##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.3 (2025-02-28)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* 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       53.821  2.136  56.130
FSmethod      53.202  1.985  55.267
corr_plot     51.322  2.241  53.738
pred_ensembel 15.737  0.377  14.761
enrichfindP    0.485  0.077   9.536
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.3 (2025-02-28) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 98.842030 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.241576 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.850803 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.677096 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.490586 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.397397 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.050127 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.235878 
iter  10 value 94.032323
final  value 94.032297 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.349834 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.502090 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.235649 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.277663 
iter  10 value 93.993242
final  value 93.992106 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.735178 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.925591 
iter  10 value 93.153723
iter  20 value 92.002185
final  value 92.002139 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.827057 
iter  10 value 85.957356
iter  20 value 83.836038
iter  30 value 83.592697
final  value 83.592557 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.847908 
iter  10 value 94.471217
iter  20 value 85.931247
iter  30 value 84.868794
iter  40 value 84.174296
iter  50 value 83.969000
iter  60 value 83.961527
final  value 83.959706 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.727540 
iter  10 value 94.471502
iter  20 value 92.053581
iter  30 value 91.774293
iter  40 value 91.619459
iter  50 value 91.300172
iter  60 value 86.030847
iter  70 value 84.590206
iter  80 value 84.549532
iter  90 value 84.466060
iter 100 value 84.168233
final  value 84.168233 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.894551 
iter  10 value 94.471678
iter  20 value 85.619243
iter  30 value 85.095366
iter  40 value 84.901864
iter  50 value 84.495081
iter  60 value 84.344290
final  value 84.335323 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.037312 
iter  10 value 94.377014
iter  20 value 93.155267
iter  30 value 91.188371
iter  40 value 88.251203
iter  50 value 85.956798
iter  60 value 85.513508
iter  70 value 85.221050
iter  80 value 83.778874
iter  90 value 83.130598
iter 100 value 82.734697
final  value 82.734697 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.187106 
iter  10 value 94.516332
iter  20 value 94.444229
iter  30 value 92.275039
iter  40 value 88.895035
iter  50 value 87.193843
iter  60 value 86.098623
iter  70 value 85.559711
iter  80 value 85.500125
final  value 85.500114 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.741836 
iter  10 value 94.483657
iter  20 value 88.259759
iter  30 value 84.768283
iter  40 value 82.774890
iter  50 value 81.867742
iter  60 value 81.454226
iter  70 value 81.268084
iter  80 value 81.145292
iter  90 value 80.989196
iter 100 value 80.943811
final  value 80.943811 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.473153 
iter  10 value 93.287998
iter  20 value 85.850475
iter  30 value 85.111731
iter  40 value 84.408276
iter  50 value 84.079854
iter  60 value 83.428969
iter  70 value 81.933007
iter  80 value 81.660144
iter  90 value 81.212594
iter 100 value 80.956144
final  value 80.956144 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.724694 
iter  10 value 94.467109
iter  20 value 87.463627
iter  30 value 85.489811
iter  40 value 85.331308
iter  50 value 84.832545
iter  60 value 83.919890
iter  70 value 82.532215
iter  80 value 81.756950
iter  90 value 81.456193
iter 100 value 81.414828
final  value 81.414828 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 129.052042 
iter  10 value 94.364417
iter  20 value 86.826321
iter  30 value 84.946509
iter  40 value 84.701283
iter  50 value 84.365142
iter  60 value 83.935194
iter  70 value 83.733135
iter  80 value 83.067093
iter  90 value 82.285546
iter 100 value 81.608887
final  value 81.608887 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.098866 
iter  10 value 94.499513
iter  20 value 88.328748
iter  30 value 85.327654
iter  40 value 85.145481
iter  50 value 84.999685
iter  60 value 84.537562
iter  70 value 84.364605
iter  80 value 84.249655
iter  90 value 83.219835
iter 100 value 81.903650
final  value 81.903650 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.871518 
iter  10 value 91.887241
iter  20 value 86.310316
iter  30 value 84.515510
iter  40 value 84.280344
iter  50 value 83.874327
iter  60 value 83.364166
iter  70 value 82.509822
iter  80 value 81.694695
iter  90 value 81.468474
iter 100 value 81.424519
final  value 81.424519 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.735734 
iter  10 value 101.071428
iter  20 value 94.466987
iter  30 value 93.742649
iter  40 value 89.853212
iter  50 value 85.992178
iter  60 value 84.947523
iter  70 value 83.823659
iter  80 value 83.033834
iter  90 value 82.605908
iter 100 value 81.606669
final  value 81.606669 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.776543 
iter  10 value 95.916070
iter  20 value 94.765392
iter  30 value 89.503100
iter  40 value 88.750129
iter  50 value 87.832189
iter  60 value 85.553389
iter  70 value 85.024745
iter  80 value 83.420998
iter  90 value 82.889839
iter 100 value 82.590504
final  value 82.590504 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.188522 
iter  10 value 94.951810
iter  20 value 94.511271
iter  30 value 94.280553
iter  40 value 92.777268
iter  50 value 91.372425
iter  60 value 91.190695
iter  70 value 89.695556
iter  80 value 86.941182
iter  90 value 84.295782
iter 100 value 83.337697
final  value 83.337697 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.017297 
