##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/site-library --timings HPiP_1.6.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0
    GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0
* running under: Ubuntu 22.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.6.0’
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 loading without being on the library search path ... 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 ... OK
* 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       35.813  0.920  36.733
corr_plot     35.919  0.664  36.592
FSmethod      34.050  0.691  34.743
pred_ensembel 13.873  0.527  10.672
enrichfindP    0.432  0.048   8.956
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/site-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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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 97.819779 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.100721 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.094499 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.843729 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.292572 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.499909 
iter  10 value 89.831880
iter  20 value 78.167159
iter  30 value 78.139306
iter  40 value 78.131670
final  value 78.131421 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.453213 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.892826 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.551378 
iter  10 value 92.945356
iter  10 value 92.945356
iter  10 value 92.945356
final  value 92.945356 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.268258 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.472941 
iter  10 value 93.765896
iter  10 value 93.765896
iter  10 value 93.765896
final  value 93.765896 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.213184 
iter  10 value 89.711698
iter  20 value 81.443464
iter  30 value 81.232287
final  value 81.232284 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.896984 
iter  10 value 92.945405
final  value 92.945356 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.945315 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.241363 
iter  10 value 92.945381
final  value 92.945355 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.038178 
iter  10 value 94.177113
iter  20 value 93.976646
iter  30 value 93.647011
iter  40 value 93.095101
iter  50 value 93.009297
iter  60 value 92.906509
iter  70 value 92.858999
iter  80 value 83.900268
iter  90 value 81.000323
iter 100 value 80.277158
final  value 80.277158 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.967822 
iter  10 value 93.568225
iter  20 value 88.425536
iter  30 value 87.639615
iter  40 value 84.195805
iter  50 value 82.583138
iter  60 value 81.754226
iter  70 value 81.238414
iter  80 value 81.161261
final  value 81.160723 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.256749 
iter  10 value 94.180887
iter  20 value 94.055561
iter  30 value 93.438717
iter  40 value 93.201520
iter  50 value 92.902703
iter  60 value 92.469592
iter  70 value 88.782694
iter  80 value 88.385225
iter  90 value 83.071871
iter 100 value 82.124008
final  value 82.124008 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.936300 
iter  10 value 94.057357
iter  20 value 93.563938
iter  30 value 93.231500
iter  40 value 91.982234
iter  50 value 86.334219
iter  60 value 83.299938
iter  70 value 81.813738
iter  80 value 81.810490
iter  80 value 81.810489
iter  80 value 81.810489
final  value 81.810489 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.990573 
iter  10 value 93.860953
iter  20 value 92.952938
iter  30 value 92.893473
iter  40 value 92.888636
iter  50 value 92.885836
iter  60 value 92.818932
iter  70 value 89.090560
iter  80 value 88.384788
iter  90 value 83.127371
iter 100 value 80.391694
final  value 80.391694 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.320289 
iter  10 value 87.603672
iter  20 value 84.950140
iter  30 value 84.242605
iter  40 value 83.655528
iter  50 value 82.147645
iter  60 value 79.761255
iter  70 value 78.172697
iter  80 value 77.156498
iter  90 value 76.880758
iter 100 value 76.561544
final  value 76.561544 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 122.151650 
iter  10 value 94.248713
iter  20 value 86.133982
iter  30 value 82.703609
iter  40 value 78.793950
iter  50 value 78.192246
iter  60 value 77.887296
iter  70 value 77.541569
iter  80 value 76.802276
iter  90 value 76.309038
iter 100 value 76.257245
final  value 76.257245 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.947514 
iter  10 value 91.676054
iter  20 value 84.216785
iter  30 value 82.424594
iter  40 value 81.877544
iter  50 value 80.206686
iter  60 value 79.612631
iter  70 value 79.259166
iter  80 value 79.155876
iter  90 value 78.834686
iter 100 value 78.412191
final  value 78.412191 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.879336 
iter  10 value 94.032216
iter  20 value 93.154015
iter  30 value 87.666263
iter  40 value 83.219675
iter  50 value 82.557376
iter  60 value 82.337299
iter  70 value 82.078412
iter  80 value 80.394625
iter  90 value 79.396976
iter 100 value 77.065132
final  value 77.065132 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 129.405013 
iter  10 value 93.367595
iter  20 value 81.637507
iter  30 value 80.691256
iter  40 value 80.378051
iter  50 value 78.519130
iter  60 value 77.606444
iter  70 value 77.470173
iter  80 value 77.053426
iter  90 value 76.819554
iter 100 value 76.387609
final  value 76.387609 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.561525 
iter  10 value 93.155684
iter  20 value 88.056600
iter  30 value 83.760198
iter  40 value 83.482267
iter  50 value 83.095779
iter  60 value 79.732885
iter  70 value 78.406341
iter  80 value 78.158315
iter  90 value 78.029513
iter 100 value 78.017053
final  value 78.017053 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.152994 
iter  10 value 94.275224
iter  20 value 92.417460
iter  30 value 83.434109
iter  40 value 82.899665
iter  50 value 82.140729
iter  60 value 81.542941
iter  70 value 81.025990
iter  80 value 79.702922
iter  90 value 78.328472
iter 100 value 77.499211
