##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2024-10-21 r87258)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* 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 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 ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       36.880  0.546  37.427
corr_plot     33.578  0.534  34.113
FSmethod      33.408  0.472  33.888
pred_ensembel 13.071  0.266  12.120
enrichfindP    0.514  0.031   8.061
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.21-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 Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 101.532183 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.785333 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.853859 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.941079 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.604795 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.748493 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.295985 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.464201 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.608952 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.541351 
iter  10 value 93.636742
iter  20 value 92.109827
iter  30 value 92.106672
final  value 92.106668 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.929328 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.544496 
final  value 94.482478 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.867130 
iter  10 value 94.465102
final  value 94.464512 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.224436 
iter  10 value 93.960015
iter  20 value 87.151688
final  value 87.151675 
converged
Fitting Repeat 5 

# weights:  507
initial  value 152.199348 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.445648 
iter  10 value 94.488604
iter  10 value 94.488603
iter  20 value 94.446351
iter  30 value 87.629006
iter  40 value 87.079201
iter  50 value 85.860654
iter  60 value 83.302314
iter  70 value 82.226011
iter  80 value 82.014970
final  value 82.014875 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.744371 
iter  10 value 94.419088
iter  20 value 89.191251
iter  30 value 86.651988
iter  40 value 86.379188
iter  50 value 85.999132
iter  60 value 85.701624
iter  70 value 85.577693
final  value 85.574277 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.249914 
iter  10 value 94.439115
iter  20 value 93.798619
iter  30 value 93.591255
iter  40 value 93.378482
iter  50 value 90.165163
iter  60 value 86.285952
iter  70 value 85.367129
iter  80 value 84.935935
iter  90 value 84.430712
iter 100 value 84.293873
final  value 84.293873 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 115.135461 
iter  10 value 94.487582
iter  20 value 91.851301
iter  30 value 88.828476
iter  40 value 87.876627
iter  50 value 87.682511
iter  60 value 85.254093
iter  70 value 85.098382
iter  80 value 83.441075
iter  90 value 82.604180
iter 100 value 82.028860
final  value 82.028860 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.561678 
iter  10 value 94.488714
iter  20 value 94.016482
iter  30 value 93.707266
iter  40 value 92.370925
iter  50 value 86.694354
iter  60 value 85.760535
iter  70 value 85.347994
iter  80 value 84.605352
iter  90 value 83.899254
iter 100 value 83.884212
final  value 83.884212 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.340054 
iter  10 value 94.421736
iter  20 value 87.792702
iter  30 value 86.853447
iter  40 value 85.782006
iter  50 value 85.178735
iter  60 value 83.841106
iter  70 value 82.527948
iter  80 value 81.673268
iter  90 value 81.538971
iter 100 value 81.376076
final  value 81.376076 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.417966 
iter  10 value 94.444995
iter  20 value 91.579657
iter  30 value 85.721965
iter  40 value 85.541462
iter  50 value 84.699615
iter  60 value 83.721896
iter  70 value 83.010043
iter  80 value 81.699428
iter  90 value 81.191539
iter 100 value 80.978474
final  value 80.978474 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.938854 
iter  10 value 94.496879
iter  20 value 90.231968
iter  30 value 87.272216
iter  40 value 86.819818
iter  50 value 85.620274
iter  60 value 85.327201
iter  70 value 85.007072
iter  80 value 84.656831
iter  90 value 84.524220
iter 100 value 84.445250
final  value 84.445250 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.201353 
iter  10 value 94.262642
iter  20 value 92.864873
iter  30 value 91.747979
iter  40 value 91.028047
iter  50 value 85.847478
iter  60 value 84.114851
iter  70 value 83.479303
iter  80 value 83.156531
iter  90 value 82.935150
iter 100 value 82.619576
final  value 82.619576 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.299564 
iter  10 value 94.412939
iter  20 value 89.381592
iter  30 value 84.066414
iter  40 value 81.991484
iter  50 value 81.488777
iter  60 value 81.415008
iter  70 value 81.330022
iter  80 value 80.809835
iter  90 value 80.454105
iter 100 value 80.381565
final  value 80.381565 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.069329 
iter  10 value 94.810485
iter  20 value 93.786673
iter  30 value 92.828096
iter  40 value 90.761613
iter  50 value 88.948212
iter  60 value 87.383813
iter  70 value 86.684995
iter  80 value 84.947138
iter  90 value 84.441648
iter 100 value 83.684370
final  value 83.684370 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.027153 
iter  10 value 94.750651
iter  20 value 91.003054
iter  30 value 86.699449
iter  40 value 85.902205
iter  50 value 83.236760
iter  60 value 82.377949
iter  70 value 81.806030
iter  80 value 81.663247
iter  90 value 81.512159
iter 100 value 81.221681
final  value 81.221681 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.196166 
iter  10 value 94.776474
iter  20 value 93.938914
iter  30 value 93.106067
iter  40 value 89.822074
iter  50 value 89.343826
iter  60 value 86.960776
iter  70 value 83.868736
iter  80 value 81.486814
iter  90 value 80.837672
iter 100 value 80.556676
final  value 80.556676 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.095655 
iter  10 value 93.847634
