##############################################################################
##############################################################################
###
### 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_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 RC (2025-06-05 r88288)
* using platform: x86_64-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 Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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
var_imp       52.519  1.808  55.738
corr_plot     50.342  1.737  53.204
FSmethod      50.127  1.760  53.107
pred_ensembel 24.920  0.398  23.391
enrichfindP    0.874  0.077  14.151
* 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-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 96.084115 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.440770 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.236437 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.029098 
final  value 91.896033 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.351816 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.984577 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.134504 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.054344 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 124.005558 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.283894 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.917419 
iter  10 value 93.121112
iter  20 value 91.947378
iter  30 value 91.060935
iter  40 value 86.603939
iter  50 value 86.582833
iter  60 value 86.456226
final  value 86.454546 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.256766 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.821521 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.556432 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.974615 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.481318 
iter  10 value 93.864534
iter  20 value 86.454757
iter  30 value 85.361189
iter  40 value 85.100135
iter  50 value 83.822101
iter  60 value 83.537717
final  value 83.530486 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.932528 
iter  10 value 93.872305
iter  20 value 85.187211
iter  30 value 83.689462
iter  40 value 83.497126
final  value 83.476142 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.139715 
iter  10 value 94.095540
iter  20 value 94.005508
iter  30 value 91.536137
iter  40 value 87.597366
iter  50 value 83.923920
iter  60 value 83.639589
iter  70 value 83.488626
iter  80 value 83.451380
iter  90 value 83.384501
iter 100 value 83.250540
final  value 83.250540 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.590665 
iter  10 value 94.056607
iter  20 value 91.916906
iter  30 value 87.563016
iter  40 value 86.327897
iter  50 value 83.969797
iter  60 value 83.461948
iter  70 value 83.383943
iter  80 value 83.295995
iter  90 value 83.239733
final  value 83.231912 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.591495 
iter  10 value 94.035906
iter  20 value 93.615218
iter  30 value 88.224688
iter  40 value 85.469645
iter  50 value 83.026918
iter  60 value 82.334815
iter  70 value 82.193101
iter  80 value 82.079553
final  value 82.079507 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.192461 
iter  10 value 94.652373
iter  20 value 93.978376
iter  30 value 93.590848
iter  40 value 88.357329
iter  50 value 85.919860
iter  60 value 85.184499
iter  70 value 85.112242
iter  80 value 82.677038
iter  90 value 81.770854
iter 100 value 81.043873
final  value 81.043873 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.670398 
iter  10 value 94.186381
iter  20 value 85.786518
iter  30 value 84.619500
iter  40 value 83.829885
iter  50 value 83.583874
iter  60 value 82.868934
iter  70 value 81.370424
iter  80 value 81.117468
iter  90 value 81.031988
iter 100 value 80.926682
final  value 80.926682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.107449 
iter  10 value 95.490952
iter  20 value 91.272438
iter  30 value 89.953585
iter  40 value 84.342006
iter  50 value 84.006866
iter  60 value 83.859981
iter  70 value 83.744945
iter  80 value 83.392697
iter  90 value 82.755460
iter 100 value 82.607979
final  value 82.607979 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.911402 
iter  10 value 94.694363
iter  20 value 84.055772
iter  30 value 83.816260
iter  40 value 83.705932
iter  50 value 83.564179
iter  60 value 83.521929
iter  70 value 83.423417
iter  80 value 83.238969
iter  90 value 82.515902
iter 100 value 81.298932
final  value 81.298932 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.419028 
iter  10 value 93.960928
iter  20 value 89.411056
iter  30 value 84.184785
iter  40 value 83.281145
iter  50 value 82.763196
iter  60 value 82.401114
iter  70 value 82.253244
iter  80 value 82.192907
iter  90 value 82.153615
iter 100 value 82.033852
final  value 82.033852 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.357559 
iter  10 value 94.283930
iter  20 value 88.420745
iter  30 value 84.595341
iter  40 value 83.098559
iter  50 value 82.794541
iter  60 value 82.715419
iter  70 value 82.665303
iter  80 value 81.985322
iter  90 value 81.164309
iter 100 value 80.534526
final  value 80.534526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.853032 
iter  10 value 93.606691
iter  20 value 84.219392
iter  30 value 83.758478
iter  40 value 83.588535
iter  50 value 83.113985
iter  60 value 81.374855
iter  70 value 80.806996
iter  80 value 80.652420
iter  90 value 80.602180
iter 100 value 80.520082
final  value 80.520082 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.518761 
iter  10 value 94.048028
iter  20 value 86.649143
iter  30 value 83.936982
iter  40 value 83.478916
iter  50 value 81.901870
iter  60 value 80.904059
iter  70 value 80.827024
iter  80 value 80.690119
iter  90 value 80.323575
iter 100 value 80.265641
final  value 80.265641 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.563966 
iter  10 value 93.855204
iter  20 value 90.070970
iter  30 value 87.458097
iter  40 value 83.170448
iter  50 value 81.855651
iter  60 value 81.599720
iter  70 value 81.471664
iter  80 value 80.810300
iter  90 value 80.422294
iter 100 value 80.293833
