##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-01-22 r87618)
* 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 ‘1.13.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      33.864  1.682  35.839
var_imp       33.456  1.734  35.473
corr_plot     33.300  1.661  35.186
pred_ensembel 13.231  0.428  11.835
enrichfindP    0.467  0.056   7.970
* 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 ‘1.13.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2025-01-22 r87618) -- "Unsuffered Consequences"
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 98.050354 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.520779 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.887481 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.704808 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.240054 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.093301 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.331363 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.247177 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.541154 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.377680 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.967426 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.181708 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.708409 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.226976 
iter  10 value 90.888695
iter  20 value 88.637667
iter  30 value 87.518525
iter  40 value 87.156657
iter  50 value 86.485521
iter  60 value 84.246273
iter  70 value 83.995264
iter  80 value 83.994424
iter  90 value 83.994078
iter 100 value 83.993873
final  value 83.993873 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.050062 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.899309 
iter  10 value 94.482401
iter  20 value 92.891305
iter  30 value 92.708393
iter  40 value 88.443593
iter  50 value 87.697757
iter  60 value 87.022821
iter  70 value 86.913541
iter  80 value 86.770063
iter  90 value 86.743907
final  value 86.743605 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.372276 
iter  10 value 94.481674
iter  20 value 94.467538
iter  30 value 91.864110
iter  40 value 88.996568
iter  50 value 88.194254
iter  60 value 87.536931
iter  70 value 87.127159
iter  80 value 87.089976
final  value 87.089777 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.839653 
iter  10 value 94.488304
iter  20 value 92.635318
iter  30 value 88.795526
iter  40 value 88.000431
iter  50 value 87.605361
iter  60 value 87.134318
iter  70 value 87.089779
final  value 87.089777 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.440687 
iter  10 value 94.442723
iter  20 value 93.061825
iter  30 value 92.416096
iter  40 value 88.336514
iter  50 value 87.978693
iter  60 value 87.376547
iter  70 value 87.179038
iter  80 value 87.093752
final  value 87.089778 
converged
Fitting Repeat 5 

# weights:  103
initial  value 117.467395 
iter  10 value 94.504547
iter  20 value 93.796024
iter  30 value 88.304628
iter  40 value 87.482309
iter  50 value 87.327527
iter  60 value 87.321124
final  value 87.321106 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.136970 
iter  10 value 94.461484
iter  20 value 91.155160
iter  30 value 89.306920
iter  40 value 88.157281
iter  50 value 86.720847
iter  60 value 86.232473
iter  70 value 85.942959
iter  80 value 84.912287
iter  90 value 84.451480
iter 100 value 84.352094
final  value 84.352094 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.220384 
iter  10 value 94.011552
iter  20 value 92.517500
iter  30 value 89.676073
iter  40 value 89.186972
iter  50 value 85.760161
iter  60 value 85.237664
iter  70 value 84.916638
iter  80 value 84.875871
iter  90 value 84.680324
iter 100 value 84.517833
final  value 84.517833 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.900574 
iter  10 value 94.534100
iter  20 value 94.486313
iter  30 value 94.340992
iter  40 value 93.000836
iter  50 value 92.692552
iter  60 value 92.617022
iter  70 value 92.542589
iter  80 value 92.471246
iter  90 value 92.197960
iter 100 value 87.302764
final  value 87.302764 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.853233 
iter  10 value 94.493155
iter  20 value 91.764778
iter  30 value 90.044043
iter  40 value 87.181179
iter  50 value 85.755540
iter  60 value 84.751665
iter  70 value 84.172634
iter  80 value 84.111062
iter  90 value 84.094270
iter 100 value 84.060727
final  value 84.060727 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.352894 
iter  10 value 90.231367
iter  20 value 88.845997
iter  30 value 87.487579
iter  40 value 87.243521
iter  50 value 86.579708
iter  60 value 85.101090
iter  70 value 84.202049
iter  80 value 84.020526
iter  90 value 83.789148
iter 100 value 83.681767
final  value 83.681767 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.778346 
iter  10 value 95.860743
iter  20 value 91.791088
iter  30 value 89.383602
iter  40 value 88.109916
iter  50 value 87.131895
iter  60 value 85.840984
iter  70 value 85.174623
iter  80 value 84.820273
iter  90 value 84.550444
iter 100 value 84.129200
final  value 84.129200 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.976443 
iter  10 value 94.595110
iter  20 value 92.171781
iter  30 value 86.914236
iter  40 value 84.802929
iter  50 value 84.151508
iter  60 value 83.989755
iter  70 value 83.933105
iter  80 value 83.788104
iter  90 value 83.665819
iter 100 value 83.540682
final  value 83.540682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.482751 
iter  10 value 94.005417
iter  20 value 90.585306
iter  30 value 89.883174
iter  40 value 86.341585
iter  50 value 85.445066
iter  60 value 84.637504
iter  70 value 84.155145
iter  80 value 83.929551
iter  90 value 83.893725
iter 100 value 83.864861
final  value 83.864861 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 134.523310 
iter  10 value 94.562058
iter  20 value 88.337992
iter  30 value 87.951783
iter  40 value 87.871997
iter  50 value 86.468920
iter  60 value 85.882516
iter  70 value 85.723172
iter  80 value 84.669487
iter  90 value 84.229870