iter  10 value 98.088326
iter  20 value 94.911700
iter  30 value 88.080946
iter  40 value 87.567603
iter  50 value 85.798532
iter  60 value 82.419208
iter  70 value 81.767582
iter  80 value 81.640921
iter  90 value 81.419825
iter 100 value 81.282855
final  value 81.282855 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 112.065398 
final  value 94.485788 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.038235 
final  value 94.485619 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.410794 
final  value 94.485746 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.806391 
final  value 94.485920 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.649033 
final  value 94.485709 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.337531 
iter  10 value 94.471762
iter  20 value 93.476439
iter  30 value 93.420270
iter  40 value 93.398746
final  value 93.346388 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.509153 
iter  10 value 94.489121
iter  20 value 94.484462
iter  30 value 94.467798
iter  40 value 94.467446
final  value 94.467436 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.130852 
iter  10 value 94.489294
iter  20 value 94.484238
iter  30 value 93.123739
iter  40 value 86.596463
iter  50 value 86.494781
final  value 86.494608 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.501053 
iter  10 value 94.487373
iter  20 value 91.501027
iter  30 value 88.916950
iter  40 value 88.914411
iter  50 value 88.856062
iter  60 value 88.555645
iter  70 value 87.693539
iter  80 value 84.943294
iter  90 value 84.645830
iter 100 value 83.065825
final  value 83.065825 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.219306 
iter  10 value 94.489266
iter  20 value 94.419166
iter  30 value 91.865027
iter  40 value 88.936072
iter  50 value 87.507616
iter  60 value 87.480310
iter  70 value 87.477265
iter  80 value 87.323592
iter  90 value 87.322659
final  value 87.322652 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.142239 
iter  10 value 94.227560
iter  20 value 87.297677
iter  30 value 87.004853
iter  40 value 86.993263
iter  50 value 86.993094
iter  60 value 86.498281
iter  70 value 86.310712
iter  80 value 82.576117
iter  90 value 81.582946
iter 100 value 81.581733
final  value 81.581733 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.490479 
iter  10 value 93.741236
iter  20 value 92.234446
iter  30 value 92.207373
iter  40 value 92.135576
iter  50 value 91.177486
iter  60 value 91.174330
iter  70 value 91.173739
iter  80 value 85.208131
iter  90 value 84.203065
iter 100 value 83.601167
final  value 83.601167 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.297020 
iter  10 value 94.490686
iter  20 value 94.474389
iter  30 value 94.468468
final  value 94.467430 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.452697 
iter  10 value 90.655083
iter  20 value 88.164052
iter  30 value 88.161788
iter  40 value 88.144593
iter  50 value 87.969746
iter  60 value 87.968247
iter  70 value 87.966251
iter  80 value 87.640232
iter  90 value 84.948652
iter 100 value 84.523734
final  value 84.523734 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.370764 
iter  10 value 94.492263
iter  20 value 94.357833
iter  30 value 85.513099
iter  30 value 85.513098
final  value 85.513097 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.061510 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.370228 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.229587 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.943977 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.923711 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.689461 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.170732 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.190994 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.330143 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.163412 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.077325 
iter  10 value 89.978418
iter  20 value 87.053989
iter  30 value 86.017517
iter  40 value 85.304009
iter  50 value 85.303335
final  value 85.303326 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.613997 
iter  10 value 92.542788
iter  20 value 86.022637
iter  30 value 83.514597
iter  40 value 83.470811
iter  50 value 83.462284
iter  60 value 83.461374
iter  70 value 83.461309
final  value 83.461301 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.587940 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.472054 
final  value 94.027933 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.907155 
iter  10 value 93.896209
final  value 93.896199 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.563122 
iter  10 value 94.058897
iter  20 value 94.000869
iter  30 value 88.700309
iter  40 value 87.821608
iter  50 value 87.442603
iter  60 value 86.978807
iter  70 value 86.725454
final  value 86.717827 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.613382 
iter  10 value 93.202566
iter  20 value 90.016055
iter  30 value 88.024867
iter  40 value 87.529795
iter  50 value 87.297025
iter  60 value 86.762972
iter  70 value 86.717470
final  value 86.717466 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.411150 
iter  10 value 94.046366
iter  20 value 93.238601
iter  30 value 92.897071
iter  40 value 92.858770
iter  50 value 88.888347
iter  60 value 87.951111
iter  70 value 86.020150
iter  80 value 85.361915
iter  90 value 84.576070
iter 100 value 84.312592
final  value 84.312592 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.177067 
iter  10 value 90.747846
iter  20 value 86.672797
iter  30 value 86.401652
iter  40 value 86.110622
iter  50 value 85.708322
iter  60 value 85.560351
iter  70 value 85.322569
iter  80 value 85.296778
final  value 85.295585 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.325600 
iter  10 value 94.048198
iter  20 value 93.643525
iter  30 value 88.792623
iter  40 value 88.222356
iter  50 value 87.714811
iter  60 value 87.267277
iter  70 value 86.790324
final  value 86.717585 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.494606 
