##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.3 (2025-02-28)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       50.820  1.741  57.928
FSmethod      50.614  1.782  54.999
corr_plot     50.566  1.723  55.273
pred_ensembel 25.251  0.386  24.456
calculateTC    4.681  0.430   5.382
enrichfindP    0.888  0.083  13.294
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.3 (2025-02-28) -- "Trophy Case"
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 101.301351 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.896610 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.959773 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.871800 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.790477 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.024654 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.171080 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 92.747216 
iter  10 value 85.285590
iter  20 value 84.394455
iter  30 value 82.345598
iter  40 value 82.147537
iter  50 value 81.966481
iter  60 value 81.966124
final  value 81.966116 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.475011 
iter  10 value 89.274152
iter  20 value 84.749041
iter  30 value 84.410663
iter  40 value 84.348223
iter  50 value 84.236204
iter  60 value 84.234783
iter  60 value 84.234783
iter  60 value 84.234783
final  value 84.234783 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.477490 
iter  10 value 93.553009
iter  20 value 93.551914
iter  20 value 93.551913
iter  20 value 93.551913
final  value 93.551913 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.011590 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.290993 
iter  10 value 90.471379
iter  20 value 85.079894
iter  30 value 84.517634
iter  40 value 84.517584
iter  40 value 84.517583
iter  40 value 84.517583
final  value 84.517583 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.591959 
final  value 93.867391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.332665 
iter  10 value 93.961057
iter  20 value 93.954973
iter  30 value 91.078142
iter  40 value 90.157955
iter  50 value 89.775923
final  value 89.775920 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.787069 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.950414 
iter  10 value 94.037611
iter  20 value 91.953830
iter  30 value 89.159362
iter  40 value 87.031804
iter  50 value 84.457735
iter  60 value 84.091614
iter  70 value 83.840699
iter  80 value 83.832230
iter  90 value 83.745402
iter 100 value 83.707037
final  value 83.707037 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.408847 
iter  10 value 93.922615
iter  20 value 93.914642
iter  30 value 92.113689
iter  40 value 91.105395
iter  50 value 90.847555
iter  60 value 90.740924
iter  70 value 84.969620
iter  80 value 83.732160
iter  90 value 83.416994
iter 100 value 83.336144
final  value 83.336144 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.001317 
iter  10 value 94.054307
iter  20 value 93.926018
iter  30 value 93.909409
iter  40 value 93.738646
iter  50 value 89.979675
iter  60 value 84.986200
iter  70 value 84.029466
iter  80 value 83.657313
iter  90 value 83.345829
iter 100 value 83.288271
final  value 83.288271 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 111.236650 
iter  10 value 93.860656
iter  20 value 87.724419
iter  30 value 86.897757
iter  40 value 86.698361
iter  50 value 86.506190
iter  60 value 86.344104
iter  70 value 83.858994
iter  80 value 83.206331
iter  90 value 82.384289
iter 100 value 82.310635
final  value 82.310635 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.799929 
iter  10 value 94.054016
iter  20 value 91.285812
iter  30 value 88.241139
iter  40 value 88.089530
iter  50 value 87.908242
iter  60 value 87.524894
iter  70 value 87.211684
iter  80 value 86.100718
iter  90 value 85.775114
iter 100 value 85.453843
final  value 85.453843 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.871708 
iter  10 value 93.882922
iter  20 value 89.160762
iter  30 value 86.056230
iter  40 value 84.134908
iter  50 value 83.793163
iter  60 value 83.759920
iter  70 value 82.771127
iter  80 value 82.375963
iter  90 value 82.205457
iter 100 value 81.898155
final  value 81.898155 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.225482 
iter  10 value 94.029487
iter  20 value 89.317448
iter  30 value 88.646118
iter  40 value 87.895436
iter  50 value 87.533072
iter  60 value 84.872926
iter  70 value 84.251660
iter  80 value 83.547573
iter  90 value 82.840773
iter 100 value 82.196031
final  value 82.196031 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.378867 
iter  10 value 89.131144
iter  20 value 85.261855
iter  30 value 83.832257
iter  40 value 82.217295
iter  50 value 81.554284
iter  60 value 81.216936
iter  70 value 81.002252
iter  80 value 80.953850
iter  90 value 80.747057
iter 100 value 80.619237
final  value 80.619237 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.429966 
iter  10 value 94.072628
iter  20 value 93.861706
iter  30 value 91.235026
iter  40 value 89.939033
iter  50 value 86.244351
iter  60 value 85.947988
iter  70 value 84.723482
iter  80 value 84.221541
iter  90 value 82.329466
iter 100 value 81.962567
final  value 81.962567 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.301007 
iter  10 value 94.061049
iter  20 value 85.296747
iter  30 value 84.939898
iter  40 value 84.107114
iter  50 value 83.783004
iter  60 value 83.567746
iter  70 value 83.302248
iter  80 value 83.045069
iter  90 value 81.957958
iter 100 value 81.722618
final  value 81.722618 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.530358 
iter  10 value 94.915048
iter  20 value 92.674148
iter  30 value 89.490877
iter  40 value 88.554324
iter  50 value 87.477496
iter  60 value 87.217575
iter  70 value 86.511851
iter  80 value 85.424232
iter  90 value 83.504958
iter 100 value 82.153020
final  value 82.153020 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.930666 
iter  10 value 94.147740
iter  20 value 84.770477
iter  30 value 83.230924
iter  40 value 81.732026
iter  50 value 81.054675
iter  60 value 80.753122
iter  70 value 80.569523