iter 100 value 84.185481
final  value 84.185481 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.180743 
iter  10 value 94.613863
iter  20 value 93.810534
iter  30 value 89.122977
iter  40 value 87.618811
iter  50 value 87.010896
iter  60 value 86.487485
iter  70 value 85.574145
iter  80 value 84.609159
iter  90 value 84.442763
iter 100 value 84.303284
final  value 84.303284 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.871915 
final  value 94.486004 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.944076 
final  value 94.485601 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.828792 
final  value 94.482065 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.834572 
final  value 94.486026 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.107075 
final  value 94.486330 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.130447 
iter  10 value 94.488719
iter  20 value 94.483936
iter  30 value 93.947082
iter  40 value 90.494931
iter  50 value 88.215324
iter  60 value 88.020809
iter  70 value 88.011237
final  value 88.011232 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.979816 
iter  10 value 94.619742
iter  20 value 94.597952
iter  30 value 93.358247
iter  40 value 93.251526
iter  50 value 93.223525
iter  60 value 93.076406
iter  70 value 89.899736
iter  80 value 89.391318
iter  90 value 89.389974
iter 100 value 87.151246
final  value 87.151246 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.613310 
iter  10 value 88.144917
iter  20 value 87.440225
iter  30 value 87.370469
final  value 87.369501 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.026627 
iter  10 value 94.489387
iter  20 value 94.455605
iter  30 value 92.875594
iter  40 value 87.127592
iter  50 value 86.927351
iter  60 value 85.609827
iter  70 value 85.580837
iter  80 value 85.395462
iter  90 value 84.932740
iter 100 value 82.946245
final  value 82.946245 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.821632 
iter  10 value 94.473735
iter  20 value 94.469695
iter  30 value 92.896081
iter  40 value 90.776746
iter  50 value 90.774203
iter  60 value 90.772719
iter  70 value 90.772284
iter  80 value 89.897469
iter  90 value 89.800764
final  value 89.800498 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.668658 
iter  10 value 94.475701
iter  20 value 94.472555
iter  30 value 94.450119
iter  40 value 93.184467
iter  50 value 92.062709
iter  60 value 92.028052
iter  70 value 92.003435
final  value 92.003408 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.342825 
iter  10 value 94.300970
iter  20 value 94.299489
iter  30 value 94.299157
iter  40 value 94.295670
iter  50 value 94.284916
iter  60 value 94.282564
iter  70 value 88.569134
iter  80 value 87.693149
iter  90 value 87.688233
iter 100 value 86.947042
final  value 86.947042 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.848980 
iter  10 value 89.411133
iter  20 value 89.131266
iter  30 value 89.030841
iter  40 value 88.770409
iter  50 value 88.600129
iter  60 value 88.597030
iter  70 value 88.286915
iter  80 value 87.575018
iter  90 value 87.559440
iter 100 value 87.558284
final  value 87.558284 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.299912 
iter  10 value 93.959003
iter  20 value 93.939922
iter  30 value 93.606311
iter  40 value 93.223393
iter  50 value 92.630424
iter  60 value 92.307276
final  value 92.306964 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.189190 
iter  10 value 94.492822
iter  20 value 94.484334
iter  30 value 94.464830
iter  40 value 94.326368
final  value 94.326265 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.886220 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.267698 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.914661 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.908271 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.792329 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.057272 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.395167 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.582755 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.120801 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.751424 
iter  10 value 93.719469
final  value 93.719417 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.001556 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.843339 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.194270 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.542444 
iter  10 value 92.254603
iter  20 value 92.208922
iter  20 value 92.208922
iter  20 value 92.208922
final  value 92.208922 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.550159 
final  value 93.531865 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.734995 
iter  10 value 92.821412
iter  20 value 86.749979
iter  30 value 86.073086
iter  40 value 85.826638
iter  50 value 85.583159
iter  60 value 85.398578
final  value 85.398298 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.349789 
iter  10 value 93.853307
iter  20 value 93.520129
iter  30 value 93.516795
iter  30 value 93.516795
final  value 93.516795 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.785631 
iter  10 value 92.588228
iter  20 value 86.811969
iter  30 value 86.288874
iter  40 value 85.850892
iter  50 value 85.402841
iter  60 value 85.398300
final  value 85.398298 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.111089 
iter  10 value 93.078546
iter  20 value 90.000717
iter  30 value 89.528652
iter  40 value 86.852080
iter  50 value 86.696714
iter  60 value 86.608070
iter  70 value 85.905551
iter  80 value 85.356454
iter  90 value 85.238622
iter 100 value 85.212324
final  value 85.212324 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.961756 
iter  10 value 94.056606
iter  20 value 91.169183
iter  30 value 88.625022
iter  40 value 86.580829
iter  50 value 84.624080
iter  60 value 83.291924
iter  70 value 82.339300
iter  80 value 81.835403
iter  90 value 81.679354
iter 100 value 81.664688
final  value 81.664688 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 119.253831 
iter  10 value 94.324439