iter  10 value 95.008903
iter  20 value 88.681572
iter  30 value 88.410790
iter  40 value 86.972486
iter  50 value 84.839305
iter  60 value 84.009220
iter  70 value 83.851844
iter  80 value 83.647656
iter  90 value 83.512253
iter 100 value 83.228374
final  value 83.228374 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.495683 
iter  10 value 94.246777
iter  20 value 88.482272
iter  30 value 87.973206
iter  40 value 86.494790
iter  50 value 85.915129
iter  60 value 85.674952
iter  70 value 84.810266
iter  80 value 83.965843
iter  90 value 83.043520
iter 100 value 82.846200
final  value 82.846200 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.193532 
iter  10 value 94.112499
iter  20 value 93.009979
iter  30 value 91.559257
iter  40 value 89.183983
iter  50 value 87.166942
iter  60 value 86.240170
iter  70 value 85.203807
iter  80 value 85.037545
iter  90 value 84.650038
iter 100 value 83.689390
final  value 83.689390 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.494182 
iter  10 value 94.719322
iter  20 value 94.193022
iter  30 value 88.918603
iter  40 value 87.821298
iter  50 value 87.258883
iter  60 value 86.383588
iter  70 value 86.306526
iter  80 value 85.869921
iter  90 value 85.501581
iter 100 value 84.954646
final  value 84.954646 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.227831 
iter  10 value 94.117189
iter  20 value 94.013335
iter  30 value 93.770795
iter  40 value 89.987884
iter  50 value 88.871097
iter  60 value 88.004021
iter  70 value 87.659741
iter  80 value 87.203928
iter  90 value 86.410697
iter 100 value 83.746197
final  value 83.746197 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.323477 
iter  10 value 99.709806
iter  20 value 93.236771
iter  30 value 88.448206
iter  40 value 87.265178
iter  50 value 85.475640
iter  60 value 84.484549
iter  70 value 84.162954
iter  80 value 83.734410
iter  90 value 83.474511
iter 100 value 83.166875
final  value 83.166875 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.137654 
iter  10 value 91.325830
iter  20 value 89.381104
iter  30 value 88.937587
iter  40 value 88.080855
iter  50 value 87.687810
iter  60 value 87.053825
iter  70 value 86.798213
iter  80 value 86.688013
iter  90 value 86.518206
iter 100 value 85.130270
final  value 85.130270 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.836172 
iter  10 value 94.094332
iter  20 value 90.340232
iter  30 value 88.652230
iter  40 value 87.898450
iter  50 value 85.186789
iter  60 value 83.826079
iter  70 value 83.755276
iter  80 value 83.587843
iter  90 value 83.323951
iter 100 value 83.141269
final  value 83.141269 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.391546 
iter  10 value 93.856277
iter  20 value 89.432931
iter  30 value 87.695840
iter  40 value 87.312830
iter  50 value 87.142910
iter  60 value 86.773492
iter  70 value 85.888890
iter  80 value 85.259005
iter  90 value 83.349842
iter 100 value 82.965247
final  value 82.965247 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.155756 
iter  10 value 95.023922
iter  20 value 93.703905
iter  30 value 89.210196
iter  40 value 85.574724
iter  50 value 85.147454
iter  60 value 84.919080
iter  70 value 84.625731
iter  80 value 84.550173
iter  90 value 84.281801
iter 100 value 83.498906
final  value 83.498906 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.708299 
final  value 94.054502 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.400927 
final  value 94.054462 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.432052 
final  value 94.054223 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.788684 
final  value 94.054644 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.503108 
iter  10 value 94.054625
final  value 94.052920 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.219573 
iter  10 value 94.032813
iter  20 value 88.968171
iter  30 value 88.131821
iter  30 value 88.131821
final  value 88.131821 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.322159 
iter  10 value 93.980439
iter  20 value 93.921861
iter  30 value 93.139307
iter  40 value 92.816918
iter  50 value 92.810598
iter  60 value 92.810435
iter  70 value 92.324236
iter  80 value 91.788602
iter  90 value 88.504331
iter 100 value 84.234331
final  value 84.234331 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.011747 
iter  10 value 94.057500
iter  20 value 93.531172
final  value 93.510752 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.226958 
iter  10 value 94.057768
iter  20 value 93.986070
iter  30 value 92.340751
iter  40 value 92.263763
iter  50 value 92.263524
iter  60 value 92.245355
final  value 92.241323 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.868671 
iter  10 value 94.057606
iter  20 value 94.053007
iter  30 value 93.916699
final  value 93.916342 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.635497 
iter  10 value 94.056960
iter  20 value 89.568031
final  value 88.692038 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.885765 
iter  10 value 93.923960
iter  20 value 93.916230
iter  30 value 93.883502
iter  40 value 89.089493
iter  50 value 88.147272
iter  60 value 88.078931
final  value 88.078867 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.890136 
iter  10 value 94.059809
iter  20 value 88.735053
iter  30 value 86.569055
iter  40 value 82.873928
iter  50 value 82.189707
iter  60 value 82.188067
final  value 82.187346 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.800572 
iter  10 value 92.536791
iter  20 value 86.645908
iter  30 value 85.589789
iter  40 value 85.587006
iter  50 value 85.579537
iter  60 value 84.686002
iter  70 value 84.611386
iter  80 value 84.606690
final  value 84.606599 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.474596 
iter  10 value 93.356309
iter  20 value 93.341883
iter  30 value 93.335901
iter  40 value 93.268202
iter  50 value 93.226472
iter  60 value 93.219973
iter  70 value 93.218749
iter  80 value 92.843866
iter  90 value 88.983099
iter 100 value 87.863659
final  value 87.863659 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.312659 
iter  10 value 92.945375
