##############################################################################
##############################################################################
###
### 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_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-01-20 r87609)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* 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 ‘1.13.0’
* 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 ... INFO
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
FSmethod      17.946  0.798  18.961
var_imp       17.663  0.748  18.474
corr_plot     17.462  0.702  18.372
pred_ensembel  5.597  0.092   5.105
enrichfindP    0.164  0.028   7.650
* 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: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.21-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/4.5-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.13.0’
** 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 Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences"
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 96.740060 
iter  10 value 89.721723
iter  20 value 87.396925
iter  30 value 87.389851
final  value 87.389808 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.041132 
final  value 93.869755 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.136833 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.007744 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.799013 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.702496 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.884416 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.956719 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 127.837940 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.568181 
final  value 94.032968 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.532568 
iter  10 value 91.696951
iter  20 value 91.696173
final  value 91.696115 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.826140 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.072742 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.974546 
final  value 93.988096 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.911714 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.770378 
iter  10 value 93.982301
iter  20 value 86.747443
iter  30 value 84.879225
iter  40 value 84.195808
iter  50 value 83.740393
iter  60 value 83.728519
iter  70 value 83.728223
final  value 83.728212 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.936724 
iter  10 value 93.314381
iter  20 value 86.801318
iter  30 value 86.423239
iter  40 value 86.017698
iter  50 value 85.877713
iter  60 value 85.319345
iter  70 value 84.943792
iter  80 value 83.849222
iter  90 value 82.985103
iter 100 value 82.965936
final  value 82.965936 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.472268 
iter  10 value 94.053399
iter  20 value 92.601935
iter  30 value 90.386590
iter  40 value 88.835314
iter  50 value 84.702613
iter  60 value 84.122253
iter  70 value 83.000724
iter  80 value 82.971831
iter  90 value 82.940984
iter 100 value 82.918297
final  value 82.918297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.762760 
iter  10 value 88.764509
iter  20 value 84.461186
iter  30 value 83.994936
iter  40 value 83.846024
iter  50 value 83.785545
final  value 83.785496 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.498801 
iter  10 value 94.045681
iter  20 value 88.528618
iter  30 value 87.152280
iter  40 value 86.358507
iter  50 value 84.292064
iter  60 value 83.836313
iter  70 value 83.785548
final  value 83.785496 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.818829 
iter  10 value 90.232984
iter  20 value 85.732019
iter  30 value 85.426949
iter  40 value 84.376261
iter  50 value 84.124902
iter  60 value 84.008127
iter  70 value 83.920855
iter  80 value 83.798740
iter  90 value 83.029697
iter 100 value 82.562887
final  value 82.562887 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.394142 
iter  10 value 94.023100
iter  20 value 90.779812
iter  30 value 88.768954
iter  40 value 87.331363
iter  50 value 85.974250
iter  60 value 85.003100
iter  70 value 84.393989
iter  80 value 83.461427
iter  90 value 82.579130
iter 100 value 81.782874
final  value 81.782874 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.404690 
iter  10 value 94.175610
iter  20 value 93.971597
iter  30 value 93.160927
iter  40 value 92.824463
iter  50 value 92.483620
iter  60 value 92.448185
iter  70 value 92.420029
iter  80 value 91.265446
iter  90 value 89.546197
iter 100 value 84.958540
final  value 84.958540 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.556282 
iter  10 value 90.678974
iter  20 value 86.984140
iter  30 value 85.265491
iter  40 value 83.149867
iter  50 value 82.406102
iter  60 value 82.198095
iter  70 value 81.974420
iter  80 value 81.796201
iter  90 value 81.699546
iter 100 value 81.687087
final  value 81.687087 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.860270 
iter  10 value 94.118224
iter  20 value 93.865285
iter  30 value 93.377417
iter  40 value 88.248888
iter  50 value 86.343557
iter  60 value 84.724091
iter  70 value 83.548233
iter  80 value 82.772314
iter  90 value 82.175463
iter 100 value 81.752190
final  value 81.752190 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.528877 
iter  10 value 92.465541
iter  20 value 87.325439
iter  30 value 86.247084
iter  40 value 84.256672
iter  50 value 82.639651
iter  60 value 82.021418
iter  70 value 81.797413
iter  80 value 81.773669
iter  90 value 81.762387
iter 100 value 81.699846
final  value 81.699846 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.477518 
iter  10 value 91.171670
iter  20 value 86.337019
iter  30 value 85.389386
iter  40 value 83.460341
iter  50 value 82.979084
iter  60 value 82.708133
iter  70 value 82.495976
iter  80 value 82.393922
iter  90 value 82.189715
iter 100 value 82.116271
final  value 82.116271 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.736467 
iter  10 value 93.936599
iter  20 value 87.348228
iter  30 value 85.645741
iter  40 value 83.982860
iter  50 value 83.684673
iter  60 value 83.536947
