value 78.114796
iter 100 value 77.985766
final  value 77.985766 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.423608 
iter  10 value 94.054463
iter  20 value 94.028769
iter  30 value 93.805740
iter  40 value 93.798625
final  value 93.792198 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.920837 
final  value 94.054350 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.733752 
final  value 93.992859 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.343506 
final  value 94.054523 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.685378 
final  value 94.054668 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.756364 
iter  10 value 94.056630
iter  20 value 93.942233
iter  30 value 93.793444
iter  40 value 93.754784
iter  50 value 87.060596
iter  60 value 87.059726
iter  70 value 87.045455
iter  80 value 87.043810
iter  90 value 87.032029
iter 100 value 84.768692
final  value 84.768692 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.672013 
iter  10 value 94.060253
iter  20 value 93.959753
iter  30 value 87.115250
iter  40 value 87.049501
iter  50 value 86.654982
iter  60 value 86.644231
final  value 86.644060 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.188891 
iter  10 value 94.057437
iter  20 value 93.971097
iter  30 value 93.805518
final  value 93.805451 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.110923 
iter  10 value 93.994033
iter  20 value 93.972827
iter  30 value 93.967937
iter  40 value 85.751155
iter  50 value 83.419281
iter  60 value 81.722407
iter  70 value 81.559381
iter  80 value 81.557943
iter  90 value 81.557500
final  value 81.557452 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.443414 
iter  10 value 94.037954
iter  20 value 93.886168
iter  30 value 93.870369
iter  40 value 93.870192
iter  50 value 85.886138
iter  60 value 85.618120
iter  70 value 85.613447
iter  80 value 85.609659
iter  90 value 84.524469
iter 100 value 84.491887
final  value 84.491887 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.947525 
iter  10 value 94.041726
iter  20 value 94.035183
iter  30 value 93.865849
iter  40 value 91.015119
iter  50 value 81.769277
iter  60 value 81.678688
iter  70 value 81.665206
iter  80 value 81.344304
iter  90 value 81.274103
iter 100 value 81.268663
final  value 81.268663 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.366852 
iter  10 value 94.041799
iter  20 value 94.018482
iter  30 value 85.733317
final  value 85.731091 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.545325 
iter  10 value 94.060490
iter  20 value 94.053261
iter  30 value 87.204633
iter  40 value 84.431403
iter  50 value 84.061986
final  value 84.060812 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.858560 
iter  10 value 94.041001
iter  20 value 94.030775
iter  30 value 85.777353
iter  40 value 82.924847
iter  50 value 81.589071
iter  60 value 80.820575
iter  70 value 80.669397
iter  80 value 80.658615
final  value 80.657782 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.214592 
iter  10 value 94.061399
iter  20 value 93.887858
iter  30 value 85.732330
final  value 85.732329 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.017110 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.535386 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.660500 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.503894 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.549544 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.274564 
iter  10 value 93.615412
iter  20 value 93.554565
final  value 93.554286 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.396020 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.608425 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.349769 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.387907 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.128902 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.777088 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.204408 
iter  10 value 90.167155
iter  20 value 89.905020
iter  30 value 89.900603
final  value 89.896825 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.626524 
iter  10 value 87.594655
iter  20 value 86.663486
final  value 86.663453 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.197376 
final  value 93.471096 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.486262 
iter  10 value 94.055325
iter  20 value 93.696301
iter  30 value 93.683808
iter  40 value 93.582849
iter  50 value 88.077311
iter  60 value 86.760705
iter  70 value 84.071115
iter  80 value 82.972259
iter  90 value 82.454426
iter 100 value 82.373394
final  value 82.373394 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.995594 
iter  10 value 87.462726
iter  20 value 85.093619
iter  30 value 84.845077