iter  20 value 90.011254
iter  30 value 86.993632
iter  40 value 86.410346
iter  50 value 85.889996
iter  60 value 85.626089
iter  70 value 83.113116
iter  80 value 82.915633
iter  90 value 82.696104
iter 100 value 82.583844
final  value 82.583844 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.551085 
iter  10 value 94.289367
iter  20 value 94.068178
iter  30 value 89.208219
iter  40 value 84.880837
iter  50 value 83.628705
iter  60 value 82.855411
iter  70 value 82.184322
iter  80 value 81.911577
iter  90 value 81.688372
iter 100 value 81.428584
final  value 81.428584 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.774877 
iter  10 value 93.737117
iter  20 value 86.122877
iter  30 value 85.577661
iter  40 value 85.132973
iter  50 value 85.068969
iter  60 value 83.351184
iter  70 value 82.371117
iter  80 value 82.208570
iter  90 value 82.024298
iter 100 value 81.344948
final  value 81.344948 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.028375 
iter  10 value 94.200388
iter  20 value 91.399987
iter  30 value 88.518701
iter  40 value 87.370085
iter  50 value 86.337466
iter  60 value 83.759454
iter  70 value 83.226085
iter  80 value 82.536863
iter  90 value 81.042567
iter 100 value 80.838742
final  value 80.838742 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.091709 
iter  10 value 93.921292
iter  20 value 91.469970
iter  30 value 86.029180
iter  40 value 85.578139
iter  50 value 82.711851
iter  60 value 82.035063
iter  70 value 81.310078
iter  80 value 80.982596
iter  90 value 80.778732
iter 100 value 80.686317
final  value 80.686317 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.378034 
iter  10 value 94.889113
iter  20 value 93.548870
iter  30 value 90.518020
iter  40 value 87.455337
iter  50 value 86.780202
iter  60 value 86.406255
iter  70 value 83.405311
iter  80 value 82.689015
iter  90 value 82.223502
iter 100 value 82.137707
final  value 82.137707 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.951657 
iter  10 value 97.501639
iter  20 value 88.712291
iter  30 value 86.135797
iter  40 value 83.520977
iter  50 value 82.061846
iter  60 value 81.654948
iter  70 value 81.579648
iter  80 value 81.346319
iter  90 value 81.331524
iter 100 value 81.317126
final  value 81.317126 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.985266 
iter  10 value 98.165400
iter  20 value 91.327856
iter  30 value 85.832112
iter  40 value 85.255122
iter  50 value 84.852269
iter  60 value 83.280186
iter  70 value 82.912843
iter  80 value 82.700104
iter  90 value 82.524708
iter 100 value 82.458838
final  value 82.458838 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.607136 
iter  10 value 94.038320
iter  20 value 91.823252
iter  30 value 86.381872
iter  40 value 85.526191
iter  50 value 85.209335
iter  60 value 83.745280
iter  70 value 82.705566
iter  80 value 82.350200
iter  90 value 82.191329
iter 100 value 82.038971
final  value 82.038971 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 143.946033 
iter  10 value 94.429228
iter  20 value 93.692717
iter  30 value 93.540474
iter  40 value 93.153612
iter  50 value 91.512469
iter  60 value 84.657782
iter  70 value 84.075316
iter  80 value 83.970258
iter  90 value 83.682573
iter 100 value 83.387869
final  value 83.387869 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.388796 
final  value 94.054394 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.629638 
final  value 94.054585 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.235390 
iter  10 value 94.008798
iter  20 value 93.744689
iter  30 value 93.246076
final  value 93.245989 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.741472 
final  value 94.054755 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.819262 
iter  10 value 94.054546
iter  20 value 94.052926
iter  20 value 94.052925
iter  20 value 94.052925
final  value 94.052925 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.704183 
iter  10 value 93.921003
final  value 93.920878 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.421045 
iter  10 value 86.871836
iter  20 value 86.801008
iter  30 value 86.279752
iter  40 value 84.862742
iter  50 value 84.774506
iter  60 value 84.773708
iter  70 value 84.771474
iter  80 value 84.770809
iter  80 value 84.770809
final  value 84.770809 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.992344 
iter  10 value 93.913192
iter  20 value 93.539689
iter  30 value 93.413471
iter  40 value 89.069121
iter  50 value 87.383276
iter  60 value 86.435814
iter  70 value 83.642428
iter  80 value 82.175192
iter  90 value 82.164589
iter 100 value 82.093097
final  value 82.093097 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.574523 
iter  10 value 94.057743
iter  20 value 93.786653
iter  30 value 93.534656
final  value 93.531943 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.819176 
iter  10 value 93.702229
iter  20 value 93.698005
final  value 93.697479 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.985565 
iter  10 value 90.247042
iter  20 value 83.973430
iter  30 value 83.671475
iter  40 value 83.595916
iter  50 value 83.535610
iter  60 value 83.518829
final  value 83.512216 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.566518 
iter  10 value 93.923985
iter  20 value 92.988300
final  value 86.454631 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.119063 
iter  10 value 94.061073
iter  20 value 94.052978
iter  30 value 91.520609
iter  40 value 84.916730
iter  50 value 81.822310
iter  60 value 80.577108
iter  70 value 80.485748
iter  80 value 80.482212
iter  90 value 80.443258
iter 100 value 79.725492
final  value 79.725492 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.237796 
iter  10 value 93.912666
iter  20 value 93.546413
iter  30 value 93.539608
iter  40 value 93.532008
iter  50 value 93.262712
iter  60 value 88.123446
iter  70 value 87.938120
iter  80 value 87.511259
iter  90 value 87.438930
final  value 87.438847 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.204620 
iter  10 value 93.783853
iter  20 value 93.489989
iter  30 value 93.485064