iter  80 value 80.526683
iter  90 value 80.485958
iter 100 value 80.445235
final  value 80.445235 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.709315 
iter  10 value 95.322830
iter  20 value 93.807772
iter  30 value 91.600386
iter  40 value 91.329725
iter  50 value 88.505295
iter  60 value 85.149933
iter  70 value 84.025728
iter  80 value 83.480151
iter  90 value 83.159968
iter 100 value 83.010255
final  value 83.010255 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.208192 
iter  10 value 93.833851
iter  20 value 87.037327
iter  30 value 86.754261
iter  40 value 86.486460
iter  50 value 86.186319
iter  60 value 86.076665
iter  70 value 85.818961
iter  80 value 85.241470
iter  90 value 82.884607
iter 100 value 82.109161
final  value 82.109161 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.902152 
iter  10 value 94.888887
iter  20 value 94.280315
iter  30 value 86.101597
iter  40 value 85.781778
iter  50 value 84.969127
iter  60 value 84.433656
iter  70 value 83.913362
iter  80 value 83.692275
iter  90 value 83.534364
iter 100 value 83.188535
final  value 83.188535 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.198746 
final  value 94.054430 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.567841 
final  value 94.054340 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.933463 
final  value 94.054605 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.771307 
final  value 93.868971 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.979278 
iter  10 value 94.081142
iter  20 value 94.063062
iter  30 value 93.788952
iter  40 value 91.956009
iter  50 value 91.952792
iter  50 value 91.952792
final  value 91.952787 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.849505 
iter  10 value 94.052934
iter  20 value 93.890583
iter  30 value 93.870133
final  value 93.869876 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.446350 
iter  10 value 94.062417
iter  20 value 94.029494
iter  30 value 93.876192
iter  40 value 93.874857
iter  50 value 93.870615
final  value 93.870181 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.218043 
iter  10 value 93.872230
iter  20 value 93.867884
final  value 93.867612 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.068003 
iter  10 value 94.057033
iter  20 value 92.112463
iter  30 value 90.875440
iter  40 value 90.652424
final  value 90.652353 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.259588 
iter  10 value 94.057571
iter  20 value 94.052939
iter  30 value 93.632149
iter  40 value 85.450455
iter  50 value 84.764694
iter  60 value 84.265734
iter  70 value 84.263474
iter  80 value 84.250922
iter  90 value 84.234404
iter 100 value 84.233344
final  value 84.233344 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.801201 
iter  10 value 93.875532
iter  20 value 93.869925
iter  30 value 93.702832
iter  40 value 93.701975
iter  50 value 93.674840
iter  60 value 87.482903
iter  70 value 83.271364
iter  80 value 81.996220
iter  90 value 81.717341
iter 100 value 81.318934
final  value 81.318934 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.967392 
iter  10 value 93.877725
iter  20 value 93.870378
iter  30 value 92.341506
iter  40 value 91.434362
iter  50 value 91.240189
iter  60 value 90.460471
iter  70 value 85.603657
iter  80 value 82.753068
iter  90 value 82.748070
iter 100 value 82.746286
final  value 82.746286 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.122369 
iter  10 value 93.875220
iter  20 value 93.868076
iter  30 value 91.782402
iter  40 value 88.161807
iter  50 value 84.212816
iter  60 value 83.816942
iter  70 value 81.944439
iter  80 value 81.083928
iter  90 value 81.052078
iter 100 value 80.934527
final  value 80.934527 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 92.743841 
iter  10 value 87.405061
iter  20 value 87.389546
iter  30 value 87.176196
iter  40 value 86.932983
iter  50 value 86.925922
iter  60 value 86.925070
iter  70 value 86.923439
final  value 86.923427 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.475597 
iter  10 value 88.762552
iter  20 value 88.178687
iter  30 value 88.051668
iter  40 value 88.049204
iter  50 value 86.936720
iter  60 value 86.927245
iter  70 value 86.925385
iter  80 value 86.609986
iter  90 value 86.349711
iter 100 value 86.348387
final  value 86.348387 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.917940 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.440738 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.945122 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.170314 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.913447 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.552676 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.335441 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.007930 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.358643 
final  value 93.893850 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.180038 
iter  10 value 93.328262
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.475386 
final  value 92.563129 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.800314 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.036071 
iter  10 value 91.563615
iter  20 value 91.278831
iter  20 value 91.278831
iter  20 value 91.278831
final  value 91.278831 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.809875 
iter  10 value 93.328268
iter  20 value 92.877717
final  value 92.833427 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.783611 
iter  10 value 94.053282
iter  20 value 91.254976
iter  30 value 89.992015
iter  40 value 89.955849
iter  40 value 89.955848
iter  40 value 89.955848
final  value 89.955848 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.157317 
iter  10 value 94.086532
iter  20 value 93.959621
iter  30 value 93.629813
iter  40 value 93.557511
iter  50 value 92.824092
iter  60 value 87.379888
iter  70 value 82.969423
iter  80 value 82.185906
iter  90 value 81.039474
iter 100 value 80.497442
final  value 80.497442 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.395819 
iter  10 value 90.905609
iter  20 value 83.012426
iter  30 value 82.413739
iter  40 value 81.473469
