##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.1 (2024-06-14 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.11.0'
* 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 whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
               user system elapsed
var_imp       35.79   1.23   37.02
FSmethod      34.46   2.23   36.74
corr_plot     33.67   1.47   35.17
pred_ensembel 15.04   0.41   11.23
enrichfindP    0.63   0.16   12.97
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'runTests.R'
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library'
* installing *source* package 'HPiP' ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 99.724654 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.380866 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.204617 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.664541 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.105260 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.604821 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.682787 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.735701 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.376533 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.041669 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.608226 
iter  10 value 93.089856
final  value 93.086891 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.295893 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.287255 
iter  10 value 88.826343
iter  20 value 88.789954
final  value 88.789943 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.156543 
iter  10 value 93.378741
iter  20 value 93.014066
final  value 93.014053 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.031235 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.406820 
iter  10 value 91.945640
iter  20 value 86.479846
iter  30 value 86.085964
iter  40 value 85.809235
iter  50 value 82.890731
iter  60 value 81.722317
iter  70 value 81.705316
iter  80 value 81.688427
iter  90 value 81.590938
iter 100 value 81.545079
final  value 81.545079 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.720875 
iter  10 value 94.045037
iter  20 value 93.449916
iter  30 value 93.327593
iter  40 value 93.248405
iter  50 value 90.658407
iter  60 value 88.993882
iter  70 value 87.257831
iter  80 value 86.822436
iter  90 value 86.633265
iter 100 value 86.614585
final  value 86.614585 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.946496 
iter  10 value 93.821539
iter  20 value 87.617955
iter  30 value 86.172798
iter  40 value 83.636336
iter  50 value 82.603505
iter  60 value 81.701631
final  value 81.691902 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.196754 
iter  10 value 92.526754
iter  20 value 89.205933
iter  30 value 86.259458
iter  40 value 86.029987
iter  50 value 85.856589
iter  60 value 85.816275
final  value 85.816255 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.804455 
iter  10 value 90.867210
iter  20 value 87.206651
iter  30 value 86.967155
iter  40 value 86.211728
iter  50 value 85.919792
iter  60 value 85.831202
iter  70 value 85.816539
final  value 85.816255 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.434172 
iter  10 value 94.059226
iter  20 value 89.040545
iter  30 value 88.782126
iter  40 value 86.965124
iter  50 value 82.954101
iter  60 value 82.327283
iter  70 value 81.938319
iter  80 value 81.765283
iter  90 value 81.678480
iter 100 value 81.424784
final  value 81.424784 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.653177 
iter  10 value 94.054451
iter  20 value 92.333870
iter  30 value 86.137479
iter  40 value 83.672060
iter  50 value 82.110936
iter  60 value 81.309947
iter  70 value 80.693321
iter  80 value 80.286345
iter  90 value 79.894101
iter 100 value 79.793486
final  value 79.793486 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.919851 
iter  10 value 93.849124
iter  20 value 89.842578
iter  30 value 89.459642
iter  40 value 85.125795
iter  50 value 83.982403
iter  60 value 83.661441
iter  70 value 82.963281
iter  80 value 82.717371
iter  90 value 82.633953
iter 100 value 82.416184
final  value 82.416184 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.256629 
iter  10 value 94.890159
iter  20 value 92.794687
iter  30 value 91.235081
iter  40 value 90.754264
iter  50 value 89.088653
iter  60 value 85.066136
iter  70 value 82.664858
iter  80 value 82.217184
iter  90 value 81.936635
iter 100 value 81.486552
final  value 81.486552 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.115997 
iter  10 value 94.118646
iter  20 value 93.452525
iter  30 value 87.619222
iter  40 value 84.903314
iter  50 value 84.250110
iter  60 value 83.928305
iter  70 value 82.668171
iter  80 value 81.843195
iter  90 value 81.476800
iter 100 value 81.086048
final  value 81.086048 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.190681 
iter  10 value 94.023900
iter  20 value 89.797942
iter  30 value 89.245725
iter  40 value 88.531525
iter  50 value 87.948697
iter  60 value 86.738578
iter  70 value 85.125927
iter  80 value 82.777149
iter  90 value 82.493823
iter 100 value 82.373647
final  value 82.373647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 145.783157 
iter  10 value 96.492850
iter  20 value 94.068836
iter  30 value 92.928226
iter  40 value 87.116460
iter  50 value 86.444807
iter  60 value 84.220170
iter  70 value 82.468470
iter  80 value 81.242146
iter  90 value 80.750647
iter 100 value 80.531632
final  value 80.531632 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.746790 
iter  10 value 94.071939
iter  20 value 93.091453
iter  30 value 89.131034
iter  40 value 85.621542
iter  50 value 82.663902
iter  60 value 81.445953
iter  70 value 80.455998
iter  80 value 80.308061
iter  90 value 80.180045
iter 100 value 80.011277
final  value 80.011277 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.879590 
iter  10 value 94.466738
iter  20 value 93.582231
iter  30 value 91.368298
iter  40 value 84.359643
iter  50 value 82.489920
iter  60 value 81.667385
iter  70 value 81.170199
iter  80 value 80.687296
iter  90 value 80.475754
iter 100 value 80.427875
final  value 80.427875 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.821005 
iter  10 value 94.050366
iter  20 value 91.918766
iter  30 value 89.221195