final  value 92.945355 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.263129 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.181455 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.813898 
iter  10 value 89.329929
iter  20 value 84.636648
iter  30 value 84.633492
iter  30 value 84.633491
iter  40 value 83.681456
final  value 83.681351 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.802262 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.658148 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.034934 
final  value 94.052874 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.551063 
final  value 93.671508 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.661968 
final  value 94.052908 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.268067 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.797088 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.664515 
iter  10 value 93.428426
iter  20 value 86.583894
iter  30 value 82.605021
iter  40 value 78.680864
iter  50 value 76.369042
iter  60 value 76.300806
final  value 76.300787 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.083199 
iter  10 value 93.097519
iter  20 value 92.576818
final  value 92.551894 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.852719 
iter  10 value 94.052875
iter  20 value 93.972116
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.610111 
iter  10 value 92.945361
final  value 92.945355 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.188843 
iter  10 value 93.809094
iter  20 value 93.232274
iter  30 value 91.425987
iter  40 value 82.954103
iter  50 value 82.775211
iter  60 value 82.628433
iter  70 value 82.457397
iter  80 value 81.801307
iter  90 value 80.391998
iter 100 value 80.226198
final  value 80.226198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.419680 
iter  10 value 90.712904
iter  20 value 86.387623
iter  30 value 85.177197
iter  40 value 82.831871
iter  50 value 82.711218
iter  60 value 82.672609
iter  70 value 82.564314
iter  80 value 82.388301
iter  90 value 80.124111
iter 100 value 79.699282
final  value 79.699282 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.860493 
iter  10 value 94.063633
iter  20 value 84.135256
iter  30 value 83.621304
iter  40 value 82.638999
iter  50 value 82.399989
iter  60 value 82.383907
iter  70 value 82.383548
final  value 82.383500 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.567398 
iter  10 value 93.940431
iter  20 value 91.475587
iter  30 value 91.411411
iter  40 value 91.398195
iter  50 value 91.397543
final  value 91.397538 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.834498 
iter  10 value 94.058447
iter  20 value 93.374647
iter  30 value 93.271349
iter  40 value 93.229747
iter  50 value 91.157017
iter  60 value 83.010634
iter  70 value 80.870652
iter  80 value 80.449570
iter  90 value 79.733051
iter 100 value 79.076907
final  value 79.076907 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.804908 
iter  10 value 99.059916
iter  20 value 93.875312
iter  30 value 85.674533
iter  40 value 83.408778
iter  50 value 81.988116
iter  60 value 81.468857
iter  70 value 80.515881
iter  80 value 78.642613
iter  90 value 78.255090
iter 100 value 78.073826
final  value 78.073826 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.312011 
iter  10 value 94.234982
iter  20 value 93.197633
iter  30 value 92.295579
iter  40 value 90.999703
iter  50 value 86.726743
iter  60 value 86.304540
iter  70 value 84.495624
iter  80 value 81.922395
iter  90 value 79.914271
iter 100 value 78.922824
final  value 78.922824 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.068466 
iter  10 value 94.226755
iter  20 value 86.760960
iter  30 value 83.034517
iter  40 value 82.419050
iter  50 value 81.278404
iter  60 value 80.189091
iter  70 value 79.886644
iter  80 value 79.866046
iter  90 value 79.387368
iter 100 value 78.975337
final  value 78.975337 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.422540 
iter  10 value 94.989600
iter  20 value 94.064843
iter  30 value 92.876427
iter  40 value 92.172297
iter  50 value 87.029061
iter  60 value 85.471258
iter  70 value 81.808773
iter  80 value 80.995391
iter  90 value 80.270047
iter 100 value 79.892255
final  value 79.892255 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.383311 
iter  10 value 93.810125
iter  20 value 86.225996
iter  30 value 82.891391
iter  40 value 82.256731
iter  50 value 82.132163
iter  60 value 81.849818
iter  70 value 81.765271
iter  80 value 81.344881
iter  90 value 80.416225
iter 100 value 78.861877
final  value 78.861877 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.723428 
iter  10 value 93.362259
iter  20 value 91.024439
iter  30 value 85.749380
iter  40 value 81.886466
iter  50 value 81.169371
iter  60 value 80.059091
iter  70 value 79.524579
iter  80 value 78.588655
iter  90 value 78.120924
iter 100 value 77.776192
final  value 77.776192 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.344243 
iter  10 value 94.322000
iter  20 value 93.445168
iter  30 value 93.160594
iter  40 value 92.395157
iter  50 value 90.036542
iter  60 value 86.727607
iter  70 value 84.851845
iter  80 value 79.038210
iter  90 value 78.559079
iter 100 value 78.244954
final  value 78.244954 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.829954 
iter  10 value 95.266547
iter  20 value 86.423044
iter  30 value 81.925055
iter  40 value 80.144479
iter  50 value 78.187892
iter  60 value 77.762886
iter  70 value 77.643706
iter  80 value 77.596317
iter  90 value 77.374994
iter 100 value 77.191544
final  value 77.191544 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.234981 
iter  10 value 97.347029
iter  20 value 92.410873
iter  30 value 86.323156
iter  40 value 83.064021
iter  50 value 81.920346
iter  60 value 81.317809
iter  70 value 81.139316
iter  80 value 80.530729
iter  90 value 79.655230
iter 100 value 79.506628
final  value 79.506628 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.741935 
iter  10 value 93.846305
iter  20 value 85.947719
iter  30 value 84.426256
iter  40 value 84.072716
iter  50 value 83.679612