iter  50 value 80.164844
iter  60 value 79.608210
iter  70 value 79.594189
iter  80 value 79.541002
iter  90 value 79.453186
final  value 79.453181 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.663810 
iter  10 value 94.059773
iter  20 value 93.717132
iter  30 value 93.543612
iter  40 value 93.536574
iter  50 value 92.086583
iter  60 value 85.121301
iter  70 value 84.542635
iter  80 value 83.382834
iter  90 value 83.301513
final  value 83.296109 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.591422 
iter  10 value 94.004472
iter  20 value 92.912211
iter  30 value 92.837412
iter  40 value 92.827439
iter  50 value 92.826044
iter  60 value 92.825797
iter  70 value 92.825453
iter  80 value 92.292388
iter  90 value 90.119648
iter 100 value 85.620377
final  value 85.620377 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.653907 
iter  10 value 93.832057
iter  20 value 85.502076
iter  30 value 81.848681
iter  40 value 81.632071
iter  50 value 80.736483
iter  60 value 80.070084
iter  70 value 78.848067
iter  80 value 78.564498
final  value 78.564430 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.913049 
iter  10 value 94.087874
iter  20 value 93.725153
iter  30 value 93.070243
iter  40 value 91.068375
iter  50 value 89.693017
iter  60 value 87.043907
iter  70 value 82.024643
iter  80 value 79.915579
iter  90 value 79.287661
iter 100 value 78.316677
final  value 78.316677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.039966 
iter  10 value 93.970721
iter  20 value 93.040192
iter  30 value 90.461805
iter  40 value 84.819428
iter  50 value 83.534978
iter  60 value 80.550393
iter  70 value 79.551285
iter  80 value 78.036904
iter  90 value 77.470234
iter 100 value 77.294529
final  value 77.294529 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.076406 
iter  10 value 93.476816
iter  20 value 84.033786
iter  30 value 82.166192
iter  40 value 79.635289
iter  50 value 78.064394
iter  60 value 77.416584
iter  70 value 77.307138
iter  80 value 77.075220
iter  90 value 76.839213
iter 100 value 76.784017
final  value 76.784017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.209034 
iter  10 value 94.224872
iter  20 value 88.791720
iter  30 value 84.850083
iter  40 value 80.631756
iter  50 value 79.003662
iter  60 value 78.424184
iter  70 value 78.353950
iter  80 value 77.518267
iter  90 value 77.350153
iter 100 value 77.034756
final  value 77.034756 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.954222 
iter  10 value 93.386679
iter  20 value 83.756934
iter  30 value 80.500173
iter  40 value 79.569361
iter  50 value 79.462544
iter  60 value 78.378641
iter  70 value 77.809396
iter  80 value 77.719706
iter  90 value 77.648606
iter 100 value 77.637341
final  value 77.637341 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.230379 
iter  10 value 96.801175
iter  20 value 93.636777
iter  30 value 93.593241
iter  40 value 92.761159
iter  50 value 82.729483
iter  60 value 81.277233
iter  70 value 79.697515
iter  80 value 78.036110
iter  90 value 77.833137
iter 100 value 77.683442
final  value 77.683442 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.056793 
iter  10 value 94.447145
iter  20 value 87.223001
iter  30 value 83.216927
iter  40 value 82.108819
iter  50 value 81.650273
iter  60 value 79.973287
iter  70 value 78.718072
iter  80 value 77.534671
iter  90 value 77.132228
iter 100 value 76.892124
final  value 76.892124 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.004838 
iter  10 value 94.510991
iter  20 value 92.853055
iter  30 value 92.161161
iter  40 value 88.348189
iter  50 value 82.199284
iter  60 value 80.363764
iter  70 value 79.926975
iter  80 value 78.598286
iter  90 value 77.458400
iter 100 value 77.054541
final  value 77.054541 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.777248 
iter  10 value 94.332553
iter  20 value 93.563942
iter  30 value 85.398500
iter  40 value 83.765390
iter  50 value 81.050729
iter  60 value 78.455531
iter  70 value 77.762791
iter  80 value 77.107704
iter  90 value 76.912520
iter 100 value 76.802833
final  value 76.802833 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.845310 
iter  10 value 95.690316
iter  20 value 93.253577
iter  30 value 88.077083
iter  40 value 81.571189
iter  50 value 80.443558
iter  60 value 79.728937
iter  70 value 79.069719
iter  80 value 78.080726
iter  90 value 77.826819
iter 100 value 77.577738
final  value 77.577738 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.504089 
final  value 94.057652 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.191535 
final  value 94.054315 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.492134 
final  value 94.054510 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.117448 
final  value 94.054465 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.157238 
iter  10 value 93.330776
iter  20 value 93.329936
iter  30 value 93.329126
final  value 93.329109 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.557929 
iter  10 value 93.431502
iter  20 value 93.429908
iter  30 value 91.256957
iter  40 value 91.255509
iter  50 value 91.219328
iter  60 value 90.842694
iter  70 value 89.416497
final  value 89.292527 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.661138 
iter  10 value 94.058535
iter  20 value 94.037062
iter  30 value 91.767346
iter  40 value 89.552169
final  value 89.550850 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.091061 
iter  10 value 94.479841
iter  20 value 93.703059
iter  30 value 93.699802
iter  40 value 83.689379
iter  50 value 82.628976
iter  60 value 82.627256
iter  70 value 80.881969
iter  80 value 80.182025
iter  90 value 80.079704
iter 100 value 80.048897
final  value 80.048897 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.009436 
iter  10 value 94.057717
iter  20 value 92.254659
iter  30 value 85.256026
iter  40 value 82.895028
iter  50 value 79.203077
iter  60 value 76.170439
iter  70 value 75.404690
iter  80 value 75.308726
iter  90 value 75.256602
iter 100 value 75.253862
final  value 75.253862 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.969946 
iter  10 value 94.072262
