##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.13.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking 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       39.318  0.459  39.846
corr_plot     37.730  0.024  37.973
FSmethod      37.316  0.248  37.637
pred_ensembel 18.327  0.513  17.883
enrichfindP    0.530  0.035  19.302
getFASTA       0.127  0.012   5.762
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.13.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 95.740506 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.218674 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.862315 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.759671 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.559913 
iter  10 value 93.628462
final  value 93.628453 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.654230 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.896061 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.141417 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.307669 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.452553 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.412628 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.216814 
final  value 93.987879 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.479070 
iter  10 value 93.867391
iter  10 value 93.867391
iter  10 value 93.867391
final  value 93.867391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.472664 
final  value 93.628453 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.058024 
iter  10 value 93.543217
final  value 93.543210 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.460953 
iter  10 value 93.766203
iter  20 value 91.808413
iter  30 value 90.271491
iter  40 value 90.060194
iter  50 value 89.923897
iter  60 value 89.827808
iter  70 value 89.775746
final  value 89.774652 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.124430 
iter  10 value 94.054325
iter  20 value 93.542339
iter  30 value 89.646228
iter  40 value 84.614074
iter  50 value 83.869964
iter  60 value 82.629738
iter  70 value 80.905929
iter  80 value 80.823688
iter  90 value 80.485255
iter 100 value 80.196950
final  value 80.196950 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.866594 
iter  10 value 92.969452
iter  20 value 84.546941
iter  30 value 84.211386
iter  40 value 84.095354
iter  50 value 84.030079
iter  60 value 83.919973
iter  70 value 82.575705
iter  80 value 81.924645
iter  90 value 81.568088
iter 100 value 81.511105
final  value 81.511105 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.557677 
iter  10 value 94.015174
iter  20 value 93.919489
iter  30 value 93.919122
iter  40 value 93.750536
iter  50 value 87.849610
iter  60 value 85.565479
iter  70 value 84.784163
iter  80 value 83.121979
iter  90 value 82.016620
iter 100 value 81.850085
final  value 81.850085 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.225262 
iter  10 value 94.055922
iter  20 value 88.488216
iter  30 value 84.600303
iter  40 value 83.127697
iter  50 value 82.373275
iter  60 value 82.237430
iter  70 value 82.229886
iter  70 value 82.229886
iter  70 value 82.229886
final  value 82.229886 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.508815 
iter  10 value 93.859222
iter  20 value 91.664656
iter  30 value 91.044143
iter  40 value 81.744366
iter  50 value 79.538755
iter  60 value 79.095768
iter  70 value 78.986607
iter  80 value 78.570802
iter  90 value 78.385506
iter 100 value 78.176996
final  value 78.176996 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.627415 
iter  10 value 93.471081
iter  20 value 90.808320
iter  30 value 89.974404
iter  40 value 89.863093
iter  50 value 89.761012
iter  60 value 88.838041
iter  70 value 83.233989
iter  80 value 81.560977
iter  90 value 80.150258
iter 100 value 79.743830
final  value 79.743830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.288487 
iter  10 value 93.146407
iter  20 value 85.206019
iter  30 value 84.396724
iter  40 value 80.802511
iter  50 value 79.843939
iter  60 value 79.232059
iter  70 value 78.891979
iter  80 value 78.641878
iter  90 value 78.584081
iter 100 value 78.567031
final  value 78.567031 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.008188 
iter  10 value 94.251327
iter  20 value 91.932199
iter  30 value 84.380629
iter  40 value 84.091529
iter  50 value 83.418529
iter  60 value 82.808489
iter  70 value 82.764858
iter  80 value 82.078129
iter  90 value 80.761139
iter 100 value 80.453729
final  value 80.453729 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.528241 
iter  10 value 94.347643
iter  20 value 94.041264
iter  30 value 93.826611
iter  40 value 93.561224
iter  50 value 89.807234
iter  60 value 89.460599
iter  70 value 85.856130
iter  80 value 82.916551
iter  90 value 79.868530
iter 100 value 79.365793
final  value 79.365793 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.120708 