iter  20 value 90.927212
iter  30 value 85.720804
iter  40 value 83.604713
iter  50 value 83.062499
iter  60 value 81.564388
iter  70 value 80.870951
iter  80 value 80.654393
iter  90 value 80.271698
iter 100 value 80.130739
final  value 80.130739 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.182778 
iter  10 value 94.279174
iter  20 value 89.705343
iter  30 value 87.941809
iter  40 value 87.673828
iter  50 value 86.018856
iter  60 value 84.095978
iter  70 value 82.168387
iter  80 value 81.341254
iter  90 value 81.143220
iter 100 value 80.994654
final  value 80.994654 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.265671 
final  value 94.486087 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.224688 
final  value 94.485746 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.510460 
iter  10 value 94.485981
iter  20 value 93.791855
iter  30 value 91.914891
final  value 91.913647 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.489561 
final  value 94.486014 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.878679 
iter  10 value 94.485956
iter  20 value 94.476382
iter  30 value 87.452478
iter  40 value 83.972588
iter  50 value 81.966117
iter  60 value 81.555331
iter  70 value 81.552312
iter  80 value 81.550828
final  value 81.549923 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.889348 
iter  10 value 94.489010
iter  20 value 94.172248
iter  30 value 87.154038
iter  40 value 86.786145
iter  50 value 86.786020
iter  60 value 86.621389
iter  70 value 86.620162
iter  80 value 86.567951
iter  90 value 82.709094
iter 100 value 81.196607
final  value 81.196607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.100736 
iter  10 value 93.642355
iter  20 value 93.638493
iter  30 value 92.217328
iter  40 value 88.823974
iter  50 value 86.819363
iter  60 value 86.185202
iter  70 value 86.184451
iter  80 value 86.174095
iter  90 value 86.173959
final  value 86.173956 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.088169 
iter  10 value 94.488609
iter  20 value 93.640222
iter  30 value 88.283617
iter  40 value 86.771673
iter  50 value 86.767117
iter  50 value 86.767116
final  value 86.767107 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.441926 
iter  10 value 93.572487
iter  20 value 92.199571
iter  30 value 84.715357
iter  40 value 84.571388
iter  50 value 84.522830
final  value 84.522594 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.216668 
iter  10 value 94.489206
iter  20 value 94.434187
iter  30 value 90.439454
iter  40 value 88.358923
iter  50 value 88.354493
iter  60 value 86.080293
iter  70 value 84.186938
iter  80 value 83.984130
iter  90 value 83.947917
iter 100 value 83.940830
final  value 83.940830 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.027303 
iter  10 value 94.492147
iter  20 value 94.409478
iter  30 value 88.344719
iter  40 value 87.162129
iter  50 value 87.128280
iter  60 value 86.919173
iter  70 value 85.548877
iter  80 value 84.925400
iter  90 value 84.918332
iter 100 value 84.906082
final  value 84.906082 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.597286 
iter  10 value 94.493148
iter  20 value 94.374141
iter  30 value 91.918197
iter  40 value 91.914027
iter  50 value 91.912906
iter  60 value 91.911591
final  value 91.911577 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.565155 
iter  10 value 94.492703
iter  20 value 94.345394
iter  30 value 91.016828
iter  40 value 86.815040
iter  50 value 86.705700
iter  60 value 86.466269
iter  70 value 86.465835
iter  80 value 86.465131
final  value 86.463880 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.015230 
iter  10 value 94.474159
iter  20 value 93.792095
iter  30 value 86.932928
iter  40 value 84.777752
iter  50 value 84.706256
iter  60 value 84.550694
iter  70 value 84.545727
iter  80 value 84.544646
iter  90 value 84.383788
iter 100 value 83.923091
final  value 83.923091 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.329406 
iter  10 value 94.493298
iter  20 value 87.612158
iter  30 value 87.160389
iter  40 value 86.524647
iter  50 value 85.051310
iter  60 value 85.039917
iter  70 value 85.038623
iter  80 value 84.827828
iter  90 value 84.243401
iter 100 value 84.080553
final  value 84.080553 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.687006 
iter  10 value 93.353594
final  value 93.262036 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.256326 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.768102 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.552565 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.052726 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.990017 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.338883 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.835378 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.337724 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.755736 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.904004 
final  value 94.052909 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.002306 
iter  10 value 94.047844
final  value 94.027933 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.230413 
iter  10 value 88.793083
iter  20 value 81.418582
iter  30 value 81.324830
iter  40 value 80.763225
iter  50 value 80.762236
iter  60 value 80.761909
final  value 80.761905 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.060900 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.061635 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.182843 
iter  10 value 94.004911
iter  20 value 93.596940
iter  30 value 93.360427
iter  40 value 93.358122
iter  50 value 82.836337
iter  60 value 80.627035
iter  70 value 80.088108
iter  80 value 79.634776
iter  90 value 79.333479
iter 100 value 79.257521
final  value 79.257521 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 112.296329 
iter  10 value 94.054873
iter  20 value 84.053955
iter  30 value 82.584610
iter  40 value 81.871472
iter  50 value 81.555352
iter  60 value 81.251845
final  value 81.251843 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.085007 
iter  10 value 93.505475
iter  20 value 83.233012