iter  40 value 87.350234
iter  50 value 86.085263
iter  60 value 85.632641
iter  70 value 83.952291
iter  80 value 83.336605
iter  90 value 83.276672
iter 100 value 82.703414
final  value 82.703414 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.753750 
iter  10 value 94.054186
iter  20 value 94.050536
iter  30 value 93.201354
iter  40 value 93.144699
final  value 93.144503 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.686660 
iter  10 value 94.054535
iter  20 value 94.052927
iter  30 value 92.902234
final  value 86.379033 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.547951 
final  value 94.054578 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.848670 
final  value 94.054713 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.097141 
final  value 94.054112 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.194274 
iter  10 value 94.057864
iter  20 value 90.873089
iter  30 value 87.785830
iter  40 value 86.203799
iter  50 value 86.195693
iter  60 value 86.192536
final  value 86.192491 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.549521 
iter  10 value 94.045080
iter  20 value 93.840602
iter  30 value 93.836541
iter  40 value 93.832603
iter  50 value 93.729795
iter  60 value 92.274365
iter  70 value 89.253301
iter  80 value 87.587843
final  value 87.587580 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.688623 
iter  10 value 93.841749
iter  20 value 93.650004
iter  30 value 91.230899
iter  40 value 87.630194
final  value 87.613123 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.545395 
iter  10 value 92.497190
iter  20 value 90.021907
iter  30 value 84.517626
iter  40 value 83.906371
iter  50 value 83.904584
iter  50 value 83.904584
final  value 83.904584 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.698155 
iter  10 value 94.016027
iter  20 value 93.361218
iter  30 value 90.971012
iter  40 value 89.472122
iter  50 value 88.791935
final  value 88.791573 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.278978 
iter  10 value 93.134437
iter  20 value 93.131992
iter  30 value 93.125582
iter  40 value 93.075613
iter  50 value 92.876622
iter  60 value 92.837301
final  value 92.837277 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.909576 
iter  10 value 92.962823
iter  20 value 92.870087
iter  30 value 92.865479
iter  40 value 92.859707
iter  50 value 92.745053
iter  60 value 92.739271
iter  70 value 92.727607
iter  80 value 92.687269
iter  90 value 92.674547
iter 100 value 92.662891
final  value 92.662891 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.241160 
iter  10 value 93.843605
iter  20 value 93.837187
iter  30 value 93.394933
iter  40 value 87.383988
iter  50 value 82.414503
iter  60 value 80.838240
iter  70 value 79.927302
iter  80 value 79.876690
iter  90 value 79.876309
iter  90 value 79.876308
iter  90 value 79.876308
final  value 79.876308 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.891827 
iter  10 value 94.060476
iter  20 value 94.052934
iter  30 value 86.322877
iter  40 value 86.189419
iter  40 value 86.189418
final  value 86.189418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.105043 
iter  10 value 93.844672
iter  20 value 93.774111
iter  30 value 89.349547
iter  40 value 87.293664
iter  50 value 85.210045
iter  60 value 84.802721
iter  70 value 84.748616
iter  80 value 84.242175
iter  90 value 83.988856
iter 100 value 83.925117
final  value 83.925117 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.337020 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.164338 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.477147 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.877648 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.627112 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.976217 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.073671 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.727058 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.527067 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.044070 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.123323 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.457994 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.427571 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.234617 
iter  10 value 94.309803
iter  10 value 94.309803
iter  10 value 94.309803
final  value 94.309803 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.293272 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.778958 
iter  10 value 94.567286
iter  20 value 94.422629
iter  30 value 88.474061
iter  40 value 86.724301
iter  50 value 85.080576
iter  60 value 84.644111
iter  70 value 84.570601
iter  80 value 84.532841
final  value 84.528277 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.370517 
iter  10 value 94.477858
iter  20 value 88.797703
iter  30 value 86.364193
iter  40 value 86.023791
iter  50 value 84.089308
iter  60 value 83.520444
iter  70 value 83.407348
iter  80 value 83.302681
final  value 83.300729 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.575064 
iter  10 value 94.280624
iter  20 value 91.349918
iter  30 value 91.055443
iter  40 value 88.674840
iter  50 value 86.564024
iter  60 value 85.348329
iter  70 value 84.285955
iter  80 value 83.692146
iter  90 value 83.623728
iter 100 value 83.598176
final  value 83.598176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.006358 
iter  10 value 94.490559
iter  20 value 94.458206
iter  30 value 94.066000
iter  40 value 92.753907
iter  50 value 92.696202
iter  60 value 92.686193
iter  70 value 92.685312
iter  80 value 92.684092
iter  90 value 92.683915
final  value 92.683888 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.704590 
iter  10 value 94.493603
iter  20 value 94.486408
iter  30 value 93.099644
iter  40 value 91.738774
iter  50 value 91.607039
iter  60 value 90.553360
iter  70 value 86.791654
iter  80 value 85.838894
iter  90 value 84.198892
iter 100 value 83.631793
final  value 83.631793 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.950730 
iter  10 value 94.667144
iter  20 value 94.491651
iter  30 value 93.880851
iter  40 value 88.463648
iter  50 value 86.415563
iter  60 value 85.746694
iter  70 value 85.302197
iter  80 value 84.459691
iter  90 value 82.829322