final  value 77.499211 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.944264 
iter  10 value 93.988999
iter  20 value 86.624196
iter  30 value 80.124255
iter  40 value 78.983185
iter  50 value 77.885483
iter  60 value 76.682501
iter  70 value 76.553418
iter  80 value 76.479970
iter  90 value 76.140385
iter 100 value 76.007394
final  value 76.007394 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.866656 
iter  10 value 95.064084
iter  20 value 93.834680
iter  30 value 93.094994
iter  40 value 91.281172
iter  50 value 87.663237
iter  60 value 83.436244
iter  70 value 80.004240
iter  80 value 77.757100
iter  90 value 77.354939
iter 100 value 77.222492
final  value 77.222492 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.832538 
iter  10 value 95.322410
iter  20 value 90.550130
iter  30 value 85.610534
iter  40 value 82.486895
iter  50 value 80.157287
iter  60 value 79.027230
iter  70 value 78.196754
iter  80 value 77.696497
iter  90 value 77.578254
iter 100 value 77.542779
final  value 77.542779 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.971473 
final  value 94.054641 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.810185 
final  value 94.054478 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.418065 
final  value 94.054398 
converged
Fitting Repeat 4 

# weights:  103
initial  value 93.884965 
final  value 92.955986 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.354219 
final  value 94.054611 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.550260 
iter  10 value 92.955614
iter  20 value 92.950754
iter  30 value 92.945963
iter  40 value 92.768479
iter  50 value 91.467061
iter  60 value 82.606411
iter  70 value 80.812817
iter  80 value 80.803955
iter  90 value 77.994514
iter 100 value 77.936204
final  value 77.936204 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.834805 
iter  10 value 92.305595
iter  20 value 92.116030
iter  30 value 90.908161
iter  40 value 80.455671
iter  50 value 79.871299
iter  60 value 79.754171
iter  70 value 79.587537
iter  80 value 79.579009
iter  90 value 79.575735
iter 100 value 79.574586
final  value 79.574586 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.653638 
iter  10 value 94.057462
iter  20 value 93.888817
iter  30 value 93.224845
iter  40 value 92.946598
final  value 92.946204 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.761063 
iter  10 value 94.058525
iter  20 value 94.053481
final  value 94.053212 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.542662 
iter  10 value 94.059981
final  value 94.055863 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.168736 
iter  10 value 92.953669
iter  20 value 92.947483
final  value 92.946378 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.433285 
iter  10 value 92.714032
iter  20 value 90.870237
iter  30 value 90.820170
iter  40 value 90.813027
iter  50 value 90.811517
iter  60 value 90.779007
iter  70 value 90.293619
iter  80 value 89.052615
iter  90 value 88.989143
iter 100 value 88.986188
final  value 88.986188 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.062630 
iter  10 value 92.953551
iter  20 value 92.835708
iter  30 value 89.072318
iter  40 value 89.065581
iter  50 value 89.063215
iter  60 value 89.062249
iter  70 value 89.062020
iter  80 value 87.598574
iter  90 value 79.293896
final  value 79.293688 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.230915 
iter  10 value 92.954637
iter  20 value 92.901055
iter  30 value 90.250011
iter  40 value 81.279711
iter  50 value 78.746800
iter  60 value 78.524564
iter  70 value 78.518644
iter  80 value 78.492071
iter  90 value 78.488957
iter 100 value 78.488926
final  value 78.488926 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.899958 
iter  10 value 92.954056
iter  20 value 92.949105
iter  30 value 92.948908
iter  40 value 92.947635
iter  50 value 85.227930
iter  60 value 82.586646
iter  70 value 82.369234
final  value 82.369189 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.679929 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.453635 
iter  10 value 93.309465
iter  20 value 88.822332
iter  30 value 83.350659
iter  40 value 83.239170
final  value 83.239160 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.038938 
final  value 94.395061 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.520127 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.091167 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.096379 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.314792 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.193008 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.786701 
final  value 93.682857 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.930993 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.698204 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.915857 
iter  10 value 94.174538
iter  20 value 86.356372
iter  30 value 85.868010
final  value 85.868007 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.521411 
final  value 94.315790 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.253513 
iter  10 value 94.232864
final  value 94.232773 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.841479 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.104265 
iter  10 value 93.892567
iter  20 value 86.783418
iter  30 value 84.406761
iter  40 value 83.921829
iter  50 value 83.576542
iter  60 value 83.339746
iter  70 value 83.014536
iter  80 value 82.928009
iter  90 value 82.923420
final  value 82.923412 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.396742 
iter  10 value 94.488578
iter  20 value 94.486702
iter  30 value 94.476486
iter  40 value 86.583916
iter  50 value 86.149551
iter  60 value 85.811416
iter  70 value 85.668507
iter  80 value 84.618633
iter  90 value 83.857353
iter 100 value 83.479122
final  value 83.479122 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.558266 
iter  10 value 94.382026
iter  20 value 85.269056
iter  30 value 84.121193
iter  40 value 82.674950
iter  50 value 81.705130
iter  60 value 81.587282
final  value 81.581739 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.628718 
iter  10 value 94.319445
iter  20 value 90.472688
iter  30 value 87.599714
iter  40 value 86.454463
iter  50 value 84.415001
iter  60 value 84.020224
iter  70 value 83.622426