iter  30 value 82.525334
iter  40 value 82.387520
iter  50 value 81.174571
iter  60 value 81.028689
iter  70 value 80.940022
final  value 80.938047 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.072527 
iter  10 value 94.027624
iter  20 value 83.431076
iter  30 value 82.896115
iter  40 value 82.665761
iter  50 value 82.206363
iter  60 value 81.253016
iter  70 value 81.251847
final  value 81.251842 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.076038 
iter  10 value 93.749801
iter  20 value 93.386127
iter  30 value 86.033212
iter  40 value 81.562705
iter  50 value 80.930222
iter  60 value 80.252478
iter  70 value 80.055839
iter  80 value 80.006394
iter  90 value 79.951133
iter 100 value 79.603206
final  value 79.603206 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.651822 
iter  10 value 89.874781
iter  20 value 81.329582
iter  30 value 80.959596
iter  40 value 80.483130
iter  50 value 79.995507
iter  60 value 79.302081
iter  70 value 78.455229
iter  80 value 78.019228
iter  90 value 77.919595
iter 100 value 77.840490
final  value 77.840490 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.116554 
iter  10 value 95.234279
iter  20 value 89.562102
iter  30 value 83.159542
iter  40 value 81.294293
iter  50 value 80.452841
iter  60 value 80.073801
iter  70 value 79.691040
iter  80 value 79.075912
iter  90 value 78.735386
iter 100 value 78.716638
final  value 78.716638 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.351365 
iter  10 value 93.885720
iter  20 value 87.238765
iter  30 value 86.053435
iter  40 value 81.937177
iter  50 value 80.697263
iter  60 value 80.462429
iter  70 value 79.632510
iter  80 value 78.345920
iter  90 value 77.670434
iter 100 value 77.632035
final  value 77.632035 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.657579 
iter  10 value 94.028916
iter  20 value 93.517773
iter  30 value 82.886182
iter  40 value 82.558754
iter  50 value 82.379627
iter  60 value 82.230755
iter  70 value 82.074298
iter  80 value 79.941936
iter  90 value 79.060614
iter 100 value 78.907156
final  value 78.907156 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.261410 
iter  10 value 95.822246
iter  20 value 94.735829
iter  30 value 91.815035
iter  40 value 88.503622
iter  50 value 84.725848
iter  60 value 81.581600
iter  70 value 80.563967
iter  80 value 79.747148
iter  90 value 79.385469
iter 100 value 79.200380
final  value 79.200380 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.729460 
iter  10 value 93.975479
iter  20 value 82.674984
iter  30 value 81.672990
iter  40 value 81.440721
iter  50 value 81.158114
iter  60 value 79.894315
iter  70 value 79.541903
iter  80 value 79.474080
iter  90 value 79.453676
iter 100 value 79.419914
final  value 79.419914 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.481897 
iter  10 value 94.347989
iter  20 value 93.693985
iter  30 value 87.090090
iter  40 value 83.263479
iter  50 value 82.098989
iter  60 value 79.887679
iter  70 value 78.648518
iter  80 value 78.308535
iter  90 value 77.602543
iter 100 value 77.386483
final  value 77.386483 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.546575 
iter  10 value 93.982525
iter  20 value 90.636716
iter  30 value 89.940804
iter  40 value 88.149821
iter  50 value 86.838062
iter  60 value 82.681440
iter  70 value 80.393017
iter  80 value 80.181323
iter  90 value 79.830538
iter 100 value 78.108004
final  value 78.108004 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.837665 
iter  10 value 93.968471
iter  20 value 82.475188
iter  30 value 80.435764
iter  40 value 79.803944
iter  50 value 79.700407
iter  60 value 79.387790
iter  70 value 78.323305
iter  80 value 78.032064
iter  90 value 77.985656
iter 100 value 77.955443
final  value 77.955443 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.486807 
iter  10 value 94.442832
iter  20 value 94.193749
iter  30 value 86.884815
iter  40 value 82.232424
iter  50 value 81.305471
iter  60 value 80.323718
iter  70 value 79.751264
iter  80 value 79.122672
iter  90 value 78.773101
iter 100 value 78.535533
final  value 78.535533 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.988400 
final  value 94.054536 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.722696 
iter  10 value 93.583988
iter  20 value 93.524048
iter  30 value 87.527013
final  value 80.886400 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.474138 
final  value 94.054518 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.883845 
iter  10 value 93.584429
iter  20 value 93.583334
iter  30 value 93.582721
iter  30 value 93.582720
final  value 93.582720 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.365044 
final  value 94.054704 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.561551 
iter  10 value 94.053685
final  value 94.053612 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.695096 
iter  10 value 93.308145
iter  20 value 93.305250
iter  30 value 91.069690
iter  40 value 83.887190
iter  50 value 83.061655
iter  60 value 82.752012
iter  70 value 82.694189
iter  80 value 82.658526
iter  90 value 82.658004
iter 100 value 82.657858
final  value 82.657858 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.302429 
iter  10 value 84.801574
iter  20 value 84.693312
iter  30 value 84.690571
final  value 84.341179 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.433587 
iter  10 value 93.506937
iter  20 value 93.503161
iter  30 value 91.822118
iter  40 value 83.693949
iter  50 value 79.938304
iter  60 value 78.305141
iter  70 value 77.696293
iter  80 value 77.642525
iter  90 value 77.464689
iter 100 value 76.935509
final  value 76.935509 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.872361 
iter  10 value 94.058175
iter  20 value 94.052937
final  value 94.052932 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.096678 
iter  10 value 93.591099
iter  20 value 93.330876
iter  30 value 91.112234
iter  40 value 86.375153
final  value 86.375144 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.279712 
iter  10 value 93.517348
iter  20 value 93.510281
iter  30 value 93.505949