iter  40 value 82.483856
iter  50 value 82.062153
iter  60 value 81.967882
iter  70 value 81.919346
iter  80 value 81.906747
iter  90 value 81.817000
iter 100 value 81.793114
final  value 81.793114 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.669965 
iter  10 value 94.056520
iter  20 value 93.769651
iter  30 value 93.696825
iter  40 value 93.689089
iter  50 value 93.688489
iter  60 value 92.581296
iter  70 value 84.741295
iter  80 value 83.512721
iter  90 value 80.969149
iter 100 value 79.674744
final  value 79.674744 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.511254 
iter  10 value 94.046937
iter  20 value 93.773004
iter  30 value 92.848197
iter  40 value 85.712858
iter  50 value 81.568062
iter  60 value 79.399384
iter  70 value 79.143366
iter  80 value 78.854029
iter  90 value 78.670273
iter 100 value 78.651566
final  value 78.651566 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 111.626611 
iter  10 value 94.053758
iter  20 value 93.694227
iter  30 value 93.633526
iter  40 value 87.052907
iter  50 value 85.635088
iter  60 value 85.497935
iter  70 value 85.459248
iter  80 value 85.259739
iter  90 value 82.627036
iter 100 value 82.430698
final  value 82.430698 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.359815 
iter  10 value 94.129976
iter  20 value 93.755915
iter  30 value 85.956045
iter  40 value 84.229769
iter  50 value 83.909378
iter  60 value 82.160638
iter  70 value 82.101693
iter  80 value 82.060461
iter  90 value 82.005592
iter 100 value 81.777623
final  value 81.777623 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.298852 
iter  10 value 94.105942
iter  20 value 93.732833
iter  30 value 93.537296
iter  40 value 90.652385
iter  50 value 89.677359
iter  60 value 82.182280
iter  70 value 80.529873
iter  80 value 80.464474
iter  90 value 80.096983
iter 100 value 79.494662
final  value 79.494662 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.623814 
iter  10 value 93.620959
iter  20 value 93.351028
iter  30 value 89.445613
iter  40 value 84.924510
iter  50 value 78.311819
iter  60 value 77.434145
iter  70 value 76.866290
iter  80 value 76.540305
iter  90 value 76.421805
iter 100 value 76.269665
final  value 76.269665 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.193346 
iter  10 value 94.076644
iter  20 value 83.123310
iter  30 value 80.818614
iter  40 value 79.958119
iter  50 value 79.585371
iter  60 value 79.526420
iter  70 value 79.381188
iter  80 value 77.389328
iter  90 value 76.772587
iter 100 value 76.712216
final  value 76.712216 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.850369 
iter  10 value 93.624509
iter  20 value 85.834438
iter  30 value 82.517485
iter  40 value 81.815839
iter  50 value 79.026650
iter  60 value 78.493738
iter  70 value 78.077883
iter  80 value 78.056649
iter  90 value 78.000500
iter 100 value 77.938434
final  value 77.938434 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.761843 
iter  10 value 94.556435
iter  20 value 91.160363
iter  30 value 86.063643
iter  40 value 81.705607
iter  50 value 80.573419
iter  60 value 77.842445
iter  70 value 77.104138
iter  80 value 76.881464
iter  90 value 76.671665
iter 100 value 76.621743
final  value 76.621743 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.368521 
iter  10 value 91.152071
iter  20 value 84.538318
iter  30 value 83.347167
iter  40 value 81.815922
iter  50 value 79.238714
iter  60 value 78.320598
iter  70 value 77.973871
iter  80 value 77.894438
iter  90 value 77.575033
iter 100 value 77.290553
final  value 77.290553 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.323108 
iter  10 value 94.055661
iter  20 value 84.488789
iter  30 value 82.940487
iter  40 value 81.834089
iter  50 value 81.182522
iter  60 value 78.333411
iter  70 value 77.517468
iter  80 value 77.183430
iter  90 value 77.165539
iter 100 value 77.040265
final  value 77.040265 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.410908 
iter  10 value 94.132478
iter  20 value 92.861987
iter  30 value 89.738940
iter  40 value 89.299417
iter  50 value 88.323878
iter  60 value 85.397258
iter  70 value 82.598533
iter  80 value 81.814062
iter  90 value 81.356505
iter 100 value 79.968688
final  value 79.968688 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.221135 
iter  10 value 93.743976
iter  20 value 92.921474
iter  30 value 87.488941
iter  40 value 82.972490
iter  50 value 82.037167
iter  60 value 81.261754
iter  70 value 80.403021
iter  80 value 80.038939
iter  90 value 79.462008
iter 100 value 79.336720
final  value 79.336720 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.060376 
final  value 94.054621 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.521696 
final  value 94.054649 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.954512 
