##############################################################################
##############################################################################
###
### 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_1.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.8.0’
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* 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       51.743  1.754  57.070
corr_plot     50.389  1.693  54.575
FSmethod      50.251  1.699  54.038
pred_ensembel 23.350  0.427  20.532
calculateTC    4.385  0.451   5.098
enrichfindP    0.870  0.083  14.693
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.18-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/4.3-x86_64/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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

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 101.929319 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.389695 
iter  10 value 88.879495
iter  20 value 84.192495
final  value 84.192382 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.559395 
iter  10 value 91.868688
iter  20 value 91.167198
iter  30 value 91.166113
final  value 91.166110 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.773279 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.641565 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.001855 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.825202 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.401636 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.607396 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.606835 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.047147 
iter  10 value 94.123745
iter  20 value 87.708404
iter  30 value 86.943321
iter  40 value 86.504150
iter  50 value 85.111358
iter  60 value 84.591409
iter  70 value 83.945380
iter  80 value 83.922481
iter  90 value 83.921932
iter 100 value 83.921897
final  value 83.921897 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.261099 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.816026 
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.010266 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.998295 
final  value 94.484209 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.264797 
iter  10 value 94.464337
iter  20 value 87.690019
iter  30 value 84.214486
iter  40 value 84.060483
iter  50 value 83.793106
iter  60 value 83.232102
iter  70 value 83.154559
iter  80 value 82.929854
iter  90 value 82.844927
final  value 82.844766 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.939815 
iter  10 value 94.475581
iter  20 value 92.131024
iter  30 value 90.803598
iter  40 value 87.947157
iter  50 value 87.124534
iter  60 value 86.460745
iter  70 value 85.986605
iter  80 value 85.936360
final  value 85.936339 
converged
Fitting Repeat 3 

# weights:  103
initial  value 116.020170 
iter  10 value 94.503097
iter  20 value 93.973271
iter  30 value 87.261306
iter  40 value 85.798633
iter  50 value 85.541378
iter  60 value 85.213225
iter  70 value 85.092380
iter  80 value 85.042712
iter  90 value 85.039424
iter  90 value 85.039424
iter  90 value 85.039424
final  value 85.039424 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.430120 
iter  10 value 94.445962
iter  20 value 93.223807
iter  30 value 92.111001
iter  40 value 90.953394
iter  50 value 90.344517
iter  60 value 86.061664
iter  70 value 85.823884
iter  80 value 85.747447
iter  90 value 85.441874
iter 100 value 85.389953
final  value 85.389953 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.847216 
iter  10 value 94.489736
iter  20 value 94.402463
iter  30 value 86.569736
iter  40 value 86.055588
iter  50 value 85.639303
iter  60 value 85.423468
iter  70 value 85.418746
iter  80 value 85.391283
final  value 85.391064 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.019791 
iter  10 value 93.934428
iter  20 value 86.802934
iter  30 value 86.093065
iter  40 value 85.917724
iter  50 value 84.420546
iter  60 value 83.373598
iter  70 value 82.922694
iter  80 value 82.345007
iter  90 value 82.017699
iter 100 value 81.983546
final  value 81.983546 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.733165 
iter  10 value 94.397452
iter  20 value 86.372995
iter  30 value 84.631340
iter  40 value 83.451693
iter  50 value 83.163002
iter  60 value 82.501875
iter  70 value 82.355805
iter  80 value 81.886390
iter  90 value 81.863402
iter 100 value 81.825057
final  value 81.825057 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.215753 
iter  10 value 94.485032
iter  20 value 91.256508
iter  30 value 86.929618
iter  40 value 86.488424
iter  50 value 86.128457
iter  60 value 86.027833
iter  70 value 84.852337
iter  80 value 82.973800
iter  90 value 82.864803
iter 100 value 82.486330
final  value 82.486330 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.449317 
iter  10 value 91.639045
iter  20 value 89.199578
iter  30 value 89.061816
iter  40 value 86.557823
iter  50 value 85.174798
iter  60 value 85.006652
iter  70 value 84.600186
iter  80 value 84.001672
iter  90 value 82.171460
iter 100 value 81.651351
final  value 81.651351 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.501429 
iter  10 value 93.882835
iter  20 value 90.904616
iter  30 value 89.086643
iter  40 value 85.870782
iter  50 value 84.057965
iter  60 value 83.641034
iter  70 value 83.107174
iter  80 value 82.598940
iter  90 value 82.418597
iter 100 value 82.271604
final  value 82.271604 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.879341 
iter  10 value 87.453467
iter  20 value 85.465769
iter  30 value 84.078941
iter  40 value 83.197372
iter  50 value 81.659425
iter  60 value 81.306220
iter  70 value 81.231538
iter  80 value 81.137454
iter  90 value 81.099663
iter 100 value 81.048071
final  value 81.048071 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.069908 
iter  10 value 94.652070
iter  20 value 90.114660
iter  30 value 88.287114
iter  40 value 85.752486
iter  50 value 84.095274
iter  60 value 83.054525
iter  70 value 82.297643
iter  80 value 81.921062
iter  90 value 81.856098
iter 100 value 81.571141
final  value 81.571141 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.296051 