iter  70 value 83.353819
iter  80 value 82.974105
iter  90 value 82.430941
iter 100 value 82.127585
final  value 82.127585 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.841241 
iter  10 value 96.253132
iter  20 value 89.130236
iter  30 value 85.959445
iter  40 value 85.299108
iter  50 value 84.707589
iter  60 value 83.257649
iter  70 value 82.356049
iter  80 value 82.256575
iter  90 value 82.011221
iter 100 value 81.391986
final  value 81.391986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 134.612280 
iter  10 value 94.284336
iter  20 value 93.672311
iter  30 value 90.612242
iter  40 value 86.565689
iter  50 value 83.741586
iter  60 value 83.109073
iter  70 value 82.841376
iter  80 value 82.550432
iter  90 value 82.370621
iter 100 value 82.140129
final  value 82.140129 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 116.918688 
final  value 94.054417 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.948327 
final  value 93.155551 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.236518 
final  value 94.054770 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.955683 
final  value 94.054272 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.035024 
final  value 94.054491 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.906489 
iter  10 value 94.038039
iter  20 value 94.033980
iter  30 value 93.968406
iter  40 value 92.166781
iter  50 value 89.759302
iter  60 value 85.500189
iter  70 value 85.250915
iter  80 value 85.249874
iter  90 value 84.609403
iter 100 value 84.556691
final  value 84.556691 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.971235 
iter  10 value 94.057127
iter  20 value 93.584800
iter  30 value 89.407054
iter  40 value 85.006624
iter  50 value 81.956788
iter  60 value 81.912220
iter  70 value 81.904482
iter  80 value 81.900588
iter  90 value 81.893966
iter 100 value 81.677453
final  value 81.677453 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.677321 
iter  10 value 94.053832
iter  20 value 94.052879
iter  30 value 88.920077
iter  40 value 85.410123
iter  50 value 84.279839
final  value 84.279671 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.416046 
iter  10 value 94.057904
iter  20 value 94.042112
iter  30 value 90.736039
iter  40 value 85.604227
iter  50 value 85.385146
iter  60 value 85.223773
iter  70 value 83.738571
iter  80 value 83.735081
final  value 83.733390 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.058730 
iter  10 value 94.058545
iter  20 value 93.680809
iter  30 value 92.797973
iter  40 value 92.766394
iter  50 value 92.764444
iter  60 value 92.763729
iter  70 value 92.762355
iter  80 value 92.759240
iter  90 value 92.758548
iter 100 value 92.659391
final  value 92.659391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.081204 
iter  10 value 94.041344
iter  20 value 94.005613
iter  30 value 88.128989
iter  40 value 85.115394
iter  40 value 85.115394
iter  40 value 85.115394
final  value 85.115394 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.832870 
iter  10 value 93.162189
iter  20 value 93.156938
iter  30 value 89.088116
iter  40 value 84.751570
iter  50 value 84.139415
iter  60 value 83.159773
iter  70 value 81.752387
iter  80 value 81.246990
iter  90 value 80.922121
iter 100 value 80.843676
final  value 80.843676 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.925301 
iter  10 value 89.062470
iter  20 value 85.847632
iter  30 value 85.094565
iter  40 value 84.924845
iter  50 value 84.807974
iter  60 value 83.998789
iter  70 value 83.266223
iter  80 value 83.126475
final  value 83.126216 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.421532 
iter  10 value 94.041203
iter  20 value 93.937731
iter  30 value 87.242692
iter  40 value 86.992661
iter  50 value 84.996044
iter  60 value 84.676644
iter  70 value 84.376566
iter  80 value 83.102297
iter  90 value 83.088691
iter 100 value 82.976326
final  value 82.976326 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.628035 
iter  10 value 94.061359
iter  20 value 94.053211
iter  30 value 94.018440
iter  40 value 86.269420
iter  50 value 84.181290
iter  60 value 82.204024
iter  70 value 82.078253
iter  80 value 80.954076
iter  90 value 80.530749
iter 100 value 80.524160
final  value 80.524160 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.008124 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.407602 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.834057 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.100157 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.990204 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.963203 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.674974 
iter  10 value 92.801133
final  value 92.790738 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.005542 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.692667 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.593844 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.807980 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.677756 
iter  10 value 88.480483
iter  20 value 84.480821
final  value 84.480000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.691263 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.370313 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.296762 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.086011 
iter  10 value 94.102402
iter  20 value 82.672457
iter  30 value 81.278566
iter  40 value 80.636001
iter  50 value 80.530924
iter  60 value 80.496603
final  value 80.496451 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.489990 
iter  10 value 94.477841
iter  20 value 94.327247
iter  30 value 92.426654
iter  40 value 78.999502
iter  50 value 78.122834
iter  60 value 77.086055
iter  70 value 76.462531
iter  80 value 76.062818
final  value 76.062198 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.613536 
iter  10 value 94.212791
iter  20 value 89.422361
iter  30 value 86.265937
iter  40 value 80.239102
iter  50 value 79.405399
iter  60 value 77.830342
iter  70 value 76.422211
iter  80 value 76.101241
iter  90 value 75.694515
final  value 75.694498 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.025339 