iter  40 value 93.476740
iter  50 value 92.622796
iter  60 value 87.279676
iter  70 value 84.966456
iter  80 value 84.937766
final  value 84.937362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 117.617830 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.462691 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.391357 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.770045 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.648531 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.409551 
iter  10 value 91.212452
iter  20 value 86.888319
iter  30 value 86.888239
final  value 86.888237 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.292237 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.672043 
iter  10 value 93.974922
iter  10 value 93.974922
iter  10 value 93.974922
final  value 93.974922 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.780486 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.775681 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.420471 
iter  10 value 93.723339
final  value 93.722225 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.847422 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.857061 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.485499 
iter  10 value 93.944597
iter  10 value 93.944597
iter  10 value 93.944597
final  value 93.944597 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.368678 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.074090 
iter  10 value 94.051187
iter  20 value 86.236114
iter  30 value 85.500933
iter  40 value 84.554668
iter  50 value 83.141048
iter  60 value 83.000695
iter  70 value 82.815298
iter  80 value 82.814604
iter  80 value 82.814604
iter  80 value 82.814604
final  value 82.814604 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.446785 
iter  10 value 93.980019
iter  20 value 87.734082
iter  30 value 85.721794
iter  40 value 85.235765
iter  50 value 85.148058
iter  60 value 85.069887
iter  70 value 85.036866
iter  80 value 83.662402
iter  90 value 82.971246
iter 100 value 82.820061
final  value 82.820061 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.063175 
iter  10 value 93.937328
iter  20 value 93.776704
iter  30 value 86.241484
iter  40 value 85.659255
iter  50 value 85.644233
iter  60 value 85.239800
iter  70 value 85.128752
iter  80 value 83.772634
iter  90 value 82.916450
iter 100 value 82.837475
final  value 82.837475 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.657680 
iter  10 value 94.060413
iter  20 value 93.865447
iter  30 value 88.393857
iter  40 value 85.956551
iter  50 value 85.264852
iter  60 value 85.151623
iter  70 value 85.077659
iter  80 value 83.243791
iter  90 value 83.002321
iter 100 value 82.984906
final  value 82.984906 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.531439 
iter  10 value 93.909486
iter  20 value 93.733695
final  value 93.705254 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.994456 
iter  10 value 94.391340
iter  20 value 93.211642
iter  30 value 84.143976
iter  40 value 83.692405
iter  50 value 83.534522
iter  60 value 82.111973
iter  70 value 81.750855
iter  80 value 81.450741
iter  90 value 80.999949
iter 100 value 80.369866
final  value 80.369866 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.902771 
iter  10 value 93.635087
iter  20 value 87.799067
iter  30 value 86.026797
iter  40 value 83.490705
iter  50 value 82.727794
iter  60 value 82.668850
iter  70 value 82.503931
iter  80 value 81.030013
iter  90 value 80.777576
iter 100 value 80.408855
final  value 80.408855 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.542303 
iter  10 value 93.806208
iter  20 value 86.244956
iter  30 value 85.115060
iter  40 value 82.927865
iter  50 value 82.638346
iter  60 value 82.591171
iter  70 value 82.580121
iter  80 value 82.554863
iter  90 value 81.507513
iter 100 value 81.110186
final  value 81.110186 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.190442 
iter  10 value 94.827675
iter  20 value 94.016920
iter  30 value 88.102770
iter  40 value 84.013060
iter  50 value 82.850396
iter  60 value 82.742745
iter  70 value 82.666446
iter  80 value 82.603460
iter  90 value 82.597314
iter 100 value 82.583892
final  value 82.583892 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.174171 
iter  10 value 93.482974
iter  20 value 85.082614
iter  30 value 83.710815
iter  40 value 83.359302
iter  50 value 82.814722
iter  60 value 82.660475
iter  70 value 81.901525
iter  80 value 81.209700
iter  90 value 80.379390
iter 100 value 80.232833
final  value 80.232833 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.190430 
iter  10 value 93.805279
iter  20 value 84.630780
iter  30 value 82.471072
iter  40 value 81.224818
iter  50 value 80.694472
iter  60 value 80.227254
iter  70 value 79.625955
iter  80 value 79.396110
iter  90 value 79.294184
iter 100 value 79.277406
final  value 79.277406 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.901651 
iter  10 value 94.069359
iter  20 value 94.022942
iter  30 value 87.472365
iter  40 value 85.359293
iter  50 value 82.694538
iter  60 value 81.137401
iter  70 value 80.798647
iter  80 value 80.375961
iter  90 value 79.993942
iter 100 value 79.891211
final  value 79.891211 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.299534 
iter  10 value 94.060384
iter  20 value 91.241217
iter  30 value 90.961817
iter  40 value 90.618460
iter  50 value 87.296595
iter  60 value 86.061954
iter  70 value 82.914825
iter  80 value 82.269590
iter  90 value 81.952230
iter 100 value 81.934847
final  value 81.934847 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.863941 
iter  10 value 93.666901
iter  20 value 88.113342
iter  30 value 84.197039
iter  40 value 81.218521
iter  50 value 80.282877
iter  60 value 79.900014
iter  70 value 79.431470
iter  80 value 79.327971
iter  90 value 79.315575
iter 100 value 79.295804
final  value 79.295804 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.502720 
iter  10 value 97.681490
iter  20 value 87.881060
iter  30 value 85.012389
iter  40 value 84.337423
iter  50 value 83.299704