final  value 80.293833 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.458213 
iter  10 value 95.714864
iter  20 value 82.949936
iter  30 value 81.498782
iter  40 value 81.268363
iter  50 value 80.974423
iter  60 value 80.711879
iter  70 value 80.588761
iter  80 value 80.269497
iter  90 value 80.151288
iter 100 value 80.133725
final  value 80.133725 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.498132 
final  value 94.054615 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.364693 
iter  10 value 94.027058
iter  20 value 87.887456
iter  30 value 83.734465
iter  40 value 83.734186
iter  50 value 83.732286
final  value 83.732202 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.541552 
final  value 94.054640 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.637779 
iter  10 value 84.900211
iter  20 value 84.657619
iter  30 value 84.655973
final  value 84.655971 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.408816 
final  value 94.054372 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.868719 
iter  10 value 94.059168
iter  20 value 94.054050
final  value 94.053916 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.791156 
iter  10 value 94.037746
iter  20 value 93.233991
iter  30 value 84.005092
iter  40 value 83.832506
iter  50 value 83.755848
iter  60 value 83.732184
iter  70 value 83.731175
iter  80 value 82.740833
iter  90 value 81.565753
iter 100 value 81.251611
final  value 81.251611 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.766684 
iter  10 value 94.057525
iter  20 value 94.033157
final  value 94.033141 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.413088 
iter  10 value 94.057809
iter  20 value 94.052962
final  value 94.052948 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.192783 
iter  10 value 94.058200
iter  20 value 94.052787
iter  30 value 93.171515
iter  40 value 87.125863
iter  50 value 85.433779
iter  60 value 84.165990
iter  70 value 82.737109
final  value 82.737036 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.879669 
iter  10 value 94.061003
iter  20 value 94.042287
iter  30 value 91.674563
iter  40 value 84.916579
iter  50 value 83.766510
iter  60 value 83.273763
iter  70 value 83.269472
iter  80 value 83.261682
iter  90 value 83.260026
iter 100 value 82.632333
final  value 82.632333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.428302 
iter  10 value 94.061005
iter  20 value 94.023351
iter  30 value 93.604585
iter  40 value 93.594186
iter  50 value 88.971503
iter  60 value 87.031847
iter  70 value 86.943895
iter  80 value 86.875160
iter  90 value 82.732441
iter 100 value 80.803114
final  value 80.803114 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.347938 
iter  10 value 94.061364
iter  20 value 94.032051
iter  30 value 84.006346
iter  40 value 82.598048
final  value 82.488038 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.802358 
iter  10 value 85.593539
iter  20 value 83.752662
iter  30 value 83.739106
iter  40 value 83.706638
iter  50 value 82.736793
iter  60 value 81.438166
iter  70 value 80.171752
iter  80 value 80.135688
iter  90 value 80.133817
final  value 80.132182 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.382640 
iter  10 value 85.864905
iter  20 value 82.636160
iter  30 value 82.505359
iter  40 value 82.494319
iter  50 value 82.491255
iter  60 value 82.486633
iter  70 value 82.444481
iter  80 value 82.444202
final  value 82.444125 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.219011 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.052155 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.169745 
iter  10 value 94.392401
iter  20 value 93.991412
final  value 93.991343 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.394449 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.956225 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.869488 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.918298 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.188975 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.272618 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.433560 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.261882 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 141.226497 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.620714 
iter  10 value 89.366108
iter  20 value 86.130815
iter  30 value 86.129753
iter  40 value 85.778707
iter  50 value 85.748722
final  value 85.748676 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.938611 
iter  10 value 94.112904
iter  10 value 94.112903
iter  10 value 94.112903
final  value 94.112903 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.261983 
iter  10 value 93.863049
iter  20 value 93.814575
iter  30 value 93.814130
final  value 93.814127 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.307728 
iter  10 value 94.446829
iter  20 value 94.271353
iter  30 value 94.159730
iter  40 value 94.086860
iter  50 value 84.736807
iter  60 value 84.164307
iter  70 value 83.867524
iter  80 value 83.565261
iter  90 value 83.315124
iter 100 value 82.966815
final  value 82.966815 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.161346 
iter  10 value 94.488532
iter  20 value 88.816825
iter  30 value 84.019079
iter  40 value 82.829107
iter  50 value 82.731790
iter  60 value 82.617419
iter  70 value 82.599116
final  value 82.599108 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.676898 
iter  10 value 94.962914
iter  20 value 94.486447
iter  30 value 94.366451
iter  40 value 88.791170
iter  50 value 84.535221
iter  60 value 83.640037
iter  70 value 83.269959
iter  80 value 83.018711
iter  90 value 83.015502
iter  90 value 83.015502
iter  90 value 83.015502
final  value 83.015502 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.824438 
iter  10 value 94.477657
iter  20 value 94.167948
iter  30 value 94.085810
iter  40 value 93.980871
iter  50 value 91.396316
iter  60 value 86.859534
iter  70 value 84.750602
iter  80 value 82.213135
iter  90 value 81.139623
iter 100 value 80.673548
final  value 80.673548 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.970478 
iter  10 value 94.132586
iter  20 value 92.949536