iter  60 value 82.707983
iter  70 value 81.711486
iter  80 value 78.843618
iter  90 value 78.002010
iter 100 value 77.737756
final  value 77.737756 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.429155 
final  value 94.054358 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.254230 
iter  10 value 94.054832
iter  20 value 94.028519
iter  30 value 92.946294
final  value 92.946290 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.978591 
iter  10 value 94.054756
iter  20 value 93.747245
iter  30 value 92.807816
iter  40 value 92.801840
iter  50 value 92.801535
iter  60 value 92.801228
iter  70 value 92.793659
iter  80 value 92.755254
iter  90 value 92.755005
final  value 92.755003 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.689285 
iter  10 value 92.947425
iter  20 value 92.946508
final  value 92.172121 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.000770 
final  value 94.054564 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.182932 
iter  10 value 94.057446
iter  20 value 94.052992
iter  30 value 92.732063
iter  40 value 91.901012
final  value 91.900996 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.521873 
iter  10 value 94.057140
iter  20 value 93.449081
iter  30 value 92.168526
iter  40 value 92.168045
iter  50 value 92.167973
final  value 92.167671 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.483725 
iter  10 value 92.096127
iter  20 value 91.914235
iter  30 value 91.911257
iter  40 value 91.910735
iter  50 value 91.908950
iter  60 value 91.908703
final  value 91.907810 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.463946 
iter  10 value 94.056911
iter  20 value 94.053005
final  value 94.052925 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.002940 
iter  10 value 92.950773
iter  20 value 92.842297
iter  30 value 92.827595
iter  40 value 92.334011
iter  50 value 92.096497
iter  60 value 92.042721
final  value 92.029964 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.307742 
iter  10 value 92.962724
iter  20 value 92.950510
iter  30 value 92.036038
iter  40 value 85.709263
iter  50 value 79.799100
iter  60 value 79.308933
iter  70 value 79.156958
iter  80 value 78.866627
iter  90 value 77.573203
iter 100 value 76.980787
final  value 76.980787 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.979956 
iter  10 value 94.060555
iter  20 value 93.978688
iter  30 value 85.533591
iter  40 value 84.491557
iter  50 value 80.236616
iter  60 value 80.141237
iter  70 value 80.134665
iter  80 value 79.470316
iter  90 value 78.333682
iter 100 value 78.256250
final  value 78.256250 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.467451 
iter  10 value 94.060913
iter  20 value 94.053941
iter  30 value 92.250207
final  value 92.248314 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.694189 
iter  10 value 88.859732
iter  20 value 86.484791
iter  30 value 86.454906
iter  40 value 86.452183
final  value 86.451104 
converged
Fitting Repeat 5 

# weights:  507
initial  value 136.917093 
iter  10 value 94.064753
iter  20 value 93.982676
iter  30 value 88.600358
iter  40 value 87.067079
iter  50 value 84.819313
iter  60 value 84.278832
iter  70 value 84.170449
iter  80 value 83.689077
iter  90 value 82.968493
iter 100 value 77.954147
final  value 77.954147 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.651693 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.534990 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.327150 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.105280 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.752195 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.501074 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.069255 
iter  10 value 89.487297
iter  20 value 89.069268
iter  30 value 89.069209
iter  40 value 89.067822
iter  50 value 89.066853
final  value 89.066850 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.590632 
final  value 94.467392 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.733862 
iter  10 value 85.460595
iter  20 value 85.198540
final  value 85.196923 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.047606 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.999275 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.973582 
iter  10 value 94.468005
final  value 94.467392 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.192489 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.731541 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.118245 
iter  10 value 90.724012
iter  20 value 90.716649
iter  30 value 90.716217
iter  30 value 90.716217
iter  30 value 90.716217
final  value 90.716217 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.849715 
iter  10 value 94.451507
iter  20 value 94.104324
iter  30 value 87.821209
iter  40 value 83.159706
iter  50 value 82.753665
iter  60 value 81.707948
iter  70 value 81.584766
final  value 81.583458 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.163178 
iter  10 value 90.929421
iter  20 value 85.143453
iter  30 value 80.514535
iter  40 value 80.235577
iter  50 value 79.888800
iter  60 value 79.746688
final  value 79.743729 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.277535 
iter  10 value 94.322505
iter  20 value 90.560994
iter  30 value 81.872321
iter  40 value 81.686843
iter  50 value 81.592469
iter  60 value 81.583732
final  value 81.583458 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.785119 
iter  10 value 94.487957
iter  20 value 93.928853
iter  30 value 88.152110
iter  40 value 87.526783
iter  50 value 83.144287
iter  60 value 82.890196
iter  70 value 81.208061
iter  80 value 80.749609
iter  90 value 80.405923
iter 100 value 80.182922
final  value 80.182922 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.635223 
iter  10 value 94.489353
iter  10 value 94.489353
iter  20 value 94.398624
iter  30 value 86.193280
iter  40 value 84.921599
iter  50 value 84.693784
iter  60 value 82.405625
iter  70 value 81.673660
iter  80 value 81.587629
iter  90 value 81.583523
final  value 81.583458 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.743544 
