##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 Patched (2024-04-24 r86482)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.4
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       53.505  1.954  67.054
corr_plot     51.678  1.992  64.682
FSmethod      51.168  1.875  62.185
pred_ensembel 25.036  0.527  26.456
calculateTC    4.879  0.464   6.271
enrichfindP    0.919  0.089  14.017
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-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 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 100.218086 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.584892 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.122582 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.064857 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.685841 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.568214 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.954001 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.408044 
final  value 93.783647 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.885250 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.159612 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.324884 
iter  10 value 94.019051
final  value 94.014407 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.033966 
iter  10 value 92.517180
iter  20 value 91.785743
iter  30 value 91.554867
final  value 91.533272 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.050664 
iter  10 value 93.977500
final  value 93.961942 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.147079 
iter  10 value 93.991508
final  value 93.822754 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.271396 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.726655 
iter  10 value 94.525127
iter  20 value 94.452379
iter  30 value 93.385140
iter  40 value 88.627990
iter  50 value 84.692198
iter  60 value 84.471974
iter  70 value 83.579364
iter  80 value 83.496461
iter  90 value 83.482528
iter 100 value 83.476793
final  value 83.476793 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.372012 
iter  10 value 94.545774
iter  20 value 86.703038
iter  30 value 84.455522
iter  40 value 84.192163
iter  50 value 83.986261
iter  60 value 83.975590
final  value 83.975588 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.640831 
iter  10 value 94.016908
iter  20 value 93.682577
iter  30 value 91.430620
iter  40 value 89.935680
iter  50 value 89.358188
iter  60 value 89.128081
iter  70 value 83.761084
iter  80 value 82.846939
iter  90 value 81.995742
iter 100 value 81.349572
final  value 81.349572 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.754275 
iter  10 value 94.460249
iter  20 value 93.982586
iter  30 value 93.877501
iter  40 value 93.795762
iter  50 value 88.445503
iter  60 value 85.010650
iter  70 value 84.401468
iter  80 value 84.293967
iter  90 value 84.040936
iter 100 value 83.979787
final  value 83.979787 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.049806 
iter  10 value 94.486684
iter  20 value 94.145864
iter  30 value 94.139029
iter  40 value 93.964394
iter  50 value 88.542636
iter  60 value 86.460910
iter  70 value 86.446546
iter  80 value 86.441787
iter  90 value 86.440920
iter 100 value 86.085948
final  value 86.085948 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 131.197727 
iter  10 value 94.300927
iter  20 value 93.131924
iter  30 value 86.573279
iter  40 value 86.064758
iter  50 value 84.771576
iter  60 value 84.291926
iter  70 value 82.399899
iter  80 value 81.504708
iter  90 value 80.729526
iter 100 value 80.185480
final  value 80.185480 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.023924 
iter  10 value 93.573536
iter  20 value 92.683058
iter  30 value 86.045002
iter  40 value 85.438632
iter  50 value 83.529178
iter  60 value 80.707664
iter  70 value 80.162749
iter  80 value 79.932144
iter  90 value 79.636395
iter 100 value 79.434341
final  value 79.434341 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.299628 
iter  10 value 94.483177
iter  20 value 94.182427
iter  30 value 94.029109
iter  40 value 91.422644
iter  50 value 84.537355
iter  60 value 84.072283
iter  70 value 82.456001
iter  80 value 81.779803
iter  90 value 81.572699
iter 100 value 80.960611
final  value 80.960611 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.378486 
iter  10 value 93.730195
iter  20 value 87.493840
iter  30 value 84.519530
iter  40 value 83.586527
iter  50 value 82.035266
iter  60 value 80.987203
iter  70 value 80.881274
iter  80 value 80.782679
iter  90 value 80.664977
iter 100 value 80.615195
final  value 80.615195 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.307767 
iter  10 value 94.720025
iter  20 value 92.940766
iter  30 value 91.872376
iter  40 value 91.367361
iter  50 value 85.159272
iter  60 value 84.031174
iter  70 value 82.294548
iter  80 value 82.148620
iter  90 value 82.081847
iter 100 value 82.023784
final  value 82.023784 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.435809 
iter  10 value 94.536608
iter  20 value 87.302782
iter  30 value 86.484549
iter  40 value 84.647718
iter  50 value 81.455036
iter  60 value 80.418628
iter  70 value 79.853234
iter  80 value 79.583543
iter  90 value 79.413963
iter 100 value 79.374227
final  value 79.374227 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.215612 
iter  10 value 94.506484
iter  20 value 94.295449
iter  30 value 91.886388
iter  40 value 86.485948
iter  50 value 82.274381
iter  60 value 82.057148
iter  70 value 81.089207
iter  80 value 79.853089
iter  90 value 79.488012
iter 100 value 79.328830
final  value 79.328830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.183966 
iter  10 value 94.208476
iter  20 value 93.545603
iter  30 value 86.158271
iter  40 value 85.669956
iter  50 value 84.935611
iter  60 value 83.452077
iter  70 value 82.113856
iter  80 value 82.001495
iter  90 value 81.353694
iter 100 value 80.181909
final  value 80.181909 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.520432 
iter  10 value 94.556678
iter  20 value 88.146791
iter  30 value 85.254236
iter  40 value 84.992706
iter  50 value 84.378118
