##############################################################################
##############################################################################
###
### 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 4.3.2 Patched (2023-11-01 r85457)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.3 (clang-1403.0.22.14.1)
    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       35.914  1.963  38.427
FSmethod      35.134  1.970  37.786
corr_plot     35.034  1.939  37.406
pred_ensembel 14.158  0.616  10.794
enrichfindP    0.498  0.069   8.557
* 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 4.3.2 Patched (2023-11-01 r85457) -- "Eye Holes"
Copyright (C) 2023 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 101.953225 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.168879 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.369756 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.829594 
iter  10 value 94.275371
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.203484 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.310289 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.451812 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.376902 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.761578 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.488279 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.891767 
iter  10 value 94.275367
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.896957 
iter  10 value 94.483888
iter  20 value 94.300238
iter  30 value 94.249355
final  value 94.247835 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.432448 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.888434 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.128788 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.905082 
iter  10 value 94.489425
iter  20 value 94.387029
iter  30 value 93.838350
iter  40 value 91.808451
iter  50 value 91.041276
iter  60 value 91.028790
final  value 91.028436 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.405332 
iter  10 value 94.014822
iter  20 value 87.155751
iter  30 value 86.059131
iter  40 value 84.999091
iter  50 value 81.125022
iter  60 value 80.632701
iter  70 value 80.454261
iter  80 value 80.423634
iter  80 value 80.423634
final  value 80.423634 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.369663 
iter  10 value 94.266901
iter  20 value 86.356027
iter  30 value 85.901876
iter  40 value 84.780803
iter  50 value 83.098026
iter  60 value 82.940298
iter  70 value 82.826999
final  value 82.823642 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.145738 
iter  10 value 94.452355
iter  20 value 93.892777
iter  30 value 84.759929
iter  40 value 82.622382
iter  50 value 82.603726
iter  60 value 82.585652
iter  70 value 82.314748
iter  80 value 82.284124
final  value 82.283126 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.161228 
iter  10 value 94.476993
iter  20 value 87.572606
iter  30 value 86.468337
iter  40 value 86.179352
iter  50 value 84.049186
iter  60 value 82.970550
iter  70 value 82.824360
final  value 82.823642 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.217545 
iter  10 value 94.353876
iter  20 value 90.080006
iter  30 value 88.209349
iter  40 value 87.518924
iter  50 value 83.908460
iter  60 value 82.559407
iter  70 value 82.316447
iter  80 value 81.823745
iter  90 value 81.291426
iter 100 value 80.568174
final  value 80.568174 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.598645 
iter  10 value 94.913180
iter  20 value 94.694291
iter  30 value 89.859171
iter  40 value 86.907461
iter  50 value 83.457096
iter  60 value 83.202017
iter  70 value 82.690878
iter  80 value 82.272859
iter  90 value 80.274694
iter 100 value 79.634447
final  value 79.634447 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.314303 
iter  10 value 94.279140
iter  20 value 88.572462
iter  30 value 83.505589
iter  40 value 83.089681
iter  50 value 82.749285
iter  60 value 82.644851
iter  70 value 82.478356
iter  80 value 81.856817
iter  90 value 80.643598
iter 100 value 79.785705
final  value 79.785705 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.224487 
iter  10 value 94.660561
iter  20 value 87.172212
iter  30 value 86.368806
iter  40 value 86.124945
iter  50 value 85.742885
iter  60 value 84.651656
iter  70 value 82.745273
iter  80 value 81.822576
iter  90 value 80.439150
iter 100 value 79.821674
final  value 79.821674 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.572840 
iter  10 value 94.384301
iter  20 value 86.585071
iter  30 value 82.121913
iter  40 value 81.479301
iter  50 value 80.929335
iter  60 value 80.670195
iter  70 value 80.223824
iter  80 value 79.608188
iter  90 value 78.850095
iter 100 value 78.664579
final  value 78.664579 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.642160 
iter  10 value 94.087043
iter  20 value 86.585321
iter  30 value 83.091241
iter  40 value 82.376721
iter  50 value 81.380111
iter  60 value 81.036683
iter  70 value 79.818905
iter  80 value 79.223950
iter  90 value 78.986722
iter 100 value 78.954170
final  value 78.954170 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.525046 
iter  10 value 94.504801
iter  20 value 94.204277
iter  30 value 87.336585
iter  40 value 85.907201
iter  50 value 84.614665
iter  60 value 82.853468
iter  70 value 82.609114
iter  80 value 82.496723
iter  90 value 82.354207
iter 100 value 82.070661
final  value 82.070661 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.756261 
iter  10 value 94.787697
iter  20 value 94.343963
iter  30 value 93.227686
iter  40 value 86.301638
iter  50 value 82.240747
iter  60 value 81.151223
iter  70 value 80.811221
iter  80 value 80.101777
iter  90 value 79.358539
iter 100 value 78.856534
final  value 78.856534 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.959755 
iter  10 value 94.937932
iter  20 value 94.450500
iter  30 value 90.456047
iter  40 value 87.097223
iter  50 value 84.246943
iter  60 value 82.806291
iter  70 value 81.722458
iter  80 value 80.243990
iter  90 value 79.717654
iter 100 value 79.458081
final  value 79.458081 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.644729 