iter  30 value 90.761122
iter  40 value 85.663254
iter  50 value 84.091133
iter  60 value 83.989328
iter  70 value 82.721586
iter  80 value 80.819127
iter  90 value 80.403011
iter 100 value 79.937409
final  value 79.937409 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.894835 
iter  10 value 94.473242
iter  20 value 94.007253
iter  30 value 92.043735
iter  40 value 85.165243
iter  50 value 83.328681
iter  60 value 82.502139
iter  70 value 81.743772
iter  80 value 80.990843
iter  90 value 80.667021
iter 100 value 80.240613
final  value 80.240613 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.352028 
iter  10 value 95.121798
iter  20 value 88.263695
iter  30 value 87.315118
iter  40 value 86.156932
iter  50 value 84.376516
iter  60 value 81.013448
iter  70 value 79.724895
iter  80 value 79.557678
iter  90 value 79.358200
iter 100 value 79.250375
final  value 79.250375 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.260093 
iter  10 value 94.388543
iter  20 value 91.130360
iter  30 value 88.802570
iter  40 value 87.151605
iter  50 value 84.462209
iter  60 value 81.380322
iter  70 value 80.477557
iter  80 value 80.233958
iter  90 value 79.809763
iter 100 value 79.495893
final  value 79.495893 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.996158 
iter  10 value 94.238121
iter  20 value 92.345765
iter  30 value 84.028423
iter  40 value 83.446694
iter  50 value 82.016252
iter  60 value 80.465412
iter  70 value 80.225716
iter  80 value 80.046869
iter  90 value 79.858890
iter 100 value 79.494017
final  value 79.494017 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.295719 
iter  10 value 97.192876
iter  20 value 91.299633
iter  30 value 86.788532
iter  40 value 82.281089
iter  50 value 81.254562
iter  60 value 80.588917
iter  70 value 80.190162
iter  80 value 79.928753
iter  90 value 79.761170
iter 100 value 79.469414
final  value 79.469414 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.812142 
iter  10 value 94.450754
iter  20 value 92.021777
iter  30 value 91.237743
iter  40 value 90.730102
iter  50 value 89.041998
iter  60 value 82.285364
iter  70 value 81.078379
iter  80 value 80.577132
iter  90 value 79.468689
iter 100 value 79.139078
final  value 79.139078 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.764695 
iter  10 value 95.078992
iter  20 value 90.851157
iter  30 value 84.993174
iter  40 value 83.928245
iter  50 value 83.245963
iter  60 value 82.001969
iter  70 value 81.414740
iter  80 value 81.216558
iter  90 value 80.493366
iter 100 value 80.093222
final  value 80.093222 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.194120 
iter  10 value 93.233084
iter  20 value 86.676222
iter  30 value 85.599676
iter  40 value 83.788806
iter  50 value 82.381413
iter  60 value 81.578075
iter  70 value 80.980620
iter  80 value 80.846963
iter  90 value 80.765367
iter 100 value 80.376274
final  value 80.376274 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.666777 
iter  10 value 94.503842
iter  20 value 88.058678
iter  30 value 84.853658
iter  40 value 84.125715
iter  50 value 83.171984
iter  60 value 81.270827
iter  70 value 80.396782
iter  80 value 80.246403
iter  90 value 79.778777
iter 100 value 79.343387
final  value 79.343387 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.315950 
iter  10 value 94.357141
iter  20 value 90.293267
iter  30 value 83.102101
iter  40 value 82.631175
iter  50 value 81.248484
iter  60 value 79.422774
iter  70 value 78.813793
iter  80 value 78.621739
iter  90 value 78.545301
iter 100 value 78.447488
final  value 78.447488 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.280669 
final  value 94.485772 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.070417 
final  value 94.114882 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.492357 
final  value 94.485844 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.054493 
final  value 94.485981 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.798341 
final  value 94.485904 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.991765 
iter  10 value 90.847326
iter  20 value 90.329372
iter  30 value 90.325874
iter  40 value 90.324123
iter  50 value 90.160859
iter  60 value 86.310816
iter  70 value 85.411743
iter  80 value 85.400765
iter  90 value 85.400343
iter 100 value 85.146647
final  value 85.146647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.360109 
iter  10 value 94.403478
iter  20 value 93.392443
iter  30 value 93.212599
iter  40 value 92.811280
iter  50 value 92.742658
iter  60 value 92.741977
iter  70 value 87.932897
final  value 87.318736 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.889389 
iter  10 value 94.117897
iter  20 value 94.113939
iter  30 value 94.062505
final  value 94.046392 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.628652 
iter  10 value 94.488977
iter  20 value 94.424791
iter  30 value 88.207835
iter  40 value 81.515260
iter  50 value 81.053026
iter  60 value 80.839376
final  value 80.839333 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.620809 
iter  10 value 94.121851
iter  20 value 94.051989
iter  30 value 94.048237
iter  40 value 93.811220
iter  50 value 93.810102
final  value 93.810094 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.200458 
iter  10 value 94.492259
iter  20 value 94.484692
iter  30 value 94.437688
iter  40 value 94.025878
iter  50 value 86.417194
iter  60 value 81.293612
iter  70 value 79.820365
iter  80 value 79.633865
iter  90 value 79.174267
iter 100 value 78.563200
final  value 78.563200 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.686139 
iter  10 value 93.774490
iter  20 value 93.770905
iter  30 value 92.153490
iter  40 value 90.781947
iter  50 value 90.590131
iter  60 value 90.324013
iter  70 value 84.936808
iter  80 value 83.094408
iter  90 value 82.631342
iter 100 value 82.181795
final  value 82.181795 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.690972 
iter  10 value 88.275353
iter  20 value 86.477363
iter  30 value 86.295556
iter  40 value 86.280397
iter  50 value 86.262857
iter  60 value 86.257417
iter  70 value 81.576297
iter  80 value 79.491296
iter  90 value 78.927225
iter 100 value 78.218734