iter  80 value 83.420582
iter  90 value 83.363167
iter 100 value 83.351396
final  value 83.351396 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.660765 
iter  10 value 94.516472
iter  20 value 94.476150
iter  30 value 92.896400
iter  40 value 84.704836
iter  50 value 83.941827
iter  60 value 83.233310
iter  70 value 82.956562
iter  80 value 82.127796
iter  90 value 81.741449
iter 100 value 81.586113
final  value 81.586113 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.692843 
iter  10 value 94.408760
iter  20 value 89.007266
iter  30 value 87.291436
iter  40 value 85.166114
iter  50 value 83.758610
iter  60 value 83.410878
iter  70 value 82.339125
iter  80 value 82.051665
iter  90 value 81.398638
iter 100 value 80.869736
final  value 80.869736 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.997759 
iter  10 value 91.585336
iter  20 value 84.364428
iter  30 value 84.266068
iter  40 value 83.966423
iter  50 value 82.616288
iter  60 value 81.915385
iter  70 value 80.872458
iter  80 value 80.714933
iter  90 value 80.379377
iter 100 value 80.124885
final  value 80.124885 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.324464 
iter  10 value 94.608337
iter  20 value 93.162799
iter  30 value 87.882129
iter  40 value 86.179401
iter  50 value 85.537346
iter  60 value 83.316708
iter  70 value 82.162041
iter  80 value 81.904898
iter  90 value 81.588030
iter 100 value 81.095296
final  value 81.095296 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.308472 
iter  10 value 93.588798
iter  20 value 85.435043
iter  30 value 84.729317
iter  40 value 84.115264
iter  50 value 82.042489
iter  60 value 81.687324
iter  70 value 81.588529
iter  80 value 81.538448
iter  90 value 81.327579
iter 100 value 80.691225
final  value 80.691225 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.238835 
iter  10 value 94.890965
iter  20 value 88.750531
iter  30 value 84.309958
iter  40 value 82.685953
iter  50 value 81.753531
iter  60 value 81.276951
iter  70 value 80.951029
iter  80 value 80.730619
iter  90 value 80.484112
iter 100 value 80.056014
final  value 80.056014 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 134.629104 
iter  10 value 94.507768
iter  20 value 89.517797
iter  30 value 85.425582
iter  40 value 84.497176
iter  50 value 83.941920
iter  60 value 82.898948
iter  70 value 82.208483
iter  80 value 80.816361
iter  90 value 80.346729
iter 100 value 80.277797
final  value 80.277797 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.801028 
iter  10 value 94.484846
iter  20 value 92.002371
iter  30 value 85.634683
iter  40 value 84.467899
iter  50 value 83.289679
iter  60 value 83.194479
iter  70 value 83.062545
iter  80 value 82.902150
iter  90 value 82.862398
iter 100 value 82.821430
final  value 82.821430 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.157819 
iter  10 value 95.504204
iter  20 value 93.455698
iter  30 value 92.415961
iter  40 value 90.794586
iter  50 value 86.539088
iter  60 value 86.393686
iter  70 value 85.519514
iter  80 value 85.236319
iter  90 value 84.496114
iter 100 value 81.766770
final  value 81.766770 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.028139 
iter  10 value 94.548149
iter  20 value 94.498155
iter  30 value 94.151992
iter  40 value 91.231590
iter  50 value 85.798664
iter  60 value 84.677170
iter  70 value 83.413241
iter  80 value 83.027755
iter  90 value 82.807969
iter 100 value 81.927134
final  value 81.927134 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.987752 
iter  10 value 94.988344
iter  20 value 91.310504
iter  30 value 84.302752
iter  40 value 83.672746
iter  50 value 82.051249
iter  60 value 81.832183
iter  70 value 81.730769
iter  80 value 81.530817
iter  90 value 81.221025
iter 100 value 80.929402
final  value 80.929402 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.001406 
iter  10 value 94.485887
iter  20 value 94.484234
iter  30 value 94.311804
iter  40 value 94.308260
final  value 94.308255 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.860557 
final  value 94.485898 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.049504 
final  value 94.485757 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.228068 
final  value 94.485679 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.717332 
final  value 94.485671 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.596701 
iter  10 value 94.485053
iter  20 value 93.516663
iter  30 value 87.916184
iter  40 value 87.765266
iter  50 value 85.021652
iter  60 value 84.179719
iter  70 value 84.144701
iter  80 value 81.237159
iter  90 value 79.481462
iter 100 value 79.448147
final  value 79.448147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.842723 
iter  10 value 94.489110
iter  20 value 94.250360
iter  30 value 88.422527
final  value 88.422233 
converged
Fitting Repeat 3 

# weights:  305
initial  value 126.435269 
iter  10 value 94.491610
iter  20 value 94.485365
iter  30 value 89.694410
iter  40 value 85.541211
iter  50 value 85.392702
iter  60 value 85.374083
iter  70 value 85.372306
iter  80 value 85.099752
iter  90 value 84.974717
iter 100 value 84.905538
final  value 84.905538 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.921256 
iter  10 value 94.411218
iter  20 value 94.408204
iter  30 value 94.260359
iter  40 value 86.326835
iter  50 value 86.276271
iter  60 value 86.256709
iter  70 value 86.254202
iter  80 value 85.996527
iter  90 value 85.837477
iter 100 value 85.763042
final  value 85.763042 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.177409 
iter  10 value 94.358857
iter  20 value 94.354454
iter  30 value 85.629754
iter  40 value 85.441137
iter  50 value 85.415519
iter  60 value 85.405344
iter  70 value 85.393235
iter  80 value 85.393099
final  value 85.393079 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.583863 
iter  10 value 94.491435
iter  20 value 94.187175
iter  30 value 93.176867
iter  40 value 92.510894
iter  50 value 88.957699
iter  60 value 88.816340
iter  70 value 87.843064
iter  80 value 87.391182
iter  90 value 87.389237
final  value 87.389127 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.196149 
iter  10 value 94.054525
iter  20 value 93.499407
iter  30 value 83.650839
iter  40 value 83.615696
iter  50 value 83.614397