iter  40 value 82.015716
iter  50 value 78.331720
iter  60 value 77.852988
iter  70 value 77.839120
iter  80 value 77.714182
iter  90 value 77.683570
iter 100 value 77.683235
final  value 77.683235 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.361540 
iter  10 value 94.063688
iter  20 value 93.787584
iter  30 value 82.528037
iter  40 value 81.621218
iter  50 value 80.506647
iter  60 value 80.446283
iter  70 value 79.008841
iter  80 value 77.934599
iter  90 value 77.923060
iter 100 value 77.891225
final  value 77.891225 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.375997 
iter  10 value 94.061080
iter  20 value 94.007503
iter  30 value 88.633304
iter  40 value 81.735796
final  value 81.731138 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.286848 
iter  10 value 93.448496
iter  20 value 93.315704
iter  30 value 91.872187
iter  40 value 82.909429
iter  50 value 81.773624
iter  50 value 81.773624
iter  50 value 81.773624
final  value 81.773624 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.274503 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.932888 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.221907 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.803897 
final  value 94.025289 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.115214 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.386481 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.499305 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.902640 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.122112 
iter  10 value 91.990226
iter  20 value 91.661267
iter  30 value 91.660130
final  value 91.660046 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.387398 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.964973 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.526612 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.548359 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.539605 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.587611 
iter  10 value 85.348927
iter  20 value 84.620896
iter  30 value 84.594496
final  value 84.580836 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.937183 
iter  10 value 94.059739
iter  20 value 94.004494
iter  30 value 91.028436
iter  40 value 88.465387
iter  50 value 86.111926
iter  60 value 85.315717
iter  70 value 84.848025
iter  80 value 84.500923
iter  90 value 84.452616
iter 100 value 84.325910
final  value 84.325910 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.572521 
iter  10 value 88.979820
iter  20 value 86.318150
iter  30 value 84.982269
iter  40 value 84.868507
iter  50 value 84.842131
final  value 84.842113 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.492089 
iter  10 value 93.620193
iter  20 value 87.075838
iter  30 value 85.985488
iter  40 value 85.525884
iter  50 value 85.298893
iter  60 value 85.135896
iter  70 value 84.948419
iter  80 value 84.713010
iter  90 value 84.673076
final  value 84.673061 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.704326 
iter  10 value 93.926138
iter  20 value 88.647914
iter  30 value 88.072451
iter  40 value 87.933280
iter  50 value 87.845526
iter  60 value 87.568518
iter  70 value 85.619013
iter  80 value 84.699580
iter  90 value 84.673110
final  value 84.673061 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.574261 
iter  10 value 94.051343
iter  20 value 93.886871
iter  30 value 93.089984
iter  40 value 92.239507
iter  50 value 90.877472
iter  60 value 90.768694
iter  70 value 90.632130
iter  80 value 90.584300
final  value 90.584139 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.837431 
iter  10 value 94.114971
iter  20 value 93.975390
iter  30 value 92.636337
iter  40 value 91.546062
iter  50 value 90.547968
iter  60 value 90.440555
iter  70 value 89.104200
iter  80 value 85.474650
iter  90 value 84.893808
iter 100 value 83.511812
final  value 83.511812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.032195 
iter  10 value 93.952996
iter  20 value 90.454007
iter  30 value 89.290947
iter  40 value 88.307890
iter  50 value 83.971646
iter  60 value 83.372639
iter  70 value 83.172478
iter  80 value 82.016929
iter  90 value 81.870989
iter 100 value 81.533859
final  value 81.533859 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.254406 
iter  10 value 94.290913
iter  20 value 89.816264
iter  30 value 84.772620
iter  40 value 83.897166
iter  50 value 83.171716
iter  60 value 82.979249
iter  70 value 82.592589
iter  80 value 82.488676
iter  90 value 82.487093
iter 100 value 82.476460
final  value 82.476460 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.091779 
iter  10 value 93.910316
iter  20 value 87.714606
iter  30 value 86.428976
iter  40 value 85.856008
iter  50 value 85.262422
iter  60 value 85.147370
iter  70 value 85.014968
iter  80 value 84.514755
iter  90 value 82.902687
iter 100 value 81.886729
final  value 81.886729 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.684568 
iter  10 value 93.920395
iter  20 value 91.614924
iter  30 value 86.015155
iter  40 value 85.127665
iter  50 value 84.670953
iter  60 value 83.878477
iter  70 value 83.071808
iter  80 value 82.278807
iter  90 value 81.677598
iter 100 value 81.364113
final  value 81.364113 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.731645 
iter  10 value 94.076248
iter  20 value 91.387487
iter  30 value 87.094844
iter  40 value 85.091261
iter  50 value 84.237761
iter  60 value 83.563148
iter  70 value 82.970709
iter  80 value 81.799119
iter  90 value 81.327834
iter 100 value 81.269358
final  value 81.269358 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.432225 
iter  10 value 94.128840
iter  20 value 87.416668
iter  30 value 86.844752
iter  40 value 83.842573
iter  50 value 82.632290
iter  60 value 81.838077
iter  70 value 81.612946
iter  80 value 81.519354
iter  90 value 81.217612
iter 100 value 81.056465
final  value 81.056465 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.270156 
iter  10 value 93.206567
iter  20 value 85.658700
iter  30 value 85.115868
iter  40 value 84.772294
iter  50 value 84.420642
iter  60 value 83.809977