iter  10 value 95.056680
iter  20 value 88.586060
iter  30 value 83.529638
iter  40 value 81.344355
iter  50 value 79.559651
iter  60 value 79.283180
iter  70 value 78.910465
iter  80 value 78.725656
iter  90 value 78.689460
iter 100 value 78.543232
final  value 78.543232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.182737 
iter  10 value 93.942042
iter  20 value 86.252799
iter  30 value 85.159530
iter  40 value 83.635696
iter  50 value 81.423683
iter  60 value 78.698752
iter  70 value 78.213097
iter  80 value 78.081883
iter  90 value 77.960208
iter 100 value 77.847129
final  value 77.847129 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.231418 
iter  10 value 94.422443
iter  20 value 93.499574
iter  30 value 91.677195
iter  40 value 90.824251
iter  50 value 90.592496
iter  60 value 88.468171
iter  70 value 84.900138
iter  80 value 82.546082
iter  90 value 81.164831
iter 100 value 80.369489
final  value 80.369489 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.389755 
iter  10 value 91.661833
iter  20 value 87.521641
iter  30 value 86.131686
iter  40 value 85.794387
iter  50 value 85.309324
iter  60 value 80.958978
iter  70 value 80.409975
iter  80 value 80.034245
iter  90 value 79.335605
iter 100 value 78.896296
final  value 78.896296 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.146393 
iter  10 value 94.182976
iter  20 value 89.241225
iter  30 value 86.230313
iter  40 value 84.100823
iter  50 value 81.229454
iter  60 value 79.524863
iter  70 value 79.353492
iter  80 value 79.030745
iter  90 value 78.591362
iter 100 value 78.428161
final  value 78.428161 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.341279 
final  value 94.054660 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.117085 
iter  10 value 93.630072
iter  20 value 93.458306
iter  30 value 83.013989
iter  40 value 81.634685
final  value 81.556859 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.705521 
final  value 94.054555 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.911810 
iter  10 value 94.054658
iter  20 value 94.052976
iter  30 value 93.526474
final  value 92.540210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.231734 
final  value 93.899066 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.811588 
iter  10 value 93.524552
iter  20 value 93.521115
iter  30 value 87.125981
iter  40 value 86.161099
final  value 86.146353 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.585900 
iter  10 value 94.058210
iter  20 value 93.998764
iter  30 value 93.097406
iter  40 value 93.096764
iter  50 value 93.035941
iter  60 value 93.031365
final  value 93.031364 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.973566 
iter  10 value 93.427545
iter  20 value 91.770006
iter  30 value 91.766638
iter  40 value 87.511805
iter  50 value 82.905838
iter  60 value 82.851941
iter  70 value 82.371875
iter  80 value 81.189325
iter  90 value 81.181750
iter 100 value 81.170692
final  value 81.170692 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.627507 
iter  10 value 94.057389
iter  20 value 93.833192
iter  30 value 89.565534
iter  40 value 88.589368
iter  50 value 82.243743
iter  60 value 82.238118
iter  70 value 82.185664
iter  80 value 81.001181
iter  90 value 78.366725
iter 100 value 78.243948
final  value 78.243948 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.028840 
iter  10 value 93.872180
iter  20 value 93.832586
iter  30 value 93.055177
iter  40 value 91.599244
iter  50 value 91.272101
iter  60 value 91.251542
iter  70 value 91.251336
iter  70 value 91.251336
iter  70 value 91.251336
final  value 91.251336 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.689572 
iter  10 value 93.231314
iter  20 value 93.226994
iter  30 value 93.182278
iter  40 value 88.162857
iter  50 value 87.728252
iter  60 value 87.695981
iter  70 value 87.695554
iter  80 value 87.390208
iter  90 value 81.804393
iter 100 value 80.249777
final  value 80.249777 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.102280 
iter  10 value 89.026306
iter  20 value 86.062676
iter  30 value 86.046549
iter  40 value 86.044908
iter  50 value 86.040290
iter  60 value 83.595033
iter  70 value 83.125568
iter  80 value 80.522164
iter  90 value 78.889701
iter 100 value 77.949665
final  value 77.949665 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.392999 
iter  10 value 93.744689
iter  20 value 93.034600
iter  30 value 92.812497
iter  40 value 92.811955
iter  50 value 92.535564
iter  60 value 88.362776
iter  70 value 86.030108
iter  80 value 86.029167
iter  90 value 84.179782
iter 100 value 82.665407
final  value 82.665407 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.309018 
iter  10 value 93.832748
iter  20 value 93.825133
iter  30 value 93.739295
iter  40 value 91.934981
iter  50 value 90.112921
iter  60 value 84.565487
iter  70 value 83.397365
iter  80 value 83.392544