iter  10 value 100.000749
iter  20 value 91.520308
iter  30 value 86.592994
iter  40 value 82.530538
iter  50 value 80.554380
iter  60 value 79.896070
iter  70 value 79.775936
iter  80 value 79.213823
iter  90 value 78.830245
iter 100 value 78.718732
final  value 78.718732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.896573 
iter  10 value 93.425281
iter  20 value 93.424938
iter  30 value 93.424507
iter  40 value 87.929138
iter  50 value 86.529434
iter  60 value 86.525595
final  value 86.525591 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.235694 
final  value 94.485904 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.574667 
iter  10 value 94.486082
iter  20 value 94.484232
final  value 94.484213 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.041982 
final  value 94.485580 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.679702 
final  value 94.485797 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.356335 
iter  10 value 94.280524
iter  20 value 94.276718
iter  30 value 94.255323
iter  40 value 94.224080
iter  50 value 94.223880
final  value 94.223834 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.544617 
iter  10 value 94.280542
iter  20 value 94.275737
final  value 94.275523 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.229181 
iter  10 value 94.280534
iter  20 value 94.256568
iter  30 value 88.746396
iter  40 value 86.862447
iter  50 value 86.253172
iter  60 value 86.159889
iter  70 value 85.345610
final  value 85.316572 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.837881 
iter  10 value 94.280405
iter  20 value 94.276094
iter  30 value 93.883714
iter  40 value 85.258936
final  value 85.258589 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.978929 
iter  10 value 94.488661
iter  20 value 94.241268
iter  30 value 89.425678
iter  40 value 87.998065
iter  50 value 87.241791
iter  60 value 85.265704
iter  70 value 83.797889
iter  80 value 83.548201
iter  90 value 83.452338
iter 100 value 83.087010
final  value 83.087010 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.243035 
iter  10 value 94.283195
iter  20 value 94.277449
iter  30 value 90.102596
iter  40 value 79.400844
iter  50 value 79.028711
iter  60 value 79.023495
iter  70 value 79.010619
iter  80 value 78.991328
final  value 78.990828 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.046325 
iter  10 value 94.491986
iter  20 value 94.484579
iter  30 value 94.454680
iter  40 value 94.259115
iter  50 value 94.249690
iter  60 value 94.248375
final  value 94.247930 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.099294 
iter  10 value 94.492968
iter  20 value 94.487593
iter  30 value 94.442247
iter  40 value 93.445593
iter  50 value 88.007501
iter  60 value 86.258241
iter  70 value 82.739384
iter  80 value 80.858303
iter  90 value 79.914465
iter 100 value 79.377568
final  value 79.377568 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.676444 
iter  10 value 94.492086
iter  20 value 94.355556
iter  30 value 94.232947
final  value 94.230000 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.001243 
iter  10 value 89.363306
iter  20 value 85.849938
iter  30 value 85.648351
iter  40 value 85.499110
iter  50 value 85.484954
iter  60 value 85.470125
iter  70 value 85.467185
iter  80 value 82.653572
iter  90 value 82.169675
iter 100 value 81.142391
final  value 81.142391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.801380 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.684501 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.999337 
iter  10 value 92.032213
iter  20 value 81.357293
iter  30 value 80.110657
iter  30 value 80.110656
iter  30 value 80.110656
final  value 80.110656 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.561807 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.554120 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.551871 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.087120 
iter  10 value 93.633932
final  value 93.259020 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.871882 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.078203 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.257355 
iter  10 value 92.867292
iter  20 value 86.425560
iter  30 value 84.368089
iter  40 value 84.182843
iter  50 value 84.159337
final  value 84.159312 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.959777 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.374544 
iter  10 value 93.330578
final  value 93.328261 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.228280 
iter  10 value 93.328262
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.152512 
iter  10 value 93.334982
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.994191 
iter  10 value 91.432776
final  value 91.432749 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.961651 
iter  10 value 94.049632
iter  20 value 93.391363
iter  30 value 91.680622
iter  40 value 90.519587
iter  50 value 90.306531
iter  60 value 90.146787
iter  70 value 90.128248
iter  80 value 90.127970
iter  80 value 90.127969
iter  80 value 90.127969
final  value 90.127969 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.394535 
iter  10 value 94.055335
iter  20 value 93.979260
iter  30 value 93.339933
iter  40 value 91.845830
iter  50 value 83.388241
iter  60 value 81.591558
iter  70 value 80.978236
iter  80 value 80.582919
iter  90 value 80.427499
iter 100 value 80.381168
final  value 80.381168 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.873467 
iter  10 value 93.598156
iter  20 value 93.305584
iter  30 value 86.368701
iter  40 value 85.706780
iter  50 value 85.245474
iter  60 value 83.536686
iter  70 value 82.833320
iter  80 value 82.764853
iter  90 value 82.762963
final  value 82.762335 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.763940 
iter  10 value 94.053423
iter  20 value 89.343370
iter  30 value 84.946718
iter  40 value 84.693918
iter  50 value 83.667442
iter  60 value 82.534233
iter  70 value 82.273354
iter  80 value 82.266984
final  value 82.266204 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.498893 
iter  10 value 93.309306
iter  20 value 92.402419
iter  30 value 89.165725