iter  70 value 82.588847
iter  80 value 82.471638
iter  90 value 82.284220
iter 100 value 82.025166
final  value 82.025166 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.397046 
iter  10 value 94.121336
iter  20 value 92.717075
iter  30 value 87.108746
iter  40 value 84.653361
iter  50 value 84.036305
iter  60 value 83.596142
iter  70 value 83.080062
iter  80 value 82.563626
iter  90 value 82.321656
iter 100 value 82.102187
final  value 82.102187 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.721834 
iter  10 value 94.061345
iter  20 value 93.633300
iter  30 value 86.556850
iter  40 value 85.837552
iter  50 value 84.685479
iter  60 value 83.008245
iter  70 value 82.254897
iter  80 value 82.062155
iter  90 value 81.741149
iter 100 value 81.697045
final  value 81.697045 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.446230 
final  value 94.054624 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.275557 
iter  10 value 94.054804
iter  20 value 93.755049
iter  30 value 85.884212
iter  40 value 85.642325
final  value 85.577439 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.084238 
iter  10 value 94.054689
iter  20 value 94.042684
iter  30 value 90.707745
iter  40 value 89.438934
iter  50 value 89.198042
iter  60 value 89.197653
iter  70 value 85.107340
iter  80 value 85.101654
iter  90 value 85.100371
iter 100 value 85.099064
final  value 85.099064 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 94.473422 
final  value 94.054743 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.741806 
final  value 94.054317 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.043679 
iter  10 value 94.037930
iter  20 value 94.033669
iter  30 value 94.032996
iter  40 value 94.005251
iter  50 value 93.245231
iter  60 value 93.223499
iter  70 value 93.180584
iter  80 value 93.146137
iter  90 value 90.925911
iter 100 value 86.697301
final  value 86.697301 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.574030 
iter  10 value 94.057399
iter  20 value 93.965337
iter  30 value 87.837976
iter  40 value 87.611224
iter  50 value 87.610988
iter  60 value 87.602435
iter  70 value 87.519887
final  value 87.519881 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.179774 
iter  10 value 94.056782
iter  20 value 86.093362
iter  30 value 85.882553
iter  40 value 85.624059
iter  50 value 85.622223
iter  60 value 84.974951
iter  70 value 83.963605
iter  80 value 83.138390
final  value 83.121081 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.378550 
iter  10 value 91.908729
iter  20 value 88.100387
iter  30 value 88.072723
iter  40 value 87.917585
final  value 87.873025 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.821665 
iter  10 value 93.248114
iter  20 value 93.185886
iter  30 value 91.459545
iter  40 value 85.414382
iter  50 value 85.309850
final  value 85.309829 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.994223 
iter  10 value 94.060957
iter  20 value 94.053142
iter  30 value 89.475905
iter  40 value 87.470779
iter  50 value 85.982713
iter  60 value 84.349186
iter  70 value 83.767513
iter  80 value 83.733980
iter  90 value 83.733435
iter 100 value 83.731805
final  value 83.731805 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.677722 
iter  10 value 94.032797
iter  20 value 94.025226
iter  30 value 94.003343
iter  40 value 94.002676
final  value 94.002655 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.408301 
iter  10 value 94.061124
iter  20 value 93.870318
iter  30 value 92.812297
iter  40 value 90.666745
iter  50 value 84.063950
iter  60 value 83.659923
iter  70 value 83.646506
iter  80 value 83.514471
iter  90 value 83.204143
iter 100 value 83.197996
final  value 83.197996 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.924797 
iter  10 value 94.061053
iter  20 value 91.469214
iter  30 value 85.686989
iter  40 value 83.490091
iter  50 value 81.711337
iter  60 value 81.451711
iter  70 value 81.449362
iter  80 value 81.439081
iter  90 value 81.438083
iter 100 value 81.436933
final  value 81.436933 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.428744 
iter  10 value 93.592653
iter  20 value 93.413331
iter  30 value 93.406149
iter  40 value 93.041075
iter  50 value 90.831884
iter  60 value 88.213525
iter  70 value 84.752479
iter  80 value 83.592767
iter  90 value 83.227348
iter 100 value 82.064175
final  value 82.064175 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.801382 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.017725 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.778409 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.625749 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.353938 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.543894 
final  value 94.052434 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.464188 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.863119 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.283035 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.599931 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.126806 
final  value 93.429675 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.118639 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.065578 
iter  10 value 94.512218
iter  20 value 93.990031
final  value 93.109890 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.237930 
iter  10 value 93.967026
iter  20 value 92.521787
iter  30 value 92.461644
final  value 92.461539 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.541043 
iter  10 value 93.806405
iter  20 value 93.423543
iter  30 value 93.423225
final  value 93.423221 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.222548 
iter  10 value 94.488603
iter  20 value 90.012791
iter  30 value 85.782632
iter  40 value 85.135141
iter  50 value 85.081553
iter  60 value 85.056166
final  value 85.056111 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.156872 
iter  10 value 94.628507
iter  20 value 94.130998
iter  30 value 94.050841
iter  40 value 90.109274
iter  50 value 86.108170
iter  60 value 85.340703
iter  70 value 85.225962
iter  80 value 85.090899