iter 100 value 81.793590
final  value 81.793590 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.250664 
iter  10 value 94.497491
iter  20 value 94.426686
iter  30 value 90.413392
iter  40 value 87.214726
iter  50 value 83.666361
iter  60 value 82.708393
iter  70 value 82.473369
iter  80 value 82.187803
iter  90 value 82.122601
iter 100 value 82.035608
final  value 82.035608 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.854987 
iter  10 value 94.567159
iter  20 value 93.139605
iter  30 value 88.131133
iter  40 value 84.775428
iter  50 value 83.464480
iter  60 value 83.111138
iter  70 value 82.881485
iter  80 value 82.341994
iter  90 value 81.992839
iter 100 value 81.928132
final  value 81.928132 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.725625 
iter  10 value 94.475404
iter  20 value 90.267130
iter  30 value 87.784113
iter  40 value 87.475362
iter  50 value 87.367701
iter  60 value 87.106627
iter  70 value 86.310455
iter  80 value 85.079065
iter  90 value 83.592880
iter 100 value 83.473363
final  value 83.473363 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.316215 
iter  10 value 94.780142
iter  20 value 92.319821
iter  30 value 86.580140
iter  40 value 84.034627
iter  50 value 83.634173
iter  60 value 83.291477
iter  70 value 82.841943
iter  80 value 82.418387
iter  90 value 81.848769
iter 100 value 81.663582
final  value 81.663582 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.701104 
iter  10 value 94.415811
iter  20 value 86.786235
iter  30 value 86.107265
iter  40 value 84.918445
iter  50 value 84.119180
iter  60 value 83.218629
iter  70 value 82.607346
iter  80 value 82.073528
iter  90 value 81.921168
iter 100 value 81.878244
final  value 81.878244 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.500114 
iter  10 value 94.678848
iter  20 value 94.509867
iter  30 value 94.128474
iter  40 value 92.339022
iter  50 value 88.836737
iter  60 value 87.840231
iter  70 value 84.727041
iter  80 value 83.742596
iter  90 value 83.004567
iter 100 value 82.667080
final  value 82.667080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.900239 
iter  10 value 94.557592
iter  20 value 94.205567
iter  30 value 88.077958
iter  40 value 86.398904
iter  50 value 84.192081
iter  60 value 83.948949
iter  70 value 83.803190
iter  80 value 83.357072
iter  90 value 83.123627
iter 100 value 83.054733
final  value 83.054733 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 149.076952 
iter  10 value 94.488803
iter  20 value 90.067326
iter  30 value 88.052614
iter  40 value 84.847681
iter  50 value 84.462277
iter  60 value 83.195355
iter  70 value 82.656562
iter  80 value 82.410657
iter  90 value 82.284440
iter 100 value 82.059740
final  value 82.059740 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.199388 
iter  10 value 94.374406
iter  20 value 86.717923
iter  30 value 84.811390
iter  40 value 83.205019
iter  50 value 83.124051
iter  60 value 83.082946
iter  70 value 83.015208
iter  80 value 82.837019
iter  90 value 82.655745
iter 100 value 82.091631
final  value 82.091631 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.699148 
iter  10 value 94.468549
iter  20 value 94.467757
final  value 94.466885 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.590307 
iter  10 value 94.486050
iter  20 value 94.484254
final  value 94.484208 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.352530 
final  value 94.485586 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.281235 
final  value 94.485705 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.687610 
final  value 94.430635 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.930021 
iter  10 value 94.489977
iter  20 value 94.484903
iter  30 value 89.797892
iter  40 value 83.923401
iter  50 value 83.921084
iter  60 value 83.535748
iter  70 value 83.464494
iter  80 value 83.451365
iter  90 value 83.444233
iter 100 value 83.425447
final  value 83.425447 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.675145 
iter  10 value 94.430807
iter  20 value 94.314431
iter  30 value 94.311089
iter  40 value 94.257112
iter  50 value 91.289752
iter  60 value 86.922844
final  value 86.922713 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.468674 
iter  10 value 94.433610
iter  20 value 94.420618
final  value 94.408677 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.639360 
iter  10 value 94.489150
iter  20 value 94.484252
iter  30 value 92.907818
iter  40 value 89.210947
iter  50 value 84.394539
iter  60 value 84.203230
iter  70 value 84.149495
iter  80 value 83.926212
iter  90 value 83.101383
iter 100 value 83.097392
final  value 83.097392 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.336303 
iter  10 value 94.471299
iter  20 value 94.467001
iter  30 value 93.174827
iter  40 value 86.984606
iter  50 value 85.118687
iter  60 value 85.041877
iter  70 value 85.041208
iter  70 value 85.041207
iter  70 value 85.041207
final  value 85.041207 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.231066 
iter  10 value 94.492161
iter  20 value 94.484320
iter  30 value 94.089325
iter  40 value 92.287864
iter  50 value 92.286485
iter  60 value 86.945576
iter  70 value 86.882641
iter  80 value 86.327845
iter  90 value 83.571246
iter 100 value 82.176775
final  value 82.176775 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.819313 
iter  10 value 94.474903
iter  20 value 94.467774
iter  30 value 94.075194
iter  40 value 87.316195
iter  50 value 84.333122
iter  60 value 81.990221
iter  70 value 81.136078
iter  80 value 80.856071
iter  90 value 80.710255
iter 100 value 80.541665
final  value 80.541665 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.288196 
iter  10 value 94.475201
iter  20 value 94.103219
iter  30 value 84.177489
iter  40 value 81.648913
iter  50 value 81.269757
iter  60 value 81.001919
iter  70 value 80.978578
iter  80 value 80.978062
final  value 80.977420 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.070137 
iter  10 value 94.361617
iter  20 value 87.994272
iter  30 value 86.962342
iter  40 value 86.960138
iter  50 value 85.646335
iter  60 value 83.404155
iter  70 value 83.390353
iter  80 value 83.390118
iter  90 value 83.372117
iter 100 value 83.314287
final  value 83.314287 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.024073 