iter  10 value 92.264644
iter  20 value 83.886061
iter  30 value 83.605269
iter  40 value 81.533768
iter  50 value 80.266785
iter  60 value 79.539194
iter  70 value 79.310616
iter  80 value 79.247994
iter  90 value 79.147832
iter 100 value 79.126717
final  value 79.126717 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.533962 
iter  10 value 94.410839
iter  20 value 82.588099
iter  30 value 81.475363
iter  40 value 81.363209
iter  50 value 81.334611
iter  60 value 81.293502
iter  70 value 80.963211
iter  80 value 80.340849
iter  90 value 79.519744
iter 100 value 78.783365
final  value 78.783365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.524074 
iter  10 value 95.023119
iter  20 value 94.266659
iter  30 value 94.062381
iter  40 value 85.640967
iter  50 value 81.902089
iter  60 value 81.132665
iter  70 value 80.897091
iter  80 value 80.754666
iter  90 value 80.577003
iter 100 value 80.298508
final  value 80.298508 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.443609 
iter  10 value 99.981334
iter  20 value 92.133238
iter  30 value 84.223271
iter  40 value 83.895167
iter  50 value 83.736202
iter  60 value 81.918442
iter  70 value 80.289083
iter  80 value 79.920354
iter  90 value 79.210687
iter 100 value 78.899349
final  value 78.899349 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.574626 
iter  10 value 94.465905
iter  20 value 89.067730
iter  30 value 84.449326
iter  40 value 82.615875
iter  50 value 81.228908
iter  60 value 80.639362
iter  70 value 80.274024
iter  80 value 79.977297
iter  90 value 79.540084
iter 100 value 79.073789
final  value 79.073789 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.410865 
iter  10 value 94.864833
iter  20 value 94.490745
iter  30 value 93.918309
iter  40 value 92.056756
iter  50 value 85.399727
iter  60 value 83.870048
iter  70 value 82.565450
iter  80 value 82.303051
iter  90 value 82.069210
iter 100 value 80.731831
final  value 80.731831 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.219614 
iter  10 value 94.354501
iter  20 value 84.745491
iter  30 value 83.221065
iter  40 value 82.632717
iter  50 value 82.326381
iter  60 value 81.992150
iter  70 value 80.949048
iter  80 value 80.236192
iter  90 value 79.528269
iter 100 value 79.080374
final  value 79.080374 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.937565 
iter  10 value 93.446934
iter  20 value 85.899049
iter  30 value 82.689463
iter  40 value 81.349840
iter  50 value 81.142616
iter  60 value 80.697845
iter  70 value 80.174730
iter  80 value 79.856738
iter  90 value 79.588167
iter 100 value 79.118867
final  value 79.118867 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.326759 
iter  10 value 94.646235
iter  20 value 92.924304
iter  30 value 92.278060
iter  40 value 90.938267
iter  50 value 88.887062
iter  60 value 82.887156
iter  70 value 81.693503
iter  80 value 81.258217
iter  90 value 80.370452
iter 100 value 79.887347
final  value 79.887347 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.909441 
iter  10 value 87.867198
iter  20 value 84.708264
iter  30 value 82.850455
iter  40 value 81.023705
iter  50 value 80.772180
iter  60 value 80.558577
iter  70 value 80.228718
iter  80 value 79.591577
iter  90 value 79.404397
iter 100 value 79.101362
final  value 79.101362 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.874217 
iter  10 value 90.700183
iter  20 value 86.115409
iter  30 value 85.748575
iter  40 value 85.635178
iter  50 value 85.041538
iter  60 value 83.801989
iter  70 value 83.560504
iter  80 value 83.427876
final  value 83.427790 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.465253 
final  value 94.486080 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.672884 
final  value 94.485892 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.258688 
final  value 94.485704 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.369745 
iter  10 value 94.469197
iter  20 value 94.467709
iter  30 value 94.467401
final  value 94.467399 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.960676 
iter  10 value 91.682257
iter  20 value 91.656561
iter  30 value 91.621356
final  value 91.614658 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.393419 
iter  10 value 94.490602
iter  20 value 94.469813
iter  30 value 94.468852
iter  40 value 83.959164
iter  50 value 81.877215
iter  60 value 80.791847
iter  70 value 80.789440
iter  80 value 80.204369
iter  90 value 79.042936
iter 100 value 79.040950
final  value 79.040950 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.166405 
iter  10 value 94.504852
iter  20 value 93.366269
iter  30 value 83.196113
iter  40 value 83.164628
iter  50 value 83.154102
iter  60 value 83.142530
iter  70 value 83.094441
iter  80 value 83.006107
iter  80 value 83.006106
iter  80 value 83.006106
final  value 83.006106 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.147447 
iter  10 value 94.406117
iter  20 value 93.911077
iter  30 value 82.571641
iter  40 value 81.164982
iter  50 value 79.942041
iter  60 value 79.928247
iter  70 value 79.902456
iter  80 value 79.901806
iter  90 value 79.859603
iter 100 value 79.779267
final  value 79.779267 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.693887 
iter  10 value 94.472177
iter  20 value 94.467751
iter  30 value 83.258591
iter  40 value 83.188473
iter  50 value 83.187531
final  value 83.187525 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.390362 
iter  10 value 94.492094
iter  20 value 94.296318
iter  30 value 86.275041
iter  40 value 83.822543
iter  50 value 79.477831
iter  60 value 78.447222
iter  70 value 77.572300
iter  80 value 77.550910
iter  90 value 77.549953
iter 100 value 77.529245
final  value 77.529245 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.547181 
iter  10 value 94.492133
iter  20 value 94.484368
iter  30 value 86.556265
iter  40 value 82.942289
iter  50 value 82.224828
iter  60 value 81.247433
iter  70 value 81.169459
iter  80 value 81.143297
iter  90 value 80.819028
iter 100 value 79.797156
final  value 79.797156 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.688887 