iter  60 value 82.642941
iter  70 value 80.260221
iter  80 value 79.641070
iter  90 value 79.380340
iter 100 value 79.348202
final  value 79.348202 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.812550 
final  value 94.054690 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.510681 
final  value 94.054433 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.293426 
final  value 94.054771 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.521409 
final  value 94.054463 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.530531 
final  value 94.054906 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.270279 
iter  10 value 94.013993
iter  20 value 93.769327
iter  30 value 93.661803
iter  40 value 93.632319
final  value 93.632263 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.005462 
iter  10 value 94.057610
iter  20 value 94.053030
final  value 94.053017 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.169126 
iter  10 value 94.057704
iter  20 value 94.008335
iter  30 value 86.810513
iter  40 value 86.372609
iter  50 value 85.358089
iter  60 value 85.062957
final  value 85.062687 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.964823 
iter  10 value 94.057691
iter  20 value 94.047653
iter  30 value 93.739467
iter  40 value 86.286789
iter  50 value 86.277955
iter  60 value 86.268074
iter  70 value 86.121153
iter  80 value 85.361402
iter  90 value 85.239148
iter 100 value 85.233730
final  value 85.233730 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.755788 
iter  10 value 94.014679
iter  20 value 93.759050
iter  30 value 87.405408
iter  40 value 82.492973
iter  50 value 81.399257
iter  60 value 81.394182
iter  70 value 81.241167
iter  80 value 81.225639
final  value 81.225549 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.678151 
iter  10 value 90.959068
iter  20 value 86.219986
iter  30 value 83.306246
iter  40 value 83.241230
iter  50 value 83.236184
iter  60 value 83.222358
iter  70 value 82.682181
iter  80 value 82.680722
iter  90 value 82.655961
iter 100 value 82.615984
final  value 82.615984 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.910258 
iter  10 value 86.772397
iter  20 value 84.412068
iter  30 value 84.409374
iter  40 value 84.331430
iter  50 value 84.329882
iter  60 value 84.329602
iter  70 value 84.173959
iter  80 value 83.169666
iter  90 value 82.981064
iter 100 value 82.938660
final  value 82.938660 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.059163 
iter  10 value 94.059161
iter  20 value 93.918338
iter  30 value 88.757231
iter  40 value 87.172356
iter  50 value 87.062351
iter  60 value 87.048147
iter  70 value 87.047531
iter  80 value 87.045817
iter  90 value 87.044098
iter 100 value 87.043382
final  value 87.043382 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.354049 
iter  10 value 93.950535
iter  20 value 93.947771
iter  30 value 93.688988
iter  40 value 87.845505
iter  50 value 84.586925
iter  60 value 84.467668
iter  70 value 84.125088
iter  80 value 84.112951
iter  90 value 83.985105
iter 100 value 83.517041
final  value 83.517041 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.904710 
iter  10 value 93.670322
iter  20 value 93.631342
iter  30 value 93.625944
iter  40 value 86.894703
iter  50 value 85.490612
iter  60 value 84.658782
iter  70 value 84.291428
final  value 84.143935 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.544271 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.013513 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.895669 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.868060 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.707235 
final  value 94.428839 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.503017 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.177120 
iter  10 value 94.364445
iter  20 value 94.292739
iter  30 value 94.292219
final  value 94.292214 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.063478 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.830659 
iter  10 value 94.354719
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.314917 
iter  10 value 94.355175
final  value 94.350744 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.333519 
iter  10 value 87.808007
iter  20 value 85.210433
iter  30 value 84.247849
iter  40 value 84.229834
final  value 84.228981 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.504505 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.271909 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.301018 
iter  10 value 94.407026
iter  20 value 94.356429
final  value 94.350744 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.405938 
final  value 94.350744 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.837287 
iter  10 value 91.846483
iter  20 value 83.069897
iter  30 value 82.827865
iter  40 value 82.203694
iter  50 value 82.130876
final  value 82.130821 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.774262 
iter  10 value 94.445963
iter  20 value 87.222802
iter  30 value 86.309125
iter  40 value 82.939152
iter  50 value 82.475256
iter  60 value 82.281611
iter  70 value 82.133312
iter  80 value 82.130894
final  value 82.130881 
converged
Fitting Repeat 3 

# weights:  103
initial  value 119.185076 
iter  10 value 94.466506
iter  20 value 91.473291
iter  30 value 87.003052
iter  40 value 83.247857
iter  50 value 82.851619
iter  60 value 82.833815
iter  70 value 82.827793
final  value 82.827555 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.172434 
iter  10 value 94.456949
iter  20 value 94.053627
iter  30 value 89.259712
iter  40 value 88.971945
iter  50 value 86.289702
iter  60 value 86.137924
iter  70 value 82.502802
iter  80 value 82.143739
iter  90 value 82.130881
final  value 82.130822 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.764259 
iter  10 value 94.486415
iter  20 value 93.763219
iter  30 value 84.662807
iter  40 value 82.671479
iter  50 value 82.134841
iter  60 value 82.130873
final  value 82.130821 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.614377 
iter  10 value 94.448337