iter  10 value 94.228137
iter  20 value 93.528132
iter  30 value 93.439785
iter  40 value 92.956182
iter  50 value 86.929667
iter  60 value 84.992632
iter  70 value 82.086137
iter  80 value 81.138397
iter  90 value 80.654170
iter 100 value 80.498022
final  value 80.498022 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.951534 
iter  10 value 93.725006
iter  20 value 93.340890
iter  30 value 82.197801
iter  40 value 78.189041
iter  50 value 77.342314
iter  60 value 76.496214
iter  70 value 76.191961
iter  80 value 75.820893
final  value 75.694498 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.315242 
iter  10 value 93.872294
iter  20 value 90.585709
iter  30 value 83.251123
iter  40 value 79.383135
iter  50 value 79.048754
iter  60 value 78.390450
iter  70 value 76.968470
iter  80 value 75.162750
iter  90 value 74.060770
iter 100 value 73.952408
final  value 73.952408 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.564452 
iter  10 value 94.129680
iter  20 value 93.592249
iter  30 value 85.565001
iter  40 value 82.384224
iter  50 value 81.760679
iter  60 value 81.027390
iter  70 value 75.794395
iter  80 value 75.551229
iter  90 value 74.908754
iter 100 value 74.766514
final  value 74.766514 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.765505 
iter  10 value 95.437895
iter  20 value 90.225488
iter  30 value 86.131687
iter  40 value 82.707817
iter  50 value 77.212895
iter  60 value 76.060429
iter  70 value 74.730362
iter  80 value 73.875606
iter  90 value 73.558178
iter 100 value 73.430068
final  value 73.430068 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.788379 
iter  10 value 94.586854
iter  20 value 88.158354
iter  30 value 84.887893
iter  40 value 83.659381
iter  50 value 82.990715
iter  60 value 81.392604
iter  70 value 79.010281
iter  80 value 78.529157
iter  90 value 78.418413
iter 100 value 77.572091
final  value 77.572091 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.432453 
iter  10 value 92.135166
iter  20 value 81.784405
iter  30 value 81.098518
iter  40 value 81.072883
iter  50 value 80.963639
iter  60 value 77.881948
iter  70 value 75.693585
iter  80 value 74.167547
iter  90 value 73.968037
iter 100 value 73.676423
final  value 73.676423 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 133.156080 
iter  10 value 94.459953
iter  20 value 85.226242
iter  30 value 82.822715
iter  40 value 78.860205
iter  50 value 77.019692
iter  60 value 76.929869
iter  70 value 76.254869
iter  80 value 75.835658
iter  90 value 74.959922
iter 100 value 73.993315
final  value 73.993315 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.062283 
iter  10 value 94.266386
iter  20 value 85.209951
iter  30 value 80.738415
iter  40 value 80.179286
iter  50 value 78.787283
iter  60 value 77.251902
iter  70 value 74.557156
iter  80 value 74.327560
iter  90 value 74.000596
iter 100 value 73.638039
final  value 73.638039 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.551728 
iter  10 value 94.224496
iter  20 value 84.273678
iter  30 value 78.993363
iter  40 value 78.301116
iter  50 value 77.244583
iter  60 value 76.856309
iter  70 value 76.039342
iter  80 value 75.536323
iter  90 value 74.662482
iter 100 value 74.247272
final  value 74.247272 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.568521 
iter  10 value 94.986214
iter  20 value 85.781148
iter  30 value 84.033171
iter  40 value 80.158615
iter  50 value 77.434285
iter  60 value 76.352378
iter  70 value 75.803106
iter  80 value 74.772470
iter  90 value 74.386916
iter 100 value 74.324926
final  value 74.324926 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.237103 
iter  10 value 89.330477
iter  20 value 82.874122
iter  30 value 79.011911
iter  40 value 78.263688
iter  50 value 76.005238
iter  60 value 74.925985
iter  70 value 74.368523
iter  80 value 73.698386
iter  90 value 73.592402
iter 100 value 73.474672
final  value 73.474672 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 115.536102 
final  value 94.485700 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.578947 
iter  10 value 94.486064
iter  20 value 94.059429
iter  30 value 90.075876
iter  40 value 88.865530
iter  50 value 88.859486
iter  60 value 88.134283
iter  70 value 87.803812
iter  80 value 87.803606
iter  90 value 87.799628
iter 100 value 87.798309
final  value 87.798309 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.977978 
final  value 94.485876 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.414049 
final  value 94.485754 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.122477 
iter  10 value 92.714574
iter  20 value 92.541725
final  value 92.541621 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.352386 
iter  10 value 94.488701
iter  20 value 94.435263
iter  30 value 81.318824
iter  40 value 80.250448
iter  50 value 77.503330
iter  60 value 77.396357
iter  70 value 77.359748
iter  80 value 76.045394
iter  90 value 74.304416
iter 100 value 73.000959
final  value 73.000959 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.942927 
iter  10 value 92.751267
iter  20 value 92.743357
iter  30 value 92.680089
iter  40 value 92.628546
final  value 92.627921 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.044973 
iter  10 value 84.680999
iter  20 value 80.068527
iter  30 value 80.065175
final  value 80.065080 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.001488 
iter  10 value 91.070111
iter  20 value 91.066297
iter  30 value 82.910325
iter  40 value 80.108451
final  value 80.103823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.811760 
iter  10 value 94.489875
iter  20 value 94.484667
final  value 94.484598 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.056969 
iter  10 value 94.492051
iter  20 value 81.651010
iter  30 value 81.226296
iter  40 value 81.219241
iter  50 value 80.137891
iter  60 value 80.128426
final  value 80.128329 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.099451 
iter  10 value 94.490367
iter  20 value 89.182998
iter  30 value 84.315608
iter  40 value 78.863120
iter  50 value 77.832745
iter  60 value 77.333980
final  value 77.332879 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.240040 