iter  10 value 94.489961
iter  20 value 92.802385
iter  30 value 88.034594
iter  40 value 87.472538
iter  50 value 87.435979
iter  60 value 82.603443
iter  70 value 82.603112
iter  80 value 82.528279
iter  90 value 82.515638
iter 100 value 82.478188
final  value 82.478188 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.299043 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.332998 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.772327 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.730529 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.254209 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.690558 
iter  10 value 94.127833
iter  20 value 94.127413
final  value 94.127406 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.850185 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.101053 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.349456 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.000935 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.185484 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.483113 
final  value 94.385584 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.463379 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.407905 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.035177 
iter  10 value 89.551684
iter  20 value 87.593475
iter  30 value 87.198816
iter  40 value 87.151044
final  value 87.150501 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.537432 
iter  10 value 86.196776
iter  20 value 84.628832
iter  30 value 84.571155
iter  40 value 84.541322
final  value 84.540269 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.113097 
iter  10 value 94.321472
iter  20 value 90.491343
iter  30 value 88.430482
iter  40 value 87.501761
iter  50 value 86.748234
iter  60 value 84.899227
iter  70 value 84.855542
iter  80 value 84.813330
iter  90 value 84.809878
iter 100 value 84.743224
final  value 84.743224 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.556463 
iter  10 value 93.573204
iter  20 value 86.550889
iter  30 value 85.774824
iter  40 value 85.726097
iter  50 value 84.701017
iter  60 value 84.686262
iter  70 value 84.676170
final  value 84.675478 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.712065 
iter  10 value 94.430924
iter  20 value 86.342363
iter  30 value 85.384609
iter  40 value 84.737925
iter  50 value 84.731843
iter  60 value 84.718369
iter  70 value 84.692701
iter  80 value 84.686562
iter  90 value 84.675507
final  value 84.675478 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.472826 
iter  10 value 88.691110
iter  20 value 85.148398
iter  30 value 84.840637
iter  40 value 84.812683
final  value 84.809918 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.723687 
iter  10 value 93.665374
iter  20 value 87.529271
iter  30 value 86.726796
iter  40 value 86.364549
iter  50 value 84.352699
iter  60 value 82.919603
iter  70 value 82.477825
iter  80 value 81.662294
iter  90 value 81.186646
iter 100 value 80.957624
final  value 80.957624 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.005174 
iter  10 value 94.347167
iter  20 value 92.472188
iter  30 value 91.195153
iter  40 value 91.099488
iter  50 value 90.939751
iter  60 value 83.913717
iter  70 value 83.574284
iter  80 value 83.492135
iter  90 value 83.442680
iter 100 value 82.988497
final  value 82.988497 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.898625 
iter  10 value 94.385677
iter  20 value 90.758132
iter  30 value 86.760291
iter  40 value 85.275740
iter  50 value 84.460623
iter  60 value 84.260576
iter  70 value 84.062826
iter  80 value 84.024195
iter  90 value 83.977985
iter 100 value 82.345654
final  value 82.345654 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.700662 
iter  10 value 93.231789
iter  20 value 86.177309
iter  30 value 84.684018
iter  40 value 84.507104
iter  50 value 84.467406
iter  60 value 84.364707
iter  70 value 84.060250
iter  80 value 83.216873
iter  90 value 82.217113
iter 100 value 82.125188
final  value 82.125188 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.654713 
iter  10 value 94.326780
iter  20 value 86.788444
iter  30 value 84.819558
iter  40 value 82.972050
iter  50 value 82.517375
iter  60 value 81.665944
iter  70 value 81.235769
iter  80 value 81.158475
iter  90 value 81.045100
iter 100 value 81.006993
final  value 81.006993 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.839344 
iter  10 value 95.614296
iter  20 value 93.756302
iter  30 value 86.091574
iter  40 value 85.342363
iter  50 value 85.214788
iter  60 value 83.924108
iter  70 value 83.499614
iter  80 value 83.268552
iter  90 value 82.768861
iter 100 value 81.987640
final  value 81.987640 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.177195 
iter  10 value 94.554988
iter  20 value 93.745493
iter  30 value 87.046024
iter  40 value 84.911114
iter  50 value 83.853781
iter  60 value 83.020835
iter  70 value 82.238435
iter  80 value 82.147029
iter  90 value 81.591958
iter 100 value 81.212068
final  value 81.212068 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.430718 
iter  10 value 94.524901
iter  20 value 93.670987
iter  30 value 87.361964
iter  40 value 85.003993
iter  50 value 83.626485
iter  60 value 83.180530
iter  70 value 82.866418
iter  80 value 81.995568
iter  90 value 81.959191
iter 100 value 81.917731
final  value 81.917731 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.911546 
iter  10 value 99.699985
iter  20 value 93.378630
iter  30 value 86.028852
iter  40 value 84.988619
iter  50 value 83.493903
iter  60 value 82.416129
iter  70 value 82.315528
iter  80 value 81.939931
iter  90 value 81.475700
iter 100 value 80.946704
final  value 80.946704 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.698568 
iter  10 value 95.140794
iter  20 value 94.427231
iter  30 value 93.783002
iter  40 value 84.979816
iter  50 value 84.266218
iter  60 value 82.974543
iter  70 value 82.459212
iter  80 value 81.217823
iter  90 value 80.777531
iter 100 value 80.521386
final  value 80.521386 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.732254 
iter  10 value 94.485771
iter  20 value 94.484145
iter  30 value 93.880306
iter  40 value 93.871686
final  value 93.871658 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.057850 