iter  60 value 82.600528
iter  70 value 81.955943
iter  80 value 81.002308
iter  90 value 80.611118
iter 100 value 80.185373
final  value 80.185373 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.998824 
iter  10 value 94.679501
iter  20 value 89.896547
iter  30 value 85.864399
iter  40 value 84.305055
iter  50 value 82.823220
iter  60 value 81.732215
iter  70 value 80.995632
iter  80 value 80.243817
iter  90 value 79.973602
iter 100 value 79.824884
final  value 79.824884 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.611985 
final  value 94.486866 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.695439 
final  value 94.486049 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.565989 
iter  10 value 94.485872
iter  20 value 94.484229
final  value 94.484219 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.422671 
final  value 94.485655 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.166276 
iter  10 value 94.486360
final  value 94.484366 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.669837 
iter  10 value 93.502422
iter  20 value 93.314632
iter  30 value 93.314217
iter  40 value 93.313018
iter  50 value 93.312275
iter  60 value 93.311793
iter  70 value 91.452160
iter  80 value 88.020228
iter  90 value 85.347675
iter 100 value 83.392590
final  value 83.392590 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 130.302752 
iter  10 value 94.489449
iter  20 value 94.484230
iter  30 value 94.031533
final  value 94.027068 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.889211 
iter  10 value 94.489155
iter  20 value 94.484262
iter  30 value 92.748672
iter  40 value 91.060124
iter  50 value 90.921801
iter  60 value 90.921644
final  value 90.921529 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.483725 
iter  10 value 94.488246
iter  20 value 93.907417
final  value 93.851640 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.172250 
iter  10 value 94.488979
iter  20 value 94.484288
iter  30 value 94.335446
iter  40 value 93.782313
iter  50 value 85.784229
iter  60 value 85.783088
final  value 85.783066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.909132 
iter  10 value 94.493615
iter  20 value 94.478610
iter  30 value 94.048918
iter  40 value 94.047990
final  value 94.047508 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.862808 
iter  10 value 94.492887
iter  20 value 94.481709
iter  30 value 93.857605
iter  40 value 87.063867
iter  50 value 87.009469
iter  60 value 87.009398
iter  60 value 87.009397
iter  60 value 87.009397
final  value 87.009397 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.184118 
iter  10 value 94.271815
iter  20 value 94.265051
iter  30 value 93.838992
final  value 93.763197 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.009432 
iter  10 value 93.879801
iter  20 value 85.984423
iter  30 value 84.007890
iter  40 value 83.988866
iter  50 value 83.978669
iter  60 value 82.575217
iter  70 value 80.907629
iter  80 value 80.885061
iter  90 value 80.139988
iter 100 value 78.703291
final  value 78.703291 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.508210 
iter  10 value 93.831230
iter  20 value 93.826116
iter  30 value 93.180778
iter  40 value 84.410340
iter  50 value 83.759141
iter  60 value 83.583234
iter  70 value 83.545098
iter  80 value 83.425166
iter  90 value 82.235292
iter 100 value 81.890650
final  value 81.890650 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.479812 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 93.395677 
iter  10 value 90.711698
iter  20 value 90.692042
iter  30 value 90.691975
iter  30 value 90.691975
iter  30 value 90.691975
final  value 90.691975 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.870736 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.165759 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.105283 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.736206 
iter  10 value 91.536377
iter  20 value 91.227311
iter  30 value 91.226771
iter  40 value 90.861537
iter  50 value 90.856923
final  value 90.856802 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.532573 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.410332 
iter  10 value 93.747884
iter  20 value 93.697144
iter  20 value 93.697144
iter  20 value 93.697144
final  value 93.697144 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.689186 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.110176 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.721604 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.843643 
iter  10 value 93.188103
iter  20 value 93.090599
iter  20 value 93.090599
iter  20 value 93.090599
final  value 93.090599 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.582226 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.577197 
iter  10 value 92.510597
iter  20 value 92.510181
final  value 92.510177 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.220857 
iter  10 value 85.343395
iter  20 value 82.903244
iter  30 value 82.884585
iter  40 value 82.837208
final  value 82.837200 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.059992 
iter  10 value 94.073657
iter  20 value 93.989285
iter  30 value 93.642478
iter  40 value 93.638532
iter  50 value 88.230685
iter  60 value 85.851626
iter  70 value 84.173539
iter  80 value 83.624722
iter  90 value 83.260470
iter 100 value 83.138627
final  value 83.138627 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.424869 
iter  10 value 93.825894
iter  20 value 87.193940
iter  30 value 83.906995
iter  40 value 83.430107
iter  50 value 83.098220
iter  60 value 82.868197
final  value 82.860405 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.634044 
iter  10 value 94.027078
iter  20 value 87.181962
iter  30 value 84.061907
iter  40 value 83.848580
iter  50 value 83.781478
iter  60 value 83.618708
iter  70 value 83.106740
iter  80 value 83.042486
iter  90 value 83.025385
iter 100 value 82.922629
final  value 82.922629 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.419964 
iter  10 value 93.692022
iter  20 value 89.054064
iter  30 value 84.350533
iter  40 value 82.833052
iter  50 value 81.254191