iter  10 value 94.492934
iter  20 value 94.453404
iter  30 value 82.859662
iter  40 value 80.878244
iter  50 value 80.868714
iter  60 value 77.406212
iter  70 value 76.444688
iter  80 value 76.291113
iter  90 value 76.130682
iter 100 value 76.128245
final  value 76.128245 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.593221 
iter  10 value 94.363021
iter  20 value 94.256026
iter  30 value 87.290419
iter  40 value 87.041444
final  value 87.041392 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.592841 
iter  10 value 93.386030
iter  20 value 92.984240
iter  30 value 92.459146
iter  40 value 92.455042
final  value 92.454466 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.788734 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.714308 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.240486 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.926558 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.052214 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.229046 
iter  10 value 92.235849
iter  20 value 88.588315
iter  30 value 88.587989
iter  40 value 88.366382
final  value 88.311610 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.949129 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.829194 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.428411 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.565278 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.906603 
iter  10 value 92.688762
iter  20 value 89.718499
iter  30 value 86.592068
final  value 86.588623 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.473595 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.038659 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.501341 
final  value 94.473119 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.700408 
iter  10 value 94.300531
final  value 94.280105 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.871219 
iter  10 value 94.381537
iter  20 value 92.426753
iter  30 value 90.997597
iter  40 value 90.715468
iter  50 value 88.462646
iter  60 value 87.661866
iter  70 value 86.904273
iter  80 value 85.403909
iter  90 value 84.463302
iter 100 value 84.308162
final  value 84.308162 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.613174 
iter  10 value 94.490398
iter  20 value 94.235798
iter  30 value 91.224153
iter  40 value 88.292503
iter  50 value 87.942421
iter  60 value 87.098778
iter  70 value 84.716088
iter  80 value 84.482603
iter  90 value 84.394066
iter 100 value 84.339401
final  value 84.339401 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.764514 
iter  10 value 94.488813
iter  20 value 94.278370
iter  30 value 93.017767
iter  40 value 92.557656
iter  50 value 92.099336
iter  60 value 88.674852
iter  70 value 88.005820
iter  80 value 86.976971
iter  90 value 85.795913
iter 100 value 84.627414
final  value 84.627414 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.871822 
iter  10 value 94.490869
iter  20 value 89.955901
iter  30 value 88.534214
iter  40 value 88.392082
iter  50 value 87.985276
iter  60 value 87.834213
iter  70 value 87.774158
iter  80 value 86.257598
iter  90 value 85.843354
iter 100 value 85.786384
final  value 85.786384 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.452584 
iter  10 value 93.824854
iter  20 value 92.932085
iter  30 value 91.722285
iter  40 value 90.393495
iter  50 value 88.239556
iter  60 value 84.902346
iter  70 value 84.295396
iter  80 value 84.118468
iter  90 value 84.039636
iter 100 value 83.969091
final  value 83.969091 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.534801 
iter  10 value 94.649262
iter  20 value 89.305317
iter  30 value 88.691940
iter  40 value 88.407679
iter  50 value 87.405509
iter  60 value 84.898922
iter  70 value 83.931330
iter  80 value 83.223151
iter  90 value 83.171246
iter 100 value 83.116483
final  value 83.116483 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.655399 
iter  10 value 93.716152
iter  20 value 87.575006
iter  30 value 87.224203
iter  40 value 86.715146
iter  50 value 84.960470
iter  60 value 83.575885
iter  70 value 83.363287
iter  80 value 83.344043
iter  90 value 83.249391
iter 100 value 83.072880
final  value 83.072880 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.645289 
iter  10 value 94.351762
iter  20 value 91.362994
iter  30 value 87.636768
iter  40 value 86.256531
iter  50 value 84.988334
iter  60 value 84.257388
iter  70 value 83.659127
iter  80 value 83.345627
iter  90 value 83.099336
iter 100 value 82.941495
final  value 82.941495 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.943251 
iter  10 value 94.295067
iter  20 value 92.146395
iter  30 value 90.109950
iter  40 value 88.715873
iter  50 value 88.591106
iter  60 value 88.457022
iter  70 value 88.187346
iter  80 value 88.089253
iter  90 value 86.668377
iter 100 value 86.123562
final  value 86.123562 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.508427 
iter  10 value 94.392922
iter  20 value 89.163345
iter  30 value 87.468915
iter  40 value 85.864922
iter  50 value 84.858867
iter  60 value 84.359177
iter  70 value 83.663429
iter  80 value 83.021359
iter  90 value 82.969975
iter 100 value 82.945009
final  value 82.945009 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.032505 
iter  10 value 94.483435
iter  20 value 91.321878
iter  30 value 87.766826
iter  40 value 86.881860
iter  50 value 85.975118
iter  60 value 85.779710
iter  70 value 83.772425
iter  80 value 83.196391
iter  90 value 83.002621
iter 100 value 82.877083
final  value 82.877083 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.583377 
iter  10 value 94.572473
iter  20 value 93.763044
iter  30 value 89.655495
iter  40 value 88.514900
iter  50 value 87.848351
iter  60 value 86.783560
iter  70 value 85.050925
iter  80 value 84.041095
iter  90 value 83.072341
iter 100 value 82.760825
final  value 82.760825 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.281243 
iter  10 value 94.711557
iter  20 value 93.607029
iter  30 value 89.692094
iter  40 value 88.147611
iter  50 value 86.883046
iter  60 value 85.518780
iter  70 value 83.958457
iter  80 value 83.488408
iter  90 value 83.134298
iter 100 value 83.096278