final  value 85.085683 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.843499 
iter  10 value 94.485430
iter  20 value 94.106682
iter  30 value 89.348449
iter  40 value 85.962290
iter  50 value 83.703577
iter  60 value 82.786271
iter  70 value 82.357336
iter  80 value 82.319734
final  value 82.319533 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.913955 
iter  10 value 94.522216
iter  20 value 88.661003
iter  30 value 86.799937
iter  40 value 86.126542
iter  50 value 85.358277
iter  60 value 85.244025
iter  70 value 85.137991
iter  80 value 85.085948
final  value 85.084917 
converged
Fitting Repeat 5 

# weights:  103
initial  value 119.701395 
iter  10 value 93.469509
iter  20 value 86.467541
iter  30 value 85.802652
iter  40 value 85.219822
iter  50 value 85.085735
iter  60 value 85.072499
iter  70 value 85.056112
iter  70 value 85.056112
iter  70 value 85.056112
final  value 85.056112 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.821758 
iter  10 value 94.505459
iter  20 value 94.217582
iter  30 value 90.607894
iter  40 value 87.738830
iter  50 value 83.761693
iter  60 value 83.118446
iter  70 value 82.208022
iter  80 value 81.579675
iter  90 value 81.417684
iter 100 value 81.287403
final  value 81.287403 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.043423 
iter  10 value 94.251701
iter  20 value 88.706181
iter  30 value 84.599408
iter  40 value 83.854956
iter  50 value 83.316327
iter  60 value 82.696624
iter  70 value 82.248142
iter  80 value 82.180822
iter  90 value 82.154892
iter 100 value 82.142610
final  value 82.142610 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.579580 
iter  10 value 94.456981
iter  20 value 91.411047
iter  30 value 86.686360
iter  40 value 85.076072
iter  50 value 84.896675
iter  60 value 84.322244
iter  70 value 82.464776
iter  80 value 81.744035
iter  90 value 81.217218
iter 100 value 81.113107
final  value 81.113107 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.080587 
iter  10 value 94.087214
iter  20 value 90.513278
iter  30 value 84.547251
iter  40 value 83.401257
iter  50 value 83.100646
iter  60 value 82.766114
iter  70 value 82.622219
iter  80 value 82.575022
iter  90 value 82.440752
iter 100 value 82.079323
final  value 82.079323 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.680664 
iter  10 value 94.615549
iter  20 value 89.020646
iter  30 value 87.739211
iter  40 value 85.728774
iter  50 value 83.886133
iter  60 value 83.119630
iter  70 value 82.707561
iter  80 value 82.223243
iter  90 value 81.625374
iter 100 value 80.890457
final  value 80.890457 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.834863 
iter  10 value 94.425070
iter  20 value 88.579911
iter  30 value 87.811930
iter  40 value 85.374730
iter  50 value 84.988428
iter  60 value 84.792423
iter  70 value 83.801245
iter  80 value 83.264264
iter  90 value 82.070923
iter 100 value 81.428571
final  value 81.428571 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.151105 
iter  10 value 94.589193
iter  20 value 93.447287
iter  30 value 92.130203
iter  40 value 84.074921
iter  50 value 83.801195
iter  60 value 83.652700
iter  70 value 83.495075
iter  80 value 83.001523
iter  90 value 82.044102
iter 100 value 81.774100
final  value 81.774100 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.342258 
iter  10 value 94.493780
iter  20 value 94.217920
iter  30 value 93.701398
iter  40 value 91.107937
iter  50 value 90.749772
iter  60 value 87.552323
iter  70 value 86.413828
iter  80 value 84.841489
iter  90 value 83.887440
iter 100 value 83.805709
final  value 83.805709 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.290737 
iter  10 value 94.485209
iter  20 value 89.366138
iter  30 value 85.924398
iter  40 value 83.918323
iter  50 value 82.428650
iter  60 value 81.899907
iter  70 value 81.488732
iter  80 value 81.363365
iter  90 value 81.200642
iter 100 value 81.037640
final  value 81.037640 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.279560 
iter  10 value 93.647814
iter  20 value 86.711990
iter  30 value 86.050874
iter  40 value 85.002695
iter  50 value 84.737467
iter  60 value 84.697117
iter  70 value 84.362102
iter  80 value 82.912831
iter  90 value 81.875429
iter 100 value 81.492440
final  value 81.492440 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.800784 
final  value 94.485997 
converged
Fitting Repeat 2 

# weights:  103
initial  value 117.039247 
final  value 94.485763 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.550823 
final  value 94.485957 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.553060 
iter  10 value 94.435464
iter  20 value 94.435025
final  value 94.383278 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.543426 
final  value 94.487670 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.355145 
iter  10 value 94.281592
iter  20 value 94.277852
iter  30 value 94.275704
iter  40 value 94.170344
iter  50 value 93.041403
iter  60 value 93.022604
iter  70 value 93.022494
iter  80 value 93.021911
final  value 93.021848 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.685039 
iter  10 value 94.280194
iter  20 value 94.018980
iter  30 value 90.059570
iter  40 value 85.842678
iter  40 value 85.842678
iter  40 value 85.842678
final  value 85.842678 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.137313 
iter  10 value 94.271607
iter  20 value 94.263254
iter  30 value 94.211562
iter  40 value 94.210094
iter  50 value 94.032611
iter  60 value 93.974340
final  value 93.974229 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.582892 
iter  10 value 94.214324
iter  20 value 94.212255
iter  30 value 93.984695
iter  40 value 93.974045
iter  50 value 87.698490
iter  60 value 85.843159
final  value 85.842186 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.161623 
iter  10 value 94.063063
iter  20 value 94.047969
iter  30 value 93.766276
iter  40 value 86.148393
iter  50 value 84.628293
iter  60 value 82.229264
iter  70 value 81.792152
iter  80 value 80.800219
iter  90 value 80.236756
iter 100 value 79.884560
final  value 79.884560 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.893218 