iter  60 value 80.695072
iter  70 value 80.579246
iter  80 value 80.569969
final  value 80.569897 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.256179 
iter  10 value 94.219449
iter  20 value 94.058498
iter  30 value 90.545189
iter  40 value 84.330909
iter  50 value 82.197588
iter  60 value 82.061609
iter  70 value 81.875487
iter  80 value 81.010637
iter  90 value 80.966238
iter 100 value 80.906639
final  value 80.906639 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.740026 
iter  10 value 93.787171
iter  20 value 86.234467
iter  30 value 85.500377
iter  40 value 85.412179
iter  50 value 83.399965
iter  60 value 82.540771
iter  70 value 81.071102
iter  80 value 80.866724
iter  90 value 80.736526
iter 100 value 80.639908
final  value 80.639908 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.207981 
iter  10 value 94.313006
iter  20 value 93.399130
iter  30 value 92.277538
iter  40 value 91.687868
iter  50 value 88.541657
iter  60 value 83.922692
iter  70 value 82.399036
iter  80 value 82.286071
iter  90 value 81.945150
iter 100 value 80.995656
final  value 80.995656 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.268431 
iter  10 value 93.107405
iter  20 value 88.607384
iter  30 value 81.875856
iter  40 value 80.887894
iter  50 value 80.343888
iter  60 value 80.084517
iter  70 value 80.059034
iter  80 value 80.022668
iter  90 value 79.928816
iter 100 value 79.868676
final  value 79.868676 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.081460 
iter  10 value 94.068204
iter  20 value 87.104747
iter  30 value 84.595866
iter  40 value 84.227292
iter  50 value 83.065472
iter  60 value 81.721330
iter  70 value 81.480963
iter  80 value 81.386876
iter  90 value 81.240961
iter 100 value 81.029098
final  value 81.029098 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.241159 
iter  10 value 93.966890
iter  20 value 87.134897
iter  30 value 84.673051
iter  40 value 83.566889
iter  50 value 81.692815
iter  60 value 81.469414
iter  70 value 81.144047
iter  80 value 80.233214
iter  90 value 79.877535
iter 100 value 79.671934
final  value 79.671934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 132.854628 
iter  10 value 95.435194
iter  20 value 93.806038
iter  30 value 85.447496
iter  40 value 84.063690
iter  50 value 83.767903
iter  60 value 82.218405
iter  70 value 80.983469
iter  80 value 80.253065
iter  90 value 80.112251
iter 100 value 80.017234
final  value 80.017234 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.315762 
iter  10 value 94.347613
iter  20 value 88.416345
iter  30 value 87.072029
iter  40 value 86.474540
iter  50 value 86.200806
iter  60 value 84.481887
iter  70 value 82.486553
iter  80 value 81.377190
iter  90 value 80.342920
iter 100 value 79.994008
final  value 79.994008 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.543198 
iter  10 value 94.072562
iter  20 value 86.198624
iter  30 value 85.291084
iter  40 value 82.331802
iter  50 value 80.392708
iter  60 value 79.817151
iter  70 value 79.681017
iter  80 value 79.412977
iter  90 value 79.379120
iter 100 value 79.354385
final  value 79.354385 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.347954 
iter  10 value 88.452048
iter  20 value 84.371785
iter  30 value 83.919172
iter  40 value 82.763277
iter  50 value 81.723617
iter  60 value 80.805728
iter  70 value 80.465376
iter  80 value 80.027930
iter  90 value 79.931396
iter 100 value 79.889616
final  value 79.889616 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.798395 
iter  10 value 94.655087
iter  20 value 93.977382
iter  30 value 93.074899
iter  40 value 89.423091
iter  50 value 87.319257
iter  60 value 86.723142
iter  70 value 82.306136
iter  80 value 80.011627
iter  90 value 79.661125
iter 100 value 79.395574
final  value 79.395574 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.387280 
final  value 94.004423 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.220321 
final  value 94.054566 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.404511 
final  value 94.054532 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.689756 
iter  10 value 93.921647
iter  20 value 93.916954
iter  30 value 93.699459
iter  40 value 86.919217
iter  50 value 86.273249
iter  60 value 86.272846
iter  70 value 86.272339
iter  80 value 85.891238
iter  90 value 82.635061
iter 100 value 81.568429
final  value 81.568429 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 112.780340 
iter  10 value 94.055182
final  value 94.053163 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.041607 
iter  10 value 94.057706
iter  20 value 94.052924
iter  30 value 86.120307
iter  40 value 86.002885
iter  50 value 85.811918
iter  60 value 84.151829
iter  70 value 82.083929
iter  80 value 81.998080
iter  90 value 81.710575
iter 100 value 81.698344
final  value 81.698344 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.724005 
iter  10 value 94.056974
iter  20 value 94.013769
final  value 93.915852 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.398526 
iter  10 value 94.058854
iter  20 value 94.044385
iter  30 value 84.910452
iter  40 value 82.518620
iter  50 value 79.936506
iter  60 value 79.317220
iter  70 value 79.234698
final  value 79.234121 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.447150 
iter  10 value 94.057741
iter  20 value 94.046928
iter  30 value 88.726660
iter  40 value 88.250644
iter  50 value 83.321436
iter  60 value 83.319725
iter  70 value 83.319513
iter  80 value 83.284835
final  value 83.284797 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.961473 
iter  10 value 90.214807
iter  20 value 90.130508
final  value 90.129388 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.727557 
iter  10 value 93.875598
iter  20 value 93.660689
iter  30 value 93.457376
iter  40 value 93.074051
iter  50 value 91.561579
iter  60 value 83.443364
iter  70 value 80.471668
iter  80 value 79.945221
iter  90 value 79.708882
final  value 79.708786 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.483835 
iter  10 value 94.062172
iter  20 value 93.527165
iter  30 value 88.001220
iter  40 value 84.915432
iter  50 value 83.917745