iter  20 value 91.199326
iter  30 value 83.365231
iter  40 value 82.436505
iter  50 value 81.565463
iter  60 value 81.463845
iter  70 value 80.875992
iter  80 value 80.684122
iter  90 value 80.650788
iter 100 value 80.586847
final  value 80.586847 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.408071 
iter  10 value 94.494255
iter  20 value 88.661708
iter  30 value 84.068778
iter  40 value 83.789329
iter  50 value 81.650861
iter  60 value 81.304673
iter  70 value 81.067177
iter  80 value 80.932095
iter  90 value 80.508229
iter 100 value 80.281844
final  value 80.281844 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.299948 
iter  10 value 94.337949
iter  20 value 87.253951
iter  30 value 85.753193
iter  40 value 85.078845
iter  50 value 82.347293
iter  60 value 80.864302
iter  70 value 80.018836
iter  80 value 79.658761
iter  90 value 79.478489
iter 100 value 78.782241
final  value 78.782241 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.778572 
iter  10 value 94.455305
iter  20 value 91.385024
iter  30 value 88.584873
iter  40 value 86.732174
iter  50 value 85.465960
iter  60 value 82.012059
iter  70 value 81.274574
iter  80 value 79.665991
iter  90 value 78.944252
iter 100 value 78.785683
final  value 78.785683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.637664 
iter  10 value 94.464300
iter  20 value 85.864384
iter  30 value 83.958463
iter  40 value 81.948052
iter  50 value 81.844381
iter  60 value 81.727897
iter  70 value 80.427814
iter  80 value 78.842206
iter  90 value 78.403242
iter 100 value 78.322145
final  value 78.322145 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.064760 
iter  10 value 94.379626
iter  20 value 87.137126
iter  30 value 84.214392
iter  40 value 83.412403
iter  50 value 81.795346
iter  60 value 81.739984
iter  70 value 81.611931
iter  80 value 80.591035
iter  90 value 78.968998
iter 100 value 78.425430
final  value 78.425430 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.616250 
iter  10 value 93.921987
iter  20 value 86.795160
iter  30 value 84.748880
iter  40 value 82.351910
iter  50 value 81.223123
iter  60 value 80.637716
iter  70 value 79.528459
iter  80 value 78.789751
iter  90 value 78.432748
iter 100 value 78.248163
final  value 78.248163 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.611972 
iter  10 value 93.787586
iter  20 value 86.720236
iter  30 value 83.069428
iter  40 value 82.856348
iter  50 value 81.928971
iter  60 value 79.281039
iter  70 value 78.866215
iter  80 value 78.754688
iter  90 value 78.683939
iter 100 value 78.456487
final  value 78.456487 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.970063 
iter  10 value 89.205221
iter  20 value 82.790533
iter  30 value 82.079219
iter  40 value 81.471839
iter  50 value 80.133992
iter  60 value 79.025912
iter  70 value 78.496631
iter  80 value 78.106578
iter  90 value 78.015219
iter 100 value 77.943420
final  value 77.943420 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.690490 
iter  10 value 94.305177
iter  20 value 85.509336
iter  30 value 84.666043
iter  40 value 84.479848
iter  50 value 84.147303
iter  60 value 83.817636
iter  70 value 82.904973
iter  80 value 81.182513
iter  90 value 79.423327
iter 100 value 78.816618
final  value 78.816618 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.356928 
final  value 94.485690 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.961753 
final  value 94.485872 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.719401 
final  value 94.486064 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.167519 
final  value 94.356146 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.826035 
final  value 94.485977 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.483722 
iter  10 value 94.489076
iter  20 value 94.449048
iter  30 value 94.380382
final  value 94.354663 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.522005 
iter  10 value 94.358915
iter  20 value 94.354517
iter  30 value 92.535946
iter  40 value 89.396697
iter  50 value 89.395345
iter  60 value 87.312525
iter  70 value 85.925323
iter  80 value 85.918465
iter  80 value 85.918464
iter  80 value 85.918464
final  value 85.918464 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.528944 
iter  10 value 94.359227
iter  20 value 94.352251
iter  30 value 94.306229
iter  40 value 93.383181
iter  50 value 90.041918
iter  60 value 88.615623
iter  70 value 86.019319
iter  80 value 86.000043
iter  90 value 84.880864
iter 100 value 84.633610
final  value 84.633610 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.562162 
iter  10 value 94.359351
iter  20 value 94.354526
iter  30 value 92.311083
iter  40 value 91.156285
iter  50 value 80.825653
iter  60 value 80.760662
iter  70 value 80.759223
iter  80 value 80.758675
iter  90 value 80.758269
iter 100 value 80.757622
final  value 80.757622 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.191123 
iter  10 value 94.358764
iter  20 value 94.050150
iter  30 value 85.653515
iter  40 value 85.651068
iter  50 value 83.273470
iter  60 value 83.266723
iter  70 value 83.092658
iter  80 value 83.061914
iter  90 value 83.049825
iter 100 value 81.980728
final  value 81.980728 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.229440 
iter  10 value 85.335698
iter  20 value 81.758710
iter  30 value 81.756013
iter  40 value 80.840255
iter  50 value 80.384401
iter  60 value 80.383578
iter  70 value 80.261978
iter  80 value 78.560465
iter  90 value 77.213513
iter 100 value 76.721297
final  value 76.721297 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.155513 
iter  10 value 94.493114
iter  20 value 94.484250
iter  30 value 89.663127
iter  40 value 85.638321
iter  50 value 85.636858
iter  60 value 85.024982
iter  70 value 83.786802
iter  80 value 80.336341
iter  90 value 80.248824
iter  90 value 80.248823
final  value 80.248812 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.587973 
iter  10 value 94.492209
iter  20 value 94.457413
iter  30 value 83.289307
iter  40 value 81.563374
iter  50 value 81.494960
iter  60 value 81.441362