iter  40 value 88.854261
iter  50 value 88.627124
iter  60 value 86.844613
iter  70 value 84.567709
iter  80 value 80.366326
iter  90 value 79.877646
iter 100 value 79.863140
final  value 79.863140 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.289878 
iter  10 value 94.281028
iter  20 value 86.233698
iter  30 value 83.199380
iter  40 value 82.725208
iter  50 value 80.654033
iter  60 value 79.649499
iter  70 value 79.495290
iter  80 value 79.339546
iter  90 value 79.087943
iter 100 value 78.644306
final  value 78.644306 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.223833 
iter  10 value 94.026586
iter  20 value 89.725880
iter  30 value 84.929228
iter  40 value 83.183720
iter  50 value 82.704258
iter  60 value 81.725283
iter  70 value 80.918402
iter  80 value 80.693147
iter  90 value 80.586262
iter 100 value 79.587053
final  value 79.587053 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.164013 
iter  10 value 94.112049
iter  20 value 90.900818
iter  30 value 82.545376
iter  40 value 82.029515
iter  50 value 79.921599
iter  60 value 79.659185
iter  70 value 79.335953
iter  80 value 79.215931
iter  90 value 79.066377
iter 100 value 78.876530
final  value 78.876530 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.608593 
iter  10 value 91.378709
iter  20 value 82.948972
iter  30 value 82.207559
iter  40 value 81.875803
iter  50 value 81.280372
iter  60 value 80.120777
iter  70 value 79.258010
iter  80 value 78.533221
iter  90 value 78.430538
iter 100 value 78.211433
final  value 78.211433 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.734300 
iter  10 value 89.555100
iter  20 value 85.463993
iter  30 value 84.863862
iter  40 value 84.458444
iter  50 value 83.646320
iter  60 value 81.618545
iter  70 value 81.176966
iter  80 value 79.436667
iter  90 value 79.105350
iter 100 value 78.890905
final  value 78.890905 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.507062 
iter  10 value 92.485511
iter  20 value 89.322071
iter  30 value 83.468155
iter  40 value 81.907520
iter  50 value 80.612456
iter  60 value 80.128016
iter  70 value 80.053377
iter  80 value 79.979468
iter  90 value 79.976753
iter 100 value 79.845798
final  value 79.845798 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.589710 
iter  10 value 94.006001
iter  20 value 89.942106
iter  30 value 86.313480
iter  40 value 83.845540
iter  50 value 80.852748
iter  60 value 80.549563
iter  70 value 79.972019
iter  80 value 79.382916
iter  90 value 78.657515
iter 100 value 78.209787
final  value 78.209787 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.077038 
iter  10 value 96.436025
iter  20 value 93.913164
iter  30 value 86.802999
iter  40 value 85.810866
iter  50 value 81.669848
iter  60 value 80.486082
iter  70 value 79.659253
iter  80 value 78.750968
iter  90 value 78.576877
iter 100 value 78.452870
final  value 78.452870 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.333459 
iter  10 value 96.426649
iter  20 value 86.904560
iter  30 value 80.599161
iter  40 value 78.821770
iter  50 value 78.173628
iter  60 value 77.925494
iter  70 value 77.909160
iter  80 value 77.861907
iter  90 value 77.799116
iter 100 value 77.736968
final  value 77.736968 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.786660 
iter  10 value 93.492785
iter  20 value 88.493960
iter  30 value 85.681027
iter  40 value 85.157579
iter  50 value 82.897667
iter  60 value 80.232082
iter  70 value 79.705191
iter  80 value 79.002809
iter  90 value 78.809782
iter 100 value 78.746859
final  value 78.746859 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.814805 
final  value 94.054775 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.755137 
final  value 94.054422 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.290608 
final  value 94.054316 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.304853 
iter  10 value 94.054668
iter  20 value 93.957708
iter  30 value 81.829549
iter  40 value 81.327187
final  value 81.323459 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.185980 
iter  10 value 94.054702
iter  20 value 93.910416
iter  30 value 85.347112
iter  40 value 84.434640
iter  50 value 84.252484
iter  60 value 84.177489
iter  70 value 84.177267
final  value 84.177129 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.056198 
iter  10 value 93.188965
iter  20 value 93.127544
final  value 93.126586 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.397696 
iter  10 value 93.350080
iter  20 value 93.333649
iter  30 value 93.319856
iter  40 value 91.935144
iter  50 value 87.855475
iter  60 value 87.852965
iter  70 value 87.852563
iter  80 value 87.806696
iter  90 value 87.698774
iter 100 value 79.973519
final  value 79.973519 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.958393 
iter  10 value 93.333456
iter  20 value 93.323586
iter  30 value 93.321688
iter  40 value 92.700816
iter  50 value 91.234948
iter  60 value 90.979336
iter  70 value 90.507406
iter  80 value 83.063540
iter  90 value 82.628168
iter 100 value 82.626459
final  value 82.626459 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.767167 
iter  10 value 94.057170
iter  20 value 93.982804
iter  30 value 91.626281
iter  40 value 90.852052
iter  50 value 90.836764
iter  60 value 90.836616
iter  70 value 90.826506
iter  80 value 90.408953
iter  90 value 80.440934
iter 100 value 80.204238
final  value 80.204238 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.150125 
iter  10 value 93.333715
iter  20 value 93.332631
iter  30 value 93.032815
iter  40 value 82.994993
iter  50 value 82.030959
iter  60 value 81.605388
final  value 81.560546 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.544498 
iter  10 value 94.060330
iter  20 value 90.809580
iter  30 value 83.905743
iter  40 value 83.769413
final  value 83.769042 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.274692 
iter  10 value 91.836564
iter  20 value 82.989580
iter  30 value 80.432102
iter  40 value 79.563536
iter  50 value 79.555067
iter  60 value 79.534811
iter  70 value 79.527455
iter  80 value 79.489212
iter  90 value 79.348519
iter 100 value 79.302190
final  value 79.302190 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.160577 