iter  60 value 83.914937
iter  70 value 83.357192
final  value 83.357184 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.698715 
iter  10 value 93.924078
iter  20 value 93.916456
iter  30 value 92.078845
iter  40 value 91.223872
iter  50 value 90.620558
final  value 90.162300 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.676716 
iter  10 value 93.188903
iter  20 value 93.185905
iter  30 value 89.617342
iter  40 value 88.337856
iter  50 value 87.899053
iter  60 value 87.859491
iter  70 value 86.992122
iter  80 value 86.877205
iter  90 value 86.872560
iter 100 value 86.872049
final  value 86.872049 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.753340 
iter  10 value 93.924254
iter  20 value 93.701089
iter  30 value 87.119641
iter  40 value 86.456320
iter  50 value 86.447700
iter  60 value 85.238151
iter  70 value 84.471176
final  value 84.470797 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.088939 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.496857 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.232811 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.164169 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.132960 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.063573 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.306015 
iter  10 value 93.017564
iter  20 value 85.158647
iter  30 value 84.876847
iter  40 value 84.717959
iter  50 value 84.578266
iter  60 value 84.575761
final  value 84.575742 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.666749 
iter  10 value 94.469182
final  value 94.423530 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.265591 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.518345 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.270163 
iter  10 value 88.268513
iter  20 value 87.242755
final  value 87.242754 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.226179 
iter  10 value 89.080657
iter  20 value 86.233078
iter  30 value 86.186813
iter  40 value 86.186670
final  value 86.186667 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.443120 
final  value 94.325945 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.244600 
iter  10 value 94.326062
final  value 94.325945 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.830102 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.336169 
iter  10 value 94.523388
iter  20 value 94.486841
iter  30 value 92.200985
iter  40 value 91.361489
iter  50 value 88.128703
iter  60 value 86.838339
iter  70 value 84.991558
iter  80 value 83.776110
iter  90 value 83.095583
iter 100 value 82.337402
final  value 82.337402 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.679428 
iter  10 value 94.487643
iter  20 value 94.415543
iter  30 value 92.034279
iter  40 value 87.554691
iter  50 value 84.357847
iter  60 value 83.638363
iter  70 value 83.474432
iter  80 value 83.317948
iter  90 value 82.901412
iter 100 value 82.291839
final  value 82.291839 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.734195 
iter  10 value 94.487199
iter  20 value 92.903499
iter  30 value 89.490433
iter  40 value 88.838325
iter  50 value 85.854561
iter  60 value 84.688613
iter  70 value 84.202394
iter  80 value 83.813494
iter  90 value 83.433891
final  value 83.431341 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.229115 
iter  10 value 94.481776
iter  20 value 94.217936
iter  30 value 94.191501
iter  40 value 94.183541
iter  50 value 94.104181
iter  60 value 88.367715
iter  70 value 87.479049
iter  80 value 87.081675
iter  90 value 86.245895
iter 100 value 85.746574
final  value 85.746574 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.873182 
iter  10 value 94.505273
iter  20 value 94.251899
iter  30 value 94.081304
iter  40 value 89.099157
iter  50 value 85.334753
iter  60 value 85.188736
iter  70 value 84.869536
iter  80 value 84.020720
iter  90 value 83.534821
iter 100 value 83.350508
final  value 83.350508 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 123.711703 
iter  10 value 94.509149
iter  20 value 90.770705
iter  30 value 89.720567
iter  40 value 89.596177
iter  50 value 86.469891
iter  60 value 83.284340
iter  70 value 82.977706
iter  80 value 82.508473
iter  90 value 82.037958
iter 100 value 81.671463
final  value 81.671463 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.120685 
iter  10 value 94.487541
iter  20 value 94.343475
iter  30 value 90.683629
iter  40 value 90.533050
iter  50 value 87.871479
iter  60 value 86.123745
iter  70 value 85.718289
iter  80 value 84.944653
iter  90 value 84.295478
iter 100 value 82.254882
final  value 82.254882 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.328340 
iter  10 value 92.801706
iter  20 value 87.987634
iter  30 value 86.109477
iter  40 value 85.623242
iter  50 value 84.789241
iter  60 value 81.782629
iter  70 value 81.294810
iter  80 value 81.109191
iter  90 value 80.947350
iter 100 value 80.910038
final  value 80.910038 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.202320 
iter  10 value 94.565294
iter  20 value 93.873281
iter  30 value 91.208230
iter  40 value 87.926616
iter  50 value 85.255872
iter  60 value 84.329991
iter  70 value 83.773583
iter  80 value 81.791908
iter  90 value 81.626370
iter 100 value 81.603907
final  value 81.603907 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.665333 
iter  10 value 94.965530
iter  20 value 91.918390
iter  30 value 90.841717
iter  40 value 89.616912
iter  50 value 85.855243
iter  60 value 84.878302
iter  70 value 83.893633
iter  80 value 83.827196
iter  90 value 83.646397
iter 100 value 83.313405
final  value 83.313405 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.294420 
iter  10 value 94.587973
iter  20 value 86.810983
iter  30 value 85.529941
iter  40 value 84.138192
iter  50 value 83.338017
iter  60 value 82.944739
iter  70 value 82.689745
iter  80 value 81.964852
iter  90 value 81.483402
iter 100 value 81.250510
final  value 81.250510 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 153.663107 
iter  10 value 95.241532
iter  20 value 91.695728
iter  30 value 90.064650
iter  40 value 88.339972