iter  10 value 94.485934
iter  20 value 94.437057
final  value 94.165221 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.438765 
iter  10 value 94.242251
iter  20 value 93.785378
final  value 93.784664 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.288255 
iter  10 value 94.485936
iter  20 value 94.484220
final  value 94.484218 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.877340 
final  value 94.485819 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.137966 
iter  10 value 94.488963
iter  20 value 94.484235
iter  30 value 92.949439
iter  40 value 85.460350
iter  50 value 85.456374
iter  60 value 85.372460
final  value 85.369375 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.566394 
iter  10 value 94.488632
iter  20 value 94.379665
iter  30 value 85.069652
iter  40 value 85.029054
iter  50 value 85.027173
iter  60 value 84.993873
iter  70 value 84.848190
iter  80 value 83.266905
iter  90 value 83.209436
iter 100 value 81.371315
final  value 81.371315 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.112981 
iter  10 value 94.488481
iter  20 value 94.157273
iter  30 value 91.819842
iter  40 value 91.807472
iter  50 value 91.536683
iter  60 value 91.534714
final  value 91.534698 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.948974 
iter  10 value 94.471592
iter  20 value 94.467253
iter  30 value 87.753309
iter  40 value 85.824023
final  value 85.818736 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.870821 
iter  10 value 94.488381
iter  20 value 94.295737
iter  30 value 85.947926
iter  40 value 84.377471
iter  50 value 84.336077
iter  60 value 84.151374
iter  70 value 84.115457
iter  80 value 84.114684
final  value 84.114594 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.709568 
iter  10 value 93.252200
iter  20 value 92.592540
iter  30 value 92.463622
iter  40 value 92.460922
iter  50 value 92.455546
iter  60 value 91.722933
iter  70 value 90.705254
iter  80 value 90.515506
iter  90 value 86.758881
iter 100 value 83.863919
final  value 83.863919 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.838201 
iter  10 value 94.440677
iter  20 value 83.531819
iter  30 value 83.484415
iter  40 value 83.416950
iter  50 value 83.415488
iter  60 value 82.890835
iter  70 value 82.869881
iter  80 value 82.861986
iter  90 value 81.708751
iter 100 value 81.468404
final  value 81.468404 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.052318 
iter  10 value 90.066876
iter  20 value 86.940125
iter  30 value 86.937778
iter  40 value 86.886540
iter  50 value 85.344959
iter  60 value 83.181682
iter  70 value 80.901321
iter  80 value 79.747314
iter  90 value 79.419900
iter 100 value 79.369145
final  value 79.369145 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.055520 
iter  10 value 93.497284
iter  20 value 93.301372
iter  30 value 86.735842
iter  40 value 86.309771
iter  50 value 86.307866
iter  60 value 86.307515
iter  70 value 86.306746
iter  80 value 86.234767
iter  90 value 85.533107
iter 100 value 85.280847
final  value 85.280847 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.103858 
iter  10 value 94.046687
iter  20 value 93.378743
iter  30 value 93.375845
iter  40 value 93.359909
iter  50 value 93.354278
iter  60 value 82.399283
iter  70 value 82.052285
iter  80 value 82.032548
iter  90 value 81.737645
iter 100 value 81.633446
final  value 81.633446 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.520897 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.391903 
iter  10 value 93.893485
iter  20 value 92.102594
iter  30 value 92.023308
iter  40 value 92.011665
iter  50 value 92.010251
final  value 92.010247 
converged
Fitting Repeat 3 

# weights:  103
initial  value 93.306050 
iter  10 value 84.765664
iter  20 value 84.100097
iter  30 value 82.863727
iter  40 value 82.850992
final  value 82.850989 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.624962 
iter  10 value 87.634464
iter  20 value 87.441561
iter  30 value 87.439484
final  value 87.439474 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.388930 
iter  10 value 94.052870
iter  10 value 94.052870
iter  20 value 93.328265
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.134251 
final  value 93.628453 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.936177 
final  value 93.328261 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.759325 
iter  10 value 93.328381
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.534963 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.218089 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.469050 
iter  10 value 87.143591
iter  20 value 83.441297
iter  30 value 83.430763
final  value 83.430740 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.493870 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.381412 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.721757 
iter  10 value 94.052911
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.875260 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.396775 
iter  10 value 93.977865
iter  20 value 86.019127
iter  30 value 83.634568
iter  40 value 83.523144
iter  50 value 82.745447
iter  60 value 82.673513
iter  70 value 82.298617
iter  80 value 81.354583
iter  90 value 81.110507
iter 100 value 80.884137
final  value 80.884137 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 111.800826 
iter  10 value 93.924071
iter  20 value 85.457654
iter  30 value 84.424743
iter  40 value 83.555672
iter  50 value 82.857386
iter  60 value 82.229879
iter  70 value 81.581895
iter  80 value 81.232202
iter  90 value 81.004380
iter 100 value 80.905754
final  value 80.905754 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.948684 
iter  10 value 93.736325
iter  20 value 84.333541
iter  30 value 83.518489
iter  40 value 82.502368
iter  50 value 82.467818
iter  60 value 82.429441
iter  70 value 82.423379
iter  80 value 81.288597
iter  90 value 81.182704
iter 100 value 80.904951
final  value 80.904951 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.553770 
iter  10 value 94.056481
iter  20 value 93.685060
iter  30 value 93.676219
iter  40 value 86.953032
iter  50 value 83.242396
iter  60 value 82.314686
iter  70 value 82.033907
iter  80 value 81.967520
final  value 81.962417 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.557204 