iter  10 value 94.525265
iter  20 value 93.400016
iter  30 value 87.122620
iter  40 value 84.188409
iter  50 value 83.663185
iter  60 value 82.358888
iter  70 value 81.482315
iter  80 value 81.306702
iter  90 value 81.170988
iter 100 value 81.146703
final  value 81.146703 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.543549 
iter  10 value 92.550553
iter  20 value 90.527558
iter  30 value 85.509685
iter  40 value 82.905927
iter  50 value 82.061621
iter  60 value 81.885185
iter  70 value 81.763616
iter  80 value 81.599674
iter  90 value 81.468173
iter 100 value 81.306066
final  value 81.306066 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.518241 
iter  10 value 90.201015
iter  20 value 89.214424
iter  30 value 87.286120
iter  40 value 85.501051
iter  50 value 84.878614
iter  60 value 84.521098
iter  70 value 83.951848
iter  80 value 82.929031
iter  90 value 81.744362
iter 100 value 81.601440
final  value 81.601440 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.122638 
final  value 94.485894 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.367810 
final  value 94.468275 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.998164 
final  value 94.485824 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.537418 
iter  10 value 92.100272
iter  20 value 91.426124
iter  30 value 90.806239
iter  40 value 86.167420
iter  50 value 85.615593
iter  60 value 85.383619
iter  70 value 85.338702
iter  80 value 85.338224
iter  90 value 85.337730
iter 100 value 85.337499
final  value 85.337499 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.605048 
final  value 94.486061 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.385515 
iter  10 value 94.471217
iter  20 value 94.466909
iter  30 value 86.748278
iter  40 value 85.760591
iter  50 value 85.397629
final  value 85.045105 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.348507 
iter  10 value 94.329152
iter  20 value 90.347537
iter  30 value 89.206920
iter  40 value 88.590382
iter  50 value 87.943275
iter  60 value 87.942528
iter  70 value 87.941437
final  value 87.941430 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.396896 
iter  10 value 94.489643
iter  20 value 94.485587
iter  30 value 94.061344
iter  40 value 91.341986
iter  50 value 88.340776
iter  60 value 88.206275
final  value 88.205551 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.205091 
iter  10 value 94.471121
iter  20 value 93.879199
iter  30 value 90.792775
iter  40 value 90.780028
iter  50 value 90.778238
iter  60 value 89.745030
iter  70 value 89.228155
iter  80 value 88.330100
iter  90 value 88.307292
iter 100 value 88.252323
final  value 88.252323 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.635755 
iter  10 value 94.488993
iter  20 value 94.462295
iter  30 value 85.800923
final  value 85.754243 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.409233 
iter  10 value 94.055089
iter  20 value 93.976643
iter  30 value 89.121605
iter  40 value 85.291357
iter  50 value 85.260452
iter  60 value 85.194826
iter  70 value 85.184872
iter  80 value 85.183435
iter  90 value 85.183137
final  value 85.183035 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.532993 
iter  10 value 94.044676
iter  20 value 94.039104
final  value 94.037013 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.801273 
iter  10 value 94.492753
iter  20 value 92.107331
iter  30 value 85.235648
iter  40 value 83.414165
iter  50 value 81.703741
iter  60 value 81.125558
iter  70 value 81.011266
iter  80 value 80.685004
iter  90 value 80.610626
iter 100 value 80.569146
final  value 80.569146 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.338689 
iter  10 value 89.421159
iter  20 value 88.604993
iter  30 value 88.597930
iter  40 value 88.589912
final  value 88.588608 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.337597 
iter  10 value 89.872819
iter  20 value 85.762391
iter  30 value 85.058491
iter  40 value 84.880392
iter  50 value 84.879135
iter  60 value 84.874556
iter  70 value 84.845153
iter  80 value 84.164677
iter  90 value 83.888826
iter 100 value 83.884457
final  value 83.884457 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.683581 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.361072 
final  value 93.637379 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.279769 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.415656 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.590064 
final  value 94.484213 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.005315 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.888337 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.836982 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.335455 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.124348 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.669377 
iter  10 value 91.904440
iter  20 value 84.323906
iter  30 value 84.289750
iter  40 value 84.289045
final  value 84.289042 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.012803 
iter  10 value 93.508987
iter  20 value 91.872101
final  value 91.858965 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.597901 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.229254 
iter  10 value 94.026543
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.845271 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.578423 
iter  10 value 94.094095
iter  20 value 88.361171
iter  30 value 85.396010
iter  40 value 84.220559
iter  50 value 83.350958
iter  60 value 82.069219
iter  70 value 80.984875
iter  80 value 80.921086
final  value 80.863667 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.439174 
iter  10 value 93.483036
iter  20 value 89.402577
iter  30 value 83.702442
iter  40 value 82.896285
iter  50 value 82.843696
iter  60 value 82.769290
iter  70 value 82.671266
iter  80 value 82.650699
iter  80 value 82.650699
iter  80 value 82.650699
final  value 82.650699 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.615173 
iter  10 value 89.005658
iter  20 value 84.428812
iter  30 value 82.933394
iter  40 value 81.739131
iter  50 value 81.080784
iter  60 value 80.948188
iter  70 value 80.765342