iter  70 value 81.243691
iter  80 value 77.574448
iter  90 value 76.898773
iter 100 value 76.868895
final  value 76.868895 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.755331 
iter  10 value 94.362916
iter  20 value 94.353441
iter  30 value 93.492977
iter  40 value 92.155516
iter  50 value 85.649298
iter  60 value 84.985784
iter  70 value 83.980949
final  value 83.980601 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.064726 
iter  10 value 94.416229
iter  20 value 94.403912
iter  30 value 81.746682
iter  40 value 81.491912
iter  50 value 81.491485
iter  60 value 81.489873
iter  70 value 80.102694
iter  80 value 78.742695
iter  90 value 77.803449
iter 100 value 77.651611
final  value 77.651611 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.648929 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.066108 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.287464 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.824192 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.821373 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.713182 
final  value 94.326053 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.125662 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.840087 
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.704091 
final  value 94.461207 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.027235 
iter  10 value 92.310000
iter  20 value 89.758886
final  value 89.721364 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.382195 
iter  10 value 93.665236
final  value 93.640752 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.867864 
iter  10 value 93.372599
iter  10 value 93.372599
iter  10 value 93.372599
final  value 93.372599 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.943911 
iter  10 value 93.735295
iter  20 value 93.233023
iter  30 value 93.022423
final  value 93.022222 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.480605 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.180718 
final  value 94.409639 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.434970 
iter  10 value 94.464267
iter  20 value 84.655451
iter  30 value 82.529172
iter  40 value 81.606577
iter  50 value 80.849709
iter  60 value 80.774359
final  value 80.774304 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.816051 
iter  10 value 94.490813
iter  20 value 93.358736
iter  30 value 84.684898
iter  40 value 83.353067
iter  50 value 80.985523
iter  60 value 80.721797
iter  70 value 79.489538
iter  80 value 79.474302
iter  80 value 79.474302
iter  80 value 79.474302
final  value 79.474302 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.725732 
iter  10 value 93.437160
iter  20 value 85.607048
iter  30 value 84.077992
iter  40 value 81.703846
iter  50 value 80.712372
iter  60 value 79.969009
iter  70 value 79.657858
iter  80 value 79.525296
final  value 79.525287 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.732495 
iter  10 value 94.465560
iter  20 value 92.602312
iter  30 value 91.960402
iter  40 value 91.596696
iter  50 value 91.533345
iter  60 value 91.386933
iter  70 value 91.254054
iter  80 value 91.106709
final  value 91.106597 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.897154 
iter  10 value 94.593388
iter  20 value 94.452834
iter  30 value 93.327087
iter  40 value 88.147182
iter  50 value 86.698283
iter  60 value 83.082206
iter  70 value 80.859061
iter  80 value 80.775380
iter  90 value 80.774305
final  value 80.774304 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.858631 
iter  10 value 94.473458
iter  20 value 93.611109
iter  30 value 88.689138
iter  40 value 86.272530
iter  50 value 83.641277
iter  60 value 82.638024
iter  70 value 81.214040
iter  80 value 80.749295
iter  90 value 80.281365
iter 100 value 80.049643
final  value 80.049643 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.521026 
iter  10 value 94.458837
iter  20 value 94.012198
iter  30 value 91.568062
iter  40 value 84.192325
iter  50 value 80.055777
iter  60 value 79.114777
iter  70 value 78.866648
iter  80 value 78.572970
iter  90 value 78.468382
iter 100 value 78.457703
final  value 78.457703 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.237393 
iter  10 value 94.402897
iter  20 value 85.775301
iter  30 value 82.413581
iter  40 value 79.528309
iter  50 value 79.131599
iter  60 value 78.623079
iter  70 value 78.356650
iter  80 value 78.169625
iter  90 value 78.144824
iter 100 value 78.045252
final  value 78.045252 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.052926 
iter  10 value 93.021716
iter  20 value 91.008797
iter  30 value 84.280565
iter  40 value 83.119361
iter  50 value 82.200356
iter  60 value 80.120490
iter  70 value 79.730336
iter  80 value 78.717678
iter  90 value 78.422855
iter 100 value 78.368391
final  value 78.368391 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.814554 
iter  10 value 94.700256
iter  20 value 94.056682
iter  30 value 88.298548
iter  40 value 87.782537
iter  50 value 84.216019
iter  60 value 82.735881
iter  70 value 80.607822
iter  80 value 78.544466
iter  90 value 78.378873
iter 100 value 78.301501
final  value 78.301501 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.581263 
iter  10 value 94.553604
iter  20 value 93.954556
iter  30 value 85.514935
iter  40 value 82.337446
iter  50 value 80.825800
iter  60 value 80.257220
iter  70 value 79.820047
iter  80 value 79.771310
iter  90 value 79.731510
iter 100 value 79.603203
final  value 79.603203 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.968212 
iter  10 value 96.778894
iter  20 value 95.204206
iter  30 value 88.101924
iter  40 value 83.120923
iter  50 value 81.410246
iter  60 value 79.632828
iter  70 value 79.057659
iter  80 value 78.998426
iter  90 value 78.851321
iter 100 value 78.520352
final  value 78.520352 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.943064 
iter  10 value 94.841377
iter  20 value 93.761409
iter  30 value 92.050397
iter  40 value 82.919880
iter  50 value 81.201693
iter  60 value 80.656119
iter  70 value 80.524018
iter  80 value 80.053755