iter  10 value 93.343184
iter  20 value 93.336239
iter  30 value 93.329192
iter  40 value 93.153977
iter  50 value 93.076481
iter  60 value 93.075883
iter  70 value 93.075698
iter  80 value 93.075463
iter  90 value 93.054783
iter 100 value 86.837595
final  value 86.837595 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.433771 
iter  10 value 93.337324
iter  20 value 93.329375
iter  30 value 91.157326
iter  40 value 84.632741
iter  50 value 83.307318
iter  60 value 82.066456
iter  70 value 80.736390
iter  80 value 80.725263
iter  90 value 80.723472
iter 100 value 80.723312
final  value 80.723312 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.247971 
iter  10 value 85.799964
iter  20 value 84.733012
iter  30 value 84.600051
iter  40 value 84.410687
iter  50 value 84.409140
iter  60 value 84.401881
iter  70 value 83.978498
iter  80 value 82.567795
iter  90 value 82.484493
iter  90 value 82.484492
iter  90 value 82.484492
final  value 82.484492 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.195301 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.289116 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.954036 
final  value 93.783647 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.334880 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.180654 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.752411 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.789655 
iter  10 value 93.717421
iter  20 value 92.930556
iter  30 value 92.928261
iter  30 value 92.928261
final  value 92.928257 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.677903 
final  value 94.400000 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.639146 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.552451 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.224682 
iter  10 value 90.492606
iter  20 value 85.620630
iter  30 value 85.495057
iter  40 value 85.462373
iter  50 value 85.460136
final  value 85.460084 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.261153 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.596140 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.292421 
iter  10 value 94.471113
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.553005 
iter  10 value 88.320456
iter  20 value 85.827130
iter  30 value 85.813873
final  value 85.813734 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.122865 
iter  10 value 94.499624
iter  20 value 94.379250
iter  30 value 87.253684
iter  40 value 86.233658
iter  50 value 85.869826
iter  60 value 85.856991
iter  70 value 85.848402
final  value 85.848362 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.900644 
iter  10 value 94.488583
iter  20 value 94.427584
iter  30 value 93.809625
iter  40 value 89.266293
iter  50 value 86.374311
iter  60 value 86.059116
iter  70 value 85.856432
iter  80 value 85.848363
iter  80 value 85.848362
iter  80 value 85.848362
final  value 85.848362 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.076855 
iter  10 value 94.422059
iter  20 value 89.914361
iter  30 value 89.455551
iter  40 value 88.314318
iter  50 value 85.756150
iter  60 value 85.485550
iter  70 value 85.479787
iter  80 value 85.478030
final  value 85.478019 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.942778 
iter  10 value 94.486671
iter  20 value 94.222625
iter  30 value 93.871298
iter  40 value 93.619884
iter  50 value 92.325926
iter  60 value 89.195778
iter  70 value 87.357315
iter  80 value 85.413838
iter  90 value 85.105103
iter 100 value 84.894347
final  value 84.894347 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.328864 
iter  10 value 94.496547
iter  20 value 94.467062
iter  30 value 94.198433
iter  40 value 94.120033
iter  50 value 89.655501
iter  60 value 89.483086
iter  70 value 86.628694
iter  80 value 86.497678
iter  90 value 85.760053
iter 100 value 85.672842
final  value 85.672842 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 124.659487 
iter  10 value 94.537227
iter  20 value 90.777904
iter  30 value 86.988857
iter  40 value 85.332214
iter  50 value 84.530568
iter  60 value 84.136183
iter  70 value 83.595520
iter  80 value 83.176830
iter  90 value 83.121899
iter 100 value 83.050524
final  value 83.050524 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.544889 
iter  10 value 94.313131
iter  20 value 90.023007
iter  30 value 89.051384
iter  40 value 85.745524
iter  50 value 84.857481
iter  60 value 84.064344
iter  70 value 83.855596
iter  80 value 83.560406
iter  90 value 83.412350
iter 100 value 83.371731
final  value 83.371731 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.933534 
iter  10 value 93.999859
iter  20 value 86.903696
iter  30 value 86.228956
iter  40 value 85.655955
iter  50 value 84.318469
iter  60 value 83.352683
iter  70 value 83.209419
iter  80 value 83.181475
iter  90 value 83.146693
iter 100 value 83.120669
final  value 83.120669 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.728308 
iter  10 value 93.123523
iter  20 value 86.729127
iter  30 value 86.046895
iter  40 value 85.573594
iter  50 value 85.337968
iter  60 value 85.008903
iter  70 value 83.987195
iter  80 value 83.243963
iter  90 value 83.214301
iter 100 value 83.203519
final  value 83.203519 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.713443 
iter  10 value 94.970105
iter  20 value 94.136216
iter  30 value 89.751965
iter  40 value 88.997961
iter  50 value 88.279636
iter  60 value 87.171578
iter  70 value 84.499975
iter  80 value 84.142024
iter  90 value 83.507939
iter 100 value 83.180769
final  value 83.180769 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.925503 
iter  10 value 94.514113
iter  20 value 88.808802
iter  30 value 88.019449
iter  40 value 87.259844
iter  50 value 85.939124
iter  60 value 85.370341
iter  70 value 84.732737
iter  80 value 83.573649
iter  90 value 82.909154
iter 100 value 82.689987
final  value 82.689987 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.559392 
iter  10 value 94.857927
iter  20 value 94.524230
iter  30 value 94.011848
iter  40 value 89.338821
iter  50 value 87.112899
iter  60 value 85.546259
iter  70 value 84.417918
iter  80 value 83.935646
iter  90 value 83.702190