final  value 83.096278 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.941241 
iter  10 value 94.443962
iter  20 value 88.740283
iter  30 value 87.511335
iter  40 value 85.551178
iter  50 value 84.900248
iter  60 value 84.448758
iter  70 value 83.465831
iter  80 value 83.058249
iter  90 value 82.961692
iter 100 value 82.859007
final  value 82.859007 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.356213 
iter  10 value 94.486376
iter  20 value 90.091211
iter  30 value 86.470053
iter  40 value 84.408563
iter  50 value 84.075649
iter  60 value 83.356141
iter  70 value 83.123562
iter  80 value 82.794294
iter  90 value 82.673863
iter 100 value 82.591391
final  value 82.591391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.253271 
iter  10 value 94.485914
iter  20 value 94.484224
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.895564 
final  value 94.485666 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.132245 
final  value 94.485765 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.117015 
iter  10 value 94.485843
iter  20 value 94.482586
iter  30 value 88.271791
iter  40 value 88.219676
iter  50 value 88.214863
iter  50 value 88.214862
iter  60 value 88.214782
iter  70 value 88.214108
iter  80 value 88.213496
iter  90 value 88.134431
iter 100 value 88.126841
final  value 88.126841 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.016484 
iter  10 value 94.486072
iter  20 value 94.477336
iter  30 value 87.403102
iter  40 value 87.331159
iter  50 value 87.273909
iter  60 value 87.238879
iter  70 value 86.891969
iter  80 value 86.066851
iter  90 value 86.049789
final  value 86.049695 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.693111 
iter  10 value 94.279449
iter  20 value 94.257990
iter  30 value 94.256088
iter  40 value 94.254156
final  value 94.253660 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.028817 
iter  10 value 94.489178
iter  20 value 94.437074
iter  30 value 94.264970
iter  40 value 94.264929
iter  40 value 94.264929
iter  40 value 94.264929
final  value 94.264929 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.920177 
iter  10 value 94.488507
iter  20 value 94.484227
iter  30 value 90.905381
iter  40 value 89.476581
iter  50 value 88.648496
iter  60 value 87.569112
iter  70 value 87.568057
iter  80 value 87.527700
iter  90 value 86.060277
iter 100 value 85.228097
final  value 85.228097 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.685351 
iter  10 value 93.797547
iter  20 value 92.593813
iter  30 value 92.400689
iter  40 value 92.142128
iter  50 value 92.138743
iter  60 value 92.137389
iter  70 value 92.116101
iter  80 value 92.071113
iter  90 value 92.069276
iter 100 value 86.462175
final  value 86.462175 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.394142 
iter  10 value 94.489663
iter  20 value 93.844103
iter  30 value 91.266785
iter  40 value 88.156880
iter  50 value 86.555931
iter  60 value 85.550090
iter  70 value 85.394156
iter  80 value 85.375984
iter  90 value 85.375651
iter 100 value 85.375525
final  value 85.375525 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.644028 
iter  10 value 94.492387
iter  20 value 94.445846
iter  30 value 89.833382
iter  40 value 89.810000
iter  50 value 88.686392
iter  60 value 87.701662
iter  70 value 87.685343
iter  80 value 87.538668
final  value 87.538623 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.209596 
iter  10 value 94.475129
iter  20 value 94.468396
iter  30 value 94.467052
iter  40 value 93.727656
iter  50 value 93.126041
iter  60 value 92.883717
iter  70 value 92.210742
iter  80 value 91.970195
final  value 91.969772 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.797567 
iter  10 value 94.491745
iter  20 value 94.461347
iter  30 value 93.242153
iter  40 value 90.308613
iter  50 value 84.362547
iter  60 value 83.572954
iter  70 value 82.439474
iter  80 value 82.001882
iter  90 value 81.764474
iter 100 value 81.642425
final  value 81.642425 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.435798 
iter  10 value 90.510823
iter  20 value 90.421253
iter  30 value 89.858754
iter  40 value 89.846772
iter  50 value 87.874135
iter  60 value 87.291679
iter  70 value 87.288267
iter  80 value 87.285947
final  value 87.285790 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.979308 
iter  10 value 94.321810
iter  20 value 94.279074
iter  30 value 88.762451
iter  40 value 88.749129
iter  50 value 88.610655
iter  60 value 87.079500
iter  70 value 86.872756
iter  80 value 86.871825
iter  90 value 86.788127
iter 100 value 86.783814
final  value 86.783814 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.492878 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.196503 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.760714 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.775888 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.558216 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.177670 
iter  10 value 92.288692
iter  20 value 92.281088
final  value 92.281082 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.335084 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.340192 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.309276 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.333303 
final  value 94.011429 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.108230 
iter  10 value 92.712272
iter  20 value 92.223960
iter  30 value 92.213882
final  value 92.213869 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.141274 
iter  10 value 92.282026
iter  20 value 92.272531
final  value 92.272521 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.594116 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.787618 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.400557 
iter  10 value 92.286541
iter  20 value 92.281087
final  value 92.281082 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.078537 
iter  10 value 93.959344
iter  20 value 92.874675
iter  30 value 92.732734
iter  40 value 89.112802
iter  50 value 82.795023
iter  60 value 82.622205
iter  70 value 82.105622
iter  80 value 80.721529
iter  90 value 80.509938
iter 100 value 80.095784