final  value 83.614204 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.750778 
iter  10 value 92.519924
iter  20 value 87.544618
iter  30 value 87.025265
iter  40 value 87.023701
iter  50 value 86.995674
iter  60 value 86.987369
iter  70 value 86.911790
iter  80 value 85.989049
iter  90 value 83.022493
iter 100 value 82.243481
final  value 82.243481 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.606071 
iter  10 value 86.554592
iter  20 value 86.377730
iter  30 value 84.137151
iter  40 value 84.045470
iter  50 value 83.653878
iter  60 value 83.377028
iter  70 value 83.334249
iter  80 value 83.333558
iter  90 value 83.145517
iter 100 value 82.789414
final  value 82.789414 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.852380 
iter  10 value 92.700899
iter  20 value 92.535345
iter  30 value 92.411461
iter  40 value 92.041211
iter  50 value 92.039737
iter  60 value 92.034887
iter  70 value 86.160804
iter  80 value 84.508423
iter  90 value 81.649972
iter 100 value 80.991689
final  value 80.991689 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.887144 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.023925 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.468821 
iter  10 value 84.389448
iter  20 value 84.213430
iter  30 value 84.206372
iter  40 value 84.204940
final  value 84.204907 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.131728 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.936586 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.550103 
final  value 94.288571 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.709724 
final  value 94.442072 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.766298 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.030616 
final  value 94.483810 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.556042 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.323125 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.582228 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.021124 
iter  10 value 88.474537
iter  20 value 84.754592
final  value 84.407432 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.072145 
iter  10 value 93.075236
iter  20 value 91.195917
final  value 91.195840 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.670082 
iter  10 value 94.128092
final  value 94.127374 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.500987 
iter  10 value 94.461444
iter  20 value 94.073769
iter  30 value 93.994624
iter  40 value 91.511746
iter  50 value 87.635416
iter  60 value 86.854940
iter  70 value 85.462257
iter  80 value 83.879280
iter  90 value 83.857998
iter 100 value 83.715500
final  value 83.715500 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.371206 
iter  10 value 93.708945
iter  20 value 92.806276
iter  30 value 89.847302
iter  40 value 86.823957
iter  50 value 86.157945
iter  60 value 85.938575
iter  70 value 85.691122
iter  80 value 85.330498
iter  90 value 85.289514
iter 100 value 85.274418
final  value 85.274418 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.521693 
iter  10 value 93.816709
iter  20 value 86.942587
iter  30 value 85.180634
iter  40 value 84.589458
iter  50 value 83.969126
iter  60 value 83.730108
iter  70 value 83.603079
final  value 83.602797 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.240180 
iter  10 value 94.488982
iter  20 value 88.454246
iter  30 value 85.524999
iter  40 value 84.989721
iter  50 value 84.763461
iter  60 value 84.724276
final  value 84.724166 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.184590 
iter  10 value 94.393259
iter  20 value 93.850847
iter  30 value 92.190498
iter  40 value 87.903123
iter  50 value 86.849114
iter  60 value 86.638222
iter  70 value 84.981171
iter  80 value 84.036570
iter  90 value 83.705768
iter 100 value 83.602699
final  value 83.602699 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.850912 
iter  10 value 94.520702
iter  20 value 93.547083
iter  30 value 86.032896
iter  40 value 84.779704
iter  50 value 84.276368
iter  60 value 84.116990
iter  70 value 84.047000
iter  80 value 83.881411
iter  90 value 83.817582
iter 100 value 83.736101
final  value 83.736101 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.815985 
iter  10 value 94.509017
iter  20 value 86.708801
iter  30 value 86.296742
iter  40 value 85.314005
iter  50 value 83.611470
iter  60 value 83.168885
iter  70 value 82.534727
iter  80 value 82.394111
iter  90 value 82.162280
iter 100 value 82.095638
final  value 82.095638 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.812365 
iter  10 value 94.458897
iter  20 value 92.377893
iter  30 value 91.510347
iter  40 value 91.425711
iter  50 value 91.386927
iter  60 value 91.046034
iter  70 value 90.891262
iter  80 value 88.412295
iter  90 value 86.060555
iter 100 value 83.838373
final  value 83.838373 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.974967 
iter  10 value 93.809924
iter  20 value 86.589723
iter  30 value 84.511896
iter  40 value 83.403823
iter  50 value 83.208980
iter  60 value 83.046707
iter  70 value 82.709805
iter  80 value 82.622692
iter  90 value 82.618611
iter 100 value 82.618085
final  value 82.618085 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.920731 
iter  10 value 94.443232
iter  20 value 91.845332
iter  30 value 91.149384
iter  40 value 88.831255
iter  50 value 86.881051
iter  60 value 86.269935
iter  70 value 85.334283
iter  80 value 84.621759
iter  90 value 83.925187
iter 100 value 83.852478
final  value 83.852478 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.978138 
iter  10 value 94.345329
iter  20 value 93.107615
iter  30 value 89.797283
iter  40 value 88.108902
iter  50 value 87.361749
iter  60 value 85.379680
iter  70 value 84.447414
iter  80 value 83.663092
iter  90 value 83.387665
iter 100 value 83.273932
final  value 83.273932 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.694942 
iter  10 value 94.541106
iter  20 value 93.473669
iter  30 value 89.938367
iter  40 value 87.206972
iter  50 value 84.544438
iter  60 value 83.951770
iter  70 value 83.520504
iter  80 value 83.069259
iter  90 value 82.666592
iter 100 value 82.548599
final  value 82.548599 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.717662 
iter  10 value 94.413740