iter  20 value 93.993546
iter  30 value 93.379636
iter  40 value 93.344077
iter  50 value 93.330699
iter  60 value 92.236986
iter  70 value 83.824805
iter  80 value 80.129427
iter  90 value 80.049588
iter 100 value 79.872377
final  value 79.872377 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 136.999331 
iter  10 value 94.061541
iter  20 value 93.949248
final  value 92.564049 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.576109 
iter  10 value 94.060346
iter  20 value 94.051510
iter  30 value 92.344005
iter  40 value 90.911245
iter  50 value 89.572455
iter  60 value 89.416058
iter  70 value 79.869146
iter  80 value 79.765727
iter  90 value 79.762930
iter 100 value 79.680737
final  value 79.680737 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.472494 
iter  10 value 93.475584
iter  20 value 93.337884
iter  30 value 91.783335
iter  40 value 84.140658
iter  50 value 84.032462
iter  60 value 84.031790
iter  70 value 83.560229
iter  80 value 81.854649
iter  90 value 77.834722
iter 100 value 76.131840
final  value 76.131840 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.008359 
iter  10 value 85.658488
iter  20 value 85.620181
iter  30 value 83.342955
iter  40 value 83.340224
final  value 83.340040 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.115521 
iter  10 value 94.060934
iter  20 value 93.824244
iter  30 value 85.034881
iter  40 value 84.375527
iter  50 value 84.365171
iter  60 value 84.346652
iter  70 value 84.343797
final  value 84.342576 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.207746 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.514487 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.930117 
iter  10 value 94.466835
final  value 94.466826 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.924238 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.223956 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.830827 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.417857 
final  value 94.387430 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.125932 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.862848 
iter  10 value 88.969403
final  value 88.912565 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.183259 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.394140 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.325091 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.532852 
final  value 94.428839 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.034978 
final  value 94.428841 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.024770 
iter  10 value 86.861708
iter  20 value 85.399313
iter  30 value 84.630909
final  value 84.630876 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.504277 
iter  10 value 94.442651
iter  20 value 92.845177
iter  30 value 91.125898
iter  40 value 87.437043
iter  50 value 85.634954
iter  60 value 84.739029
iter  70 value 84.112183
iter  80 value 83.611520
iter  90 value 83.341468
iter 100 value 83.093675
final  value 83.093675 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.793886 
iter  10 value 94.417640
iter  20 value 87.899051
iter  30 value 87.026821
iter  40 value 86.183723
iter  50 value 85.756062
final  value 85.753656 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.672711 
iter  10 value 94.486781
iter  20 value 94.384747
iter  30 value 88.455059
iter  40 value 85.703106
iter  50 value 85.378335
iter  60 value 85.237056
iter  70 value 83.839969
iter  80 value 83.501132
iter  90 value 83.297622
final  value 83.292856 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.709262 
iter  10 value 94.407548
iter  20 value 90.535164
iter  30 value 88.207327
iter  40 value 85.490316
iter  50 value 84.823194
iter  60 value 84.084170
iter  70 value 83.608646
iter  80 value 83.514829
iter  90 value 83.388563
iter 100 value 83.292867
final  value 83.292867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.185619 
iter  10 value 91.482661
iter  20 value 88.860462
iter  30 value 86.665430
iter  40 value 85.969463
iter  50 value 85.788030
iter  60 value 85.753681
final  value 85.753656 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.218550 
iter  10 value 88.732969
iter  20 value 86.453819
iter  30 value 85.860363
iter  40 value 85.430293
iter  50 value 85.196031
iter  60 value 83.982325
iter  70 value 83.891179
iter  80 value 83.401693
iter  90 value 82.830445
iter 100 value 82.666456
final  value 82.666456 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.275681 
iter  10 value 94.271303
iter  20 value 93.059000
iter  30 value 92.830648
iter  40 value 87.701282
iter  50 value 87.113426
iter  60 value 86.502286
iter  70 value 86.362436
iter  80 value 86.071277
iter  90 value 85.859188
iter 100 value 85.053365
final  value 85.053365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.244767 
iter  10 value 94.515262
iter  20 value 93.185218
iter  30 value 86.188405
iter  40 value 85.330011
iter  50 value 84.698089
iter  60 value 83.304956
iter  70 value 82.829401
iter  80 value 82.572894
iter  90 value 82.301569
iter 100 value 82.155557
final  value 82.155557 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.646865 
iter  10 value 94.148721
iter  20 value 88.902161
iter  30 value 87.938739
iter  40 value 86.985260
iter  50 value 85.797901
iter  60 value 85.558115
iter  70 value 85.460948
iter  80 value 84.429144
iter  90 value 83.870336
iter 100 value 83.835351
final  value 83.835351 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.310696 
iter  10 value 94.859532
iter  20 value 88.097137
iter  30 value 87.369781
iter  40 value 85.875577
iter  50 value 85.506434
iter  60 value 85.188996
iter  70 value 85.007558
iter  80 value 83.759320
iter  90 value 82.674028
iter 100 value 82.373027
final  value 82.373027 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.823572 
iter  10 value 94.886507
iter  20 value 89.892286
iter  30 value 88.657968
iter  40 value 87.746571
iter  50 value 87.123572
iter  60 value 86.817495
iter  70 value 85.808663
iter  80 value 82.831261
iter  90 value 82.166002
iter 100 value 82.010836
final  value 82.010836 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.768954 