iter  90 value 83.391568
iter 100 value 83.384184
final  value 83.384184 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.933709 
iter  10 value 93.875888
iter  20 value 93.872158
iter  30 value 93.870368
iter  40 value 93.859702
iter  50 value 90.136778
iter  60 value 87.031812
iter  70 value 86.810065
iter  80 value 86.802464
final  value 86.802196 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.652921 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.887325 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.077389 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.356539 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.142108 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.310502 
final  value 93.991525 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.823946 
iter  10 value 93.499474
iter  20 value 91.988556
iter  30 value 91.987135
final  value 91.987133 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.744837 
iter  10 value 93.582419
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.986306 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.253219 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.948448 
iter  10 value 93.461620
final  value 93.458062 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.510665 
iter  10 value 85.988719
iter  20 value 85.024600
iter  30 value 85.010064
final  value 85.010019 
converged
Fitting Repeat 3 

# weights:  507
initial  value 93.836728 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.436448 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.873403 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.754501 
iter  10 value 93.576207
iter  20 value 88.829148
iter  30 value 86.671124
iter  40 value 86.336197
iter  50 value 85.974259
iter  60 value 85.455213
iter  70 value 85.207743
iter  80 value 85.181785
final  value 85.181770 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.328667 
iter  10 value 94.012333
iter  20 value 93.636751
iter  30 value 93.603065
iter  40 value 87.839506
iter  50 value 86.916540
iter  60 value 85.339745
iter  70 value 84.087020
iter  80 value 83.701855
iter  90 value 83.159558
iter 100 value 83.141217
final  value 83.141217 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.405738 
iter  10 value 94.055342
iter  20 value 93.840768
iter  30 value 86.955881
iter  40 value 86.460019
iter  50 value 85.926009
iter  60 value 85.283468
iter  70 value 84.885229
iter  80 value 83.625699
iter  90 value 83.164768
iter 100 value 83.108545
final  value 83.108545 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.195330 
iter  10 value 94.031396
iter  20 value 93.509265
iter  30 value 87.581768
iter  40 value 86.321896
iter  50 value 85.697136
iter  60 value 85.116885
iter  70 value 84.940026
iter  80 value 84.831970
iter  90 value 84.817781
final  value 84.817771 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.539562 
iter  10 value 94.057470
iter  20 value 92.733052
iter  30 value 91.954610
iter  40 value 87.489749
iter  50 value 86.580623
iter  60 value 86.307571
iter  70 value 85.827410
iter  80 value 85.417601
final  value 85.417568 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.789482 
iter  10 value 93.911714
iter  20 value 89.463147
iter  30 value 85.735685
iter  40 value 85.141333
iter  50 value 84.664523
iter  60 value 84.011314
iter  70 value 83.334628
iter  80 value 83.125299
iter  90 value 83.035599
iter 100 value 82.670063
final  value 82.670063 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.479254 
iter  10 value 94.095441
iter  20 value 94.008476
iter  30 value 93.000777
iter  40 value 89.904140
iter  50 value 87.700982
iter  60 value 84.602831
iter  70 value 82.976196
iter  80 value 82.202630
iter  90 value 81.969765
iter 100 value 81.649867
final  value 81.649867 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.923300 
iter  10 value 94.015298
iter  20 value 93.637940
iter  30 value 93.561184
iter  40 value 91.884335
iter  50 value 88.149981
iter  60 value 86.714240
iter  70 value 85.056715
iter  80 value 83.358950
iter  90 value 83.150875
iter 100 value 82.325211
final  value 82.325211 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.510777 
iter  10 value 94.209933
iter  20 value 94.025916
iter  30 value 93.634140
iter  40 value 87.774101
iter  50 value 86.652815
iter  60 value 85.671952
iter  70 value 82.764627
iter  80 value 81.899872
iter  90 value 81.687804
iter 100 value 81.599302
final  value 81.599302 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.124626 
iter  10 value 93.893343
iter  20 value 91.152326
iter  30 value 87.935199
iter  40 value 85.699752
iter  50 value 85.559998
iter  60 value 85.159414
iter  70 value 82.825369
iter  80 value 82.051882
iter  90 value 81.445616
iter 100 value 81.279536
final  value 81.279536 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.843209 
iter  10 value 93.617932