iter  80 value 80.629730
final  value 80.629711 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.034703 
iter  10 value 94.486471
iter  20 value 94.151290
iter  30 value 94.125506
iter  40 value 93.686701
iter  50 value 92.155156
iter  60 value 86.195343
iter  70 value 82.755818
iter  80 value 82.721834
iter  90 value 82.666250
iter 100 value 82.650741
final  value 82.650741 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.095703 
iter  10 value 94.455113
iter  20 value 90.477617
iter  30 value 85.935999
iter  40 value 83.404127
iter  50 value 82.052045
iter  60 value 80.894556
iter  70 value 80.801344
final  value 80.801330 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.619823 
iter  10 value 94.379522
iter  20 value 87.956503
iter  30 value 86.561318
iter  40 value 84.217657
iter  50 value 83.320899
iter  60 value 81.586800
iter  70 value 80.711427
iter  80 value 79.917241
iter  90 value 79.629339
iter 100 value 79.591485
final  value 79.591485 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.414665 
iter  10 value 94.489297
iter  20 value 84.383800
iter  30 value 83.836954
iter  40 value 83.249545
iter  50 value 82.307074
iter  60 value 81.946453
iter  70 value 81.435460
iter  80 value 81.263436
iter  90 value 80.988599
iter 100 value 80.883074
final  value 80.883074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.805411 
iter  10 value 94.518101
iter  20 value 85.027759
iter  30 value 81.646716
iter  40 value 81.059585
iter  50 value 80.755891
iter  60 value 80.632440
iter  70 value 80.461964
iter  80 value 80.121037
iter  90 value 79.633303
iter 100 value 79.395125
final  value 79.395125 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.881106 
iter  10 value 94.298964
iter  20 value 93.707926
iter  30 value 93.343582
iter  40 value 89.699295
iter  50 value 88.621833
iter  60 value 88.310386
iter  70 value 85.938419
iter  80 value 83.062753
iter  90 value 81.321781
iter 100 value 80.184992
final  value 80.184992 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.202317 
iter  10 value 96.068542
iter  20 value 85.913955
iter  30 value 84.303728
iter  40 value 84.139485
iter  50 value 82.553217
iter  60 value 81.652479
iter  70 value 81.316120
iter  80 value 81.232213
iter  90 value 80.954909
iter 100 value 80.571695
final  value 80.571695 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.900631 
iter  10 value 94.939324
iter  20 value 86.604700
iter  30 value 83.464016
iter  40 value 80.888449
iter  50 value 79.954413
iter  60 value 79.664196
iter  70 value 79.477392
iter  80 value 79.342067
iter  90 value 79.250644
iter 100 value 79.113637
final  value 79.113637 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.749890 
iter  10 value 94.452253
iter  20 value 90.999053
iter  30 value 84.071337
iter  40 value 80.689722
iter  50 value 80.066243
iter  60 value 79.911734
iter  70 value 79.810987
iter  80 value 79.533915
iter  90 value 79.454431
iter 100 value 79.378452
final  value 79.378452 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.723323 
iter  10 value 90.415956
iter  20 value 85.254608
iter  30 value 84.554910
iter  40 value 83.015376
iter  50 value 81.273090
iter  60 value 80.759006
iter  70 value 80.268446
iter  80 value 79.645013
iter  90 value 79.535663
iter 100 value 79.329050
final  value 79.329050 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.528190 
iter  10 value 93.953318
iter  20 value 87.954054
iter  30 value 83.975072
iter  40 value 83.228932
iter  50 value 82.515768
iter  60 value 80.418010
iter  70 value 79.667018
iter  80 value 79.489927
iter  90 value 79.303595
iter 100 value 79.277802
final  value 79.277802 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 137.105625 
iter  10 value 95.189046
iter  20 value 94.539819
iter  30 value 87.968621
iter  40 value 86.900352
iter  50 value 85.288933
iter  60 value 82.089992
iter  70 value 80.622061
iter  80 value 79.795411
iter  90 value 79.645099
iter 100 value 79.549434
final  value 79.549434 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.759336 
iter  10 value 94.486045
iter  20 value 94.479288
iter  30 value 93.638132
final  value 93.638129 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.055155 
iter  10 value 94.485798
iter  20 value 94.484228
final  value 94.484218 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.833583 
iter  10 value 94.486064
iter  20 value 94.484315
final  value 94.484215 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.058165 
final  value 94.486009 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.966986 
iter  10 value 94.485788
iter  20 value 94.484272
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 134.231892 
iter  10 value 94.489248
iter  20 value 94.484293
iter  30 value 93.277437
iter  40 value 83.358670
iter  50 value 82.608614
iter  60 value 81.159845
iter  70 value 80.905280
iter  80 value 80.879587
iter  90 value 80.526088
iter 100 value 79.477164
final  value 79.477164 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.767204 
iter  10 value 94.032138
iter  20 value 94.030282
iter  30 value 94.027138
iter  40 value 93.230843
iter  50 value 88.172742
iter  60 value 88.147129
iter  70 value 88.146598
iter  70 value 88.146597
final  value 88.146553 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.560647 
iter  10 value 94.488961
iter  20 value 94.317004
iter  30 value 84.882437
iter  40 value 84.544160
iter  50 value 83.466567
final  value 83.465624 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.490939 
iter  10 value 94.031639
iter  20 value 94.027075
iter  30 value 83.624789
iter  40 value 83.465664
iter  50 value 83.201503
iter  60 value 83.166920
iter  70 value 83.108015
iter  80 value 82.115517
iter  90 value 80.760997
iter 100 value 80.670495
final  value 80.670495 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.220269 
iter  10 value 94.488643
iter  20 value 94.292883
iter  30 value 83.183170
iter  40 value 83.131966
iter  50 value 83.131378
final  value 83.131367 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.502675 
iter  10 value 94.113704
iter  20 value 94.107016
iter  30 value 93.760317
iter  40 value 92.557164
iter  50 value 83.776245