iter 100 value 83.238157
final  value 83.238157 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.137284 
iter  10 value 94.494901
iter  20 value 87.879613
iter  30 value 87.276200
iter  40 value 86.544745
iter  50 value 84.788022
iter  60 value 83.461208
iter  70 value 83.149581
iter  80 value 83.086633
iter  90 value 82.915721
iter 100 value 82.820865
final  value 82.820865 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.160680 
iter  10 value 94.374572
iter  20 value 93.177686
iter  30 value 88.654581
iter  40 value 88.213916
iter  50 value 86.646749
iter  60 value 84.971607
iter  70 value 83.443885
iter  80 value 82.939658
iter  90 value 82.841855
iter 100 value 82.750966
final  value 82.750966 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.985014 
iter  10 value 92.590873
iter  20 value 88.814812
iter  30 value 86.789245
iter  40 value 84.312070
iter  50 value 83.972648
iter  60 value 83.675293
iter  70 value 83.425968
iter  80 value 83.193611
iter  90 value 83.007786
iter 100 value 82.859168
final  value 82.859168 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.133312 
final  value 94.485763 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.253566 
final  value 94.307733 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.245431 
final  value 94.485682 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.798875 
final  value 94.486254 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.418235 
final  value 94.485843 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.612436 
iter  10 value 94.488528
iter  20 value 94.312318
iter  30 value 93.812512
iter  40 value 93.733666
final  value 93.730682 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.364631 
iter  10 value 94.480626
iter  20 value 94.471553
iter  30 value 94.467436
iter  30 value 94.467436
final  value 94.467436 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.949157 
iter  10 value 94.492163
iter  20 value 94.485674
iter  30 value 94.155533
iter  40 value 94.058601
iter  50 value 94.057419
final  value 94.057389 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.387645 
iter  10 value 92.483102
iter  20 value 89.943445
iter  30 value 89.510252
iter  40 value 89.509324
iter  50 value 86.944617
iter  60 value 86.889855
iter  70 value 86.030719
iter  80 value 85.215176
iter  90 value 85.194807
iter 100 value 85.147234
final  value 85.147234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.865172 
iter  10 value 94.489427
iter  20 value 94.476945
iter  30 value 87.817118
iter  40 value 86.063206
iter  50 value 85.415068
iter  60 value 85.411286
iter  70 value 85.345954
iter  80 value 85.071097
iter  90 value 84.869163
final  value 84.869159 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.867045 
iter  10 value 94.475660
iter  20 value 94.467427
iter  30 value 93.252134
iter  40 value 91.976680
iter  50 value 91.975270
iter  50 value 91.975269
iter  50 value 91.975269
final  value 91.975269 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.701342 
iter  10 value 94.065439
iter  20 value 93.983925
iter  30 value 88.752977
iter  40 value 88.728401
iter  50 value 88.728323
iter  60 value 87.097334
iter  70 value 86.124969
iter  80 value 82.922359
iter  90 value 82.317926
iter 100 value 82.219101
final  value 82.219101 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.413489 
iter  10 value 94.156057
iter  20 value 94.148735
iter  30 value 94.141424
iter  40 value 89.457354
iter  50 value 85.228367
iter  60 value 85.133567
iter  70 value 84.615970
iter  80 value 84.226336
iter  90 value 82.693914
iter 100 value 82.558890
final  value 82.558890 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.271805 
iter  10 value 94.495721
iter  20 value 94.487698
iter  30 value 88.045408
iter  40 value 87.102117
iter  50 value 87.088575
iter  60 value 86.795236
iter  70 value 86.730500
final  value 86.730373 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.723541 
iter  10 value 94.492575
iter  20 value 94.484672
iter  30 value 94.111643
iter  40 value 94.057688
final  value 94.057529 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.638069 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.343627 
iter  10 value 89.833956
iter  20 value 89.011454
iter  30 value 88.797124
iter  40 value 88.754415
iter  50 value 88.739572
final  value 88.739561 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.227409 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.657219 
final  value 93.551913 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.874578 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.157630 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.070860 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.040131 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.620927 
final  value 93.551913 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.515925 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.332411 
iter  10 value 93.352955
iter  10 value 93.352954
iter  10 value 93.352954
final  value 93.352954 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.373784 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.267140 
iter  10 value 93.175288
final  value 93.164499 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.762966 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.135414 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.355169 
iter  10 value 94.054697
iter  20 value 89.625104
iter  30 value 86.085562
iter  40 value 85.136160
iter  50 value 85.005584
iter  60 value 84.548665
iter  70 value 84.000045
iter  80 value 83.627564
final  value 83.623846 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.569123 
iter  10 value 94.059800
iter  20 value 93.949030
iter  30 value 89.169174
iter  40 value 84.890421
iter  50 value 83.756001
iter  60 value 83.309926
iter  70 value 82.482641
iter  80 value 81.672805
iter  90 value 81.665248
final  value 81.665240 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.742729 
iter  10 value 94.057751
iter  20 value 93.765065
iter  30 value 89.859189
iter  40 value 84.766545
iter  50 value 83.855189
iter  60 value 83.402694
iter  70 value 82.994679
iter  80 value 82.882229