iter  50 value 86.039752
iter  60 value 83.969985
iter  70 value 83.026161
iter  80 value 82.658363
iter  90 value 82.223101
iter 100 value 81.694743
final  value 81.694743 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.566435 
iter  10 value 94.499780
iter  20 value 92.805264
iter  30 value 87.600147
iter  40 value 86.492697
iter  50 value 85.345867
iter  60 value 83.601595
iter  70 value 82.332380
iter  80 value 81.864737
iter  90 value 81.619409
iter 100 value 81.519527
final  value 81.519527 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.206091 
iter  10 value 94.616656
iter  20 value 94.360359
iter  30 value 86.570975
iter  40 value 85.184455
iter  50 value 81.984205
iter  60 value 81.420395
iter  70 value 81.142015
iter  80 value 80.962251
iter  90 value 80.929055
iter 100 value 80.821506
final  value 80.821506 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.271896 
iter  10 value 96.841213
iter  20 value 93.121712
iter  30 value 90.823389
iter  40 value 85.747704
iter  50 value 84.379962
iter  60 value 83.023109
iter  70 value 82.052298
iter  80 value 81.382247
iter  90 value 81.277107
iter 100 value 81.058227
final  value 81.058227 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.272890 
final  value 94.485886 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.027791 
final  value 94.485898 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.140289 
iter  10 value 94.486113
iter  20 value 94.173623
iter  30 value 92.944583
iter  40 value 92.919499
iter  50 value 91.119189
iter  60 value 90.495710
iter  70 value 90.405739
iter  80 value 90.381789
iter  90 value 90.370827
iter 100 value 89.894237
final  value 89.894237 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.077580 
final  value 94.485763 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.351231 
iter  10 value 94.469867
iter  20 value 94.468134
iter  30 value 94.450431
iter  40 value 87.155272
iter  50 value 87.106937
iter  60 value 87.102096
iter  70 value 87.100103
iter  70 value 87.100102
iter  70 value 87.100101
final  value 87.100101 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.886672 
iter  10 value 94.489533
iter  20 value 94.220547
iter  30 value 84.949809
iter  40 value 84.884786
iter  50 value 84.884344
iter  60 value 84.797241
iter  70 value 84.522090
iter  80 value 84.519548
iter  90 value 84.519090
iter 100 value 84.518725
final  value 84.518725 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.438989 
iter  10 value 94.471418
iter  20 value 94.430153
iter  30 value 86.698515
iter  40 value 86.401575
iter  50 value 86.401447
iter  60 value 86.389489
final  value 86.389488 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.634195 
iter  10 value 94.064485
iter  20 value 90.846901
iter  30 value 89.375012
iter  40 value 89.344054
iter  50 value 88.524696
final  value 88.523834 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.300154 
iter  10 value 94.489131
iter  20 value 94.484220
iter  20 value 94.484220
iter  20 value 94.484220
final  value 94.484220 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.562544 
iter  10 value 94.488554
iter  20 value 93.929577
iter  30 value 84.463829
iter  40 value 84.033132
iter  50 value 84.027604
final  value 84.027602 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.135072 
iter  10 value 94.491328
iter  20 value 94.323669
iter  30 value 87.931244
iter  40 value 87.885708
iter  50 value 87.051254
iter  60 value 84.049636
iter  70 value 84.024678
iter  80 value 84.022616
iter  90 value 83.984594
iter 100 value 83.976883
final  value 83.976883 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.983676 
iter  10 value 94.489770
iter  20 value 94.474469
iter  30 value 94.466946
iter  40 value 94.241946
iter  50 value 84.815749
iter  60 value 84.763033
iter  70 value 83.467529
iter  80 value 83.077553
iter  90 value 82.587482
iter 100 value 82.501278
final  value 82.501278 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.283192 
iter  10 value 93.743618
iter  20 value 92.888627
iter  30 value 92.869205
final  value 92.869082 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.510229 
iter  10 value 94.464049
iter  20 value 94.053939
iter  30 value 93.383670
iter  40 value 87.794965
iter  50 value 81.586303
iter  60 value 81.405301
iter  70 value 80.906466
iter  80 value 80.455180
iter  90 value 80.377204
iter 100 value 80.334562
final  value 80.334562 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 93.235117 
iter  10 value 91.183995
iter  20 value 90.387707
iter  30 value 90.256832
iter  40 value 90.254918
iter  50 value 90.250970
iter  60 value 89.886903
final  value 89.853908 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.971422 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.152284 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.255290 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.048210 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.574292 
iter  10 value 84.000886
iter  20 value 83.291746
final  value 83.289849 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.538937 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.335023 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.212325 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.458194 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.254752 
iter  10 value 93.701645
iter  20 value 93.674331
final  value 93.674286 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.247207 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.325986 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.521976 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.470166 
iter  10 value 93.016303
final  value 93.016092 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.823302 
iter  10 value 94.246785
iter  20 value 94.089294
final  value 94.089150 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.242570 
iter  10 value 94.604599
iter  20 value 94.467067
iter  30 value 93.281315
iter  40 value 93.221303
iter  50 value 93.208318
iter  60 value 88.295499
iter  70 value 87.610687
iter  80 value 87.404689
iter  90 value 87.231970
iter 100 value 86.976525