final  value 83.464417 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.596510 
iter  10 value 94.492444
iter  20 value 91.096875
iter  30 value 84.203064
iter  40 value 84.151343
iter  50 value 84.125674
iter  60 value 84.103947
iter  70 value 84.103535
final  value 84.099978 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.232761 
iter  10 value 94.078423
iter  20 value 94.031192
iter  30 value 94.025319
iter  40 value 93.629554
iter  50 value 93.347777
iter  60 value 93.346305
iter  70 value 92.641937
final  value 92.636901 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.916746 
iter  10 value 94.034727
iter  20 value 94.030197
iter  30 value 94.016653
final  value 93.550503 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.593994 
iter  10 value 86.385174
iter  20 value 82.983763
iter  30 value 82.977917
iter  40 value 82.976214
iter  50 value 82.381529
iter  60 value 81.610670
iter  70 value 81.517092
iter  80 value 81.512431
iter  90 value 81.237152
iter 100 value 79.528049
final  value 79.528049 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.568072 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.556520 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.858431 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.378578 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.709611 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.160157 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.233927 
final  value 93.395952 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.071499 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.619163 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.345686 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.221110 
iter  10 value 93.506090
iter  20 value 93.471195
final  value 93.470905 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.397538 
iter  10 value 94.081189
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.900908 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.811506 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.042444 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.902112 
iter  10 value 94.157234
iter  20 value 94.050079
iter  30 value 90.589379
iter  40 value 87.702628
iter  50 value 87.039304
iter  60 value 85.734073
iter  70 value 84.111300
iter  80 value 83.621894
iter  90 value 83.003520
iter 100 value 82.946322
final  value 82.946322 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.770582 
iter  10 value 94.056924
iter  20 value 94.048036
iter  30 value 93.244212
iter  40 value 88.181597
iter  50 value 87.894077
iter  60 value 85.771309
iter  70 value 85.168415
iter  80 value 84.921282
iter  90 value 84.863939
final  value 84.863928 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.183894 
iter  10 value 94.056476
iter  20 value 93.775195
iter  30 value 88.302061
iter  40 value 86.078637
iter  50 value 85.966662
iter  60 value 85.885626
iter  70 value 85.806199
final  value 85.805254 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.562260 
iter  10 value 94.056133
iter  20 value 94.028484
iter  30 value 89.079418
iter  40 value 88.433330
iter  50 value 88.403342
iter  60 value 86.396716
iter  70 value 85.378146
iter  80 value 85.366967
iter  90 value 85.317516
iter 100 value 85.257686
final  value 85.257686 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.273115 
iter  10 value 94.054871
iter  20 value 91.201408
iter  30 value 86.324207
iter  40 value 85.506517
iter  50 value 85.372849
iter  60 value 85.262504
iter  70 value 85.221648
final  value 85.219624 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.507489 
iter  10 value 94.030995
iter  20 value 92.347439
iter  30 value 90.055094
iter  40 value 87.771054
iter  50 value 84.993122
iter  60 value 83.276958
iter  70 value 83.190378
iter  80 value 82.930353
iter  90 value 82.855312
iter 100 value 82.623415
final  value 82.623415 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.971903 
iter  10 value 94.280712
iter  20 value 94.054620
iter  30 value 92.349545
iter  40 value 91.136713
iter  50 value 88.489442
iter  60 value 85.466660
iter  70 value 84.043664
iter  80 value 83.744229
iter  90 value 83.226943
iter 100 value 83.057521
final  value 83.057521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.514662 
iter  10 value 94.087955
iter  20 value 93.980968
iter  30 value 92.007454
iter  40 value 91.340110
iter  50 value 89.782696
iter  60 value 87.699259
iter  70 value 86.143113
iter  80 value 85.188368
iter  90 value 84.666485
iter 100 value 83.789826
final  value 83.789826 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.072753 
iter  10 value 94.106765
iter  20 value 92.404498
iter  30 value 86.895090
iter  40 value 84.336109
iter  50 value 82.686852
iter  60 value 82.586962
iter  70 value 82.487862
iter  80 value 82.331380
iter  90 value 81.938773
iter 100 value 81.687916
final  value 81.687916 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.963387 
iter  10 value 93.794060
iter  20 value 91.477490
iter  30 value 88.695906
iter  40 value 86.529841
iter  50 value 84.412090
iter  60 value 83.180238
iter  70 value 82.907253
iter  80 value 82.749578
iter  90 value 82.111273
iter 100 value 81.950914
final  value 81.950914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.177257 
iter  10 value 93.833379
iter  20 value 87.856080
iter  30 value 86.296582
iter  40 value 85.896093
iter  50 value 84.795603
iter  60 value 83.309213
iter  70 value 82.406819
iter  80 value 81.504455
iter  90 value 81.382703
iter 100 value 81.266807
final  value 81.266807 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.904755 
iter  10 value 94.056815
iter  20 value 92.614418
iter  30 value 90.299650
iter  40 value 89.816991
iter  50 value 87.691082
iter  60 value 85.580536
iter  70 value 84.746238
iter  80 value 83.458238
iter  90 value 82.725734
iter 100 value 82.158066
final  value 82.158066 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.361291 
iter  10 value 92.910605
iter  20 value 91.303467
iter  30 value 89.542860
iter  40 value 87.316454
iter  50 value 86.359282
iter  60 value 84.885069
iter  70 value 84.055229
iter  80 value 82.999694
iter  90 value 82.215743