iter  90 value 81.692834
iter 100 value 81.665251
final  value 81.665251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.166193 
iter  10 value 94.046209
iter  20 value 93.525374
iter  30 value 93.455741
iter  40 value 93.448048
iter  50 value 93.385731
iter  60 value 86.865240
iter  70 value 84.257632
iter  80 value 84.053416
iter  90 value 83.499231
iter 100 value 83.420719
final  value 83.420719 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.532527 
iter  10 value 94.055338
iter  20 value 93.604754
iter  30 value 89.066053
iter  40 value 87.734785
iter  50 value 85.865444
iter  60 value 84.819567
iter  70 value 84.251892
iter  80 value 83.733089
iter  90 value 83.631673
final  value 83.623846 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.487748 
iter  10 value 95.714236
iter  20 value 94.177900
iter  30 value 93.488733
iter  40 value 92.728779
iter  50 value 89.783743
iter  60 value 85.406001
iter  70 value 83.044976
iter  80 value 81.380495
iter  90 value 80.958324
iter 100 value 80.430102
final  value 80.430102 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.002311 
iter  10 value 93.348631
iter  20 value 85.857034
iter  30 value 83.126070
iter  40 value 82.332437
iter  50 value 81.977186
iter  60 value 81.297468
iter  70 value 81.027994
iter  80 value 80.917438
iter  90 value 80.849994
iter 100 value 80.700280
final  value 80.700280 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.977505 
iter  10 value 93.985128
iter  20 value 85.285945
iter  30 value 84.570899
iter  40 value 84.195090
iter  50 value 83.878785
iter  60 value 83.537118
iter  70 value 83.272674
iter  80 value 82.168744
iter  90 value 81.912573
iter 100 value 81.831114
final  value 81.831114 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.184032 
iter  10 value 94.076830
iter  20 value 90.119655
iter  30 value 88.063541
iter  40 value 84.391282
iter  50 value 83.493614
iter  60 value 83.343181
iter  70 value 82.587564
iter  80 value 82.503439
iter  90 value 82.440981
iter 100 value 81.932673
final  value 81.932673 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.484705 
iter  10 value 93.873277
iter  20 value 86.206921
iter  30 value 85.170420
iter  40 value 85.008609
iter  50 value 84.706855
iter  60 value 84.157288
iter  70 value 82.129319
iter  80 value 81.623983
iter  90 value 81.116194
iter 100 value 80.980476
final  value 80.980476 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.034232 
iter  10 value 95.947991
iter  20 value 87.878151
iter  30 value 85.840166
iter  40 value 82.548263
iter  50 value 82.185942
iter  60 value 81.675157
iter  70 value 81.289249
iter  80 value 80.587137
iter  90 value 80.273254
iter 100 value 80.130009
final  value 80.130009 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.681592 
iter  10 value 94.064571
iter  20 value 87.054417
iter  30 value 85.368838
iter  40 value 84.856120
iter  50 value 84.143188
iter  60 value 81.999818
iter  70 value 81.411828
iter  80 value 81.173504
iter  90 value 80.696938
iter 100 value 80.508406
final  value 80.508406 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.694326 
iter  10 value 98.364807
iter  20 value 97.549861
iter  30 value 86.987493
iter  40 value 85.857550
iter  50 value 85.363109
iter  60 value 83.115478
iter  70 value 82.384046
iter  80 value 81.074247
iter  90 value 80.521351
iter 100 value 80.288409
final  value 80.288409 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.389014 
iter  10 value 95.046116
iter  20 value 84.175871
iter  30 value 82.781390
iter  40 value 81.327207
iter  50 value 80.840025
iter  60 value 80.679669
iter  70 value 80.595350
iter  80 value 80.552399
iter  90 value 80.507853
iter 100 value 80.330085
final  value 80.330085 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.525356 
iter  10 value 95.174063
iter  20 value 88.686575
iter  30 value 86.920254
iter  40 value 85.417884
iter  50 value 83.624400
iter  60 value 81.762121
iter  70 value 80.894244
iter  80 value 80.660320
iter  90 value 80.482058
iter 100 value 80.270750
final  value 80.270750 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.817297 
final  value 94.054508 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.187422 
final  value 94.054459 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.312286 
final  value 94.054588 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.451742 
final  value 94.054530 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.082239 
final  value 93.917637 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.935842 
iter  10 value 94.058206
iter  20 value 94.052969
iter  30 value 93.699231
iter  40 value 87.636172
iter  50 value 87.623453
final  value 87.623357 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.992330 
iter  10 value 94.057962
iter  20 value 94.052961
final  value 94.052909 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.739477 
iter  10 value 93.920491
iter  20 value 93.864689
final  value 93.356934 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.366818 
iter  10 value 94.057534
iter  20 value 94.052872
iter  30 value 93.957609
iter  40 value 88.305270
iter  50 value 85.102751
iter  60 value 84.776906
iter  70 value 81.517741
iter  80 value 80.770106
iter  90 value 80.634906
final  value 80.634213 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.582483 
iter  10 value 94.057880
iter  20 value 91.981298
iter  30 value 85.716209
iter  40 value 85.428385
iter  50 value 85.116710
iter  60 value 84.783450
iter  70 value 83.591725
iter  80 value 83.356423
iter  90 value 83.354858
final  value 83.353638 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.816160 
iter  10 value 93.924233
iter  20 value 93.916268
iter  30 value 92.977808
iter  40 value 86.327063
iter  50 value 84.653481
iter  60 value 84.651638
iter  70 value 84.651286
iter  80 value 84.552595
iter  90 value 84.507688
iter  90 value 84.507688
final  value 84.507688 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.133126 
iter  10 value 94.061048
iter  20 value 94.054214
iter  30 value 87.763677
iter  40 value 83.393218
iter  50 value 82.091199
iter  60 value 82.038279
iter  70 value 82.035929
iter  80 value 81.525701