iter  10 value 92.658682
iter  20 value 91.855006
iter  30 value 91.853094
iter  40 value 91.852178
iter  50 value 91.848414
iter  60 value 91.847288
iter  70 value 91.847056
iter  80 value 91.846391
final  value 91.846301 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.233767 
iter  10 value 94.283500
iter  20 value 94.277936
final  value 94.276237 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.281857 
iter  10 value 92.977980
iter  20 value 92.947174
iter  30 value 92.681153
iter  40 value 92.621476
iter  50 value 91.286070
iter  60 value 87.365443
iter  70 value 87.081700
iter  80 value 87.080873
iter  90 value 86.921773
iter 100 value 86.884946
final  value 86.884946 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.489893 
iter  10 value 93.966586
iter  20 value 93.929976
iter  30 value 93.928673
iter  40 value 93.867975
iter  50 value 93.852308
iter  60 value 93.850181
iter  70 value 90.416837
iter  80 value 85.411550
iter  90 value 84.808669
iter 100 value 81.424986
final  value 81.424986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.999566 
iter  10 value 94.141671
iter  20 value 94.132339
iter  30 value 94.101327
iter  40 value 91.580315
iter  50 value 88.515977
iter  60 value 85.850587
iter  70 value 85.847287
iter  80 value 85.842764
iter  90 value 85.735468
final  value 85.735465 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.478305 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.140831 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.065394 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.766307 
iter  10 value 93.776047
iter  20 value 92.610458
iter  30 value 86.775544
iter  40 value 86.747405
iter  50 value 86.747309
final  value 86.747307 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.537602 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.968512 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.057727 
final  value 94.484137 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.656167 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.540154 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.664000 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 140.103108 
iter  10 value 94.484224
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.966194 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.365943 
final  value 94.443241 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.552860 
iter  10 value 94.443246
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.134707 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.783846 
iter  10 value 94.486501
iter  20 value 93.011479
iter  30 value 84.063024
iter  40 value 83.259196
iter  50 value 82.833452
iter  60 value 82.644664
iter  70 value 81.880154
iter  80 value 81.612419
iter  90 value 81.517860
iter 100 value 81.438570
final  value 81.438570 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.730614 
iter  10 value 94.486494
iter  20 value 94.181575
iter  30 value 91.431041
iter  40 value 88.631057
iter  50 value 84.230959
iter  60 value 83.434433
iter  70 value 83.089066
final  value 83.082721 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.866250 
iter  10 value 94.403045
iter  20 value 93.114219
iter  30 value 90.407424
iter  40 value 88.653576
iter  50 value 88.268326
iter  60 value 87.044816
iter  70 value 86.787065
iter  80 value 85.900548
iter  90 value 85.008284
iter 100 value 84.992010
final  value 84.992010 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.219769 
iter  10 value 94.494032
iter  20 value 93.775511
iter  30 value 89.851058
iter  40 value 88.624128
iter  50 value 88.246460
iter  60 value 85.994439
iter  70 value 82.330333
iter  80 value 81.967527
iter  90 value 81.552739
iter 100 value 81.490643
final  value 81.490643 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.418654 
iter  10 value 94.503674
iter  20 value 92.677551
iter  30 value 87.342036
iter  40 value 85.189779
iter  50 value 84.560140
iter  60 value 84.138093
iter  70 value 83.718858
iter  80 value 83.389527
iter  90 value 83.112566
iter 100 value 83.082721
final  value 83.082721 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.714071 
iter  10 value 94.537342
iter  20 value 91.472443
iter  30 value 87.502135
iter  40 value 86.867986
iter  50 value 86.663462
iter  60 value 86.413795
iter  70 value 83.033596
iter  80 value 81.766224
iter  90 value 81.348348
iter 100 value 80.720515
final  value 80.720515 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.967672 
iter  10 value 94.464363
iter  20 value 92.433888
iter  30 value 85.691031
iter  40 value 84.179162
iter  50 value 82.730523
iter  60 value 81.929145
iter  70 value 80.971533
iter  80 value 80.280999
iter  90 value 79.869478
iter 100 value 79.614143
final  value 79.614143 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.973375 
iter  10 value 94.499985
iter  20 value 85.477528
iter  30 value 83.956541
iter  40 value 83.236967
iter  50 value 83.175665
iter  60 value 83.023234
iter  70 value 82.638312
iter  80 value 82.544127
iter  90 value 82.413639
iter 100 value 82.188085
final  value 82.188085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.367326 
iter  10 value 94.361598
iter  20 value 89.241264
iter  30 value 87.343288
iter  40 value 86.979299
iter  50 value 86.098201
iter  60 value 85.056480
iter  70 value 83.880186
iter  80 value 83.147242
iter  90 value 82.574622
iter 100 value 82.281382
final  value 82.281382 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.495688 
iter  10 value 94.494046
iter  20 value 89.814140
iter  30 value 86.777090
iter  40 value 85.899331
iter  50 value 82.909509
iter  60 value 81.160020
iter  70 value 80.867426
iter  80 value 80.807268
iter  90 value 80.205626
iter 100 value 79.978634
final  value 79.978634 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 145.846134 
iter  10 value 94.686885
iter  20 value 89.589230
iter  30 value 88.037462
iter  40 value 87.691035
iter  50 value 86.485653
iter  60 value 84.954696
iter  70 value 83.378992
iter  80 value 81.413131
iter  90 value 81.176713