iter 100 value 81.778271
final  value 81.778271 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.559217 
iter  10 value 94.110155
iter  20 value 93.291413
iter  30 value 85.984523
iter  40 value 84.718709
iter  50 value 84.488668
iter  60 value 84.393278
iter  70 value 83.186657
iter  80 value 82.839885
iter  90 value 82.671077
iter 100 value 82.553580
final  value 82.553580 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.186186 
iter  10 value 95.500339
iter  20 value 93.111721
iter  30 value 88.317893
iter  40 value 84.605899
iter  50 value 83.720885
iter  60 value 83.170480
iter  70 value 82.682436
iter  80 value 82.648149
iter  90 value 82.593169
iter 100 value 82.397659
final  value 82.397659 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.169142 
final  value 94.054608 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.955851 
iter  10 value 94.010316
iter  20 value 93.882244
iter  30 value 85.707827
iter  40 value 84.592948
iter  50 value 84.550312
iter  60 value 84.403337
iter  70 value 84.403252
final  value 84.403224 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.175497 
final  value 94.054446 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.588871 
iter  10 value 94.010267
iter  20 value 94.009855
iter  30 value 94.008807
final  value 94.008751 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.762212 
iter  10 value 94.054636
iter  20 value 94.052970
final  value 94.052916 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.610938 
iter  10 value 94.057592
iter  20 value 93.652233
iter  30 value 85.732238
final  value 85.106619 
converged
Fitting Repeat 2 

# weights:  305
initial  value 133.198362 
iter  10 value 94.058894
iter  20 value 93.992289
iter  30 value 85.139261
iter  40 value 82.872257
iter  50 value 82.805316
final  value 82.805246 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.739231 
iter  10 value 94.057992
iter  20 value 93.739926
iter  30 value 88.852280
iter  40 value 88.208817
iter  50 value 88.208442
final  value 88.208353 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.100380 
iter  10 value 94.057222
iter  20 value 93.659322
iter  30 value 88.212866
iter  40 value 88.210897
iter  50 value 88.209500
iter  60 value 88.204407
iter  70 value 88.089709
iter  80 value 87.776495
iter  90 value 83.637159
iter 100 value 83.552238
final  value 83.552238 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.383398 
iter  10 value 94.057851
iter  20 value 94.052931
iter  30 value 93.979780
iter  40 value 93.810339
iter  50 value 93.757856
iter  60 value 87.575105
iter  70 value 87.544650
iter  70 value 87.544649
iter  70 value 87.544649
final  value 87.544649 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.215646 
iter  10 value 94.061516
iter  20 value 94.051870
iter  30 value 93.724580
iter  40 value 93.444033
iter  50 value 92.037613
iter  60 value 86.391564
iter  70 value 85.883795
iter  80 value 85.838767
iter  90 value 85.838216
final  value 85.837442 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.883140 
iter  10 value 94.037343
iter  20 value 94.016063
iter  30 value 93.835932
iter  40 value 85.554890
iter  50 value 85.089288
iter  60 value 83.609309
iter  70 value 81.839941
iter  80 value 81.829320
iter  90 value 81.828512
final  value 81.827294 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.286577 
iter  10 value 93.645168
iter  20 value 93.639576
iter  30 value 90.209193
iter  40 value 87.004817
iter  50 value 84.356580
iter  60 value 84.259307
iter  70 value 84.259050
iter  80 value 84.257210
final  value 84.257075 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.278339 
iter  10 value 94.017185
iter  20 value 93.918993
iter  30 value 92.604851
iter  40 value 84.659207
iter  50 value 84.145970
iter  60 value 84.117302
final  value 84.117237 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.481393 
iter  10 value 94.060430
iter  20 value 92.371377
iter  30 value 88.283868
iter  40 value 86.966625
iter  50 value 86.954492
iter  60 value 86.953644
final  value 86.950976 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.781600 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.734353 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.340930 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.786414 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.075047 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.076821 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.530142 
iter  10 value 94.213603
iter  20 value 87.244797
iter  30 value 85.320176
final  value 84.267099 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.349979 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.608175 
iter  10 value 83.510858
iter  20 value 81.762073
iter  30 value 81.742768
final  value 81.739033 
converged
Fitting Repeat 5 

# weights:  305
initial  value 93.539989 
iter  10 value 82.303170
iter  20 value 80.292145
iter  30 value 80.282842
final  value 80.279601 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.400561 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.558998 
final  value 94.480519 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.039439 
iter  10 value 93.947376
final  value 93.947313 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.741651 
iter  10 value 94.482932
iter  10 value 94.482932
iter  10 value 94.482932
final  value 94.482932 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.433664 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.755583 
iter  10 value 94.411858
iter  20 value 90.890909
iter  30 value 86.449677
iter  40 value 82.745208
iter  50 value 82.101890
iter  60 value 81.730504
iter  70 value 80.231568
iter  80 value 79.662053
iter  90 value 79.519269
iter 100 value 79.293522
final  value 79.293522 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.868929 
iter  10 value 93.858737
iter  20 value 85.855642
iter  30 value 83.276982
iter  40 value 82.730690
iter  50 value 81.553082
iter  60 value 81.219490
final  value 81.200415 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.366431 
iter  10 value 94.486612
iter  20 value 83.576489
iter  30 value 83.299287
iter  40 value 82.770692