iter  20 value 91.218961
iter  30 value 85.857006
iter  40 value 85.386439
iter  50 value 84.114777
iter  60 value 83.582789
iter  70 value 82.862353
iter  80 value 82.717861
iter  90 value 82.565898
iter 100 value 82.367744
final  value 82.367744 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.830842 
iter  10 value 94.666116
iter  20 value 92.342284
iter  30 value 85.286478
iter  40 value 84.294845
iter  50 value 83.991270
iter  60 value 83.956456
iter  70 value 83.453116
iter  80 value 82.749626
iter  90 value 82.459460
iter 100 value 82.303426
final  value 82.303426 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.935285 
iter  10 value 94.669057
iter  20 value 94.448739
iter  30 value 94.001540
iter  40 value 92.699895
iter  50 value 89.411329
iter  60 value 86.260014
iter  70 value 84.280028
iter  80 value 83.856900
iter  90 value 83.592178
iter 100 value 83.427396
final  value 83.427396 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.811157 
iter  10 value 94.485880
iter  20 value 94.484229
iter  30 value 94.290178
iter  40 value 93.349734
iter  50 value 93.222159
iter  60 value 89.872392
iter  70 value 88.290606
iter  80 value 88.228456
iter  90 value 88.227935
iter 100 value 88.208596
final  value 88.208596 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.713101 
final  value 94.485916 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.383139 
final  value 94.485629 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.983855 
final  value 94.485786 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.539809 
final  value 94.485890 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.323726 
iter  10 value 94.488919
iter  20 value 94.322493
iter  30 value 92.926953
iter  40 value 92.830118
iter  50 value 92.303166
iter  60 value 92.170264
iter  70 value 92.169296
iter  80 value 92.083510
iter  80 value 92.083510
iter  80 value 92.083510
final  value 92.083510 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.401678 
iter  10 value 94.359744
iter  20 value 94.354681
final  value 94.354615 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.007288 
iter  10 value 94.324996
iter  20 value 94.321691
iter  30 value 94.318634
iter  40 value 89.380302
iter  50 value 86.604916
iter  60 value 86.587145
iter  70 value 86.573554
iter  80 value 86.506694
iter  90 value 86.405870
iter 100 value 85.749376
final  value 85.749376 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.931902 
iter  10 value 93.706969
iter  20 value 93.705371
iter  30 value 93.698435
iter  40 value 93.581741
iter  50 value 87.596586
iter  60 value 84.414778
iter  70 value 84.409051
final  value 84.408998 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.799561 
iter  10 value 94.359112
iter  20 value 94.354971
iter  30 value 94.227582
iter  40 value 85.516750
iter  50 value 85.514959
final  value 85.513328 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.428353 
iter  10 value 94.362345
iter  20 value 94.354673
iter  30 value 94.251297
iter  40 value 87.126474
iter  50 value 87.116243
iter  60 value 87.070856
final  value 87.070798 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.785164 
iter  10 value 94.350547
iter  20 value 94.341994
iter  30 value 93.298726
iter  40 value 91.833736
iter  50 value 91.800672
iter  60 value 91.767037
iter  70 value 91.764910
iter  80 value 91.755930
iter  90 value 91.276963
iter 100 value 87.775398
final  value 87.775398 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.861719 
iter  10 value 94.300223
iter  20 value 94.053733
iter  30 value 94.027884
iter  40 value 93.944535
iter  50 value 93.940681
iter  60 value 93.938793
iter  70 value 92.584297
iter  80 value 86.411156
iter  90 value 85.899002
iter 100 value 84.018731
final  value 84.018731 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.887493 
iter  10 value 94.504722
iter  20 value 94.495093
iter  30 value 94.087440
iter  40 value 87.175334
iter  50 value 84.642031
iter  60 value 84.113602
iter  70 value 83.954040
iter  80 value 83.908046
iter  90 value 83.907552
iter 100 value 83.901595
final  value 83.901595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.572725 
iter  10 value 89.584400
iter  20 value 89.060541
iter  30 value 89.049318
iter  40 value 86.050847
iter  50 value 83.978784
iter  60 value 83.977540
iter  70 value 83.977212
iter  80 value 83.963456
iter  90 value 83.956651
iter 100 value 83.872580
final  value 83.872580 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.553291 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.303208 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.027911 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.248523 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.224804 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.882652 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.294563 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.115498 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.169949 
iter  10 value 94.484432
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.167541 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.431619 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.297952 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.526402 
iter  10 value 94.473119
iter  10 value 94.473118
iter  10 value 94.473118
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.357283 
final  value 94.473118 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.337309 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.421381 
iter  10 value 94.423199
iter  20 value 93.980960
iter  30 value 92.328303
iter  40 value 92.078565
iter  50 value 92.030075
iter  60 value 86.635695
iter  70 value 84.560693
iter  80 value 84.447460
iter  90 value 84.294652
iter 100 value 83.245907
final  value 83.245907 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.079612 
iter  10 value 94.490046
iter  20 value 94.423750
iter  30 value 94.068315
iter  40 value 93.987307
iter  50 value 93.963090
iter  60 value 93.835632
iter  70 value 92.229428
iter  80 value 91.929536
iter  90 value 91.863413
iter 100 value 91.361003
final  value 91.361003 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.158789 
iter  10 value 94.498304
iter  20 value 93.947083
iter  30 value 87.594353