iter 100 value 81.084838
final  value 81.084838 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.610889 
iter  10 value 95.903138
iter  20 value 89.019751
iter  30 value 87.795288
iter  40 value 84.278661
iter  50 value 83.162408
iter  60 value 82.634501
iter  70 value 82.266545
iter  80 value 81.449281
iter  90 value 81.169582
iter 100 value 80.865444
final  value 80.865444 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.235677 
iter  10 value 94.846834
iter  20 value 94.445548
iter  30 value 90.826857
iter  40 value 85.057966
iter  50 value 84.761826
iter  60 value 84.500729
iter  70 value 83.950351
iter  80 value 83.716723
iter  90 value 82.469411
iter 100 value 81.653141
final  value 81.653141 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.545865 
iter  10 value 94.645475
iter  20 value 94.552101
iter  30 value 92.556682
iter  40 value 87.955910
iter  50 value 83.649903
iter  60 value 82.144150
iter  70 value 80.728723
iter  80 value 80.040456
iter  90 value 79.939488
iter 100 value 79.895116
final  value 79.895116 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.608467 
iter  10 value 95.623333
iter  20 value 95.163671
iter  30 value 93.061957
iter  40 value 88.288568
iter  50 value 86.355293
iter  60 value 84.291839
iter  70 value 83.892295
iter  80 value 83.593845
iter  90 value 82.762473
iter 100 value 80.701259
final  value 80.701259 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.884463 
final  value 94.444747 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.141357 
final  value 94.485601 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.140708 
final  value 94.485948 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.664663 
final  value 94.481991 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.958231 
final  value 94.485763 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.881889 
iter  10 value 94.456435
iter  20 value 91.014413
iter  30 value 88.098213
iter  40 value 87.871215
final  value 87.870719 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.288529 
iter  10 value 94.489435
iter  20 value 94.461486
iter  30 value 90.635222
iter  40 value 85.386997
iter  50 value 85.115590
iter  60 value 85.113682
iter  70 value 85.110714
iter  80 value 85.097799
iter  90 value 84.345480
iter 100 value 82.910237
final  value 82.910237 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.038478 
iter  10 value 94.448487
iter  20 value 94.443517
iter  30 value 94.339664
iter  40 value 92.024740
iter  50 value 91.834797
iter  60 value 86.998623
iter  70 value 84.233951
iter  80 value 82.146078
iter  90 value 82.106698
iter 100 value 82.106180
final  value 82.106180 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.600389 
iter  10 value 94.489349
iter  20 value 94.453453
iter  30 value 88.734904
iter  40 value 88.570040
iter  50 value 88.567711
iter  60 value 88.434165
iter  70 value 88.422684
iter  80 value 88.422466
iter  90 value 87.190318
iter 100 value 86.958888
final  value 86.958888 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.845344 
iter  10 value 94.489312
iter  20 value 94.437539
iter  30 value 88.806895
final  value 88.525425 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.086388 
iter  10 value 92.840887
iter  20 value 92.693061
iter  30 value 91.525168
iter  40 value 88.717668
iter  50 value 83.833952
iter  60 value 82.070583
iter  70 value 81.838780
iter  80 value 80.981718
iter  90 value 80.488417
iter 100 value 80.026911
final  value 80.026911 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.385379 
iter  10 value 88.628850
iter  20 value 87.612875
iter  30 value 87.592197
iter  40 value 84.873989
iter  50 value 84.648570
iter  60 value 84.643198
iter  70 value 84.641878
iter  80 value 84.641670
final  value 84.641574 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.182658 
iter  10 value 94.451819
iter  20 value 94.443258
iter  30 value 87.136461
iter  40 value 85.010186
iter  50 value 84.965230
iter  60 value 82.854026
final  value 82.795732 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.759564 
iter  10 value 87.568530
iter  20 value 86.963429
iter  30 value 86.863393
final  value 86.861960 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.080455 
iter  10 value 94.492077
iter  20 value 94.384031
iter  30 value 92.982381
iter  40 value 92.957487
iter  50 value 89.053876
iter  60 value 85.328087
iter  70 value 85.069369
iter  80 value 84.909374
iter  90 value 83.565718
iter 100 value 83.564644
final  value 83.564644 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 137.939218 
iter  10 value 117.891165
iter  20 value 109.733389
iter  30 value 106.915641
iter  40 value 104.864280
iter  50 value 100.875049
iter  60 value 100.792857
iter  70 value 100.755301
iter  80 value 100.754114
iter  90 value 100.751677
iter 100 value 100.735214
final  value 100.735214 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 179.791859 
iter  10 value 117.763560
iter  20 value 117.759377
final  value 117.758872 
converged
Fitting Repeat 3 

# weights:  305
initial  value 154.970957 
iter  10 value 117.895543
iter  20 value 113.507876
iter  30 value 107.156028
iter  40 value 107.155184
iter  50 value 107.009128
iter  60 value 106.970797
iter  70 value 105.668663
iter  80 value 105.521952
iter  90 value 105.490980
iter 100 value 104.702630
final  value 104.702630 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.654714 
iter  10 value 117.010434
iter  20 value 115.441542
iter  30 value 114.303703
iter  40 value 114.297714
iter  50 value 114.294952
iter  50 value 114.294952
final  value 114.294952 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.190053 
iter  10 value 113.311326
iter  20 value 112.776309
iter  30 value 112.653543
iter  40 value 112.600148
iter  50 value 112.445229
iter  60 value 105.395092
iter  70 value 105.056666
iter  80 value 105.055395
iter  90 value 105.054991
iter 100 value 105.039512
final  value 105.039512 
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 -- Fri Jan 10 23:04:07 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 
 40.965   1.131  49.074