iter  10 value 95.912604
iter  20 value 94.477318
iter  30 value 93.731005
iter  40 value 91.726446
iter  50 value 86.098666
iter  60 value 84.681863
iter  70 value 83.978288
iter  80 value 82.940179
iter  90 value 81.941115
iter 100 value 81.530778
final  value 81.530778 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.493667 
iter  10 value 93.976673
iter  20 value 88.961432
iter  30 value 88.033105
iter  40 value 87.489798
iter  50 value 86.077057
iter  60 value 86.003538
iter  70 value 85.874199
iter  80 value 85.188488
iter  90 value 84.265941
iter 100 value 83.929979
final  value 83.929979 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 133.792497 
iter  10 value 94.469595
iter  20 value 88.294678
iter  30 value 87.490973
iter  40 value 86.855740
iter  50 value 83.948924
iter  60 value 82.461883
iter  70 value 82.305467
iter  80 value 81.887659
iter  90 value 81.723821
iter 100 value 81.627222
final  value 81.627222 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.741467 
iter  10 value 99.204659
iter  20 value 88.107660
iter  30 value 83.631310
iter  40 value 82.861352
iter  50 value 82.563261
iter  60 value 82.120351
iter  70 value 81.738101
iter  80 value 81.596401
iter  90 value 81.536379
iter 100 value 81.447496
final  value 81.447496 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.509894 
iter  10 value 93.089686
iter  20 value 86.951801
iter  30 value 86.471514
iter  40 value 86.454083
iter  40 value 86.454082
final  value 86.454082 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.129168 
final  value 94.486020 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.988785 
iter  10 value 94.485881
iter  20 value 94.484271
iter  30 value 94.390257
iter  40 value 94.029586
final  value 93.746226 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.819716 
final  value 94.485842 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.109160 
final  value 94.485854 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.853481 
iter  10 value 94.472015
iter  20 value 94.468112
final  value 94.467896 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.091357 
iter  10 value 94.143746
iter  20 value 89.852349
iter  30 value 89.636724
iter  40 value 89.367665
final  value 89.367211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.043293 
iter  10 value 93.845275
iter  20 value 93.750884
iter  30 value 93.745443
iter  40 value 88.109821
iter  50 value 86.519765
iter  60 value 86.507032
iter  70 value 86.506790
iter  80 value 86.506532
iter  90 value 86.504436
iter 100 value 85.816141
final  value 85.816141 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.926323 
iter  10 value 94.471661
iter  20 value 94.466998
iter  30 value 94.444227
iter  40 value 92.634181
iter  50 value 92.633094
iter  60 value 92.557584
iter  70 value 92.286318
iter  80 value 91.439143
final  value 91.438972 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.535228 
iter  10 value 94.487422
iter  20 value 94.231133
iter  30 value 87.613046
iter  40 value 83.718480
iter  50 value 83.135210
iter  60 value 82.997572
iter  70 value 82.970509
iter  80 value 82.554825
iter  90 value 81.644774
iter 100 value 81.175214
final  value 81.175214 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.432896 
iter  10 value 94.492064
iter  20 value 90.416927
iter  30 value 89.378832
iter  40 value 89.376688
iter  50 value 89.359603
iter  60 value 88.070320
iter  70 value 86.703337
iter  80 value 86.078447
final  value 86.078264 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.290424 
iter  10 value 94.503342
iter  20 value 94.494081
iter  30 value 93.930560
iter  40 value 88.097770
iter  50 value 87.632486
final  value 87.630344 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.807844 
iter  10 value 94.492024
iter  20 value 88.580750
iter  30 value 86.947828
iter  40 value 86.825002
final  value 86.782538 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.008841 
iter  10 value 94.492662
iter  20 value 94.450783
iter  30 value 94.023975
iter  40 value 93.799329
iter  50 value 88.084837
iter  60 value 85.185940
iter  70 value 84.891513
iter  80 value 84.692160
iter  90 value 84.643874
iter 100 value 84.613416
final  value 84.613416 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.271878 
iter  10 value 89.447665
iter  20 value 86.073664
iter  30 value 85.890046
iter  40 value 85.884173
iter  40 value 85.884173
final  value 85.884173 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.908527 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.731110 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.555824 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.989212 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.042155 
iter  10 value 92.764220
iter  20 value 88.031081
iter  30 value 87.658227
iter  40 value 87.605786
iter  50 value 87.601213
final  value 87.601115 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.217651 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.938878 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.676829 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.106206 
iter  10 value 94.187451
iter  20 value 93.300014
iter  20 value 93.300014
final  value 93.300002 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.744300 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.332539 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.794609 
final  value 93.701657 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.559358 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.943328 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.598301 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 119.076853 
iter  10 value 94.487815
iter  20 value 93.795051
iter  30 value 92.820321
iter  40 value 86.749582
iter  50 value 86.599533
iter  60 value 86.483130
iter  70 value 85.829435
iter  80 value 85.268823
iter  90 value 85.136981
iter 100 value 85.134363
final  value 85.134363 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.375311 
final  value 94.488547 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.502723 