final  value 78.218734 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.937157 
iter  10 value 94.121305
iter  20 value 94.116895
iter  30 value 93.815237
iter  40 value 93.334822
iter  50 value 84.193395
iter  60 value 83.261039
iter  70 value 83.255954
iter  80 value 83.205731
iter  90 value 83.099405
iter 100 value 83.078932
final  value 83.078932 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.151553 
iter  10 value 94.491748
iter  20 value 94.231394
iter  30 value 89.633855
iter  40 value 89.632807
iter  50 value 84.948165
iter  60 value 84.323707
iter  70 value 84.316461
iter  80 value 84.030723
iter  90 value 83.984468
iter 100 value 83.977731
final  value 83.977731 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.896423 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.301732 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.893582 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.949962 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.762091 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.313445 
iter  10 value 94.053087
final  value 94.052874 
converged
Fitting Repeat 2 

# weights:  305
initial  value 126.716799 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.530953 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.494407 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.241096 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.443331 
iter  10 value 93.343368
final  value 93.338302 
converged
Fitting Repeat 2 

# weights:  507
initial  value 128.610408 
iter  10 value 93.582453
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.318939 
iter  10 value 93.001884
iter  20 value 86.677715
iter  30 value 85.883641
iter  40 value 84.843424
iter  50 value 84.474883
iter  60 value 84.459853
final  value 84.459452 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.181476 
iter  10 value 93.566476
iter  20 value 90.122265
iter  30 value 88.676962
final  value 88.455909 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.505637 
iter  10 value 91.983274
iter  20 value 91.098418
final  value 91.098362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.902786 
iter  10 value 94.056440
iter  20 value 93.687368
iter  30 value 93.647182
iter  40 value 89.079449
iter  50 value 88.672789
iter  60 value 88.528407
iter  70 value 85.798828
iter  80 value 85.268837
iter  90 value 84.970673
iter 100 value 84.939965
final  value 84.939965 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.246921 
iter  10 value 94.009044
iter  20 value 92.689569
iter  30 value 89.648534
iter  40 value 89.334472
iter  50 value 85.365148
iter  60 value 85.147840
iter  70 value 83.978967
iter  80 value 83.335522
iter  90 value 83.189686
iter 100 value 82.688699
final  value 82.688699 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.521894 
iter  10 value 94.049607
iter  20 value 89.123459
iter  30 value 86.384137
iter  40 value 85.897646
iter  50 value 85.701420
iter  60 value 85.690199
final  value 85.690191 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.877480 
iter  10 value 93.906378
iter  20 value 91.039077
iter  30 value 89.457350
iter  40 value 86.793241
iter  50 value 86.230115
iter  60 value 86.019888
iter  70 value 85.797084
iter  80 value 85.690779
iter  90 value 85.690192
iter  90 value 85.690192
iter  90 value 85.690192
final  value 85.690192 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.372174 
iter  10 value 94.053659
iter  20 value 93.863697
iter  30 value 93.806204
iter  40 value 93.789078
iter  50 value 93.090894
iter  60 value 88.817401
iter  70 value 86.580715
iter  80 value 84.714704
iter  90 value 83.788452
iter 100 value 83.296983
final  value 83.296983 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.862864 
iter  10 value 94.173489
iter  20 value 94.055311
iter  30 value 93.707840
iter  40 value 92.600318
iter  50 value 88.952983
iter  60 value 86.659247
iter  70 value 84.733373
iter  80 value 83.705695
iter  90 value 83.523403
iter 100 value 82.470861
final  value 82.470861 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.569522 
iter  10 value 93.569129
iter  20 value 87.545942
iter  30 value 86.244979
iter  40 value 85.970741
iter  50 value 85.763519
iter  60 value 85.608428
iter  70 value 85.344126
iter  80 value 84.583570
iter  90 value 83.862804
iter 100 value 83.599523
final  value 83.599523 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.556755 
iter  10 value 91.865066
iter  20 value 90.431036
iter  30 value 90.098036
iter  40 value 89.979784
iter  50 value 89.706575
iter  60 value 88.492230
iter  70 value 86.505764
iter  80 value 85.351126
iter  90 value 83.446915
iter 100 value 83.267709
final  value 83.267709 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.434277 
iter  10 value 94.430579
iter  20 value 88.384447
iter  30 value 84.948957
iter  40 value 83.213746
iter  50 value 82.705443
iter  60 value 82.598269
iter  70 value 82.533813
iter  80 value 82.428004
iter  90 value 82.357648
iter 100 value 81.896289
final  value 81.896289 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.894193 
iter  10 value 94.082385
iter  20 value 93.833346
iter  30 value 90.828115
iter  40 value 86.660049
iter  50 value 85.930118
iter  60 value 83.125857
iter  70 value 82.220718
iter  80 value 82.018079
iter  90 value 81.906007
iter 100 value 81.872108
final  value 81.872108 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.135342 
iter  10 value 94.131423
iter  20 value 92.484996
iter  30 value 87.811372
iter  40 value 84.335721
iter  50 value 83.345062
iter  60 value 82.859301
iter  70 value 82.574086
iter  80 value 82.183230
iter  90 value 82.102586
iter 100 value 82.009331
final  value 82.009331 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.616303 
iter  10 value 93.630080
iter  20 value 88.399825
iter  30 value 85.981073
iter  40 value 84.876492
iter  50 value 83.149715
iter  60 value 81.840558
iter  70 value 81.604100
iter  80 value 81.579595
iter  90 value 81.529751
iter 100 value 81.227838
final  value 81.227838 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.972566 
iter  10 value 94.036794
iter  20 value 93.689485
iter  30 value 92.061481