iter  50 value 81.225806
iter  60 value 80.921121
iter  70 value 80.913742
final  value 80.913121 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.718684 
iter  10 value 94.560720
iter  20 value 94.044498
iter  30 value 83.865256
iter  40 value 83.009996
iter  50 value 81.474837
iter  60 value 80.756858
iter  70 value 80.273940
iter  80 value 80.064028
iter  90 value 79.694016
iter 100 value 79.310864
final  value 79.310864 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.427755 
iter  10 value 94.510264
iter  20 value 94.485592
iter  30 value 94.307632
iter  40 value 89.197303
iter  50 value 88.770621
iter  60 value 86.907264
iter  70 value 85.373422
iter  80 value 84.197428
iter  90 value 84.081868
iter 100 value 82.890791
final  value 82.890791 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.428935 
iter  10 value 94.483152
iter  20 value 88.203674
iter  30 value 84.446526
iter  40 value 80.127179
iter  50 value 78.742684
iter  60 value 78.542984
iter  70 value 78.431374
iter  80 value 78.151674
iter  90 value 78.023275
iter 100 value 77.916892
final  value 77.916892 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.746821 
iter  10 value 94.055343
iter  20 value 84.100479
iter  30 value 83.273115
iter  40 value 82.625197
iter  50 value 81.746732
iter  60 value 81.393448
iter  70 value 80.324071
iter  80 value 79.059687
iter  90 value 78.033570
iter 100 value 77.540405
final  value 77.540405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.264858 
iter  10 value 95.035491
iter  20 value 92.452444
iter  30 value 88.361344
iter  40 value 85.730934
iter  50 value 81.888290
iter  60 value 79.122100
iter  70 value 78.545706
iter  80 value 77.892373
iter  90 value 77.762926
iter 100 value 77.622310
final  value 77.622310 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.653593 
iter  10 value 94.960987
iter  20 value 86.901550
iter  30 value 83.561584
iter  40 value 82.644071
iter  50 value 81.668766
iter  60 value 81.503209
iter  70 value 79.883196
iter  80 value 78.680129
iter  90 value 78.196807
iter 100 value 78.141122
final  value 78.141122 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.343668 
iter  10 value 94.444502
iter  20 value 88.708946
iter  30 value 83.593796
iter  40 value 83.382031
iter  50 value 80.080681
iter  60 value 79.671140
iter  70 value 79.349489
iter  80 value 78.508648
iter  90 value 78.092271
iter 100 value 77.626649
final  value 77.626649 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.129445 
iter  10 value 94.185322
iter  20 value 83.313849
iter  30 value 82.729364
iter  40 value 82.160846
iter  50 value 81.537468
iter  60 value 81.103583
iter  70 value 80.692652
iter  80 value 78.147274
iter  90 value 77.415408
iter 100 value 77.323034
final  value 77.323034 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.796666 
iter  10 value 95.116650
iter  20 value 88.532190
iter  30 value 84.191283
iter  40 value 83.927416
iter  50 value 81.864942
iter  60 value 80.132789
iter  70 value 79.353796
iter  80 value 78.408289
iter  90 value 77.344990
iter 100 value 77.132273
final  value 77.132273 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.919307 
iter  10 value 94.124387
iter  20 value 89.561967
iter  30 value 88.791140
iter  40 value 83.743833
iter  50 value 81.652767
iter  60 value 79.984747
iter  70 value 78.691824
iter  80 value 77.906875
iter  90 value 77.716201
iter 100 value 77.665816
final  value 77.665816 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.520893 
iter  10 value 93.809324
iter  20 value 83.983046
iter  30 value 82.043439
iter  40 value 81.438819
iter  50 value 81.384909
iter  60 value 81.144913
iter  70 value 79.897969
iter  80 value 78.346996
iter  90 value 77.761560
iter 100 value 77.594905
final  value 77.594905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.576320 
iter  10 value 94.520893
iter  20 value 91.968324
iter  30 value 83.618834
iter  40 value 83.490313
iter  50 value 82.627354
iter  60 value 80.935791
iter  70 value 79.355417
iter  80 value 77.935721
iter  90 value 77.514081
iter 100 value 77.296286
final  value 77.296286 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.614719 
final  value 94.468682 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.666853 
final  value 94.486070 
converged
Fitting Repeat 3 

# weights:  103
initial  value 93.408422 
iter  10 value 85.959349
iter  20 value 84.841767
iter  30 value 83.857852
iter  40 value 83.414365
iter  50 value 83.403203
iter  60 value 83.402834
iter  70 value 83.402067
iter  80 value 81.125944
iter  90 value 80.180772
iter 100 value 80.103473
final  value 80.103473 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 108.620865 
final  value 94.486130 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.000210 
final  value 93.703322 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.491942 
iter  10 value 94.480646
iter  20 value 94.471881
iter  30 value 94.469968
iter  40 value 94.429448
iter  50 value 94.429202
final  value 94.429180 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.660101 
iter  10 value 94.454259
iter  20 value 88.803389
iter  30 value 85.360458
iter  30 value 85.360458
iter  30 value 85.360458
final  value 85.360458 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.655368 
iter  10 value 94.488599
iter  20 value 87.711467
final  value 87.353899 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.331985 
iter  10 value 94.577661
iter  20 value 94.377328
iter  30 value 91.129418
iter  40 value 80.225230
iter  50 value 79.053329
iter  60 value 79.052818
iter  70 value 79.052153
iter  80 value 79.051679
iter  90 value 79.051599
final  value 79.050739 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.129379 
iter  10 value 94.489035
iter  20 value 94.299368
iter  30 value 85.796449
iter  40 value 84.230232
iter  50 value 83.455377
iter  60 value 82.806401
iter  70 value 82.804578
final  value 82.804564 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.315529 
iter  10 value 94.492498
iter  20 value 94.293962
iter  30 value 84.337694
iter  40 value 83.988156
iter  50 value 83.975085
iter  60 value 83.684492
iter  70 value 83.676297
iter  80 value 83.407936