final  value 94.054412 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.495838 
iter  10 value 93.580684
final  value 93.580222 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.851887 
iter  10 value 94.054659
iter  20 value 94.052971
final  value 94.052918 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.589817 
iter  10 value 94.056452
iter  20 value 93.913859
iter  30 value 86.812082
iter  40 value 78.276718
iter  50 value 77.818633
iter  60 value 77.816220
iter  70 value 77.815601
final  value 77.815251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.457748 
iter  10 value 87.195129
iter  20 value 86.416933
iter  30 value 86.395671
iter  40 value 86.348966
iter  50 value 85.761009
iter  60 value 85.759292
iter  70 value 81.960871
iter  80 value 78.703563
iter  90 value 78.566465
final  value 78.564689 
converged
Fitting Repeat 3 

# weights:  305
initial  value 126.261915 
iter  10 value 94.057819
iter  20 value 94.052964
final  value 94.052918 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.038632 
iter  10 value 93.967050
iter  20 value 93.965230
iter  30 value 93.962055
iter  40 value 93.577562
iter  50 value 93.471390
final  value 93.471325 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.632330 
iter  10 value 93.730091
iter  20 value 93.705531
iter  30 value 93.474103
iter  40 value 93.472495
final  value 93.471834 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.606055 
iter  10 value 91.560019
iter  20 value 91.179455
iter  30 value 90.583801
iter  40 value 90.246635
iter  50 value 90.234344
iter  60 value 90.233044
iter  70 value 89.465063
iter  80 value 89.438116
iter  90 value 89.437557
iter 100 value 89.433293
final  value 89.433293 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.170544 
iter  10 value 93.813063
iter  20 value 91.551249
iter  30 value 84.098139
iter  40 value 83.403381
iter  50 value 82.782711
iter  60 value 82.782022
iter  70 value 82.779477
iter  80 value 82.600983
iter  90 value 82.221558
iter 100 value 82.217832
final  value 82.217832 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.237882 
iter  10 value 94.040539
iter  20 value 94.036190
iter  30 value 94.034942
iter  40 value 93.747172
iter  50 value 88.114127
iter  60 value 79.164004
iter  70 value 79.022952
iter  80 value 79.013714
iter  90 value 78.988590
iter 100 value 78.983542
final  value 78.983542 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.454020 
iter  10 value 93.585949
iter  20 value 93.552435
iter  30 value 92.501539
iter  40 value 87.572235
iter  50 value 87.320619
iter  60 value 83.696278
iter  70 value 82.720498
iter  80 value 82.661538
iter  90 value 82.660901
iter  90 value 82.660901
final  value 82.660901 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.563418 
iter  10 value 94.061684
iter  20 value 89.643266
iter  30 value 88.606534
iter  40 value 88.594786
final  value 88.594456 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.461351 
iter  10 value 91.979920
iter  20 value 88.328704
final  value 88.328109 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.499157 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.281166 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.159195 
iter  10 value 92.339219
final  value 92.227947 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.989854 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.613832 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.101795 
final  value 94.448052 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.360990 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.571351 
iter  10 value 91.018227
iter  20 value 83.346095
iter  30 value 82.376230
iter  40 value 81.882282
iter  50 value 81.771729
final  value 81.771726 
converged
Fitting Repeat 5 

# weights:  305
initial  value 127.168227 
final  value 94.275363 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.522183 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.016070 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.837994 
iter  10 value 94.242146
iter  10 value 94.242146
iter  10 value 94.242146
final  value 94.242146 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.963507 
iter  10 value 89.994460
iter  20 value 87.815996
iter  30 value 87.810964
iter  40 value 87.810093
iter  40 value 87.810093
iter  40 value 87.810093
final  value 87.810093 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.485850 
iter  10 value 93.464316
iter  20 value 92.298564
iter  30 value 92.065592
final  value 92.064568 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.822179 
iter  10 value 94.420918
iter  20 value 90.389368
iter  30 value 86.214018
iter  40 value 86.107789
iter  50 value 85.992452
iter  60 value 85.593712
iter  70 value 84.122767
iter  80 value 83.018781