iter  40 value 89.243854
iter  50 value 87.611742
iter  60 value 84.864342
iter  70 value 83.982710
iter  80 value 83.020426
iter  90 value 82.576866
iter 100 value 82.549574
final  value 82.549574 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.568691 
iter  10 value 93.942539
iter  20 value 92.232716
iter  30 value 89.410453
iter  40 value 86.097734
iter  50 value 83.686152
iter  60 value 82.325435
iter  70 value 81.613647
iter  80 value 81.385518
iter  90 value 81.309064
iter 100 value 81.278118
final  value 81.278118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.500204 
iter  10 value 94.094037
iter  20 value 89.692783
iter  30 value 87.887467
iter  40 value 85.968421
iter  50 value 84.994217
iter  60 value 84.934941
iter  70 value 84.598016
iter  80 value 82.739816
iter  90 value 82.227027
iter 100 value 81.775112
final  value 81.775112 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.258847 
final  value 94.058258 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.487378 
final  value 94.054631 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.392945 
final  value 94.054443 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.220402 
iter  10 value 89.816007
iter  20 value 89.618471
iter  30 value 89.495661
iter  40 value 89.495105
iter  50 value 89.383174
final  value 89.354259 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.896416 
final  value 94.054577 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.913500 
iter  10 value 93.626062
iter  20 value 93.586893
iter  30 value 90.793902
iter  40 value 85.426751
iter  50 value 84.782947
iter  60 value 84.578723
iter  70 value 84.578579
final  value 84.578387 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.689068 
iter  10 value 94.057753
iter  20 value 93.761987
iter  30 value 88.069932
iter  40 value 86.729747
iter  50 value 86.289879
iter  60 value 86.287122
iter  70 value 86.285458
iter  80 value 84.380143
iter  90 value 82.494721
iter 100 value 81.703631
final  value 81.703631 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.949926 
iter  10 value 94.057491
iter  20 value 91.137617
iter  30 value 87.697286
iter  40 value 86.881625
iter  50 value 86.475607
final  value 86.471773 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.106394 
iter  10 value 94.057861
iter  20 value 94.052978
iter  20 value 94.052977
iter  20 value 94.052977
final  value 94.052977 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.058615 
iter  10 value 93.806835
iter  20 value 92.662344
iter  30 value 90.160683
iter  40 value 90.112735
iter  50 value 90.061036
iter  60 value 90.057903
iter  70 value 89.409639
iter  80 value 89.122185
iter  90 value 88.898248
iter 100 value 88.897013
final  value 88.897013 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.072967 
iter  10 value 94.060513
iter  20 value 93.955218
iter  30 value 92.508405
iter  40 value 90.431743
iter  50 value 90.430838
iter  60 value 90.371390
iter  70 value 84.064148
iter  80 value 83.302616
iter  90 value 83.302351
iter 100 value 83.250790
final  value 83.250790 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 93.826469 
iter  10 value 91.427268
iter  20 value 91.418131
iter  30 value 91.338264
iter  40 value 91.333119
iter  50 value 91.296971
iter  60 value 91.294213
final  value 91.294207 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.045952 
iter  10 value 89.030380
iter  20 value 88.815614
iter  30 value 88.813927
iter  40 value 88.811049
iter  50 value 88.809121
iter  60 value 88.672714
iter  70 value 88.142151
iter  80 value 87.962079
iter  90 value 87.961236
iter 100 value 87.959832
final  value 87.959832 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.636153 
iter  10 value 94.060968
iter  20 value 93.773837
iter  30 value 91.099361
iter  40 value 91.066572
iter  50 value 91.066452
iter  60 value 90.832588
iter  70 value 89.612734
final  value 89.612667 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.900336 
iter  10 value 94.061615
iter  20 value 94.053476
iter  30 value 92.983691
iter  40 value 88.851073
iter  50 value 88.816041
iter  60 value 88.815789
iter  70 value 88.814381
iter  80 value 88.814249
iter  90 value 88.813891
final  value 88.813802 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.922845 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.140166 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.617563 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.324103 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.582292 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.881003 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.228048 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.229383 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.705115 
iter  10 value 94.304609
iter  10 value 94.304609
iter  10 value 94.304609
final  value 94.304609 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.348495 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.883956 
iter  10 value 94.662750
iter  20 value 92.104566
final  value 91.651099 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.755464 
final  value 91.608212 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.166114 
iter  10 value 94.461763
final  value 94.461721 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.511334 
iter  10 value 94.483809
iter  10 value 94.483809
iter  10 value 94.483809
final  value 94.483809 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.817495 
final  value 94.313818 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.406864 
iter  10 value 94.488550
iter  20 value 93.713020
iter  30 value 88.667044
iter  40 value 88.069839
iter  50 value 87.248964
iter  60 value 87.223002
iter  70 value 87.095013
iter  80 value 83.558849
iter  90 value 83.276143
iter 100 value 83.253814
final  value 83.253814 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.536619 
iter  10 value 94.489651
iter  20 value 94.353850
iter  30 value 89.845935
iter  40 value 88.463463
iter  50 value 85.599453
iter  60 value 84.908101
iter  70 value 83.871550
iter  80 value 83.349962
iter  90 value 82.168843
iter 100 value 81.497471