iter  10 value 93.858331
iter  20 value 89.761739
iter  30 value 88.524934
iter  40 value 85.603536
iter  50 value 83.976003
iter  60 value 83.427324
iter  70 value 81.302133
iter  80 value 80.981611
iter  90 value 80.867368
iter 100 value 80.766979
final  value 80.766979 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 98.477468 
iter  10 value 88.322102
iter  20 value 84.184985
iter  30 value 82.008265
iter  40 value 81.659933
iter  50 value 81.622784
iter  60 value 81.608499
iter  70 value 81.554149
iter  80 value 81.065477
iter  90 value 80.716763
iter 100 value 80.676815
final  value 80.676815 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.005368 
iter  10 value 91.026865
iter  20 value 84.706603
iter  30 value 83.999552
iter  40 value 82.027567
iter  50 value 81.424948
iter  60 value 81.163062
iter  70 value 80.979891
iter  80 value 80.419827
iter  90 value 80.137851
iter 100 value 79.766132
final  value 79.766132 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.587267 
iter  10 value 94.327422
iter  20 value 84.982843
iter  30 value 84.324680
iter  40 value 83.335200
iter  50 value 83.185040
iter  60 value 82.667835
iter  70 value 81.449353
iter  80 value 80.502603
iter  90 value 79.984523
iter 100 value 79.739940
final  value 79.739940 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.172274 
iter  10 value 93.644105
iter  20 value 86.002326
iter  30 value 82.919926
iter  40 value 82.078562
iter  50 value 80.888715
iter  60 value 80.261455
iter  70 value 79.525946
iter  80 value 79.381465
iter  90 value 79.252409
iter 100 value 79.139285
final  value 79.139285 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 127.000742 
iter  10 value 94.037071
iter  20 value 89.626465
iter  30 value 85.249320
iter  40 value 83.140111
iter  50 value 82.886183
iter  60 value 81.900705
iter  70 value 80.396738
iter  80 value 79.763220
iter  90 value 79.632040
iter 100 value 79.552338
final  value 79.552338 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.980192 
iter  10 value 94.804996
iter  20 value 86.238735
iter  30 value 83.066475
iter  40 value 82.024748
iter  50 value 81.624653
iter  60 value 80.938723
iter  70 value 80.291048
iter  80 value 80.139146
iter  90 value 79.983743
iter 100 value 79.924527
final  value 79.924527 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.356526 
iter  10 value 94.084854
iter  20 value 93.330782
iter  30 value 86.843418
iter  40 value 84.857917
iter  50 value 83.345073
iter  60 value 82.473619
iter  70 value 81.869297
iter  80 value 81.665604
iter  90 value 80.963550
iter 100 value 80.351579
final  value 80.351579 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.486776 
iter  10 value 95.412025
iter  20 value 93.490765
iter  30 value 84.464828
iter  40 value 82.779623
iter  50 value 82.162307
iter  60 value 81.810337
iter  70 value 81.061940
iter  80 value 80.621919
iter  90 value 80.217030
iter 100 value 79.960224
final  value 79.960224 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.882981 
iter  10 value 93.959058
iter  20 value 93.143247
iter  30 value 88.289084
iter  40 value 85.756176
iter  50 value 84.318351
iter  60 value 83.468256
iter  70 value 82.313759
iter  80 value 81.967235
iter  90 value 81.618842
iter 100 value 80.643833
final  value 80.643833 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.898944 
iter  10 value 94.275818
iter  20 value 85.764380
iter  30 value 83.118262
iter  40 value 83.003306
iter  50 value 82.547601
iter  60 value 81.623944
iter  70 value 81.379772
iter  80 value 81.159999
iter  90 value 80.851171
iter 100 value 80.579510
final  value 80.579510 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.783649 
iter  10 value 94.054715
iter  20 value 94.046572
iter  30 value 89.644636
iter  40 value 85.848049
iter  50 value 85.829469
iter  60 value 85.827490
iter  70 value 85.825647
iter  80 value 85.716464
iter  90 value 85.702093
iter 100 value 85.698755
final  value 85.698755 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 94.872911 
final  value 94.054343 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.578811 
iter  10 value 93.889551
iter  20 value 92.843106
iter  30 value 92.840292
iter  40 value 92.572024
iter  50 value 92.556917
final  value 92.556913 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.256452 
iter  10 value 94.054430
iter  20 value 94.052968
iter  30 value 93.980092
iter  40 value 92.273652
iter  50 value 92.267636
iter  60 value 92.266656
iter  70 value 92.266607
iter  80 value 92.266171
iter  90 value 92.247411
final  value 92.246351 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.107198 
final  value 94.054450 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.269199 
iter  10 value 93.333579
iter  20 value 93.327824
iter  30 value 83.219137
iter  40 value 83.070308
final  value 83.070045 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.458162 
iter  10 value 94.057278
iter  20 value 93.911793
iter  30 value 91.961219
iter  40 value 84.721162
iter  50 value 83.989958
iter  60 value 83.963666
iter  70 value 82.438428
iter  80 value 81.617224
iter  90 value 80.229150
iter 100 value 80.227456
final  value 80.227456 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.754357 
iter  10 value 94.057818
iter  20 value 94.030888
iter  30 value 84.351874
iter  40 value 84.327085
iter  50 value 84.030679
final  value 84.030654 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.453139 
iter  10 value 94.054889
iter  20 value 93.335947
final  value 93.328726 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.454432 
iter  10 value 93.333471
iter  20 value 93.284421
final  value 93.274241 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.107537 
iter  10 value 83.321000
iter  20 value 81.299012
iter  30 value 80.328652
iter  40 value 80.324944
iter  50 value 80.164001
iter  60 value 80.093675
iter  70 value 80.092046
iter  80 value 80.081582
iter  90 value 80.063062
iter 100 value 80.056036
final  value 80.056036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.789485 
iter  10 value 93.336746
iter  20 value 93.330366
iter  30 value 93.288643
iter  40 value 86.846902
iter  50 value 80.992151
iter  60 value 78.451783
iter  70 value 78.115420
iter  80 value 78.106858