iter  90 value 82.599641
iter 100 value 81.679746
final  value 81.679746 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.039985 
iter  10 value 90.065760
iter  20 value 84.748264
iter  30 value 81.845642
iter  40 value 81.416865
iter  50 value 81.403065
final  value 81.402977 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.998600 
iter  10 value 94.494101
iter  20 value 94.035120
iter  30 value 93.715538
iter  40 value 93.606219
iter  50 value 93.310805
iter  60 value 86.686219
iter  70 value 85.779720
iter  80 value 85.150533
iter  90 value 84.971002
iter 100 value 84.957830
final  value 84.957830 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.328611 
iter  10 value 94.362545
iter  20 value 94.339379
iter  30 value 94.298526
iter  40 value 91.402476
iter  50 value 90.163421
iter  60 value 89.137859
iter  70 value 89.123968
iter  80 value 89.121081
final  value 89.121006 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.645626 
iter  10 value 94.489532
iter  20 value 94.365998
iter  30 value 87.678810
iter  40 value 85.196130
iter  50 value 85.083835
iter  60 value 84.311903
iter  70 value 84.148462
final  value 84.148232 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.148949 
iter  10 value 94.444741
iter  20 value 86.414458
iter  30 value 85.105882
iter  40 value 84.938153
iter  50 value 84.333140
iter  60 value 83.736127
iter  70 value 82.317371
iter  80 value 81.403416
iter  90 value 80.846793
iter 100 value 80.668510
final  value 80.668510 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.518247 
iter  10 value 94.691870
iter  20 value 87.292011
iter  30 value 86.336468
iter  40 value 84.682769
iter  50 value 82.707537
iter  60 value 81.525349
iter  70 value 81.041414
iter  80 value 80.869029
iter  90 value 80.668422
iter 100 value 80.602199
final  value 80.602199 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.498054 
iter  10 value 94.539786
iter  20 value 94.487376
iter  30 value 94.009883
iter  40 value 86.279510
iter  50 value 83.539991
iter  60 value 83.111337
iter  70 value 82.096761
iter  80 value 81.360454
iter  90 value 81.160532
iter 100 value 80.407850
final  value 80.407850 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.281015 
iter  10 value 94.515348
iter  20 value 93.692958
iter  30 value 87.110139
iter  40 value 83.819153
iter  50 value 82.920803
iter  60 value 81.819367
iter  70 value 80.952580
iter  80 value 80.592648
iter  90 value 80.483656
iter 100 value 80.331164
final  value 80.331164 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.398354 
iter  10 value 94.605085
iter  20 value 94.387755
iter  30 value 89.800724
iter  40 value 84.056646
iter  50 value 82.870099
iter  60 value 82.076844
iter  70 value 81.326303
iter  80 value 81.167894
iter  90 value 80.785025
iter 100 value 80.605937
final  value 80.605937 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.928047 
iter  10 value 94.395755
iter  20 value 92.361870
iter  30 value 85.509098
iter  40 value 84.220357
iter  50 value 81.787063
iter  60 value 81.335576
iter  70 value 80.596086
iter  80 value 80.273010
iter  90 value 80.138399
iter 100 value 80.034232
final  value 80.034232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.880144 
iter  10 value 94.639786
iter  20 value 94.468778
iter  30 value 94.191427
iter  40 value 91.516981
iter  50 value 86.408755
iter  60 value 85.551407
iter  70 value 84.811964
iter  80 value 83.796277
iter  90 value 81.627501
iter 100 value 80.902619
final  value 80.902619 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.256566 
iter  10 value 94.855975
iter  20 value 93.245383
iter  30 value 88.042266
iter  40 value 87.194005
iter  50 value 84.213748
iter  60 value 82.492313
iter  70 value 82.293314
iter  80 value 82.139270
iter  90 value 81.636615
iter 100 value 81.209670
final  value 81.209670 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.326796 
iter  10 value 94.915613
iter  20 value 89.874720
iter  30 value 84.925967
iter  40 value 82.955928
iter  50 value 82.632638
iter  60 value 81.907159
iter  70 value 81.073659
iter  80 value 80.695515
iter  90 value 80.665346
iter 100 value 80.596908
final  value 80.596908 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.993712 
iter  10 value 95.021642
iter  20 value 93.600147
iter  30 value 90.105268
iter  40 value 83.612806
iter  50 value 81.380113
iter  60 value 80.986007
iter  70 value 80.894831
iter  80 value 80.744540
iter  90 value 80.282922
iter 100 value 80.071876
final  value 80.071876 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.292159 
final  value 94.485897 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.433657 
iter  10 value 94.276902
iter  20 value 94.246971
iter  30 value 92.231458
iter  40 value 92.231146
iter  50 value 92.230722