final  value 81.497471 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.337325 
iter  10 value 94.408713
iter  20 value 91.964763
iter  30 value 86.137789
iter  40 value 85.288681
iter  50 value 85.219499
iter  60 value 85.131415
iter  70 value 84.933010
iter  80 value 84.280854
iter  90 value 83.820506
final  value 83.792293 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.917880 
iter  10 value 94.565847
iter  20 value 94.487383
iter  30 value 94.340831
iter  40 value 87.727006
iter  50 value 86.990505
iter  60 value 86.371295
iter  70 value 85.950826
iter  80 value 85.067173
iter  90 value 84.469167
iter 100 value 84.402836
final  value 84.402836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.589706 
iter  10 value 94.434480
iter  20 value 92.287359
iter  30 value 89.924306
iter  40 value 86.754672
iter  50 value 84.883670
iter  60 value 83.962068
iter  70 value 83.466848
iter  80 value 82.842992
iter  90 value 81.729667
iter 100 value 81.102576
final  value 81.102576 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.632208 
iter  10 value 94.503359
iter  20 value 85.476620
iter  30 value 85.192558
iter  40 value 85.121812
iter  50 value 84.729370
iter  60 value 84.207310
iter  70 value 83.972011
iter  80 value 83.740704
iter  90 value 83.474946
iter 100 value 82.099742
final  value 82.099742 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.451964 
iter  10 value 92.463108
iter  20 value 88.106350
iter  30 value 87.460987
iter  40 value 83.424838
iter  50 value 83.250101
iter  60 value 82.393283
iter  70 value 82.082750
iter  80 value 81.910359
iter  90 value 81.611171
iter 100 value 81.452511
final  value 81.452511 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.083911 
iter  10 value 94.487751
iter  20 value 93.408652
iter  30 value 86.743364
iter  40 value 84.691926
iter  50 value 83.601201
iter  60 value 83.512979
iter  70 value 82.341878
iter  80 value 81.886179
iter  90 value 81.693860
iter 100 value 81.597952
final  value 81.597952 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.753759 
iter  10 value 94.133386
iter  20 value 93.184424
iter  30 value 87.221312
iter  40 value 84.926016
iter  50 value 83.620939
iter  60 value 83.325054
iter  70 value 83.134121
iter  80 value 81.994292
iter  90 value 80.822287
iter 100 value 80.206111
final  value 80.206111 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.271717 
iter  10 value 94.485276
iter  20 value 91.503896
iter  30 value 87.580853
iter  40 value 82.175033
iter  50 value 81.629219
iter  60 value 81.128794
iter  70 value 80.569913
iter  80 value 80.401314
iter  90 value 80.179280
iter 100 value 79.744684
final  value 79.744684 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.441518 
iter  10 value 94.392548
iter  20 value 88.418041
iter  30 value 86.540981
iter  40 value 84.631415
iter  50 value 84.163609
iter  60 value 83.798856
iter  70 value 83.540704
iter  80 value 82.855776
iter  90 value 82.779112
iter 100 value 82.680559
final  value 82.680559 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.513020 
iter  10 value 97.429162
iter  20 value 86.420821
iter  30 value 84.328491
iter  40 value 83.824533
iter  50 value 83.458151
iter  60 value 82.758869
iter  70 value 81.036505
iter  80 value 80.705971
iter  90 value 80.185035
iter 100 value 79.891842
final  value 79.891842 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.359584 
iter  10 value 92.696468
iter  20 value 86.675794
iter  30 value 84.667410
iter  40 value 83.708112
iter  50 value 83.233508
iter  60 value 82.364132
iter  70 value 81.502775
iter  80 value 80.915332
iter  90 value 80.714079
iter 100 value 79.990262
final  value 79.990262 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.367624 
iter  10 value 98.349584
iter  20 value 94.492906
iter  30 value 87.824076
iter  40 value 85.856994
iter  50 value 82.123324
iter  60 value 80.890671
iter  70 value 80.282744
iter  80 value 79.845180
iter  90 value 79.658105
iter 100 value 79.592376
final  value 79.592376 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.099370 
iter  10 value 94.480068
iter  20 value 86.661094
iter  30 value 85.472037
iter  40 value 84.040294
iter  50 value 81.125874
iter  60 value 80.518524
iter  70 value 80.200899
iter  80 value 80.146582
iter  90 value 79.874455
iter 100 value 79.757584
final  value 79.757584 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.487887 
final  value 94.485839 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.401447 
final  value 94.485899 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.874837 
final  value 94.485869 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.483180 
final  value 94.468563 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.090567 
final  value 94.485668 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.349903 
iter  10 value 94.489327
iter  20 value 94.484635
iter  30 value 93.527599
iter  40 value 85.263139
iter  50 value 84.632735
iter  60 value 84.598087
final  value 84.597566 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.130294 
iter  10 value 94.489234
iter  20 value 90.774413
iter  30 value 84.889782
iter  40 value 83.343945
iter  50 value 83.342245
final  value 83.342216 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.635422 
iter  10 value 94.488965
iter  20 value 94.484247
iter  30 value 93.793644
iter  40 value 90.278664
iter  50 value 90.274476
iter  50 value 90.274476
iter  50 value 90.274476
final  value 90.274476 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.056074 
iter  10 value 94.488967
final  value 94.488260 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.457028 
iter  10 value 92.338037
iter  20 value 90.984308
iter  30 value 90.982630
iter  40 value 90.244574
iter  50 value 90.207312
final  value 90.206805 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.274375 
iter  10 value 94.492631
iter  20 value 94.461394
iter  30 value 86.709105
iter  40 value 79.607248
iter  50 value 78.991686
iter  60 value 78.579350
iter  70 value 78.415087
iter  80 value 78.407003
iter  90 value 78.373934
iter 100 value 78.358284
final  value 78.358284 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.786382 
iter  10 value 94.498002