iter  90 value 78.103315
final  value 78.103314 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.279595 
iter  10 value 94.035500
iter  20 value 84.594031
iter  30 value 82.734902
iter  40 value 82.261085
iter  50 value 82.259246
iter  60 value 82.255479
iter  70 value 81.863483
iter  80 value 81.086178
iter  90 value 81.085042
iter 100 value 80.196462
final  value 80.196462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.350607 
iter  10 value 94.060422
iter  20 value 93.762503
iter  30 value 89.116040
iter  40 value 87.183434
iter  50 value 87.095718
iter  60 value 85.742561
iter  70 value 85.671946
iter  80 value 85.030705
iter  90 value 84.435062
iter 100 value 84.015788
final  value 84.015788 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.823661 
iter  10 value 87.803063
iter  20 value 83.495752
iter  30 value 83.418490
iter  40 value 83.025091
iter  50 value 83.018851
iter  60 value 83.013362
iter  70 value 83.013051
iter  80 value 82.878980
iter  90 value 82.199361
iter 100 value 81.844192
final  value 81.844192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.070555 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.174022 
final  value 94.476471 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.267941 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.313473 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.250702 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.160185 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.657592 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.381638 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.284008 
final  value 94.428839 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.086262 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.871407 
iter  10 value 94.466824
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.373831 
final  value 94.129870 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.906542 
final  value 94.476471 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.276266 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.735307 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.690514 
iter  10 value 94.473164
iter  20 value 92.320265
iter  30 value 86.586339
iter  40 value 84.791821
iter  50 value 83.915728
iter  60 value 81.696585
iter  70 value 81.411030
iter  80 value 81.400810
final  value 81.400754 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.848804 
iter  10 value 94.488535
iter  20 value 93.923266
iter  30 value 90.155424
iter  40 value 86.228612
iter  50 value 85.649850
iter  60 value 85.283098
iter  70 value 85.144122
iter  80 value 84.871857
iter  90 value 78.566530
iter 100 value 78.354096
final  value 78.354096 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.077833 
iter  10 value 97.165562
iter  20 value 94.315911
iter  30 value 93.730261
iter  40 value 88.818635
iter  50 value 87.711178
iter  60 value 87.496789
iter  70 value 87.448897
iter  80 value 86.281099
iter  90 value 83.378134
iter 100 value 81.195804
final  value 81.195804 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.880825 
iter  10 value 94.463541
iter  20 value 90.811503
iter  30 value 84.308665
iter  40 value 82.751758
iter  50 value 82.177293
iter  60 value 81.634538
iter  70 value 81.533497
iter  80 value 81.412273
iter  90 value 81.400780
final  value 81.400753 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.403567 
iter  10 value 94.482015
iter  20 value 93.896452
iter  30 value 93.718192
iter  40 value 92.105511
iter  50 value 85.252783
iter  60 value 83.051571
iter  70 value 81.399569
iter  80 value 80.921703
iter  90 value 80.889750
iter  90 value 80.889750
iter  90 value 80.889750
final  value 80.889750 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.012455 
iter  10 value 94.928659
iter  20 value 93.127050
iter  30 value 87.069681
iter  40 value 80.431128
iter  50 value 79.776393
iter  60 value 79.547715
iter  70 value 78.866388
iter  80 value 78.586768
iter  90 value 78.340955
iter 100 value 78.300311
final  value 78.300311 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.133429 
iter  10 value 94.487511
iter  20 value 92.686650
iter  30 value 87.246982
iter  40 value 86.116453
iter  50 value 81.628600
iter  60 value 80.671663
iter  70 value 80.096908
iter  80 value 79.537660
iter  90 value 79.115051
iter 100 value 78.507478
final  value 78.507478 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.992796 
iter  10 value 94.490831
iter  20 value 93.134489
iter  30 value 87.413694
iter  40 value 80.621291
iter  50 value 80.193364
iter  60 value 78.906847
iter  70 value 78.465173
iter  80 value 77.925495
iter  90 value 77.595700
iter 100 value 77.468900
final  value 77.468900 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.346944 
iter  10 value 85.102077
iter  20 value 82.971208
iter  30 value 81.257136
iter  40 value 80.956587
iter  50 value 80.528018
iter  60 value 80.317003
iter  70 value 78.380070
iter  80 value 78.184026
iter  90 value 77.979310
iter 100 value 77.750106
final  value 77.750106 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.531603 
iter  10 value 94.594820
iter  20 value 90.900685
iter  30 value 90.571806
iter  40 value 89.904330
iter  50 value 85.156717
iter  60 value 82.581326
iter  70 value 79.841396
iter  80 value 78.307283
iter  90 value 77.657980
iter 100 value 77.156520
final  value 77.156520 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.662347 
iter  10 value 101.967396
iter  20 value 94.683751
iter  30 value 93.300051
iter  40 value 89.962249
iter  50 value 84.668266
iter  60 value 80.224830
iter  70 value 79.682423
iter  80 value 78.428121
iter  90 value 77.905093
iter 100 value 77.420951
final  value 77.420951 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.624225 
iter  10 value 94.307628
iter  20 value 87.193716
iter  30 value 85.422538
iter  40 value 82.180824
iter  50 value 78.612058
iter  60 value 78.215481
iter  70 value 78.070054
iter  80 value 78.012187
iter  90 value 77.725670
iter 100 value 77.663650
final  value 77.663650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.261234 
iter  10 value 94.456254
iter  20 value 84.230220
iter  30 value 83.157657
iter  40 value 81.371144
iter  50 value 79.778516
iter  60 value 78.795172
iter  70 value 78.602014