iter  20 value 92.633298
iter  30 value 86.271698
iter  40 value 85.992132
iter  50 value 84.987810
iter  60 value 83.703887
iter  70 value 83.526287
iter  80 value 83.503466
iter  90 value 83.308916
iter 100 value 82.774147
final  value 82.774147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.435460 
iter  10 value 95.355947
iter  20 value 86.671826
iter  30 value 84.952370
iter  40 value 83.604147
iter  50 value 83.126458
iter  60 value 83.002879
iter  70 value 82.987124
iter  80 value 82.960998
iter  90 value 82.762458
iter 100 value 82.516909
final  value 82.516909 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.850467 
iter  10 value 94.523629
iter  20 value 91.406451
iter  30 value 87.113943
iter  40 value 86.502388
iter  50 value 85.965739
iter  60 value 85.705318
iter  70 value 85.602552
iter  80 value 84.578203
iter  90 value 83.242932
iter 100 value 82.084131
final  value 82.084131 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.010144 
iter  10 value 94.548958
iter  20 value 88.361747
iter  30 value 86.044661
iter  40 value 85.470077
iter  50 value 84.454573
iter  60 value 82.710433
iter  70 value 81.984551
iter  80 value 81.933695
iter  90 value 81.928889
iter 100 value 81.898834
final  value 81.898834 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.609124 
iter  10 value 94.176354
iter  20 value 90.538825
iter  30 value 88.395658
iter  40 value 85.920948
iter  50 value 83.405749
iter  60 value 82.029151
iter  70 value 81.735082
iter  80 value 81.282125
iter  90 value 81.231782
iter 100 value 81.175091
final  value 81.175091 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.385877 
final  value 94.054400 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.076024 
final  value 94.054758 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.630066 
final  value 94.054362 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.029973 
final  value 94.054357 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.385495 
final  value 94.054356 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.976134 
iter  10 value 94.057773
final  value 94.052952 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.704484 
iter  10 value 94.013486
iter  20 value 94.009205
iter  30 value 90.893273
iter  40 value 84.621731
iter  50 value 84.274730
iter  60 value 84.167135
iter  70 value 84.061612
iter  80 value 83.538570
iter  90 value 83.294718
final  value 83.176395 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.650363 
iter  10 value 94.058286
iter  20 value 94.000924
iter  30 value 93.593792
final  value 93.593779 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.502313 
iter  10 value 94.057639
iter  20 value 94.055448
iter  30 value 94.048446
iter  40 value 91.543595
iter  50 value 86.741954
iter  60 value 86.663620
final  value 86.646767 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.021211 
iter  10 value 90.075330
iter  20 value 88.002772
iter  30 value 87.907033
iter  40 value 87.882420
iter  50 value 86.622468
iter  60 value 86.619226
iter  70 value 86.618539
iter  80 value 85.686238
iter  90 value 85.313120
iter 100 value 85.312813
final  value 85.312813 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.795368 
iter  10 value 86.046281
iter  20 value 83.710777
iter  30 value 83.681892
iter  40 value 83.645252
iter  50 value 83.580824
iter  60 value 83.531477
iter  70 value 83.529673
iter  80 value 83.528827
iter  90 value 83.528409
iter 100 value 83.527557
final  value 83.527557 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.344978 
iter  10 value 93.960579
iter  20 value 92.448682
iter  30 value 92.427914
iter  40 value 92.404844
iter  50 value 92.178711
iter  60 value 92.167347
iter  70 value 91.991530
iter  80 value 91.975519
iter  90 value 91.973188
iter 100 value 91.807788
final  value 91.807788 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.008267 
iter  10 value 93.590690
iter  20 value 93.477785
iter  30 value 93.447960
iter  40 value 93.444650
iter  50 value 93.444298
iter  60 value 93.442317
iter  70 value 93.434256
iter  80 value 83.579226
iter  90 value 81.495638
iter 100 value 80.639854
final  value 80.639854 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.395938 
iter  10 value 93.579530
iter  20 value 93.510466
iter  30 value 92.392891
iter  40 value 88.503582
iter  50 value 84.244517
iter  60 value 83.509992
iter  70 value 82.230643
iter  80 value 82.211169
iter  90 value 82.156555
iter 100 value 81.827914
final  value 81.827914 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.495806 
iter  10 value 94.060724
iter  20 value 94.052987
iter  30 value 93.619996