final  value 86.976525 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.544510 
iter  10 value 94.488798
iter  20 value 90.124898
iter  30 value 85.470319
iter  40 value 85.265635
iter  50 value 83.288343
iter  60 value 82.877789
iter  70 value 82.870095
iter  80 value 82.490962
iter  90 value 82.410881
final  value 82.410761 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.715100 
iter  10 value 94.489096
iter  20 value 91.787299
iter  30 value 86.878776
iter  40 value 84.031616
iter  50 value 83.791951
iter  60 value 83.597178
iter  70 value 83.302555
iter  80 value 83.186150
final  value 83.186123 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.225419 
iter  10 value 94.704342
iter  20 value 94.443984
iter  30 value 93.565606
iter  40 value 93.283631
iter  50 value 91.663224
iter  60 value 84.371249
iter  70 value 82.539132
iter  80 value 82.001751
iter  90 value 81.601632
iter 100 value 81.135104
final  value 81.135104 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.063586 
iter  10 value 94.492158
iter  20 value 94.429007
iter  30 value 93.662844
iter  40 value 84.340284
iter  50 value 83.432373
iter  60 value 83.096864
iter  70 value 82.873783
iter  80 value 82.855023
final  value 82.853968 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.448576 
iter  10 value 94.767943
iter  20 value 94.431991
iter  30 value 91.876726
iter  40 value 87.255069
iter  50 value 86.846169
iter  60 value 86.361329
iter  70 value 86.271883
iter  80 value 86.092432
iter  90 value 84.568350
iter 100 value 82.440551
final  value 82.440551 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.968476 
iter  10 value 94.439810
iter  20 value 93.362475
iter  30 value 92.131902
iter  40 value 86.865257
iter  50 value 82.069393
iter  60 value 80.981588
iter  70 value 80.245339
iter  80 value 80.065485
iter  90 value 79.965715
iter 100 value 79.889136
final  value 79.889136 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.156221 
iter  10 value 87.674453
iter  20 value 83.889366
iter  30 value 83.293744
iter  40 value 82.820588
iter  50 value 82.594138
iter  60 value 82.483271
iter  70 value 82.083602
iter  80 value 80.986900
iter  90 value 80.465725
iter 100 value 80.379992
final  value 80.379992 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.929130 
iter  10 value 94.698223
iter  20 value 88.376422
iter  30 value 87.671370
iter  40 value 87.301008
iter  50 value 84.688369
iter  60 value 82.937303
iter  70 value 81.369333
iter  80 value 81.286990
iter  90 value 81.162228
iter 100 value 81.128878
final  value 81.128878 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.274878 
iter  10 value 94.317090
iter  20 value 93.755166
iter  30 value 93.083307
iter  40 value 86.466591
iter  50 value 83.647294
iter  60 value 83.391999
iter  70 value 82.383698
iter  80 value 80.898693
iter  90 value 80.333054
iter 100 value 80.098992
final  value 80.098992 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.889582 
iter  10 value 94.655111
iter  20 value 93.221320
iter  30 value 90.952828
iter  40 value 84.021938
iter  50 value 83.012743
iter  60 value 82.905209
iter  70 value 82.586830
iter  80 value 82.196097
iter  90 value 81.265151
iter 100 value 80.991176
final  value 80.991176 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.418414 
iter  10 value 94.506235
iter  20 value 92.988885
iter  30 value 87.332891
iter  40 value 85.438375
iter  50 value 82.038471
iter  60 value 80.238992
iter  70 value 79.756507
iter  80 value 79.257786
iter  90 value 79.165539
iter 100 value 79.088460
final  value 79.088460 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.069242 
iter  10 value 94.999697
iter  20 value 94.419249
iter  30 value 89.494273
iter  40 value 83.787242
iter  50 value 82.468190
iter  60 value 81.602557
iter  70 value 81.169259
iter  80 value 79.984695
iter  90 value 79.532545
iter 100 value 79.329462
final  value 79.329462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 144.156355 
iter  10 value 93.793729
iter  20 value 93.303243
iter  30 value 92.894334
iter  40 value 90.933909
iter  50 value 83.201871
iter  60 value 81.441440
iter  70 value 80.701017
iter  80 value 80.248139
iter  90 value 79.972760
iter 100 value 79.682138
final  value 79.682138 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.649107 
iter  10 value 94.576964
iter  20 value 94.140590
iter  30 value 90.853278
iter  40 value 86.500636
iter  50 value 83.603562
iter  60 value 81.496888
iter  70 value 80.716101
iter  80 value 79.956314
iter  90 value 79.630357
iter 100 value 79.480571
final  value 79.480571 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.300061 
final  value 94.485507 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.386380 
final  value 94.486023 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.630965 
final  value 94.485800 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.715147 
final  value 94.485763 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.540125 
final  value 94.485907 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.754359 
iter  10 value 94.471788
iter  20 value 94.467446
final  value 94.467406 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.851899 
iter  10 value 94.488370
iter  20 value 93.598512
iter  30 value 93.035703
iter  40 value 93.024984
iter  50 value 93.024087
iter  60 value 92.969896
iter  70 value 92.738512
iter  80 value 92.737920
iter  90 value 92.736950
iter 100 value 92.736708
final  value 92.736708 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.982239 
iter  10 value 94.489018
iter  20 value 92.204375
iter  30 value 90.522898
iter  40 value 90.497455
iter  50 value 90.497120
iter  60 value 90.496628
iter  70 value 90.496455
iter  80 value 85.706462
iter  90 value 83.014192
iter 100 value 81.886058
final  value 81.886058 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.888949 
iter  10 value 94.489114
iter  20 value 94.479438
iter  30 value 87.819822
iter  40 value 86.964307
iter  50 value 85.770233
iter  60 value 84.710764
iter  70 value 83.981655
iter  80 value 83.931982
iter  90 value 82.307623
iter 100 value 81.201373