iter  10 value 94.472605
iter  20 value 93.261540
iter  30 value 91.547721
iter  40 value 89.522510
iter  50 value 86.030594
iter  60 value 85.707578
iter  70 value 84.876454
iter  80 value 84.775920
final  value 84.775918 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.116302 
iter  10 value 94.387916
iter  20 value 93.644323
iter  30 value 93.251532
iter  40 value 91.260351
iter  50 value 83.348547
iter  60 value 83.024242
iter  70 value 81.771939
iter  80 value 80.522175
iter  90 value 80.327019
iter 100 value 80.257036
final  value 80.257036 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.517669 
iter  10 value 94.352476
iter  20 value 93.627608
iter  30 value 93.543764
iter  40 value 92.922142
iter  50 value 88.463982
iter  60 value 86.655245
iter  70 value 83.544450
iter  80 value 83.250815
iter  90 value 83.209730
final  value 83.209548 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.828545 
iter  10 value 94.506558
iter  20 value 94.459199
iter  30 value 90.652853
iter  40 value 85.193448
iter  50 value 84.674293
iter  60 value 82.944825
iter  70 value 82.696398
iter  80 value 82.669211
iter  90 value 82.595382
iter 100 value 81.426615
final  value 81.426615 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.485813 
iter  10 value 94.624236
iter  20 value 94.453874
iter  30 value 85.513475
iter  40 value 84.960865
iter  50 value 84.414686
iter  60 value 83.269163
iter  70 value 83.153011
iter  80 value 82.953582
iter  90 value 82.657362
iter 100 value 82.613055
final  value 82.613055 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.715418 
iter  10 value 93.734010
iter  20 value 87.359125
iter  30 value 86.664563
iter  40 value 83.840893
iter  50 value 83.270053
iter  60 value 82.687092
iter  70 value 82.182234
iter  80 value 82.125493
iter  90 value 82.044304
iter 100 value 81.872714
final  value 81.872714 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.039168 
iter  10 value 94.381730
iter  20 value 93.612154
iter  30 value 93.524461
iter  40 value 92.865188
iter  50 value 90.775969
iter  60 value 84.917279
iter  70 value 84.736191
iter  80 value 83.007188
iter  90 value 82.459857
iter 100 value 81.557414
final  value 81.557414 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.531436 
iter  10 value 94.150037
iter  20 value 88.755780
iter  30 value 82.983445
iter  40 value 82.568916
iter  50 value 80.747997
iter  60 value 80.519147
iter  70 value 80.394369
iter  80 value 80.233791
iter  90 value 79.493080
iter 100 value 79.135584
final  value 79.135584 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.224921 
iter  10 value 92.858537
iter  20 value 87.360608
iter  30 value 86.233201
iter  40 value 85.589836
iter  50 value 83.787196
iter  60 value 82.195644
iter  70 value 80.933794
iter  80 value 79.477084
iter  90 value 78.826954
iter 100 value 78.308410
final  value 78.308410 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.393537 
iter  10 value 94.548889
iter  20 value 87.505304
iter  30 value 83.623479
iter  40 value 83.411109
iter  50 value 82.974134
iter  60 value 82.013469
iter  70 value 81.167732
iter  80 value 80.394448
iter  90 value 79.603186
iter 100 value 79.366641
final  value 79.366641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.900519 
iter  10 value 94.426227
iter  20 value 91.396617
iter  30 value 88.865027
iter  40 value 88.373374
iter  50 value 86.918650
iter  60 value 83.832758
iter  70 value 82.310874
iter  80 value 81.755381
iter  90 value 80.027334
iter 100 value 78.938981
final  value 78.938981 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.345772 
iter  10 value 94.463004
iter  20 value 90.194338
iter  30 value 86.691093
iter  40 value 82.964583
iter  50 value 79.811315
iter  60 value 79.480001
iter  70 value 79.344135
iter  80 value 79.089586
iter  90 value 78.787586
iter 100 value 78.612262
final  value 78.612262 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.025180 
iter  10 value 94.621388
iter  20 value 90.988946
iter  30 value 87.476971
iter  40 value 86.938005
iter  50 value 85.724942
iter  60 value 83.115705
iter  70 value 81.553541
iter  80 value 80.928288
iter  90 value 80.749306
iter 100 value 80.566546
final  value 80.566546 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.046882 
iter  10 value 94.485889
iter  20 value 94.484174
iter  30 value 87.301605
iter  40 value 85.415946
iter  50 value 83.512804
iter  60 value 83.510894
iter  70 value 83.375168
iter  70 value 83.375167
iter  70 value 83.375167
final  value 83.375167 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.050369 
final  value 94.485764 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.904132 
final  value 94.486093 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.688958 
iter  10 value 94.486058
final  value 94.484222 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.796146 
final  value 94.486028 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.481300 
iter  10 value 94.488805
iter  20 value 94.484265
iter  30 value 94.340503
iter  40 value 93.702963
iter  50 value 93.702456
iter  50 value 93.702456
iter  50 value 93.702456
final  value 93.702456 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.529121 
iter  10 value 94.487741
iter  20 value 94.472658
iter  30 value 92.109871
iter  40 value 85.723359
iter  50 value 84.893194
iter  60 value 81.249401
iter  70 value 80.508993
iter  80 value 80.502479
iter  90 value 79.481488
iter 100 value 76.894569
final  value 76.894569 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.149837 
iter  10 value 94.317465
iter  20 value 94.313219
iter  30 value 94.310782
iter  40 value 94.236953
iter  50 value 90.474751
iter  60 value 84.131377
iter  70 value 81.706978
iter  80 value 81.670280
iter  90 value 81.669092
iter 100 value 81.666288
final  value 81.666288 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.850849 
iter  10 value 94.359312
iter  20 value 94.348697
iter  30 value 85.340601
iter  40 value 84.203798
iter  50 value 84.199073
iter  60 value 82.338113
final  value 82.337424 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.592492 
iter  10 value 94.488517