iter  90 value 79.811656
final  value 79.797999 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.663714 
iter  10 value 93.587584
iter  20 value 93.550798
iter  30 value 93.543722
final  value 93.018205 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.506399 
iter  10 value 86.562397
iter  20 value 86.468859
iter  30 value 86.283708
iter  40 value 85.858706
iter  50 value 85.856971
iter  60 value 85.621544
iter  70 value 85.447963
iter  80 value 85.447911
final  value 85.447890 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.369674 
iter  10 value 93.560579
iter  20 value 90.256890
iter  30 value 86.207310
iter  40 value 83.038190
iter  50 value 81.856964
iter  60 value 81.854393
iter  70 value 81.853969
iter  80 value 81.853507
iter  90 value 81.850505
iter 100 value 81.833761
final  value 81.833761 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.032092 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.626092 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.843453 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.370572 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.384166 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.316420 
final  value 94.461538 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.341595 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.360512 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.132407 
iter  10 value 93.707667
iter  20 value 92.524602
iter  30 value 92.519298
iter  30 value 92.519298
iter  30 value 92.519298
final  value 92.519298 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.568837 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.513883 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.449694 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 135.624983 
iter  10 value 94.446920
final  value 94.445714 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.079067 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 136.792997 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.010957 
iter  10 value 89.427680
iter  20 value 85.399153
iter  30 value 82.396034
iter  40 value 82.110967
iter  50 value 82.028693
iter  60 value 81.782064
iter  70 value 81.623348
final  value 81.623069 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.164526 
iter  10 value 94.412795
iter  20 value 88.181839
iter  30 value 86.974575
iter  40 value 86.092828
iter  50 value 85.897285
iter  60 value 85.618768
iter  70 value 84.866421
iter  80 value 84.055305
iter  90 value 83.878558
final  value 83.878557 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.026296 
iter  10 value 94.478145
iter  20 value 88.101177
iter  30 value 85.972882
iter  40 value 85.447301
iter  50 value 85.409396
iter  60 value 85.293219
iter  70 value 85.233024
iter  80 value 84.951863
iter  90 value 84.010801
iter 100 value 83.878564
final  value 83.878564 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.041203 
iter  10 value 94.171065
iter  20 value 86.955286
iter  30 value 85.291499
iter  40 value 84.677127
iter  50 value 84.522702
iter  60 value 84.335040
iter  70 value 84.280335
iter  80 value 84.170781
final  value 84.164926 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.319431 
iter  10 value 94.497956
iter  20 value 92.427309
iter  30 value 87.744618
iter  40 value 86.811288
iter  50 value 85.525812
iter  60 value 85.256285
iter  70 value 84.710144
iter  80 value 84.567852
iter  90 value 84.011012
final  value 83.878557 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.534611 
iter  10 value 94.389957
iter  20 value 92.318017
iter  30 value 88.159420
iter  40 value 85.902390
iter  50 value 83.577828
iter  60 value 80.951072
iter  70 value 80.586958
iter  80 value 80.488092
iter  90 value 80.461047
iter 100 value 80.458020
final  value 80.458020 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.415600 
iter  10 value 94.455594
iter  20 value 91.988877
iter  30 value 85.033324
iter  40 value 83.232637
iter  50 value 82.834544
iter  60 value 82.744658
iter  70 value 82.255807
iter  80 value 80.932746
iter  90 value 80.809927
iter 100 value 80.783216
final  value 80.783216 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 135.201592 
iter  10 value 94.925663
iter  20 value 90.877801
iter  30 value 88.146361
iter  40 value 86.192260
iter  50 value 85.308223
iter  60 value 85.069097
iter  70 value 83.804614
iter  80 value 83.090311
iter  90 value 81.737675
iter 100 value 80.912191
final  value 80.912191 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.322419 
iter  10 value 94.466289
iter  20 value 91.438489
iter  30 value 87.700072
iter  40 value 86.345800
iter  50 value 86.066455
iter  60 value 85.331223
iter  70 value 84.824127
iter  80 value 84.787408
iter  90 value 84.351546
iter 100 value 84.143105
final  value 84.143105 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.986124 
iter  10 value 90.837249
iter  20 value 86.477585
iter  30 value 86.026765
iter  40 value 85.477486
iter  50 value 84.516440
iter  60 value 84.021301
iter  70 value 82.111910
iter  80 value 81.694354
iter  90 value 81.627148
iter 100 value 81.309318
final  value 81.309318 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.323284 
iter  10 value 95.236754
iter  20 value 92.029273
iter  30 value 88.835433
iter  40 value 86.080812
iter  50 value 84.419979
iter  60 value 83.357945
iter  70 value 82.146726
iter  80 value 81.860192
iter  90 value 81.703260
iter 100 value 81.494833
final  value 81.494833 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.701981 
iter  10 value 94.422582
iter  20 value 88.099453
iter  30 value 86.931664
iter  40 value 84.753418
iter  50 value 84.420310
iter  60 value 82.651859
iter  70 value 82.156025
iter  80 value 81.857095
iter  90 value 81.367507
iter 100 value 80.945323
final  value 80.945323 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.500866 
iter  10 value 92.860523
iter  20 value 86.874690
iter  30 value 85.834025
iter  40 value 83.620466
iter  50 value 83.141962
iter  60 value 82.601611
iter  70 value 82.436019
iter  80 value 81.896175
iter  90 value 80.999336
iter 100 value 80.352871
final  value 80.352871 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.867444 