final  value 93.582831 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.939066 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.821805 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.324208 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.603520 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.349915 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.270602 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.807398 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 127.836314 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.264674 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.164986 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.086571 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.099731 
iter  10 value 93.838662
iter  20 value 87.559837
iter  30 value 86.947232
iter  40 value 85.433378
iter  50 value 84.956809
iter  60 value 84.956541
iter  60 value 84.956541
iter  60 value 84.956541
final  value 84.956541 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.710698 
final  value 94.203915 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.499278 
iter  10 value 86.003098
iter  20 value 85.952221
iter  30 value 85.948748
final  value 85.948718 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.492129 
iter  10 value 86.722643
iter  20 value 85.999121
iter  30 value 85.965710
final  value 85.965640 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.768278 
iter  10 value 93.815251
iter  20 value 92.244077
iter  30 value 90.615913
iter  40 value 86.207492
iter  50 value 85.903667
iter  60 value 85.478386
iter  70 value 84.653645
iter  80 value 84.256934
iter  90 value 84.171681
final  value 84.163219 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.399761 
iter  10 value 94.253813
iter  20 value 86.367331
iter  30 value 86.048306
iter  40 value 85.837921
iter  50 value 84.719130
iter  60 value 84.306750
iter  70 value 84.164186
final  value 84.163218 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.330407 
iter  10 value 94.101410
iter  20 value 90.047001
iter  30 value 88.047487
iter  40 value 85.908647
iter  50 value 84.265765
iter  60 value 82.603657
iter  70 value 81.938444
iter  80 value 81.760406
iter  90 value 81.597667
iter 100 value 81.589370
final  value 81.589370 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.592613 
iter  10 value 91.589204
iter  20 value 84.535064
iter  30 value 84.376616
iter  40 value 84.169281
iter  50 value 83.998611
iter  60 value 82.895273
iter  70 value 82.465176
iter  80 value 81.964375
iter  90 value 81.930903
iter 100 value 81.905040
final  value 81.905040 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.409260 
iter  10 value 94.489077
iter  20 value 91.185064
iter  30 value 87.050562
iter  40 value 84.679694
iter  50 value 84.436983
iter  60 value 84.411905
final  value 84.411878 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.248733 
iter  10 value 95.072213
iter  20 value 94.199862
iter  30 value 94.190180
iter  40 value 87.558370
iter  50 value 84.767099
iter  60 value 83.675438
iter  70 value 82.246457
iter  80 value 81.693546
iter  90 value 81.532855
iter 100 value 81.003490
final  value 81.003490 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.647597 
iter  10 value 94.169792
iter  20 value 89.289979
iter  30 value 84.909050
iter  40 value 83.743462
iter  50 value 82.523734
iter  60 value 82.319980
iter  70 value 81.884826
iter  80 value 81.085052
iter  90 value 80.682524
iter 100 value 80.624229
final  value 80.624229 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.596644 
iter  10 value 94.516531
iter  20 value 93.139358
iter  30 value 88.629365
iter  40 value 88.224360
iter  50 value 86.577441
iter  60 value 85.489402
iter  70 value 84.475041
iter  80 value 84.063187
iter  90 value 82.112779
iter 100 value 81.453552
final  value 81.453552 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.538216 
iter  10 value 94.259657
iter  20 value 86.824588
iter  30 value 86.201129
iter  40 value 85.322240
iter  50 value 84.339398
iter  60 value 84.103912
iter  70 value 83.398437
iter  80 value 82.233661
iter  90 value 81.208137
iter 100 value 80.872333
final  value 80.872333 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.699680 
iter  10 value 94.478850
iter  20 value 92.446405
iter  30 value 85.904433
iter  40 value 84.627100
iter  50 value 82.715994
iter  60 value 81.337872
iter  70 value 80.929642
iter  80 value 80.770807
iter  90 value 80.376019
iter 100 value 80.214282
final  value 80.214282 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.011376 
iter  10 value 95.226255
iter  20 value 93.948651
iter  30 value 88.541473
iter  40 value 85.291352
iter  50 value 83.781607
iter  60 value 83.184535
iter  70 value 81.776231
iter  80 value 80.997743
iter  90 value 80.652948
iter 100 value 80.480792
final  value 80.480792 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.506450 
iter  10 value 94.409066
iter  20 value 89.591310
iter  30 value 86.269459
iter  40 value 85.874547
iter  50 value 84.491801
iter  60 value 83.965536
iter  70 value 83.566939
iter  80 value 82.839769
iter  90 value 81.745592