final  value 80.095784 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 113.252196 
iter  10 value 93.887840
iter  20 value 92.302542
iter  30 value 86.587365
iter  40 value 86.158308
iter  50 value 85.733259
iter  60 value 85.458333
iter  70 value 84.996039
iter  80 value 84.622664
iter  90 value 84.584282
final  value 84.584281 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.394688 
iter  10 value 93.334533
iter  20 value 89.681559
iter  30 value 89.045230
iter  40 value 86.498721
iter  50 value 85.333553
iter  60 value 84.425917
iter  70 value 84.213573
iter  80 value 84.155107
final  value 84.155055 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.199429 
iter  10 value 93.853390
iter  20 value 90.137072
iter  30 value 88.276050
iter  40 value 88.102678
iter  50 value 88.013549
iter  60 value 84.576596
iter  70 value 84.473392
iter  80 value 84.469553
final  value 84.469519 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.164938 
iter  10 value 94.054966
iter  20 value 90.056783
iter  30 value 88.177238
iter  40 value 87.607789
iter  50 value 86.782840
iter  60 value 85.994793
iter  70 value 85.220728
iter  80 value 84.539623
iter  90 value 84.469747
final  value 84.469519 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.405610 
iter  10 value 94.400648
iter  20 value 88.835659
iter  30 value 85.579729
iter  40 value 83.877717
iter  50 value 83.525420
iter  60 value 82.350126
iter  70 value 81.509679
iter  80 value 80.957022
iter  90 value 80.645069
iter 100 value 80.447697
final  value 80.447697 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 135.749141 
iter  10 value 94.053862
iter  20 value 88.127292
iter  30 value 86.420123
iter  40 value 86.333097
iter  50 value 85.525480
iter  60 value 84.076418
iter  70 value 83.598299
iter  80 value 83.464462
iter  90 value 83.431826
iter 100 value 83.309205
final  value 83.309205 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.107731 
iter  10 value 94.056575
iter  20 value 92.714940
iter  30 value 88.976492
iter  40 value 85.437340
iter  50 value 83.319490
iter  60 value 83.077086
iter  70 value 83.006217
iter  80 value 81.670270
iter  90 value 80.034042
iter 100 value 79.685174
final  value 79.685174 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.397382 
iter  10 value 93.214037
iter  20 value 88.327393
iter  30 value 84.517801
iter  40 value 81.200063
iter  50 value 78.801006
iter  60 value 78.334618
iter  70 value 78.284832
iter  80 value 78.171099
iter  90 value 78.106126
iter 100 value 78.094145
final  value 78.094145 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.961971 
iter  10 value 92.737725
iter  20 value 87.691947
iter  30 value 86.602201
iter  40 value 85.262540
iter  50 value 84.457174
iter  60 value 82.277789
iter  70 value 81.533022
iter  80 value 80.656376
iter  90 value 79.812059
iter 100 value 78.926971
final  value 78.926971 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.834204 
iter  10 value 91.982592
iter  20 value 87.193735
iter  30 value 86.480068
iter  40 value 86.262270
iter  50 value 82.533020
iter  60 value 80.981533
iter  70 value 79.865401
iter  80 value 79.214617
iter  90 value 78.666940
iter 100 value 77.979643
final  value 77.979643 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.796944 
iter  10 value 93.220474
iter  20 value 91.822707
iter  30 value 88.720304
iter  40 value 82.557056
iter  50 value 80.986416
iter  60 value 80.235669
iter  70 value 78.884378
iter  80 value 78.458778
iter  90 value 78.341581
iter 100 value 78.190809
final  value 78.190809 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.045712 
iter  10 value 99.112997
iter  20 value 91.425142
iter  30 value 89.130061
iter  40 value 85.801407
iter  50 value 84.406073
iter  60 value 81.674705
iter  70 value 80.016451
iter  80 value 79.490705
iter  90 value 78.849864
iter 100 value 78.209380
final  value 78.209380 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.298819 
iter  10 value 94.058311
iter  20 value 92.041566
iter  30 value 86.015040
iter  40 value 85.120806
iter  50 value 84.343580
iter  60 value 83.434435
iter  70 value 82.082998
iter  80 value 81.935488
iter  90 value 80.403868
iter 100 value 79.669443
final  value 79.669443 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.708898 
iter  10 value 94.080618
iter  20 value 92.488640
iter  30 value 86.105340
iter  40 value 82.722775
iter  50 value 80.699091
iter  60 value 80.509630
iter  70 value 80.107803
iter  80 value 80.088983
iter  90 value 80.005832
iter 100 value 79.788277
final  value 79.788277 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.848819 
final  value 94.054674 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.563460 
iter  10 value 94.054849
iter  20 value 94.052916
iter  30 value 92.305871
iter  40 value 92.295476
iter  50 value 92.292204
iter  60 value 92.289730
iter  60 value 92.289729
iter  60 value 92.289729
final  value 92.289729 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.891174 
final  value 94.054448 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.332653 
iter  10 value 94.054327
final  value 94.053095 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.406874 
final  value 94.054822 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.875693 
iter  10 value 94.059009
iter  20 value 93.695659
iter  30 value 88.605298
iter  40 value 82.978850
iter  50 value 82.949396
iter  60 value 82.944318
iter  70 value 82.943267
iter  80 value 82.212999
iter  90 value 81.922151
iter 100 value 80.770160
final  value 80.770160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.702770 
iter  10 value 91.857594
iter  20 value 91.372370
iter  30 value 90.834445
iter  40 value 90.831665
iter  50 value 90.705613
iter  60 value 90.470412
iter  70 value 90.469607
iter  80 value 90.469056
final  value 90.468634 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.055851 
iter  10 value 94.058174
iter  20 value 94.053030
iter  30 value 92.292469
final  value 92.286170 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.691130 
iter  10 value 92.294953
iter  20 value 92.290873
iter  30 value 87.026490
iter  40 value 82.958981
iter  50 value 82.925158