final  value 81.201373 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.996495 
iter  10 value 94.472170
iter  20 value 94.468267
iter  30 value 94.467409
final  value 94.467405 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.582998 
final  value 94.492809 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.493436 
iter  10 value 94.492381
iter  20 value 94.078647
iter  30 value 89.502898
iter  40 value 89.331673
iter  50 value 88.305963
iter  60 value 88.303615
iter  60 value 88.303615
final  value 88.303615 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.328052 
iter  10 value 94.492021
iter  20 value 94.286296
iter  30 value 91.768896
iter  40 value 91.466534
iter  50 value 91.444066
iter  60 value 88.656034
iter  70 value 86.159627
iter  80 value 84.308172
iter  90 value 83.284213
iter 100 value 83.275814
final  value 83.275814 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.438041 
iter  10 value 94.476191
iter  20 value 93.201618
iter  30 value 92.957037
iter  40 value 92.956524
iter  50 value 92.956205
iter  60 value 92.923861
iter  70 value 84.909788
iter  80 value 84.894486
iter  90 value 84.281641
iter 100 value 84.246574
final  value 84.246574 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.655082 
iter  10 value 87.525912
iter  20 value 84.919321
iter  30 value 84.587638
iter  40 value 84.584251
iter  50 value 82.579889
iter  60 value 81.942570
iter  70 value 81.853014
iter  80 value 81.762834
iter  90 value 81.762322
final  value 81.762278 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.387271 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.471463 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.684791 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.041618 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.280364 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.134563 
iter  10 value 93.907062
final  value 93.904720 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.958525 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.862747 
iter  10 value 93.225585
iter  20 value 93.012279
iter  30 value 92.956644
final  value 92.956640 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.904623 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.520530 
final  value 94.052902 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.555047 
iter  10 value 93.937271
iter  20 value 93.302565
iter  30 value 93.300441
final  value 93.300433 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.922024 
iter  10 value 93.690084
final  value 93.672973 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.290006 
iter  10 value 85.046970
iter  20 value 84.591420
iter  30 value 84.583113
final  value 84.577375 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.943585 
iter  10 value 92.746246
iter  20 value 92.644560
final  value 92.644454 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.953775 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 130.111675 
iter  10 value 93.984883
iter  20 value 86.966853
iter  30 value 84.680423
iter  40 value 83.858893
iter  50 value 83.069372
iter  60 value 82.915233
iter  70 value 82.850729
final  value 82.850544 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.646282 
iter  10 value 93.962377
iter  20 value 92.490340
iter  30 value 92.185096
iter  40 value 92.107572
iter  50 value 92.075598
iter  60 value 92.063920
iter  70 value 92.017078
iter  80 value 91.969244
iter  90 value 84.568700
iter 100 value 84.389969
final  value 84.389969 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.288437 
iter  10 value 93.922991
iter  20 value 86.493072
iter  30 value 86.072166
iter  40 value 85.264586
iter  50 value 84.272617
iter  60 value 83.852608
iter  70 value 83.850496
final  value 83.850427 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.715832 
iter  10 value 94.100496
iter  20 value 93.671552
iter  30 value 92.704745
iter  40 value 85.863595
iter  50 value 85.657048
iter  60 value 85.353205
iter  70 value 84.621931
iter  80 value 83.618036
iter  90 value 83.404515
iter 100 value 83.402053
final  value 83.402053 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.240962 
iter  10 value 94.044337
iter  20 value 86.405697
iter  30 value 84.775895
iter  40 value 83.726675
iter  50 value 83.057132
iter  60 value 82.783497
iter  70 value 82.741749
iter  80 value 82.718517
iter  90 value 82.652080
iter 100 value 82.620307
final  value 82.620307 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.888488 
iter  10 value 94.665396
iter  20 value 94.072181
iter  30 value 94.060733
iter  40 value 90.522011
iter  50 value 86.503492
iter  60 value 85.381790
iter  70 value 84.426903
iter  80 value 84.084532
iter  90 value 83.981192
iter 100 value 83.866376
final  value 83.866376 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.915982 
iter  10 value 94.175510
iter  20 value 94.047757
iter  30 value 87.201505
iter  40 value 86.000179
iter  50 value 84.665234
iter  60 value 84.451330
iter  70 value 82.804108
iter  80 value 81.919507
iter  90 value 80.510922
iter 100 value 80.171728
final  value 80.171728 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.188611 
iter  10 value 94.141885
iter  20 value 93.654262
iter  30 value 87.140282
iter  40 value 86.588189
iter  50 value 85.557519
iter  60 value 84.555976
iter  70 value 83.582879
iter  80 value 83.373679
iter  90 value 83.320621
iter 100 value 82.060392
final  value 82.060392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.513575 
iter  10 value 94.791805
iter  20 value 93.451838
iter  30 value 87.947286
iter  40 value 86.079199
iter  50 value 84.782003
iter  60 value 84.376126
iter  70 value 83.608391
iter  80 value 83.390665
iter  90 value 83.348345
iter 100 value 83.025630
final  value 83.025630 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.500619 
iter  10 value 87.970312
iter  20 value 86.787952
iter  30 value 85.468724
iter  40 value 84.667649
iter  50 value 84.227436
iter  60 value 82.980544
iter  70 value 81.241145
iter  80 value 80.427610
iter  90 value 80.227107
iter 100 value 80.109484