iter  80 value 78.409876
iter  90 value 78.256370
iter 100 value 78.017074
final  value 78.017074 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.915595 
iter  10 value 94.795385
iter  20 value 94.253358
iter  30 value 85.060580
iter  40 value 83.564690
iter  50 value 83.402822
iter  60 value 83.320713
iter  70 value 83.307013
iter  80 value 81.879473
iter  90 value 81.375054
iter 100 value 81.105006
final  value 81.105006 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.706702 
iter  10 value 94.543817
iter  20 value 92.566134
iter  30 value 84.954923
iter  40 value 80.591657
iter  50 value 78.820193
iter  60 value 77.978192
iter  70 value 77.677732
iter  80 value 77.243340
iter  90 value 77.009529
iter 100 value 76.718524
final  value 76.718524 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.582126 
iter  10 value 94.486042
iter  20 value 94.484283
iter  30 value 94.465580
iter  40 value 82.808131
iter  50 value 82.805467
iter  60 value 82.719063
iter  70 value 82.690213
final  value 82.690071 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.586356 
final  value 94.485856 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.094199 
iter  10 value 94.485903
iter  20 value 94.484290
final  value 94.484213 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.654969 
iter  10 value 94.430102
iter  20 value 94.429480
final  value 94.428270 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.207663 
iter  10 value 94.468469
iter  20 value 94.467672
iter  20 value 94.467671
iter  20 value 94.467671
final  value 94.467671 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.416305 
iter  10 value 87.357428
iter  20 value 86.948711
iter  30 value 86.947501
iter  40 value 86.881419
iter  50 value 85.215602
iter  60 value 85.211883
final  value 85.211725 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.723588 
iter  10 value 94.471122
iter  20 value 94.308795
final  value 93.560445 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.755084 
iter  10 value 94.471720
iter  20 value 94.468586
iter  30 value 94.468345
iter  40 value 94.161676
iter  50 value 82.790881
iter  60 value 82.742870
final  value 82.742614 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.453055 
iter  10 value 94.249079
iter  20 value 93.746219
iter  30 value 87.963858
iter  40 value 83.473676
iter  50 value 83.376180
iter  60 value 83.323279
iter  70 value 83.322075
iter  80 value 83.321901
iter  90 value 83.319038
final  value 83.318865 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.249343 
iter  10 value 94.489665
iter  20 value 94.464402
iter  30 value 85.417936
iter  40 value 85.280384
iter  50 value 85.278728
final  value 85.278712 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.760314 
iter  10 value 94.493072
iter  20 value 94.480218
iter  30 value 85.425027
iter  40 value 85.183059
iter  50 value 84.421978
iter  60 value 80.367395
iter  70 value 80.267911
iter  80 value 80.267558
iter  90 value 80.187912
iter 100 value 80.098608
final  value 80.098608 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.230945 
iter  10 value 94.546487
iter  20 value 94.437610
iter  30 value 94.435336
iter  40 value 82.737670
iter  50 value 81.845488
iter  60 value 81.840692
iter  70 value 81.825969
iter  80 value 81.823874
iter  90 value 81.814010
iter 100 value 80.041036
final  value 80.041036 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.466803 
iter  10 value 94.492336
iter  20 value 94.373517
iter  30 value 88.574022
iter  40 value 88.288194
iter  50 value 82.103182
iter  60 value 82.030236
iter  70 value 82.016151
final  value 82.016083 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.216827 
iter  10 value 94.488913
iter  20 value 86.561799
iter  30 value 86.036470
iter  40 value 85.677606
iter  50 value 85.401671
iter  60 value 84.809712
iter  70 value 84.264576
iter  80 value 84.201642
iter  90 value 84.200363
iter 100 value 84.199926
final  value 84.199926 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.511239 
iter  10 value 94.475061
iter  20 value 94.429747
iter  30 value 83.321117
iter  40 value 82.624296
iter  50 value 82.623706
iter  60 value 81.734350
iter  70 value 81.394084
iter  80 value 81.269979
iter  90 value 81.255653
iter  90 value 81.255652
iter  90 value 81.255652
final  value 81.255652 
converged
Fitting Repeat 1 

# weights:  305
initial  value 131.921827 
iter  10 value 117.916948
iter  20 value 117.884865
iter  30 value 112.086616
iter  40 value 106.240491
iter  50 value 103.180860
iter  60 value 102.920599
iter  70 value 102.690082
iter  80 value 101.957078
iter  90 value 101.233571
iter 100 value 101.107658
final  value 101.107658 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 170.406285 
iter  10 value 125.951727
iter  20 value 116.917354
iter  30 value 115.607995
iter  40 value 105.192231
iter  50 value 104.470036
iter  60 value 104.244754
iter  70 value 103.796620
iter  80 value 103.239556
iter  90 value 102.212433
iter 100 value 101.875323
final  value 101.875323 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 147.455086 
iter  10 value 117.906943
iter  20 value 112.912582
iter  30 value 108.049230
iter  40 value 107.403904
iter  50 value 107.187321
iter  60 value 106.346756
iter  70 value 105.884810
iter  80 value 104.594302
iter  90 value 104.328074
iter 100 value 104.299306
final  value 104.299306 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 132.088231 
iter  10 value 117.838686
iter  20 value 117.560426
iter  30 value 110.773624
iter  40 value 107.505964
iter  50 value 106.409847
iter  60 value 105.713578
iter  70 value 105.575930
iter  80 value 104.559158
iter  90 value 102.821049
iter 100 value 102.150956
final  value 102.150956 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.210143 
iter  10 value 117.233489
iter  20 value 108.932745
iter  30 value 106.293797
iter  40 value 105.530752
iter  50 value 104.207330
iter  60 value 101.813557
iter  70 value 100.976888
iter  80 value 100.602481
iter  90 value 100.425323
iter 100 value 100.379427
final  value 100.379427 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Jul 16 01:20:10 2024 
*********************************************** 
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 
  47.09    1.96   49.31