iter  60 value 81.990647
iter  70 value 78.078127
iter  80 value 76.934301
iter  90 value 76.375513
iter 100 value 76.067483
final  value 76.067483 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.611822 
iter  10 value 92.832538
iter  20 value 92.177136
iter  30 value 92.135032
iter  40 value 92.088226
iter  50 value 92.085288
iter  60 value 88.533216
iter  70 value 85.848798
iter  80 value 85.846738
iter  90 value 85.035772
iter 100 value 83.841044
final  value 83.841044 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.200010 
iter  10 value 94.056004
iter  20 value 92.287072
iter  30 value 86.910433
iter  40 value 86.787838
iter  50 value 86.787633
iter  60 value 83.876063
iter  70 value 83.411200
iter  80 value 82.463777
iter  90 value 82.294753
iter 100 value 82.294180
final  value 82.294180 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.959479 
iter  10 value 93.384547
iter  20 value 93.365647
iter  30 value 92.901984
iter  40 value 86.067150
iter  50 value 83.661908
iter  60 value 83.507440
final  value 83.507372 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.809684 
iter  10 value 94.060959
iter  20 value 93.997480
iter  30 value 93.669323
iter  40 value 90.082660
iter  50 value 84.794317
iter  60 value 84.084615
iter  70 value 83.417615
final  value 83.415937 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.376781 
iter  10 value 90.220473
iter  20 value 81.966867
iter  30 value 80.997287
iter  40 value 80.461523
iter  50 value 80.275241
iter  60 value 80.176494
iter  70 value 80.080285
final  value 80.079534 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.405624 
iter  10 value 92.328994
iter  20 value 92.296804
iter  30 value 92.286636
final  value 92.286533 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.735513 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.205679 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.483470 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.061130 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.385835 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.308185 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.068767 
iter  10 value 94.428657
final  value 94.423530 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.396481 
iter  10 value 94.529087
iter  20 value 94.428873
final  value 94.428840 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.949295 
iter  10 value 94.481829
final  value 94.481804 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.397656 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.176391 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.696333 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.484195 
final  value 93.783647 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.607189 
final  value 94.423529 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.111989 
final  value 93.755649 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.520655 
iter  10 value 94.488759
iter  20 value 94.466063
iter  30 value 93.383875
iter  40 value 93.266746
iter  50 value 93.195981
iter  60 value 88.052207
iter  70 value 86.554712
iter  80 value 85.579150
iter  90 value 85.404892
iter 100 value 85.372665
final  value 85.372665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 117.697983 
iter  10 value 94.323701
iter  20 value 86.098016
iter  30 value 85.682737
iter  40 value 85.255948
iter  50 value 85.091008
iter  60 value 84.609808
iter  70 value 84.486021
iter  80 value 84.460251
iter  90 value 84.445872
final  value 84.445649 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.132862 
iter  10 value 94.297163
iter  20 value 90.800859
iter  30 value 88.414774
iter  40 value 87.896413
iter  50 value 86.490816
iter  60 value 86.020896
iter  70 value 85.757933
iter  80 value 85.351765
final  value 85.330886 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.092341 
iter  10 value 94.414648
iter  20 value 93.516879
iter  30 value 93.215415
iter  40 value 93.050502
iter  50 value 92.204792
iter  60 value 92.004030
final  value 92.001615 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.023803 
iter  10 value 94.488862
iter  20 value 93.658219
iter  30 value 92.850468
iter  40 value 89.075358
iter  50 value 84.838760
iter  60 value 84.543943
iter  70 value 84.224652
iter  80 value 84.124248
iter  90 value 84.091428
iter 100 value 83.795060
final  value 83.795060 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.522907 
iter  10 value 93.928333
iter  20 value 90.146755
iter  30 value 88.522154
iter  40 value 87.613008
iter  50 value 85.013905
iter  60 value 84.356579
iter  70 value 84.180318
iter  80 value 84.054992
iter  90 value 83.626770
iter 100 value 83.457602
final  value 83.457602 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.108630 
iter  10 value 94.755654
iter  20 value 89.409926
iter  30 value 87.379940
iter  40 value 85.961799
iter  50 value 84.085292
iter  60 value 83.603211
iter  70 value 83.287194
iter  80 value 83.105001
iter  90 value 82.577961
iter 100 value 82.298030
final  value 82.298030 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.929509 
iter  10 value 94.798269
iter  20 value 86.783595
iter  30 value 85.539062
iter  40 value 85.238384
iter  50 value 84.944168
iter  60 value 84.456991
iter  70 value 83.652779
iter  80 value 83.417658
iter  90 value 83.002650
iter 100 value 82.846983
final  value 82.846983 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.772064 
iter  10 value 90.282620
iter  20 value 85.197350
iter  30 value 84.592878
iter  40 value 84.446206
iter  50 value 84.272414
iter  60 value 84.123564
iter  70 value 84.047562
iter  80 value 83.977859
iter  90 value 83.618358
iter 100 value 83.449551
final  value 83.449551 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.494800 
iter  10 value 94.519883
iter  20 value 94.402662
iter  30 value 91.874583
iter  40 value 88.869835
iter  50 value 87.549218
iter  60 value 87.072461
iter  70 value 84.106215
iter  80 value 83.170980
iter  90 value 82.968925
iter 100 value 82.843762
final  value 82.843762 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.441585 
iter  10 value 94.818585