final  value 80.109484 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.359664 
iter  10 value 94.134807
iter  20 value 86.019294
iter  30 value 85.279791
iter  40 value 84.165676
iter  50 value 82.969300
iter  60 value 82.627098
iter  70 value 82.045699
iter  80 value 80.715506
iter  90 value 80.354105
iter 100 value 80.314753
final  value 80.314753 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.965938 
iter  10 value 94.926679
iter  20 value 93.524005
iter  30 value 92.489539
iter  40 value 87.581855
iter  50 value 83.072590
iter  60 value 81.872955
iter  70 value 81.474592
iter  80 value 80.983631
iter  90 value 80.379769
iter 100 value 80.222841
final  value 80.222841 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.988392 
iter  10 value 92.793297
iter  20 value 91.997677
iter  30 value 91.827843
iter  40 value 91.699614
iter  50 value 91.573647
iter  60 value 88.557004
iter  70 value 85.126867
iter  80 value 83.733335
iter  90 value 83.208845
iter 100 value 83.098828
final  value 83.098828 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.276445 
iter  10 value 93.945852
iter  20 value 86.509067
iter  30 value 84.334661
iter  40 value 82.482119
iter  50 value 81.211618
iter  60 value 80.493627
iter  70 value 80.016156
iter  80 value 79.811394
iter  90 value 79.691132
iter 100 value 79.626281
final  value 79.626281 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.619480 
iter  10 value 94.818229
iter  20 value 94.427652
iter  30 value 91.799580
iter  40 value 88.193200
iter  50 value 84.035249
iter  60 value 81.637271
iter  70 value 81.166790
iter  80 value 80.474559
iter  90 value 80.262159
iter 100 value 80.228885
final  value 80.228885 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.010071 
iter  10 value 94.054813
iter  20 value 92.803202
iter  30 value 91.947865
iter  40 value 91.944534
iter  50 value 91.944367
iter  50 value 91.944367
iter  50 value 91.944367
final  value 91.944367 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.687887 
final  value 94.054658 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.241729 
iter  10 value 93.906399
iter  20 value 93.195563
iter  30 value 91.946222
iter  40 value 91.944471
iter  50 value 85.300784
iter  60 value 82.969721
iter  70 value 82.724601
iter  80 value 82.623444
final  value 82.622048 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.014256 
final  value 94.054239 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.082307 
iter  10 value 94.054372
iter  20 value 94.052968
final  value 94.052914 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.667829 
iter  10 value 94.057730
iter  20 value 93.933968
iter  30 value 93.500142
final  value 93.492073 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.019300 
iter  10 value 88.125082
iter  20 value 83.845914
iter  30 value 83.812499
final  value 83.812252 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.653988 
iter  10 value 94.058174
iter  20 value 94.052982
iter  30 value 92.671433
iter  40 value 84.298251
iter  50 value 82.297442
iter  60 value 80.646892
iter  70 value 79.081649
iter  80 value 78.552946
iter  90 value 78.533495
iter 100 value 78.525263
final  value 78.525263 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.959826 
iter  10 value 94.055943
iter  20 value 92.825983
iter  30 value 91.610753
iter  40 value 91.540591
iter  50 value 91.493476
final  value 91.493459 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.853811 
iter  10 value 94.057787
iter  20 value 93.966552
iter  30 value 93.587448
iter  40 value 93.582800
final  value 93.582710 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.068295 
iter  10 value 93.682003
iter  20 value 93.676768
iter  30 value 93.562479
iter  40 value 93.561804
iter  50 value 87.415403
iter  60 value 86.497064
iter  70 value 86.357404
iter  80 value 86.352788
iter  90 value 86.263085
iter  90 value 86.263085
iter  90 value 86.263084
final  value 86.263084 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.316802 
iter  10 value 93.577865
iter  20 value 93.572856
iter  30 value 93.571066
iter  40 value 86.649001
iter  50 value 85.697543
iter  60 value 85.582205
iter  70 value 84.498445
final  value 84.442625 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.377651 
iter  10 value 94.060395
iter  20 value 94.028971
iter  30 value 93.673302
iter  30 value 93.673302
iter  30 value 93.673302
final  value 93.673302 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.349506 
iter  10 value 94.061856
iter  20 value 93.602757
iter  30 value 93.536256
iter  40 value 91.557116
iter  50 value 83.721495
iter  60 value 82.436400
iter  70 value 82.329674
iter  80 value 82.323592
iter  90 value 82.319963
final  value 82.258237 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.027773 
iter  10 value 93.681533
iter  20 value 93.677941
iter  30 value 93.574652
iter  40 value 93.559258
iter  50 value 93.559108
final  value 93.558997 
converged
Fitting Repeat 1 

# weights:  305
initial  value 153.999022 
iter  10 value 117.764022
iter  20 value 117.759741
final  value 117.759024 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.833133 
iter  10 value 117.895313
iter  20 value 117.890604
iter  30 value 115.387940
iter  40 value 107.010215
iter  50 value 107.004155
final  value 107.004148 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.678648 
iter  10 value 117.894156
iter  20 value 117.648230
final  value 117.549863 
converged
Fitting Repeat 4 

# weights:  305
initial  value 123.780736 
iter  10 value 117.894896
iter  20 value 117.890307
iter  30 value 117.682482
iter  40 value 107.004994
iter  50 value 107.003609
iter  60 value 106.838811
iter  70 value 106.655627
iter  80 value 106.647799
iter  90 value 106.647676
iter 100 value 105.019331
final  value 105.019331 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.446092 
iter  10 value 117.732823
iter  20 value 117.730806
iter  30 value 117.595069
iter  40 value 117.594756
iter  50 value 117.500072
final  value 117.500066 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Thu May  2 05:59:01 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 
 72.234   2.265  89.127