iter  20 value 94.484223
iter  20 value 94.484222
iter  20 value 94.484222
final  value 94.484222 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.995540 
iter  10 value 94.492177
iter  20 value 94.475969
iter  30 value 93.702085
iter  30 value 93.702084
iter  30 value 93.702084
final  value 93.702084 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.427849 
iter  10 value 94.363018
iter  20 value 94.355533
final  value 94.354975 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.135503 
iter  10 value 94.208856
iter  20 value 93.608219
iter  30 value 93.515616
iter  40 value 93.038961
iter  50 value 83.511146
iter  60 value 83.296252
iter  70 value 82.562645
iter  80 value 82.561266
iter  90 value 82.401982
iter 100 value 81.658294
final  value 81.658294 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.286929 
iter  10 value 94.185904
iter  20 value 93.622468
iter  30 value 93.619279
iter  40 value 92.093142
iter  50 value 92.091494
final  value 92.091476 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.747516 
iter  10 value 93.479575
iter  20 value 93.473274
final  value 93.471254 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.914955 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.481500 
iter  10 value 86.538772
iter  20 value 85.647798
iter  30 value 85.647281
iter  30 value 85.647280
iter  30 value 85.647280
final  value 85.647280 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.787554 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.363342 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.019094 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.399617 
iter  10 value 93.637302
final  value 93.634731 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.649052 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.030538 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.594906 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.795350 
iter  10 value 90.653929
iter  20 value 90.085137
iter  30 value 89.975061
iter  40 value 89.974592
final  value 89.974577 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.512400 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.667155 
iter  10 value 94.028703
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.802007 
iter  10 value 93.323356
final  value 93.320225 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.712015 
iter  10 value 93.320231
final  value 93.320225 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.406877 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.626197 
iter  10 value 94.490970
iter  20 value 94.485979
iter  30 value 91.362935
iter  40 value 87.627269
iter  50 value 86.255271
iter  60 value 85.816860
iter  70 value 85.797787
iter  80 value 84.916720
iter  90 value 84.499487
iter 100 value 84.079971
final  value 84.079971 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 110.013929 
iter  10 value 94.569264
iter  20 value 93.578712
iter  30 value 87.048522
iter  40 value 86.403042
iter  50 value 86.271838
iter  60 value 85.245887
iter  70 value 84.718131
iter  80 value 84.350303
iter  90 value 84.214107
final  value 84.214054 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.443753 
iter  10 value 94.460630
iter  20 value 94.160841
iter  30 value 93.487286
iter  40 value 92.584482
iter  50 value 85.892799
iter  60 value 84.698296
iter  70 value 84.434547
iter  80 value 83.662380
iter  90 value 83.002658
iter 100 value 82.220154
final  value 82.220154 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.313481 
iter  10 value 88.017480
iter  20 value 84.681204
iter  30 value 84.275261
iter  40 value 84.240172
final  value 84.240114 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.261572 
iter  10 value 89.309933
iter  20 value 85.108408
iter  30 value 84.666926
iter  40 value 84.490215
iter  50 value 84.361179
iter  60 value 83.990411
iter  70 value 83.839902
final  value 83.832437 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.538743 
iter  10 value 95.410815
iter  20 value 90.527693
iter  30 value 86.806482
iter  40 value 84.832283
iter  50 value 82.563290
iter  60 value 81.597576
iter  70 value 81.275361
iter  80 value 80.973442
iter  90 value 80.881801
iter 100 value 80.795769
final  value 80.795769 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.891393 
iter  10 value 93.630020
iter  20 value 85.182166
iter  30 value 84.958772
iter  40 value 84.542758
iter  50 value 84.157075
iter  60 value 83.940894
iter  70 value 82.939423
iter  80 value 81.503926
iter  90 value 81.430681
iter 100 value 81.124345
final  value 81.124345 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.059715 
iter  10 value 94.513413
iter  20 value 87.502718
iter  30 value 86.213139
iter  40 value 83.033891
iter  50 value 82.198311
iter  60 value 81.684709
iter  70 value 81.157235
iter  80 value 81.040576
iter  90 value 80.989043
iter 100 value 80.980293
final  value 80.980293 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.616120 
iter  10 value 94.609298
iter  20 value 91.315394
iter  30 value 88.241609
iter  40 value 85.821242
iter  50 value 83.485736
iter  60 value 82.935588
iter  70 value 81.905816
iter  80 value 81.347794
iter  90 value 80.989664
iter 100 value 80.597767
final  value 80.597767 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.944005 
iter  10 value 94.258173
iter  20 value 91.355246
iter  30 value 87.134612
iter  40 value 85.865364
iter  50 value 83.483033
iter  60 value 82.082706
iter  70 value 81.729974
iter  80 value 81.471801
iter  90 value 81.221422
iter 100 value 81.151040
final  value 81.151040 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.886261 
iter  10 value 91.404887
iter  20 value 90.744070
iter  30 value 87.562257
iter  40 value 83.540207
iter  50 value 82.576645
iter  60 value 81.474765
iter  70 value 80.613509
iter  80 value 80.370417
iter  90 value 80.292078
iter 100 value 80.212724
final  value 80.212724 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.039533 
iter  10 value 99.658467
iter  20 value 94.477539
iter  30 value 90.191959
iter  40 value 85.327377
iter  50 value 84.113574
iter  60 value 83.637044