iter  90 value 79.547926
iter 100 value 79.331445
final  value 79.331445 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.621084 
iter  10 value 94.545605
iter  20 value 87.636711
iter  30 value 85.085489
iter  40 value 83.008185
iter  50 value 79.757854
iter  60 value 79.193849
iter  70 value 78.850236
iter  80 value 78.506506
iter  90 value 78.220872
iter 100 value 78.125482
final  value 78.125482 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.210362 
iter  10 value 91.550288
iter  20 value 83.449821
iter  30 value 79.263825
iter  40 value 78.509562
iter  50 value 78.220449
iter  60 value 78.141257
iter  70 value 78.122392
iter  80 value 78.117932
iter  90 value 78.104374
iter 100 value 78.007261
final  value 78.007261 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.218353 
iter  10 value 93.774861
iter  20 value 93.365475
iter  30 value 85.614274
iter  40 value 85.233727
iter  50 value 85.207208
iter  60 value 85.196374
final  value 85.196356 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.095271 
iter  10 value 94.485753
iter  20 value 94.484224
iter  30 value 94.454899
iter  40 value 83.485249
iter  50 value 82.712496
iter  60 value 80.686231
iter  70 value 80.682593
final  value 80.682554 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.871052 
iter  10 value 94.485676
iter  20 value 94.484211
iter  30 value 94.403988
iter  40 value 91.935092
iter  50 value 91.931557
iter  60 value 91.930984
iter  60 value 91.930984
iter  60 value 91.930984
final  value 91.930984 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.776347 
final  value 94.485993 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.943977 
final  value 94.462920 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.579829 
iter  10 value 94.489041
iter  20 value 94.484224
iter  30 value 93.774779
final  value 93.773494 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.346178 
iter  10 value 94.487547
iter  20 value 94.084474
iter  30 value 91.839900
iter  40 value 86.371684
iter  50 value 85.598837
iter  60 value 85.382393
iter  70 value 82.887175
iter  80 value 82.872366
iter  90 value 81.369325
iter 100 value 80.971649
final  value 80.971649 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.669355 
iter  10 value 94.466182
iter  20 value 94.339726
iter  30 value 93.773774
final  value 93.773766 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.463151 
iter  10 value 89.071251
iter  20 value 87.918122
iter  30 value 86.358848
iter  40 value 86.312945
iter  50 value 86.309175
iter  60 value 86.303858
iter  70 value 85.134342
iter  80 value 84.785074
final  value 84.785036 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.954098 
iter  10 value 94.488897
iter  20 value 94.484045
iter  30 value 93.774265
final  value 93.773709 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.405496 
iter  10 value 90.970728
iter  20 value 86.960429
iter  30 value 85.892955
iter  40 value 85.759786
iter  50 value 80.924979
iter  60 value 80.375291
iter  70 value 80.298840
iter  80 value 80.298109
iter  90 value 80.117888
iter 100 value 79.108192
final  value 79.108192 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.712386 
iter  10 value 93.935712
iter  20 value 93.857623
iter  30 value 93.038439
iter  40 value 91.047094
iter  50 value 90.945036
iter  60 value 89.961817
iter  70 value 85.866862
iter  80 value 85.856749
final  value 85.846096 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.298360 
iter  10 value 94.195224
iter  20 value 92.168692
iter  30 value 85.853808
iter  40 value 83.662786
iter  50 value 82.373378
iter  60 value 82.354834
iter  70 value 82.353015
final  value 82.351053 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.917955 
iter  10 value 94.492810
iter  20 value 94.462476
iter  30 value 89.010775
final  value 89.009895 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.969890 
iter  10 value 93.508881
iter  20 value 93.277284
iter  30 value 93.221714
iter  40 value 92.658157
iter  50 value 92.569866
iter  60 value 92.531203
iter  70 value 92.530935
iter  80 value 92.529795
iter  90 value 92.529377
iter  90 value 92.529377
final  value 92.529377 
converged
Fitting Repeat 1 

# weights:  507
initial  value 148.670255 
iter  10 value 117.427842
iter  20 value 109.723413
iter  30 value 109.270134
iter  40 value 104.666915
iter  50 value 103.775414
iter  60 value 103.183875
iter  70 value 101.999468
iter  80 value 101.390759
iter  90 value 101.028321
iter 100 value 100.934698
final  value 100.934698 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 138.134982 
iter  10 value 118.936147
iter  20 value 114.476541
iter  30 value 108.959669
iter  40 value 106.975059
iter  50 value 105.917690
iter  60 value 105.036851
iter  70 value 104.718308
iter  80 value 104.622525
iter  90 value 104.246839
iter 100 value 103.351465
final  value 103.351465 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 144.936182 
iter  10 value 118.681487
iter  20 value 116.546320
iter  30 value 107.544296
iter  40 value 107.245897
iter  50 value 106.629601
iter  60 value 105.729408
iter  70 value 102.175289
iter  80 value 101.904145
iter  90 value 101.526837
iter 100 value 101.084566
final  value 101.084566 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 152.019820 
iter  10 value 117.664873
iter  20 value 111.764913
iter  30 value 104.297071
iter  40 value 103.123974
iter  50 value 102.709305
iter  60 value 102.376404
iter  70 value 101.762251
iter  80 value 101.510264
iter  90 value 101.500761
iter 100 value 101.463765
final  value 101.463765 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 137.096370 
iter  10 value 118.020070
iter  20 value 117.824038
iter  30 value 117.673554
iter  40 value 109.002293
iter  50 value 107.603524
iter  60 value 106.539375
iter  70 value 105.756615
iter  80 value 103.933711
iter  90 value 101.587719
iter 100 value 101.307660
final  value 101.307660 
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 -- Mon Feb  3 21:12:52 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 
 39.552   1.589 115.716