iter  20 value 94.163856
iter  30 value 87.888670
iter  40 value 85.257611
iter  50 value 85.251442
iter  60 value 85.248693
iter  70 value 83.651059
iter  80 value 83.618201
iter  90 value 83.396419
iter 100 value 83.278807
final  value 83.278807 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.934181 
iter  10 value 90.728985
iter  20 value 83.994964
iter  30 value 83.976137
iter  40 value 83.594593
iter  50 value 83.414679
final  value 83.411193 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.884032 
iter  10 value 94.474564
iter  20 value 94.466935
iter  30 value 94.361456
iter  40 value 88.763731
iter  50 value 88.167141
iter  60 value 88.020849
iter  70 value 88.020789
iter  80 value 87.003263
iter  90 value 84.148852
iter 100 value 80.723914
final  value 80.723914 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.807090 
iter  10 value 94.451154
iter  20 value 94.448370
iter  30 value 94.443849
iter  40 value 94.443274
iter  50 value 94.440538
iter  60 value 89.732517
iter  70 value 89.246374
iter  80 value 84.012299
iter  90 value 80.319037
iter 100 value 80.254702
final  value 80.254702 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.919737 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.799656 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.122329 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.596914 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.507988 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.774951 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.368544 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.681130 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.960952 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.016223 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.108712 
final  value 94.228783 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.718173 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.342382 
iter  10 value 91.984076
iter  20 value 83.276827
iter  30 value 83.270502
iter  40 value 83.270288
iter  50 value 82.430284
final  value 82.426095 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.021377 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 93.072305 
iter  10 value 91.032769
iter  20 value 91.032279
final  value 91.032263 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.698762 
iter  10 value 94.559913
iter  20 value 94.488420
iter  30 value 90.078204
iter  40 value 85.779244
iter  50 value 85.489675
iter  60 value 83.550260
iter  70 value 82.873311
iter  80 value 82.836395
iter  90 value 82.526940
iter 100 value 82.255801
final  value 82.255801 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.583884 
iter  10 value 92.751507
iter  20 value 88.270335
iter  30 value 88.180252
iter  40 value 87.067156
iter  50 value 86.842803
iter  60 value 86.688206
iter  70 value 85.452502
iter  80 value 85.197374
iter  90 value 85.169524
iter 100 value 85.166404
final  value 85.166404 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.942833 
iter  10 value 94.610306
iter  20 value 94.331055
iter  30 value 93.424277
iter  40 value 86.807736
iter  50 value 86.281106
iter  60 value 85.672360
iter  70 value 85.374372
iter  80 value 85.199427
final  value 85.199395 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.476465 
iter  10 value 94.481851
iter  20 value 94.101228
iter  30 value 89.298828
iter  40 value 86.138967
iter  50 value 85.588627
iter  60 value 84.800530
final  value 84.776944 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.549576 
iter  10 value 94.488526
iter  20 value 94.283433
iter  30 value 90.195383
iter  40 value 87.968899
iter  50 value 87.540304
iter  60 value 86.902838
iter  70 value 86.241569
iter  80 value 85.228657
iter  90 value 84.777956
iter 100 value 84.776951
final  value 84.776951 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.987048 
iter  10 value 94.441035
iter  20 value 86.863862
iter  30 value 84.223082
iter  40 value 83.332221
iter  50 value 82.891479
iter  60 value 82.538170
iter  70 value 81.986659
iter  80 value 81.306731
iter  90 value 80.757142
iter 100 value 80.722762
final  value 80.722762 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.854364 
iter  10 value 96.230633
iter  20 value 90.609300
iter  30 value 87.270562
iter  40 value 85.366219
iter  50 value 84.472359
iter  60 value 82.446655
iter  70 value 81.952019
iter  80 value 81.324850
iter  90 value 81.113414
iter 100 value 81.037648
final  value 81.037648 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.687893 
iter  10 value 94.484677
iter  20 value 88.001817
iter  30 value 84.922562
iter  40 value 84.679849
iter  50 value 83.842625
iter  60 value 82.644363
iter  70 value 82.242789
iter  80 value 82.219277
iter  90 value 82.029943
iter 100 value 81.650385
final  value 81.650385 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.433878 
iter  10 value 94.577727
iter  20 value 88.205853
iter  30 value 86.202479
iter  40 value 85.597109
iter  50 value 84.893474
iter  60 value 84.776693
iter  70 value 83.124649
iter  80 value 82.645871
iter  90 value 82.240517
iter 100 value 81.674348
final  value 81.674348 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.264235 
iter  10 value 94.487144
iter  20 value 87.116877
iter  30 value 85.770794
iter  40 value 85.581448
iter  50 value 85.475510
final  value 85.472546 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.169915 
iter  10 value 100.043484
iter  20 value 93.471049
iter  30 value 91.783755
iter  40 value 86.788922
iter  50 value 85.729808
iter  60 value 85.312392
iter  70 value 83.540295
iter  80 value 82.951514
iter  90 value 82.447753
iter 100 value 81.883156
final  value 81.883156 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.289034 
iter  10 value 94.383348
iter  20 value 88.795321
iter  30 value 87.367354
iter  40 value 84.546187
iter  50 value 82.613514
iter  60 value 82.245855
iter  70 value 82.015489
iter  80 value 81.573810
iter  90 value 81.117052
iter 100 value 81.067748
final  value 81.067748 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.156668 
iter  10 value 94.425215
iter  20 value 93.352539
iter  30 value 89.543259