iter  90 value 83.406183
iter 100 value 83.403187
final  value 83.403187 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.420421 
iter  10 value 93.628985
iter  20 value 93.178929
iter  30 value 93.116237
iter  40 value 93.093977
final  value 93.093494 
converged
Fitting Repeat 3 

# weights:  507
initial  value 143.785331 
iter  10 value 94.168933
iter  20 value 82.934362
iter  30 value 82.649374
iter  40 value 81.618135
iter  50 value 81.197805
iter  60 value 81.195002
iter  70 value 81.165894
iter  80 value 81.059800
iter  90 value 80.851196
iter 100 value 80.849085
final  value 80.849085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.357492 
iter  10 value 94.375509
iter  20 value 94.197840
iter  30 value 93.955092
iter  40 value 93.057648
iter  50 value 91.615008
iter  60 value 91.576507
iter  70 value 83.422980
iter  80 value 80.095653
iter  90 value 78.115950
iter 100 value 77.988510
final  value 77.988510 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.943201 
iter  10 value 94.472500
iter  20 value 93.221349
iter  30 value 87.519721
iter  40 value 87.323058
iter  50 value 87.321462
iter  60 value 87.319118
iter  70 value 87.317750
iter  80 value 87.166089
iter  90 value 83.417205
iter 100 value 81.048828
final  value 81.048828 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.341462 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.084005 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.399114 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.841605 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.699797 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.272697 
iter  10 value 90.406212
iter  20 value 89.039807
iter  30 value 88.989773
iter  40 value 83.945738
iter  50 value 83.214465
iter  60 value 82.786184
iter  70 value 82.779131
final  value 82.779051 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.207657 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.653489 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.523390 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.940838 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.535913 
final  value 93.912644 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.375665 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.990136 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.891586 
iter  10 value 93.553229
iter  20 value 93.013829
iter  30 value 91.070766
iter  40 value 91.067133
final  value 91.067082 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.180904 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.558716 
iter  10 value 93.789427
iter  20 value 89.961019
iter  30 value 85.642704
iter  40 value 84.887036
iter  50 value 84.444338
iter  60 value 84.033064
iter  70 value 83.889130
iter  80 value 83.825115
final  value 83.824149 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.333340 
iter  10 value 94.056741
iter  20 value 94.039423
iter  30 value 93.954948
iter  40 value 93.943825
iter  50 value 93.766908
iter  60 value 93.442461
iter  70 value 93.173599
iter  80 value 92.220256
iter  90 value 85.974597
iter 100 value 84.617567
final  value 84.617567 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 109.330623 
iter  10 value 93.984734
iter  20 value 91.541394
iter  30 value 84.930963
iter  40 value 84.628400
iter  50 value 84.513445
iter  60 value 84.497529
iter  60 value 84.497529
iter  60 value 84.497529
final  value 84.497529 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.970387 
iter  10 value 94.056832
iter  20 value 93.549040
iter  30 value 93.465037
iter  40 value 93.403499
iter  50 value 93.267280
iter  60 value 88.052730
iter  70 value 85.572406
iter  80 value 85.450727
iter  90 value 85.358913
iter 100 value 84.864037
final  value 84.864037 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.163230 
iter  10 value 94.024306
iter  20 value 89.265557
iter  30 value 84.156005
iter  40 value 83.458247
iter  50 value 83.317970
iter  60 value 83.065041
iter  70 value 81.990995
iter  80 value 81.867093
iter  90 value 81.817694
final  value 81.817396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.158921 
iter  10 value 94.054933
iter  20 value 92.908858
iter  30 value 91.392363
iter  40 value 91.326695
iter  50 value 89.252451
iter  60 value 85.609805
iter  70 value 84.141602
iter  80 value 82.648636
iter  90 value 82.172884
iter 100 value 80.950861
final  value 80.950861 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.103960 
iter  10 value 89.481120
iter  20 value 87.620878
iter  30 value 86.763081
iter  40 value 84.102689
iter  50 value 81.500992
iter  60 value 80.704573
iter  70 value 80.097028
iter  80 value 79.995456
iter  90 value 79.979771
iter 100 value 79.902755
final  value 79.902755 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.510646 
iter  10 value 94.045882
iter  20 value 88.309894
iter  30 value 86.866897
iter  40 value 86.227447
iter  50 value 83.803972
iter  60 value 83.089058
iter  70 value 82.796157
iter  80 value 82.631300
iter  90 value 82.137592
iter 100 value 82.042433
final  value 82.042433 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.279719 
iter  10 value 94.057137
iter  20 value 92.012890
iter  30 value 85.946996
iter  40 value 84.442795
iter  50 value 82.369955
iter  60 value 81.963295
iter  70 value 81.393117
iter  80 value 81.163966
iter  90 value 81.029069
iter 100 value 80.853524
final  value 80.853524 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.527701 
iter  10 value 94.217593
iter  20 value 88.982653
iter  30 value 87.772238
iter  40 value 85.008869
iter  50 value 84.359632
iter  60 value 83.830644
iter  70 value 83.305756
iter  80 value 82.200727
iter  90 value 81.629993
iter 100 value 81.606026
final  value 81.606026 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.173568 
iter  10 value 94.334192
iter  20 value 93.664496
iter  30 value 88.314237
iter  40 value 87.341708
iter  50 value 87.235777
iter  60 value 87.006566
iter  70 value 86.308369
iter  80 value 85.866516
iter  90 value 83.927467
iter 100 value 82.473094
final  value 82.473094 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.150642 
iter  10 value 94.161041