iter  40 value 87.046943
iter  50 value 86.989252
iter  60 value 86.827720
iter  70 value 86.599162
final  value 86.599146 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.967459 
iter  10 value 93.954285
iter  20 value 92.129330
iter  30 value 92.068191
iter  40 value 91.773273
iter  50 value 90.774971
iter  60 value 90.741173
iter  70 value 90.739459
iter  80 value 90.733650
iter  90 value 90.726020
iter 100 value 90.679750
final  value 90.679750 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.268882 
iter  10 value 94.473626
iter  20 value 90.664355
iter  30 value 90.250966
iter  40 value 89.076815
iter  50 value 88.433725
iter  60 value 85.974047
iter  70 value 85.849477
iter  80 value 85.797505
iter  90 value 85.283406
iter 100 value 84.907662
final  value 84.907662 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.295749 
iter  10 value 93.155135
iter  20 value 87.846584
iter  30 value 86.289005
iter  40 value 85.591552
iter  50 value 84.999484
iter  60 value 83.915911
iter  70 value 83.506969
iter  80 value 83.197355
iter  90 value 83.007004
iter 100 value 82.849939
final  value 82.849939 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.796906 
iter  10 value 94.352452
iter  20 value 92.863006
iter  30 value 90.361806
iter  40 value 86.896897
iter  50 value 83.025656
iter  60 value 82.663451
iter  70 value 82.195462
iter  80 value 81.953216
iter  90 value 81.764275
iter 100 value 81.756881
final  value 81.756881 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.320787 
iter  10 value 99.971178
iter  20 value 94.495798
iter  30 value 91.620270
iter  40 value 89.407675
iter  50 value 89.221792
iter  60 value 89.018546
iter  70 value 88.793774
iter  80 value 85.868360
iter  90 value 84.820916
iter 100 value 83.874484
final  value 83.874484 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.280539 
iter  10 value 94.504741
iter  20 value 91.695254
iter  30 value 87.716365
iter  40 value 85.716022
iter  50 value 85.016906
iter  60 value 84.301969
iter  70 value 83.884874
iter  80 value 82.832004
iter  90 value 82.081989
iter 100 value 81.765981
final  value 81.765981 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.987020 
iter  10 value 94.416852
iter  20 value 89.806156
iter  30 value 87.968694
iter  40 value 86.051693
iter  50 value 84.446319
iter  60 value 84.331387
iter  70 value 82.644424
iter  80 value 81.906664
iter  90 value 81.674652
iter 100 value 81.643409
final  value 81.643409 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.680370 
iter  10 value 94.628390
iter  20 value 94.409519
iter  30 value 92.670149
iter  40 value 83.481395
iter  50 value 82.028542
iter  60 value 81.859073
iter  70 value 81.676019
iter  80 value 81.248675
iter  90 value 81.083741
iter 100 value 80.857479
final  value 80.857479 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.474648 
iter  10 value 90.360889
iter  20 value 88.400034
iter  30 value 84.657162
iter  40 value 83.497282
iter  50 value 82.760342
iter  60 value 82.474260
iter  70 value 82.113960
iter  80 value 81.395070
iter  90 value 81.233973
iter 100 value 81.118905
final  value 81.118905 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.086182 
iter  10 value 94.964974
iter  20 value 94.431935
iter  30 value 91.887793
iter  40 value 89.378643
iter  50 value 89.179662
iter  60 value 87.876042
iter  70 value 86.183271
iter  80 value 85.352300
iter  90 value 83.541904
iter 100 value 82.468475
final  value 82.468475 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.419376 
iter  10 value 93.978410
iter  20 value 93.379378
iter  30 value 89.614291
iter  40 value 86.767360
iter  50 value 83.418533
iter  60 value 82.006332
iter  70 value 81.449501
iter  80 value 81.374570
iter  90 value 81.271051
iter 100 value 81.243653
final  value 81.243653 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.927999 
iter  10 value 96.573312
iter  20 value 94.534909
iter  30 value 94.207771
iter  40 value 90.885824
iter  50 value 89.491492
iter  60 value 86.514300
iter  70 value 83.743309
iter  80 value 82.914174
iter  90 value 82.508155
iter 100 value 81.506994
final  value 81.506994 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.931573 
final  value 94.486156 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.394364 
final  value 94.485984 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.846521 
final  value 94.486043 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.616375 
final  value 94.485947 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.286560 
final  value 94.486228 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.793775 
iter  10 value 94.488742
iter  20 value 94.323646
iter  30 value 93.947134
iter  40 value 92.913578
iter  50 value 86.102202
iter  60 value 86.025000
iter  70 value 85.977135
iter  80 value 85.972276
final  value 85.972230 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.080265 
iter  10 value 94.489246
iter  20 value 94.436737
iter  30 value 94.094032
final  value 94.093881 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.314764 
iter  10 value 93.459898
iter  20 value 93.404518
iter  30 value 93.388218
iter  40 value 93.042550
iter  50 value 91.397507
iter  60 value 90.399720
iter  70 value 90.389144
iter  80 value 90.387570
iter  90 value 90.387415
iter 100 value 89.508261
final  value 89.508261 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.084731 
iter  10 value 94.489198
iter  20 value 94.466917
iter  30 value 94.166397
iter  40 value 91.919700
iter  50 value 86.372158
iter  60 value 83.779195
iter  70 value 83.742423
iter  80 value 83.732925
iter  90 value 82.910042
iter 100 value 82.860227
final  value 82.860227 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.119560 
iter  10 value 92.940012
iter  20 value 92.843507
iter  30 value 91.845529
iter  40 value 91.833595
iter  50 value 91.831030
iter  60 value 91.802268
iter  70 value 91.778424
final  value 91.778127 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.802461 
iter  10 value 94.431726
iter  20 value 94.427720
iter  30 value 94.355059
iter  40 value 91.703076
iter  50 value 89.610818
iter  60 value 85.762657
iter  70 value 83.489237
iter  80 value 82.573091
iter  90 value 81.083735
iter 100 value 80.164796