iter  60 value 92.230635
iter  70 value 92.229999
iter  80 value 85.178988
iter  90 value 83.553999
iter 100 value 83.543862
final  value 83.543862 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.752853 
final  value 94.486610 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.014798 
final  value 94.485919 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.152685 
iter  10 value 94.485906
iter  20 value 94.096555
iter  30 value 90.682659
final  value 90.682307 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.324140 
iter  10 value 92.234092
iter  20 value 92.231743
iter  30 value 84.298392
iter  40 value 84.055880
iter  50 value 84.017785
final  value 84.017629 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.918728 
iter  10 value 94.280219
iter  20 value 94.261636
iter  30 value 93.541401
iter  40 value 89.245510
iter  50 value 88.713149
iter  60 value 88.650988
iter  70 value 86.412465
iter  80 value 82.834065
iter  90 value 82.534660
iter 100 value 82.312441
final  value 82.312441 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.358771 
iter  10 value 94.280339
iter  20 value 94.278990
iter  30 value 94.275253
iter  40 value 94.160394
iter  50 value 94.159572
final  value 94.159570 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.693823 
iter  10 value 94.168175
iter  20 value 87.711031
iter  30 value 83.699862
iter  40 value 82.237303
iter  50 value 82.182247
iter  60 value 82.181365
iter  70 value 82.179709
final  value 82.179346 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.901797 
iter  10 value 94.488959
iter  20 value 94.428097
iter  30 value 85.089513
iter  40 value 85.044359
final  value 85.043802 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.813018 
iter  10 value 94.491802
iter  20 value 94.347405
iter  30 value 88.514104
iter  40 value 88.476639
iter  50 value 88.476324
iter  60 value 88.475927
final  value 88.475651 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.987306 
iter  10 value 94.238204
iter  20 value 94.232917
iter  30 value 85.448718
iter  40 value 84.720375
iter  50 value 84.331613
iter  60 value 84.240385
iter  70 value 84.010667
iter  80 value 83.941954
iter  90 value 83.445605
iter 100 value 83.442456
final  value 83.442456 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.567847 
iter  10 value 94.487655
iter  20 value 94.484969
final  value 94.484642 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.746741 
iter  10 value 88.139128
iter  20 value 84.299226
iter  30 value 83.813036
iter  40 value 83.755215
iter  50 value 83.748969
iter  60 value 83.746403
iter  70 value 83.741043
iter  80 value 83.571894
iter  90 value 83.488464
final  value 83.488279 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.370524 
iter  10 value 94.314246
iter  20 value 94.289982
iter  30 value 89.781490
iter  40 value 89.513666
iter  50 value 89.512975
final  value 89.512967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 153.080866 
iter  10 value 118.544926
iter  20 value 110.170941
iter  30 value 105.719847
iter  40 value 104.966145
iter  50 value 104.203884
iter  60 value 103.755868
iter  70 value 103.355072
iter  80 value 103.143792
iter  90 value 102.761919
iter 100 value 102.087249
final  value 102.087249 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.156335 
iter  10 value 117.977567
iter  20 value 109.073813
iter  30 value 107.881457
iter  40 value 105.275970
iter  50 value 102.846052
iter  60 value 102.151660
iter  70 value 101.368453
iter  80 value 101.036610
iter  90 value 100.844045
iter 100 value 100.712548
final  value 100.712548 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.562204 
iter  10 value 118.632839
iter  20 value 117.567758
iter  30 value 116.112140
iter  40 value 109.904318
iter  50 value 104.894427
iter  60 value 102.741853
iter  70 value 101.978147
iter  80 value 101.551227
iter  90 value 101.272813
iter 100 value 100.990599
final  value 100.990599 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.167185 
iter  10 value 117.922598
iter  20 value 108.260195
iter  30 value 105.405321
iter  40 value 104.484158
iter  50 value 102.958283
iter  60 value 101.708325
iter  70 value 101.351823
iter  80 value 101.120144
iter  90 value 100.936515
iter 100 value 100.707143
final  value 100.707143 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.784016 
iter  10 value 124.145985
iter  20 value 110.242432
iter  30 value 108.758857
iter  40 value 106.665642
iter  50 value 104.971782
iter  60 value 104.234968
iter  70 value 102.770836
iter  80 value 101.515311
iter  90 value 100.971549
iter 100 value 100.807918
final  value 100.807918 
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 04:05:10 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 
  47.06    7.62   56.15