iter  20 value 90.743160
iter  30 value 89.035260
iter  40 value 85.923121
iter  50 value 85.525033
iter  60 value 85.284876
iter  70 value 84.047328
iter  80 value 83.546297
iter  90 value 83.022872
iter 100 value 82.960435
final  value 82.960435 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.119409 
iter  10 value 95.543191
iter  20 value 94.379879
iter  30 value 89.777312
iter  40 value 88.527676
iter  50 value 86.486502
iter  60 value 84.323897
iter  70 value 83.386314
iter  80 value 83.049488
iter  90 value 82.625870
iter 100 value 82.342930
final  value 82.342930 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.206726 
iter  10 value 94.400717
iter  20 value 88.698666
iter  30 value 87.980980
iter  40 value 87.700135
iter  50 value 85.855569
iter  60 value 85.522887
iter  70 value 85.025825
iter  80 value 83.333227
iter  90 value 82.915180
iter 100 value 82.749244
final  value 82.749244 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.006326 
iter  10 value 94.515429
iter  20 value 94.408002
iter  30 value 89.494709
iter  40 value 88.717640
iter  50 value 85.524318
iter  60 value 84.310670
iter  70 value 84.039477
iter  80 value 83.061988
iter  90 value 82.427167
iter 100 value 82.282140
final  value 82.282140 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.136660 
iter  10 value 94.846124
iter  20 value 94.698773
iter  30 value 86.368420
iter  40 value 85.388665
iter  50 value 84.976289
iter  60 value 84.364793
iter  70 value 84.134513
iter  80 value 84.116921
iter  90 value 84.009866
iter 100 value 83.187816
final  value 83.187816 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.654163 
iter  10 value 91.978422
final  value 91.978265 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.918472 
final  value 94.485692 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.802915 
iter  10 value 94.485815
iter  20 value 94.481256
final  value 94.467404 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.426655 
final  value 93.785366 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.663059 
final  value 94.485942 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.922521 
iter  10 value 94.488402
iter  20 value 88.644562
iter  30 value 87.130251
final  value 87.119609 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.273465 
iter  10 value 94.472401
iter  20 value 94.468284
iter  30 value 93.900318
iter  40 value 93.723404
iter  50 value 89.398247
iter  60 value 84.669742
iter  70 value 84.666846
final  value 84.666837 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.438209 
iter  10 value 94.489093
iter  20 value 93.663574
iter  30 value 87.011275
iter  40 value 86.987157
iter  50 value 86.717081
iter  60 value 84.052639
iter  70 value 83.739560
final  value 83.739237 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.516783 
iter  10 value 94.488621
iter  20 value 93.847226
iter  30 value 84.967714
iter  40 value 84.697869
iter  50 value 84.617814
iter  60 value 84.397868
iter  70 value 84.382633
iter  80 value 84.299562
iter  90 value 83.967245
iter 100 value 83.922065
final  value 83.922065 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.204316 
iter  10 value 92.345467
iter  20 value 92.298470
iter  30 value 92.293397
iter  40 value 91.907189
iter  50 value 91.781166
iter  60 value 91.779444
iter  70 value 91.779216
iter  80 value 91.779161
final  value 91.779159 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.400258 
iter  10 value 94.518669
iter  20 value 94.271429
iter  30 value 94.265159
iter  40 value 94.263799
final  value 94.263795 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.825100 
iter  10 value 94.486304
iter  20 value 94.169665
iter  30 value 86.164010
iter  40 value 86.159012
iter  50 value 85.141421
iter  60 value 84.750814
iter  70 value 83.977252
iter  80 value 83.975551
iter  90 value 83.965244
iter 100 value 83.854911
final  value 83.854911 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.611533 
iter  10 value 94.475692
iter  20 value 94.468914
iter  30 value 89.946763
iter  40 value 85.984891
iter  50 value 84.626093
iter  60 value 83.691833
iter  70 value 83.262411
iter  80 value 83.250935
iter  90 value 83.123505
final  value 83.094707 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.909422 
iter  10 value 94.475225
iter  20 value 94.453732
iter  30 value 87.869301
iter  40 value 86.937382
final  value 86.926248 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.039781 
iter  10 value 94.475577
iter  20 value 94.269396
iter  30 value 85.687222
iter  40 value 83.567975
iter  50 value 83.179866
iter  60 value 82.513156
iter  70 value 82.351926
iter  80 value 82.210710
iter  90 value 82.113352
iter 100 value 82.066051
final  value 82.066051 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.940667 
iter  10 value 109.495988
iter  20 value 109.295266
iter  30 value 109.291729
iter  40 value 109.290763
iter  50 value 106.982495
iter  60 value 106.649689
iter  70 value 106.649501
iter  80 value 106.648597
iter  90 value 106.648168
final  value 106.647991 
converged
Fitting Repeat 2 

# weights:  305
initial  value 128.207782 
iter  10 value 117.895346
iter  20 value 117.411610
iter  30 value 107.023928
iter  40 value 105.540264
iter  50 value 104.923724
iter  60 value 104.377370
iter  70 value 103.988690
iter  80 value 103.795833
iter  90 value 103.701426
iter 100 value 103.696557
final  value 103.696557 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.105209 
iter  10 value 117.894726
iter  20 value 117.883560
iter  30 value 117.607925
final  value 117.607866 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.102168 
iter  10 value 117.892009
iter  20 value 117.210232
final  value 117.206259 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.998713 
iter  10 value 117.895001
iter  20 value 117.795918
iter  30 value 112.648296
iter  40 value 111.008028
iter  50 value 111.007202
iter  60 value 109.139078
iter  70 value 109.072476
iter  70 value 109.072475
iter  70 value 109.072475
final  value 109.072475 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Jan 31 19:43:51 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 
 16.647   0.418  65.564