iter 100 value 81.308922
final  value 81.308922 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.895036 
iter  10 value 94.887920
iter  20 value 85.417083
iter  30 value 84.293221
iter  40 value 82.699009
iter  50 value 81.600379
iter  60 value 80.742758
iter  70 value 80.603304
iter  80 value 80.291008
iter  90 value 80.093146
iter 100 value 79.994594
final  value 79.994594 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.915778 
iter  10 value 94.882690
iter  20 value 89.016079
iter  30 value 88.643042
iter  40 value 85.827899
iter  50 value 84.068764
iter  60 value 83.325666
iter  70 value 82.373547
iter  80 value 80.936220
iter  90 value 80.159437
iter 100 value 79.917472
final  value 79.917472 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.571137 
iter  10 value 94.508668
iter  20 value 92.797091
iter  30 value 86.466089
iter  40 value 84.951662
iter  50 value 84.034092
iter  60 value 82.448046
iter  70 value 80.882161
iter  80 value 79.973172
iter  90 value 79.769432
iter 100 value 79.645386
final  value 79.645386 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.283567 
final  value 94.486065 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.586894 
final  value 94.485849 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.509220 
final  value 94.485948 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.743672 
final  value 94.485712 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.261110 
final  value 94.485814 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.421846 
iter  10 value 86.959602
iter  20 value 86.888701
iter  30 value 86.888407
iter  40 value 86.880732
iter  50 value 85.981799
iter  60 value 85.966763
final  value 85.966460 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.383480 
iter  10 value 94.489253
iter  20 value 94.475072
iter  30 value 93.784532
final  value 93.784502 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.616837 
iter  10 value 94.279859
iter  20 value 90.720210
iter  30 value 85.247866
iter  40 value 85.240467
iter  50 value 85.107082
iter  60 value 85.025952
iter  70 value 85.024749
final  value 85.024085 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.898577 
iter  10 value 94.489141
final  value 94.484603 
converged
Fitting Repeat 5 

# weights:  305
initial  value 125.882484 
iter  10 value 94.489007
iter  20 value 94.353430
iter  30 value 90.952840
iter  40 value 86.876510
iter  50 value 86.869558
iter  60 value 86.868910
iter  70 value 85.423498
iter  80 value 85.381685
final  value 85.380224 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.918755 
iter  10 value 94.273446
iter  20 value 94.258543
iter  30 value 94.034934
iter  40 value 87.150710
iter  50 value 83.376767
iter  60 value 82.365471
iter  70 value 82.284864
final  value 82.284853 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.962805 
iter  10 value 94.283552
iter  20 value 94.260688
iter  30 value 93.110205
iter  40 value 84.559651
iter  50 value 84.461558
iter  60 value 84.459011
iter  70 value 84.172276
iter  80 value 84.115897
iter  90 value 84.115801
final  value 84.115703 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.449191 
iter  10 value 94.492118
iter  20 value 94.415113
iter  30 value 92.292125
iter  40 value 89.241515
iter  50 value 86.662527
iter  60 value 85.783632
iter  70 value 85.779609
iter  80 value 85.778632
iter  90 value 84.069716
iter 100 value 83.655981
final  value 83.655981 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.929371 
iter  10 value 94.492209
iter  20 value 94.350358
iter  30 value 92.421783
iter  40 value 92.421157
final  value 92.421154 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.563951 
iter  10 value 94.166677
iter  20 value 94.161564
iter  30 value 92.918701
iter  40 value 86.100136
iter  50 value 86.086288
iter  60 value 86.070513
iter  70 value 86.063476
iter  80 value 86.063033
iter  90 value 85.892961
iter 100 value 85.770644
final  value 85.770644 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.114414 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.747202 
iter  10 value 92.826627
iter  20 value 82.311707
iter  30 value 82.169130
final  value 82.168831 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.468475 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.026371 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.669253 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.740887 
iter  10 value 94.396689
iter  20 value 94.395064
final  value 94.395062 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.684616 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.190937 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.333418 
final  value 93.930685 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.884312 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.988740 
iter  10 value 92.214675
iter  20 value 84.299640