iter  70 value 83.362977
iter  80 value 83.213540
iter  90 value 83.180702
iter 100 value 82.276965
final  value 82.276965 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.390945 
iter  10 value 94.521923
iter  20 value 87.252563
iter  30 value 85.460051
iter  40 value 84.058229
iter  50 value 82.235497
iter  60 value 81.568444
iter  70 value 81.172743
iter  80 value 81.060642
iter  90 value 80.988973
iter 100 value 80.921064
final  value 80.921064 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.551935 
iter  10 value 98.934756
iter  20 value 91.294529
iter  30 value 86.182249
iter  40 value 83.203557
iter  50 value 81.666114
iter  60 value 81.313289
iter  70 value 80.954977
iter  80 value 80.801955
iter  90 value 80.750209
iter 100 value 80.652066
final  value 80.652066 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.296413 
iter  10 value 94.414519
iter  20 value 86.889582
iter  30 value 86.153735
iter  40 value 85.461905
iter  50 value 83.937449
iter  60 value 83.062703
iter  70 value 82.625820
iter  80 value 82.388376
iter  90 value 81.391526
iter 100 value 80.817452
final  value 80.817452 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.820786 
final  value 94.485913 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.600917 
final  value 94.485684 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.795518 
iter  10 value 94.485972
iter  20 value 94.484303
iter  30 value 93.320715
final  value 93.320711 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.507369 
final  value 94.486153 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.873549 
iter  10 value 94.485066
iter  20 value 94.114224
iter  30 value 85.471224
iter  40 value 84.539859
iter  50 value 83.875354
iter  60 value 82.688336
iter  70 value 82.650939
iter  80 value 82.238339
iter  90 value 81.567167
iter 100 value 81.474848
final  value 81.474848 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 96.120356 
iter  10 value 88.427450
iter  20 value 85.657316
iter  30 value 85.652948
iter  40 value 85.651684
iter  50 value 85.651292
iter  60 value 84.431200
iter  70 value 84.418317
iter  70 value 84.418316
final  value 84.418307 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.658345 
iter  10 value 93.325880
iter  20 value 93.322672
iter  30 value 93.322513
iter  40 value 92.580777
iter  50 value 85.985103
iter  60 value 85.275850
iter  70 value 83.206086
iter  80 value 82.762988
iter  90 value 82.628273
iter 100 value 82.389857
final  value 82.389857 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.373113 
iter  10 value 94.031780
iter  20 value 94.029275
iter  30 value 94.026780
iter  40 value 93.775943
iter  50 value 93.743131
iter  60 value 93.742722
final  value 93.742717 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.701401 
iter  10 value 94.031631
iter  20 value 93.679069
iter  30 value 85.666895
iter  40 value 84.762839
final  value 84.762649 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.542141 
iter  10 value 94.448410
iter  20 value 94.296130
iter  30 value 94.147505
iter  40 value 94.147071
iter  40 value 94.147071
iter  40 value 94.147071
final  value 94.147071 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.523354 
iter  10 value 94.451943
iter  20 value 94.446914
iter  30 value 93.382966
iter  40 value 85.513796
iter  50 value 84.913210
final  value 84.913114 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.175443 
iter  10 value 93.072912
iter  20 value 92.821844
iter  30 value 92.642797
iter  40 value 92.449904
iter  50 value 92.449603
iter  60 value 92.448651
final  value 92.448621 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.464569 
iter  10 value 93.710195
iter  20 value 93.666219
iter  30 value 93.642298
iter  40 value 93.635783
iter  50 value 91.916987
iter  60 value 88.577399
iter  70 value 86.017938
iter  80 value 85.101744
iter  90 value 81.428443
iter 100 value 81.111789
final  value 81.111789 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.649672 
iter  10 value 94.519319
iter  20 value 94.465185
iter  30 value 94.150163
iter  40 value 94.101714
iter  50 value 94.032689
iter  60 value 93.383819
iter  70 value 93.113060
iter  80 value 90.044419
iter  90 value 85.331282
iter 100 value 84.595459
final  value 84.595459 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.127706 
iter  10 value 94.007676
iter  20 value 94.006445
iter  30 value 93.711967
iter  40 value 93.374040
iter  50 value 93.360081
iter  60 value 93.114627
iter  70 value 93.114413
iter  80 value 92.815110
iter  90 value 92.674568
iter 100 value 92.615535
final  value 92.615535 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.422071 
iter  10 value 110.858281
iter  20 value 110.845397
iter  30 value 108.534647
iter  40 value 108.529312
iter  50 value 108.529109
iter  60 value 107.665371
final  value 107.181467 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.785124 
iter  10 value 117.897004
iter  20 value 117.104199
iter  30 value 109.413408
iter  40 value 108.339763
iter  50 value 102.221092
iter  60 value 101.300066
iter  70 value 100.885430
iter  80 value 100.864472
iter  90 value 100.863653
iter 100 value 100.857987
final  value 100.857987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.326055 
iter  10 value 117.897734
iter  20 value 117.467690
iter  30 value 114.561298
iter  40 value 114.397531
iter  50 value 114.393096
final  value 114.392739 
converged
Fitting Repeat 4 

# weights:  507
initial  value 149.105731 
iter  10 value 117.898395
iter  20 value 117.848264
iter  30 value 106.063167
iter  40 value 102.103226
iter  50 value 101.191829
iter  60 value 101.001504
iter  70 value 100.911838
iter  80 value 100.910538
iter  90 value 100.349918
iter 100 value 99.673704
final  value 99.673704 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.499100 
iter  10 value 117.022253
iter  20 value 115.217680
iter  30 value 115.040769
iter  40 value 115.040286
iter  40 value 115.040285
iter  40 value 115.040285
final  value 115.040285 
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 Mar 28 04:33:04 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 
 76.214   1.988 118.864