iter  40 value 86.951982
iter  50 value 81.873575
iter  60 value 80.985450
iter  70 value 80.432028
iter  80 value 80.363878
iter  90 value 80.274595
iter 100 value 80.108226
final  value 80.108226 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.574792 
iter  10 value 94.667018
iter  20 value 90.155174
iter  30 value 87.152317
iter  40 value 83.684685
iter  50 value 82.393932
iter  60 value 82.057332
iter  70 value 81.222822
iter  80 value 80.402457
iter  90 value 80.081488
iter 100 value 79.979623
final  value 79.979623 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.232680 
iter  10 value 90.304835
iter  20 value 86.282159
iter  30 value 85.689305
iter  40 value 84.989458
iter  50 value 82.949151
iter  60 value 82.732094
iter  70 value 82.404745
iter  80 value 81.882852
iter  90 value 81.153814
iter 100 value 80.958688
final  value 80.958688 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.086590 
final  value 94.485774 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.234252 
iter  10 value 94.485877
iter  20 value 94.484255
final  value 94.484215 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.100786 
iter  10 value 94.486085
iter  20 value 94.484266
iter  30 value 94.214465
iter  40 value 94.214352
final  value 94.214343 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.433378 
final  value 94.468458 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.216208 
iter  10 value 94.485947
iter  20 value 94.219823
iter  30 value 84.116175
iter  40 value 83.784341
iter  50 value 83.437873
iter  60 value 83.366710
iter  70 value 83.360349
iter  80 value 83.320616
iter  90 value 83.319381
iter 100 value 83.318954
final  value 83.318954 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.545575 
iter  10 value 94.488958
iter  20 value 94.432252
iter  30 value 92.648853
iter  40 value 92.629626
iter  50 value 91.330707
iter  60 value 91.323398
final  value 91.323231 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.588188 
iter  10 value 93.788624
iter  20 value 93.784190
final  value 93.783994 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.507896 
iter  10 value 94.488643
iter  20 value 94.381164
final  value 93.784268 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.016376 
iter  10 value 94.489117
iter  20 value 94.478861
iter  30 value 94.241294
iter  40 value 86.943976
iter  50 value 85.591902
final  value 85.589846 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.388505 
iter  10 value 94.488763
iter  20 value 94.256195
iter  30 value 94.133972
iter  40 value 94.112666
iter  50 value 87.176440
iter  60 value 86.269606
final  value 86.268194 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.711109 
iter  10 value 93.757750
iter  20 value 93.728113
iter  30 value 93.725978
iter  40 value 93.574353
iter  50 value 93.488372
iter  60 value 93.484973
iter  70 value 93.482209
iter  80 value 93.481275
iter  90 value 93.480686
iter 100 value 93.479050
final  value 93.479050 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.630829 
iter  10 value 94.490701
iter  20 value 94.471005
iter  30 value 93.402464
iter  40 value 85.996771
iter  50 value 85.276094
iter  60 value 83.354434
iter  70 value 81.362116
iter  80 value 80.133524
iter  90 value 79.826051
iter 100 value 79.609248
final  value 79.609248 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.847335 
iter  10 value 94.492663
iter  20 value 94.463961
iter  30 value 93.620284
iter  40 value 92.183398
iter  50 value 92.163078
iter  60 value 89.371336
iter  70 value 88.729081
iter  80 value 85.258532
iter  90 value 84.995332
iter 100 value 84.994023
final  value 84.994023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.628904 
iter  10 value 93.605178
iter  20 value 93.585898
iter  30 value 92.840926
iter  40 value 88.327179
iter  50 value 88.269969
iter  60 value 86.005375
iter  70 value 84.808458
iter  80 value 84.631650
iter  90 value 84.630296
final  value 84.630212 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.375776 
iter  10 value 94.475464
iter  20 value 94.209870
iter  30 value 94.194200
iter  40 value 94.188887
iter  50 value 94.145809
iter  60 value 89.098283
iter  70 value 86.998920
iter  80 value 86.778165
iter  90 value 86.754584
iter 100 value 85.160026
final  value 85.160026 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 144.907748 
iter  10 value 116.169244
iter  20 value 109.215381
iter  30 value 107.700591
iter  40 value 105.487678
iter  50 value 104.336152
iter  60 value 103.490615
iter  70 value 101.470937
iter  80 value 101.161421
iter  90 value 101.108707
iter 100 value 100.993670
final  value 100.993670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 132.924527 
iter  10 value 112.740744
iter  20 value 106.306401
iter  30 value 105.812118
iter  40 value 105.773704
iter  50 value 105.301133
iter  60 value 102.435830
iter  70 value 101.958987
iter  80 value 101.393062
iter  90 value 100.976205
iter 100 value 100.845213
final  value 100.845213 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 171.406115 
iter  10 value 117.901637
iter  20 value 115.936079
iter  30 value 112.972515
iter  40 value 108.106811
iter  50 value 104.928423
iter  60 value 102.190810
iter  70 value 101.721254
iter  80 value 101.187434
iter  90 value 100.976118
iter 100 value 100.869718
final  value 100.869718 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 140.970292 
iter  10 value 119.143289
iter  20 value 113.573796
iter  30 value 107.443109
iter  40 value 104.036027
iter  50 value 102.528857
iter  60 value 101.334377
iter  70 value 100.543654
iter  80 value 100.432331
iter  90 value 100.387779
iter 100 value 100.358028
final  value 100.358028 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.900647 
iter  10 value 117.825165
iter  20 value 113.144971
iter  30 value 107.529492
iter  40 value 106.237238
iter  50 value 102.594500
iter  60 value 101.687033
iter  70 value 101.431204
iter  80 value 101.359378
iter  90 value 101.102094
iter 100 value 100.964932
final  value 100.964932 
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 Aug 26 05:01:24 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 
 77.318   2.163 171.972