iter  30 value 84.289259
final  value 84.289242 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.578931 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.916169 
final  value 94.057229 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.269260 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.444039 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.233973 
iter  10 value 90.380175
iter  20 value 82.968429
iter  30 value 82.867961
iter  40 value 82.751899
iter  50 value 82.703328
final  value 82.702611 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.297411 
iter  10 value 95.962325
iter  20 value 92.156961
iter  30 value 83.722308
iter  40 value 83.088229
iter  50 value 83.041246
final  value 83.041115 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.299616 
iter  10 value 94.092427
iter  20 value 89.796707
iter  30 value 83.336939
iter  40 value 83.158278
iter  50 value 83.147922
iter  60 value 82.944468
iter  70 value 82.769663
iter  80 value 82.741607
iter  90 value 82.695587
final  value 82.693106 
converged
Fitting Repeat 4 

# weights:  103
initial  value 118.314138 
iter  10 value 94.232384
iter  20 value 86.308344
iter  30 value 85.429635
iter  40 value 83.302556
iter  50 value 83.057716
iter  60 value 83.041303
final  value 83.041300 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.787844 
iter  10 value 94.183316
iter  20 value 93.023328
iter  30 value 85.595541
iter  40 value 83.242885
iter  50 value 82.827396
iter  60 value 82.703036
final  value 82.702612 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.216463 
iter  10 value 94.455550
iter  20 value 89.752124
iter  30 value 86.227102
iter  40 value 84.821333
iter  50 value 80.780091
iter  60 value 80.108645
iter  70 value 79.831828
iter  80 value 79.676996
iter  90 value 79.622497
iter 100 value 79.412059
final  value 79.412059 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.192694 
iter  10 value 94.588529
iter  20 value 93.865802
iter  30 value 85.280665
iter  40 value 83.103137
iter  50 value 82.822980
iter  60 value 81.039113
iter  70 value 80.866240
iter  80 value 80.800153
iter  90 value 80.653579
iter 100 value 80.492984
final  value 80.492984 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.893101 
iter  10 value 94.851627
iter  20 value 87.660045
iter  30 value 84.771089
iter  40 value 84.694440
iter  50 value 83.185687
iter  60 value 82.723754
iter  70 value 82.126190
iter  80 value 80.403207
iter  90 value 79.685721
iter 100 value 79.436319
final  value 79.436319 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.941169 
iter  10 value 94.442565
iter  20 value 93.776107
iter  30 value 90.068260
iter  40 value 83.729249
iter  50 value 83.039828
iter  60 value 82.721613
iter  70 value 82.377415
iter  80 value 82.288929
iter  90 value 81.432321
iter 100 value 80.326766
final  value 80.326766 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.579526 
iter  10 value 94.595691
iter  20 value 89.228161
iter  30 value 84.130610
iter  40 value 83.060304
iter  50 value 82.292586
iter  60 value 80.821429
iter  70 value 80.358066
iter  80 value 79.759729
iter  90 value 79.419800
iter 100 value 79.305067
final  value 79.305067 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.528667 
iter  10 value 95.149311
iter  20 value 94.270453
iter  30 value 85.452214
iter  40 value 84.543905
iter  50 value 81.848350
iter  60 value 80.473972
iter  70 value 80.049237
iter  80 value 79.617475
iter  90 value 79.411171
iter 100 value 79.077848
final  value 79.077848 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.195616 
iter  10 value 94.403356
iter  20 value 85.407890
iter  30 value 84.845283
iter  40 value 82.751762
iter  50 value 82.417126
iter  60 value 82.296201
iter  70 value 82.040774
iter  80 value 79.997961
iter  90 value 79.047606
iter 100 value 78.911091
final  value 78.911091 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.034487 
iter  10 value 94.320564
iter  20 value 90.994247
iter  30 value 86.847569
iter  40 value 83.914638
iter  50 value 81.880349
iter  60 value 81.408489
iter  70 value 81.223998
iter  80 value 80.983910
iter  90 value 80.451292
iter 100 value 79.760714
final  value 79.760714 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.563228 
iter  10 value 94.438958
iter  20 value 88.611312
iter  30 value 86.905992
iter  40 value 86.607116
iter  50 value 84.418468
iter  60 value 81.330561
iter  70 value 79.677103
iter  80 value 79.277632
iter  90 value 79.123538
iter 100 value 78.901491
final  value 78.901491 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.592941 
iter  10 value 94.844120
iter  20 value 88.542195
iter  30 value 84.982052
iter  40 value 83.891993
iter  50 value 82.334563
iter  60 value 81.371273
iter  70 value 80.382061
iter  80 value 80.021519
iter  90 value 79.627009
iter 100 value 79.587184
final  value 79.587184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.923053 