final  value 80.164796 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 134.554149 
iter  10 value 94.492871
iter  20 value 94.484801
iter  30 value 94.319277
iter  40 value 88.250599
iter  50 value 86.604355
iter  60 value 86.593769
iter  70 value 86.589162
iter  80 value 86.505999
iter  90 value 84.959530
iter 100 value 84.055139
final  value 84.055139 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.810266 
iter  10 value 92.976163
iter  20 value 87.881980
iter  30 value 87.879749
final  value 87.878985 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.552077 
iter  10 value 94.491421
iter  20 value 94.378957
iter  30 value 93.948063
iter  40 value 86.140974
iter  50 value 85.165097
iter  60 value 84.889112
iter  70 value 84.766085
iter  80 value 82.167947
iter  90 value 82.142933
final  value 82.142482 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.997600 
iter  10 value 93.709434
iter  20 value 93.143640
iter  30 value 91.189146
iter  40 value 90.242778
iter  50 value 89.957185
iter  60 value 89.915077
iter  70 value 89.896202
iter  80 value 89.896160
iter  90 value 89.896069
iter 100 value 89.895988
final  value 89.895988 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.708624 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.450781 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.341639 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.086551 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.642399 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.180960 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.399481 
iter  10 value 92.779088
iter  20 value 91.360087
final  value 91.360074 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.274587 
iter  10 value 93.732893
iter  10 value 93.732893
iter  10 value 93.732893
final  value 93.732893 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.842460 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.296988 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.223502 
iter  10 value 93.545562
final  value 93.097211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.881474 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.504516 
iter  10 value 94.052911
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.193016 
final  value 94.052908 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.210238 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.946037 
iter  10 value 93.994910
iter  20 value 89.270254
iter  30 value 86.692258
iter  40 value 84.112739
iter  50 value 83.735864
iter  60 value 83.105582
iter  70 value 81.376371
iter  80 value 81.124827
iter  90 value 81.120605
iter 100 value 81.098612
final  value 81.098612 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 113.282732 
iter  10 value 93.749104
iter  20 value 85.216160
iter  30 value 83.976937
iter  40 value 83.703946
iter  50 value 83.502873
iter  60 value 82.277063
iter  70 value 81.986464
iter  80 value 81.700432
iter  90 value 81.568912
iter 100 value 81.522250
final  value 81.522250 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.525757 
iter  10 value 94.063748
iter  20 value 93.963249
iter  30 value 91.521735
iter  40 value 90.868300
iter  50 value 90.799224
iter  60 value 90.760933
iter  70 value 90.756502
iter  70 value 90.756501
iter  70 value 90.756501
final  value 90.756501 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.233574 
iter  10 value 94.067905
iter  20 value 93.785827
iter  30 value 87.544810
iter  40 value 85.308486
iter  50 value 85.098515
iter  60 value 84.660895
iter  70 value 84.122744
iter  80 value 83.992325
iter  90 value 83.944508
iter 100 value 83.868357
final  value 83.868357 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.352426 
iter  10 value 92.837179
iter  20 value 85.101565
iter  30 value 84.856646
iter  40 value 84.708853
iter  50 value 84.559438
iter  60 value 82.684854
iter  70 value 82.363054
iter  80 value 82.271918
iter  90 value 82.254895
iter 100 value 81.103030
final  value 81.103030 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.812789 
iter  10 value 94.190951
iter  20 value 88.659492
iter  30 value 85.445707
iter  40 value 84.765509
iter  50 value 84.518480
iter  60 value 84.347195
iter  70 value 82.714258
iter  80 value 82.172057
iter  90 value 81.587818
iter 100 value 81.418923
final  value 81.418923 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.541617 
iter  10 value 93.815837
iter  20 value 86.960715
iter  30 value 83.681476
iter  40 value 82.341860
iter  50 value 81.609010
iter  60 value 81.471512
iter  70 value 81.156293
iter  80 value 80.996609
iter  90 value 80.866694
iter 100 value 80.514286
final  value 80.514286 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.046324 
iter  10 value 94.042147
iter  20 value 87.367512
iter  30 value 84.844811
iter  40 value 83.119308
iter  50 value 82.416485
iter  60 value 81.360194
iter  70 value 80.846709
iter  80 value 80.454117
iter  90 value 80.015312
iter 100 value 79.890446
final  value 79.890446 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.418917 
iter  10 value 94.384188
iter  20 value 94.012989
iter  30 value 89.038636
iter  40 value 86.707473
iter  50 value 85.811688
iter  60 value 85.303181
iter  70 value 85.125529
iter  80 value 83.677532
iter  90 value 83.345574
iter 100 value 82.761345
final  value 82.761345 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.113319 
iter  10 value 94.062697
iter  20 value 92.134241
iter  30 value 84.577119
iter  40 value 84.304617
iter  50 value 84.116573
iter  60 value 83.927471
iter  70 value 83.795897
iter  80 value 83.587566
iter  90 value 83.484600
iter 100 value 83.325093
final  value 83.325093 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.707009 
iter  10 value 95.241400
iter  20 value 94.201886
iter  30 value 89.384002
iter  40 value 84.186567
iter  50 value 83.727704
iter  60 value 83.532066
iter  70 value 83.380264
iter  80 value 81.594772
iter  90 value 81.503793
iter 100 value 81.194240
final  value 81.194240 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.348389 
iter  10 value 90.474553
iter  20 value 82.939799
iter  30 value 82.275359
iter  40 value 81.804461
iter  50 value 80.969212
iter  60 value 80.734835
iter  70 value 80.652095
iter  80 value 80.568935