iter  10 value 94.488046
iter  20 value 92.942037
iter  30 value 85.810924
iter  40 value 83.679226
iter  50 value 82.674440
iter  60 value 81.394780
iter  70 value 80.970526
iter  80 value 80.829874
iter  90 value 80.660166
iter 100 value 80.357969
final  value 80.357969 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.661750 
iter  10 value 92.154372
iter  20 value 86.549356
iter  30 value 85.686422
iter  40 value 83.587733
iter  50 value 81.818265
iter  60 value 81.136709
iter  70 value 80.849484
iter  80 value 80.721772
iter  90 value 80.500314
iter 100 value 80.378526
final  value 80.378526 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.715542 
iter  10 value 94.486042
iter  20 value 94.169580
iter  30 value 84.499795
iter  40 value 84.044617
iter  50 value 83.787511
iter  60 value 83.785574
iter  70 value 83.592163
iter  80 value 83.303131
final  value 83.302816 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.453853 
final  value 94.485643 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.332071 
iter  10 value 94.485789
iter  20 value 94.468660
iter  30 value 87.930366
iter  40 value 86.529819
iter  50 value 86.527697
final  value 86.527557 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.081348 
iter  10 value 94.485798
iter  20 value 94.484225
iter  30 value 94.444537
iter  40 value 85.228753
iter  50 value 85.201241
iter  60 value 85.200783
iter  70 value 83.031814
final  value 83.029479 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.466752 
final  value 94.485630 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.985742 
iter  10 value 94.489453
iter  20 value 86.914735
iter  30 value 86.877554
iter  40 value 86.494006
iter  50 value 86.419566
iter  60 value 86.419004
iter  70 value 84.866803
iter  80 value 84.865462
iter  90 value 84.862533
iter 100 value 84.856586
final  value 84.856586 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.098668 
iter  10 value 94.488588
iter  20 value 94.484246
iter  30 value 94.266078
iter  40 value 91.526721
iter  50 value 87.968736
iter  60 value 87.953347
iter  70 value 87.951478
iter  80 value 87.557567
final  value 87.551964 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.427283 
iter  10 value 94.484323
iter  20 value 94.466049
iter  30 value 94.462264
iter  40 value 92.609037
iter  50 value 85.699343
iter  60 value 81.976488
iter  70 value 81.976343
iter  80 value 81.732416
iter  90 value 81.717136
iter 100 value 81.716940
final  value 81.716940 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.197806 
iter  10 value 94.471582
iter  20 value 94.469453
iter  30 value 94.467649
iter  40 value 86.763164
final  value 86.145139 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.170410 
iter  10 value 94.137717
iter  20 value 94.134193
iter  30 value 94.105861
iter  40 value 94.024515
iter  50 value 94.023060
final  value 94.023052 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.342278 
iter  10 value 93.952353
iter  20 value 93.146947
iter  30 value 86.919575
iter  40 value 84.262098
iter  50 value 84.259609
iter  60 value 83.376852
iter  70 value 81.822298
iter  80 value 81.408254
iter  90 value 81.013180
iter 100 value 80.836835
final  value 80.836835 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.711141 
iter  10 value 94.475638
iter  20 value 94.467093
iter  30 value 94.466825
iter  30 value 94.466825
final  value 94.466825 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.986417 
iter  10 value 94.474605
iter  20 value 92.010918
iter  30 value 85.707713
iter  40 value 84.520343
iter  50 value 84.079081
iter  60 value 83.956665
iter  70 value 83.880624
iter  80 value 83.781238
iter  90 value 83.780122
final  value 83.780108 
converged
Fitting Repeat 4 

# weights:  507
initial  value 93.987803 
iter  10 value 87.956399
iter  20 value 87.952540
iter  30 value 87.561800
iter  40 value 87.263982
iter  50 value 84.896801
final  value 84.896476 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.466259 
iter  10 value 94.331371
iter  20 value 94.325785
iter  30 value 88.563704
iter  40 value 84.413523
iter  50 value 84.106041
iter  60 value 84.035773
iter  70 value 84.029988
iter  80 value 84.015826
iter  90 value 83.922979
iter 100 value 83.859314
final  value 83.859314 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 141.028756 
iter  10 value 118.041773
iter  20 value 117.290272
iter  30 value 106.711750
iter  40 value 105.126046
iter  50 value 103.925108
iter  60 value 103.126693
iter  70 value 103.002669
iter  80 value 101.867282
iter  90 value 101.214242
iter 100 value 101.118018
final  value 101.118018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 151.652416 
iter  10 value 118.375940
iter  20 value 115.903097
iter  30 value 107.504290
iter  40 value 104.991215
iter  50 value 103.526658
iter  60 value 101.725455
iter  70 value 101.172274
iter  80 value 100.913414
iter  90 value 100.610824
iter 100 value 100.272765
final  value 100.272765 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.946151 
iter  10 value 121.225735
iter  20 value 109.674286
iter  30 value 109.089092
iter  40 value 105.424686
iter  50 value 103.386837
iter  60 value 102.968635
iter  70 value 102.604418
iter  80 value 102.384762
iter  90 value 101.087713
iter 100 value 100.916049
final  value 100.916049 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.953616 
iter  10 value 116.810669
iter  20 value 106.652142
iter  30 value 105.989861
iter  40 value 104.737469
iter  50 value 104.341005
iter  60 value 103.655705
iter  70 value 102.723867
iter  80 value 101.902730
iter  90 value 101.451519
iter 100 value 100.981662
final  value 100.981662 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 165.394461 
iter  10 value 118.212259
iter  20 value 117.835101
iter  30 value 108.816421
iter  40 value 106.981000
iter  50 value 103.421432
iter  60 value 102.606332
iter  70 value 102.158919
iter  80 value 101.870818
iter  90 value 101.379640
iter 100 value 101.005816
final  value 101.005816 
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 -- Sun Mar  3 21:16:35 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 
 43.479   2.133  44.551