iter  10 value 94.492296
iter  20 value 94.439367
iter  30 value 89.647497
iter  40 value 81.490136
iter  50 value 81.478567
iter  50 value 81.478567
iter  50 value 81.478567
final  value 81.478567 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.652958 
iter  10 value 94.492873
iter  20 value 94.485122
iter  30 value 94.476562
iter  40 value 94.214101
iter  50 value 92.955482
iter  60 value 91.510081
iter  70 value 91.508844
iter  80 value 91.274920
iter  90 value 83.880349
iter 100 value 81.800401
final  value 81.800401 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.954247 
iter  10 value 87.127128
iter  20 value 85.578091
iter  30 value 84.255853
iter  40 value 84.247131
iter  50 value 84.240734
iter  60 value 84.235763
iter  70 value 84.235133
final  value 84.234415 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.996602 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.736402 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.931578 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.096479 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.641933 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.551525 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.915791 
iter  10 value 93.183528
iter  20 value 91.085490
iter  30 value 83.731715
iter  40 value 83.487038
final  value 83.485378 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.780620 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.955631 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.290919 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.352842 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.939202 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.147990 
iter  10 value 94.327106
iter  20 value 94.325946
iter  20 value 94.325946
iter  20 value 94.325946
final  value 94.325946 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.645720 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.879025 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.192103 
iter  10 value 91.560377
iter  20 value 83.872667
iter  30 value 83.285822
iter  40 value 83.197849
iter  50 value 83.103931
iter  60 value 82.442480
iter  70 value 81.483322
iter  80 value 81.381723
iter  90 value 81.375785
final  value 81.375313 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.586709 
iter  10 value 94.460260
iter  20 value 94.260797
iter  30 value 88.383592
iter  40 value 87.562430
iter  50 value 84.930817
iter  60 value 84.479213
iter  70 value 84.457374
iter  80 value 84.112054
iter  90 value 83.644537
iter 100 value 83.451314
final  value 83.451314 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.215064 
iter  10 value 94.496401
iter  20 value 92.256575
iter  30 value 90.696888
iter  40 value 89.923466
iter  50 value 89.335836
iter  60 value 89.281161
final  value 89.280519 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.047517 
iter  10 value 94.490827
iter  20 value 94.479110
iter  30 value 90.750671
iter  40 value 90.072027
iter  50 value 89.772182
iter  60 value 89.523779
iter  70 value 89.407451
final  value 89.404632 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.833462 
iter  10 value 94.488350
iter  20 value 92.994730
iter  30 value 90.098122
iter  40 value 88.353408
iter  50 value 88.281876
iter  60 value 85.491488
iter  70 value 85.244689
iter  80 value 85.224855
iter  90 value 84.661646
iter 100 value 83.577244
final  value 83.577244 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.190276 
iter  10 value 94.591974
iter  20 value 88.091535
iter  30 value 86.390916
iter  40 value 85.848102
iter  50 value 85.064078
iter  60 value 81.913465
iter  70 value 80.295125
iter  80 value 78.994850
iter  90 value 78.784976
iter 100 value 78.429526
final  value 78.429526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.446282 
iter  10 value 94.538050
iter  20 value 92.923495
iter  30 value 90.975308
iter  40 value 85.850652
iter  50 value 85.445005
iter  60 value 83.113067
iter  70 value 81.564117
iter  80 value 81.360649
iter  90 value 81.060434
iter 100 value 79.429166
final  value 79.429166 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.517591 
iter  10 value 93.893708
iter  20 value 86.671601
iter  30 value 85.198480
iter  40 value 82.851741
iter  50 value 82.068451
iter  60 value 80.081739
iter  70 value 79.201349
iter  80 value 78.881050
iter  90 value 78.779124
iter 100 value 78.759375
final  value 78.759375 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.904349 
iter  10 value 94.377796
iter  20 value 92.047366
iter  30 value 90.606611
iter  40 value 89.664286
iter  50 value 89.580020
iter  60 value 89.434312
iter  70 value 85.671976
iter  80 value 82.046831
iter  90 value 80.135872
iter 100 value 79.180936
final  value 79.180936 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.965841 
iter  10 value 93.661776
iter  20 value 86.529828
iter  30 value 84.803490
iter  40 value 83.135567
iter  50 value 81.781824
iter  60 value 80.616320
iter  70 value 79.841516
iter  80 value 79.813423
iter  90 value 79.739328
iter 100 value 79.710257
final  value 79.710257 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.365127 
iter  10 value 93.243736
iter  20 value 90.050571
iter  30 value 84.101494
iter  40 value 80.225852
iter  50 value 79.822000
iter  60 value 79.668841
iter  70 value 79.648155
iter  80 value 79.625091
iter  90 value 79.595262
iter 100 value 79.231111
final  value 79.231111 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.293343 
iter  10 value 94.684474
iter  20 value 86.920006
iter  30 value 85.540523
iter  40 value 84.906997
iter  50 value 81.500310
iter  60 value 81.191276
iter  70 value 79.862985
iter  80 value 79.247489
iter  90 value 78.776539
iter 100 value 78.514521
final  value 78.514521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.696783 
iter  10 value 94.480186
iter  20 value 91.335953
iter  30 value 89.359741
iter  40 value 83.850463
iter  50 value 83.635502
iter  60 value 83.312486
iter  70 value 80.707030
iter  80 value 79.398951
iter  90 value 79.028711
iter 100 value 78.111019