iter  90 value 80.353883
iter 100 value 80.187509
final  value 80.187509 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.505322 
iter  10 value 91.068989
iter  20 value 86.828828
iter  30 value 86.373233
iter  40 value 84.923027
iter  50 value 83.028481
iter  60 value 81.755505
iter  70 value 81.393117
iter  80 value 81.248422
iter  90 value 80.816502
iter 100 value 80.466638
final  value 80.466638 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.106772 
iter  10 value 96.513946
iter  20 value 94.251316
iter  30 value 93.515938
iter  40 value 86.496826
iter  50 value 86.243460
iter  60 value 84.801436
iter  70 value 81.591014
iter  80 value 80.993561
iter  90 value 80.814288
iter 100 value 80.673215
final  value 80.673215 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.989753 
iter  10 value 94.127985
iter  20 value 91.046720
iter  30 value 86.945998
iter  40 value 86.159784
iter  50 value 85.888106
iter  60 value 84.481246
iter  70 value 82.259529
iter  80 value 82.036869
iter  90 value 81.453925
iter 100 value 80.975002
final  value 80.975002 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.765514 
final  value 94.054673 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.631009 
final  value 93.290664 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.199179 
final  value 94.054373 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.088220 
final  value 94.054560 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.846812 
final  value 94.054629 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.873314 
iter  10 value 94.135202
iter  20 value 93.805475
iter  30 value 86.144696
iter  40 value 86.019465
iter  50 value 85.511141
iter  60 value 85.472921
iter  70 value 85.470038
iter  80 value 85.438007
iter  90 value 83.454373
iter 100 value 83.436324
final  value 83.436324 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.679209 
iter  10 value 94.057742
iter  20 value 94.052550
iter  30 value 94.050505
final  value 94.050483 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.189899 
iter  10 value 94.057012
iter  20 value 91.339046
iter  30 value 86.378594
iter  40 value 86.378277
iter  50 value 85.210473
iter  60 value 85.210118
final  value 85.210108 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.801315 
iter  10 value 92.832080
iter  20 value 91.951015
iter  30 value 91.949056
iter  40 value 91.413484
iter  50 value 91.413313
iter  60 value 91.411159
iter  70 value 91.331661
iter  80 value 91.283620
final  value 91.283584 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.082564 
iter  10 value 94.057091
iter  20 value 86.300857
iter  30 value 82.840703
iter  40 value 80.292547
iter  50 value 79.919312
iter  60 value 79.916818
iter  70 value 79.911334
iter  80 value 79.760259
iter  90 value 79.753002
iter 100 value 79.751968
final  value 79.751968 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.281119 
iter  10 value 92.156545
iter  20 value 91.988831
iter  30 value 91.983281
iter  40 value 91.981700
iter  50 value 91.963669
iter  60 value 91.961213
iter  70 value 91.931850
iter  80 value 87.761605
iter  90 value 86.314278
iter 100 value 86.311008
final  value 86.311008 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.809228 
iter  10 value 94.060716
iter  20 value 93.823333
iter  30 value 83.871381
iter  40 value 83.323901
iter  50 value 83.305365
iter  60 value 82.284003
iter  70 value 81.581532
iter  80 value 81.371898
iter  90 value 81.342199
iter 100 value 81.308749
final  value 81.308749 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.127295 
iter  10 value 94.059558
iter  20 value 93.316181
iter  30 value 92.893850
iter  40 value 91.949121
iter  50 value 91.357290
iter  60 value 91.357178
iter  70 value 91.357132
iter  80 value 91.357040
final  value 91.357022 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.057863 
iter  10 value 94.061149
iter  20 value 93.816121
iter  30 value 86.791191
iter  40 value 81.758318
iter  50 value 80.788169
final  value 80.783287 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.846653 
iter  10 value 86.391752
iter  20 value 85.385680
iter  30 value 85.322181
iter  40 value 85.320752
iter  50 value 83.285337
iter  60 value 83.147992
iter  70 value 83.037914
iter  80 value 83.037405
iter  90 value 83.036661
final  value 83.036146 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.996879 
iter  10 value 118.046730
iter  20 value 117.418331
iter  30 value 108.901297
iter  40 value 106.639773
iter  50 value 104.910275
iter  60 value 102.583462
iter  70 value 102.288810
iter  80 value 101.557680
iter  90 value 100.486068
iter 100 value 100.163930
final  value 100.163930 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 138.054771 
iter  10 value 112.678992
iter  20 value 109.415264
iter  30 value 105.939792
iter  40 value 104.964846
iter  50 value 103.929211
iter  60 value 103.623273
iter  70 value 103.450250
iter  80 value 103.372083
iter  90 value 103.175911
iter 100 value 102.863482
final  value 102.863482 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 153.281074 
iter  10 value 118.056790
iter  20 value 117.822596
iter  30 value 107.956990
iter  40 value 107.758445
iter  50 value 107.386188
iter  60 value 104.959114
iter  70 value 102.166326
iter  80 value 101.830362
iter  90 value 101.706892
iter 100 value 101.504612
final  value 101.504612 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.892737 
iter  10 value 117.586915
iter  20 value 107.779410
iter  30 value 102.531780
iter  40 value 101.963533
iter  50 value 101.694439
iter  60 value 101.544394
iter  70 value 100.985025
iter  80 value 100.546975
iter  90 value 100.459589
iter 100 value 100.375251
final  value 100.375251 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 162.896574 
iter  10 value 115.760380
iter  20 value 107.604838
iter  30 value 106.033409
iter  40 value 104.478886
iter  50 value 103.853949
iter  60 value 103.702165
iter  70 value 102.878515
iter  80 value 102.188588
iter  90 value 101.934497
iter 100 value 101.152563
final  value 101.152563 
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 -- Sun Oct 15 22:07:34 2023 
*********************************************** 
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 
 44.141   1.710  42.906