iter  20 value 87.555054
iter  30 value 86.429704
iter  40 value 84.857018
iter  50 value 82.408562
iter  60 value 81.389047
iter  70 value 80.937929
iter  80 value 80.734380
iter  90 value 80.678990
iter 100 value 80.556521
final  value 80.556521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.579213 
iter  10 value 94.086320
iter  20 value 90.192585
iter  30 value 86.637504
iter  40 value 85.866960
iter  50 value 82.329893
iter  60 value 80.699402
iter  70 value 80.614565
iter  80 value 80.284163
iter  90 value 80.134521
iter 100 value 79.987441
final  value 79.987441 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.000902 
iter  10 value 93.617112
iter  20 value 87.001423
iter  30 value 85.824871
iter  40 value 84.298038
iter  50 value 82.670748
iter  60 value 81.339037
iter  70 value 80.955833
iter  80 value 80.709412
iter  90 value 80.267636
iter 100 value 80.226148
final  value 80.226148 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.680013 
iter  10 value 93.820067
iter  20 value 84.220382
iter  30 value 82.503708
iter  40 value 81.282869
iter  50 value 80.554482
iter  60 value 80.268047
iter  70 value 80.183873
iter  80 value 80.116740
iter  90 value 79.881985
iter 100 value 79.641260
final  value 79.641260 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.333378 
final  value 94.054509 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.557012 
final  value 94.054683 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.727589 
iter  10 value 94.054706
iter  20 value 94.052661
iter  30 value 93.412969
final  value 93.412740 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.841333 
final  value 94.054846 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.388057 
iter  10 value 93.688425
iter  20 value 93.673052
iter  30 value 93.671682
iter  40 value 93.487066
iter  50 value 91.898591
iter  60 value 86.563320
iter  70 value 82.569739
iter  80 value 82.414126
iter  90 value 82.410368
iter 100 value 82.333632
final  value 82.333632 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.750145 
iter  10 value 94.057739
iter  20 value 93.880481
iter  30 value 89.261937
iter  40 value 88.592637
iter  50 value 88.558519
iter  60 value 88.354646
final  value 88.354536 
converged
Fitting Repeat 2 

# weights:  305
initial  value 124.461304 
iter  10 value 94.057466
iter  20 value 94.031026
iter  30 value 93.290767
final  value 93.290763 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.590148 
iter  10 value 94.058081
iter  20 value 94.026934
iter  30 value 93.836434
final  value 93.836433 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.577582 
iter  10 value 93.415302
iter  20 value 93.409644
iter  30 value 93.290672
final  value 93.290628 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.738123 
iter  10 value 94.057534
iter  20 value 94.049934
iter  30 value 93.079866
iter  40 value 92.809798
final  value 92.809453 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.857184 
iter  10 value 93.844166
iter  20 value 87.354267
iter  30 value 87.053436
iter  40 value 86.920053
iter  50 value 86.596545
iter  60 value 86.595905
final  value 86.592182 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.500151 
iter  10 value 94.059697
iter  20 value 94.055514
iter  30 value 93.911185
iter  40 value 93.448431
iter  50 value 93.290845
iter  60 value 93.202535
iter  70 value 93.010449
final  value 92.986792 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.580344 
iter  10 value 93.844665
iter  20 value 93.816095
iter  30 value 93.325151
iter  40 value 93.258728
iter  50 value 93.258030
iter  60 value 93.257779
iter  70 value 93.257577
final  value 93.257454 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.532235 
iter  10 value 94.060935
iter  20 value 94.029824
iter  30 value 87.669757
iter  40 value 86.849005
iter  50 value 85.086139
iter  60 value 83.401916
iter  70 value 83.162929
iter  70 value 83.162928
final  value 83.162927 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.830351 
iter  10 value 93.845378
iter  20 value 93.841153
iter  30 value 93.488468
iter  40 value 84.878867
iter  50 value 84.520197
iter  60 value 83.872129
iter  70 value 80.993824
iter  80 value 79.603381
iter  90 value 78.843251
iter 100 value 78.203034
final  value 78.203034 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 140.342845 
iter  10 value 117.795446
iter  20 value 115.901146
iter  30 value 108.898249
iter  40 value 105.619217
iter  50 value 105.230406
iter  60 value 104.641185
iter  70 value 103.304518
iter  80 value 102.706035
iter  90 value 102.346467
iter 100 value 101.537206
final  value 101.537206 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 135.884909 
iter  10 value 117.906572
iter  20 value 117.770252
iter  30 value 117.349512
iter  40 value 109.985511
iter  50 value 109.271935
iter  60 value 106.501215
iter  70 value 105.579572
iter  80 value 105.369092
iter  90 value 104.588728
iter 100 value 104.101182
final  value 104.101182 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.545671 
iter  10 value 117.902400
iter  20 value 110.370391
iter  30 value 107.330870
iter  40 value 105.181561
iter  50 value 102.987741
iter  60 value 102.232738
iter  70 value 102.084623
iter  80 value 101.970316
iter  90 value 101.432356
iter 100 value 101.207093
final  value 101.207093 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 136.375757 
iter  10 value 117.869938
iter  20 value 117.611539
iter  30 value 109.038069
iter  40 value 107.835518
iter  50 value 106.965682
iter  60 value 102.452006
iter  70 value 101.085296
iter  80 value 100.894359
iter  90 value 100.882931
iter 100 value 100.824405
final  value 100.824405 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 146.445584 
iter  10 value 117.595779
iter  20 value 110.814535
iter  30 value 107.791123
iter  40 value 107.573512
iter  50 value 103.881894
iter  60 value 102.204223
iter  70 value 101.883235
iter  80 value 101.785552
iter  90 value 101.673047
iter 100 value 101.658993
final  value 101.658993 
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 -- Tue Apr 16 04:11:29 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 
 69.596   2.060  78.439