final  value 78.111019 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.963538 
iter  10 value 92.819112
iter  20 value 84.032864
iter  30 value 83.238740
iter  40 value 80.531973
iter  50 value 79.178536
iter  60 value 78.714113
iter  70 value 78.510190
iter  80 value 78.394794
iter  90 value 78.251239
iter 100 value 78.130931
final  value 78.130931 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.112304 
iter  10 value 94.495251
iter  20 value 94.104538
iter  30 value 86.182682
iter  40 value 84.428893
iter  50 value 83.599349
iter  60 value 82.013365
iter  70 value 81.172892
iter  80 value 80.382725
iter  90 value 79.341486
iter 100 value 79.092022
final  value 79.092022 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.187487 
iter  10 value 94.486033
iter  20 value 94.377855
iter  30 value 90.555069
iter  40 value 82.706310
iter  50 value 82.619450
iter  60 value 82.506959
final  value 82.506313 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.476775 
iter  10 value 90.560642
final  value 90.557087 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.621448 
final  value 94.485815 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.312090 
final  value 94.486013 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.785927 
final  value 94.327705 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.143665 
iter  10 value 94.489120
iter  20 value 94.473984
iter  30 value 90.346316
iter  40 value 90.029044
iter  50 value 84.440193
iter  60 value 80.020929
iter  70 value 78.789220
iter  80 value 78.201278
iter  90 value 77.582485
final  value 77.552678 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.513898 
iter  10 value 94.487941
iter  20 value 94.474361
iter  30 value 94.269398
iter  40 value 91.543257
iter  50 value 90.144392
iter  60 value 88.194635
iter  70 value 86.130531
iter  80 value 86.079426
iter  90 value 85.937747
iter 100 value 85.912040
final  value 85.912040 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.154248 
iter  10 value 94.179565
iter  20 value 94.138953
iter  30 value 94.137512
iter  40 value 94.119979
iter  50 value 94.095200
iter  50 value 94.095199
iter  50 value 94.095199
final  value 94.095199 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.293629 
iter  10 value 94.280675
iter  20 value 94.138544
iter  30 value 93.443519
iter  40 value 93.058646
iter  50 value 90.554381
final  value 90.486653 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.281647 
iter  10 value 94.488811
iter  20 value 94.440903
final  value 94.275907 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.642195 
iter  10 value 94.492562
iter  20 value 94.437089
iter  30 value 93.046851
iter  40 value 83.682378
iter  50 value 82.890808
iter  60 value 82.627388
iter  70 value 82.616952
iter  80 value 82.616503
iter  90 value 81.184044
iter 100 value 79.044665
final  value 79.044665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.179964 
iter  10 value 94.283138
iter  20 value 94.236256
iter  30 value 94.234872
iter  40 value 88.194314
iter  50 value 83.549361
iter  60 value 83.179607
iter  70 value 83.179401
iter  80 value 83.176233
iter  90 value 82.258354
iter 100 value 82.204487
final  value 82.204487 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.249886 
iter  10 value 94.487959
iter  20 value 93.779553
iter  30 value 93.727760
iter  40 value 93.658498
iter  50 value 93.353824
iter  60 value 90.241979
iter  70 value 89.130441
iter  80 value 88.783018
final  value 88.783012 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.453786 
iter  10 value 94.217261
iter  20 value 94.142283
iter  30 value 93.048157
iter  40 value 82.481435
iter  50 value 81.620858
iter  60 value 79.569611
iter  70 value 78.676085
iter  80 value 77.999433
iter  90 value 77.458220
iter 100 value 76.565651
final  value 76.565651 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.387520 
iter  10 value 94.297876
iter  20 value 94.291867
iter  30 value 94.288753
iter  40 value 94.287425
iter  50 value 89.374342
iter  60 value 83.791659
iter  70 value 83.150349
iter  80 value 82.601673
iter  90 value 82.464871
iter 100 value 82.348133
final  value 82.348133 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.289512 
iter  10 value 116.386048
iter  20 value 108.500324
iter  30 value 107.831365
iter  40 value 106.530686
iter  50 value 105.516627
iter  60 value 104.661616
iter  70 value 103.457814
iter  80 value 101.914954
iter  90 value 101.719846
iter 100 value 101.415284
final  value 101.415284 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.379450 
iter  10 value 117.513494
iter  20 value 112.701267
iter  30 value 108.061364
iter  40 value 106.154802
iter  50 value 105.559125
iter  60 value 104.400491
iter  70 value 103.882150
iter  80 value 103.303603
iter  90 value 102.961610
iter 100 value 102.627327
final  value 102.627327 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 150.061243 
iter  10 value 116.503731
iter  20 value 111.910384
iter  30 value 107.211095
iter  40 value 102.411726
iter  50 value 102.007718
iter  60 value 101.540441
iter  70 value 101.229723
iter  80 value 100.929424
iter  90 value 100.643313
iter 100 value 100.401397
final  value 100.401397 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.513129 
iter  10 value 117.909825
iter  20 value 111.703366
iter  30 value 107.076991
iter  40 value 104.508163
iter  50 value 104.130567
iter  60 value 103.565191
iter  70 value 102.322685
iter  80 value 101.838427
iter  90 value 101.791432
iter 100 value 101.717772
final  value 101.717772 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.992218 
iter  10 value 118.898982
iter  20 value 117.356459
iter  30 value 109.594884
iter  40 value 104.980032
iter  50 value 104.497037
iter  60 value 103.730573
iter  70 value 102.550688
iter  80 value 101.577433
iter  90 value 101.177162
iter 100 value 100.753070
final  value 100.753070 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Mar 18 22:32:00 2025 
*********************************************** 
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 
 50.553   1.561 130.748