final  value 94.485797 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.593701 
iter  10 value 94.487106
iter  20 value 94.484262
final  value 94.484225 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.254452 
iter  10 value 84.735216
iter  20 value 84.304809
iter  30 value 84.300448
iter  40 value 84.012640
iter  50 value 84.008393
iter  60 value 84.004990
final  value 84.004977 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.162085 
iter  10 value 94.485899
iter  20 value 94.419117
iter  30 value 84.297642
iter  40 value 84.292867
iter  50 value 84.291639
iter  60 value 84.006003
final  value 84.006002 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.494218 
final  value 94.486036 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.341066 
iter  10 value 94.489185
iter  20 value 94.468750
iter  30 value 94.058397
iter  40 value 93.676198
iter  50 value 84.093029
iter  60 value 84.084308
iter  70 value 84.083737
iter  80 value 83.670467
iter  90 value 82.111739
iter 100 value 81.268002
final  value 81.268002 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.141339 
iter  10 value 93.980626
iter  20 value 93.747311
iter  30 value 93.670059
iter  40 value 93.669484
iter  50 value 83.821955
iter  60 value 82.779202
iter  70 value 81.556660
iter  80 value 81.159179
final  value 81.156390 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.069159 
iter  10 value 94.488818
iter  20 value 94.227801
iter  30 value 85.690687
iter  40 value 82.831572
iter  50 value 81.941258
iter  60 value 80.956148
iter  70 value 80.926977
iter  80 value 80.637469
iter  90 value 79.501417
iter 100 value 79.346367
final  value 79.346367 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.632906 
iter  10 value 94.488075
iter  20 value 94.247892
iter  30 value 84.945053
iter  40 value 84.728244
iter  50 value 82.315161
iter  60 value 82.254224
final  value 82.246623 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.765041 
iter  10 value 94.448059
iter  20 value 89.008318
final  value 82.314334 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.306896 
iter  10 value 94.504274
iter  20 value 94.479943
iter  30 value 93.765042
iter  40 value 93.754075
iter  50 value 93.461483
iter  60 value 86.259635
iter  70 value 81.840633
iter  80 value 81.512340
iter  90 value 81.443400
iter 100 value 80.650599
final  value 80.650599 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.648624 
iter  10 value 93.213266
iter  20 value 84.652688
iter  30 value 83.891045
iter  40 value 81.994906
iter  50 value 81.924521
iter  60 value 81.785358
iter  70 value 81.779125
iter  80 value 81.774733
iter  90 value 81.603811
iter 100 value 80.546987
final  value 80.546987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.889130 
iter  10 value 94.034803
iter  20 value 94.002717
iter  30 value 84.274107
iter  40 value 83.916965
iter  50 value 83.850154
final  value 83.849730 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.087010 
iter  10 value 94.491804
iter  20 value 92.122361
iter  30 value 82.159142
iter  40 value 81.774334
iter  40 value 81.774334
iter  40 value 81.774334
final  value 81.774334 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.341227 
iter  10 value 94.035668
iter  20 value 94.028083
final  value 94.027848 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.089305 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.053323 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.085125 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.261816 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.402292 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.291490 
final  value 93.637380 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.645487 
final  value 94.444193 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.667654 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.994761 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.605741 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.785872 
iter  10 value 94.466844
final  value 94.466822 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.017068 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.617505 
final  value 94.323809 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.789837 
final  value 94.427726 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.514841 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.643911 
iter  10 value 94.519442
iter  20 value 94.462670
iter  30 value 89.239437
iter  40 value 86.855121
iter  50 value 85.648804
iter  60 value 85.218880
iter  70 value 85.016218
iter  80 value 84.826442
iter  90 value 82.683947
iter 100 value 82.194405
final  value 82.194405 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.876566 
iter  10 value 94.417334
iter  20 value 93.619249
iter  30 value 93.196609
iter  40 value 86.065310
iter  50 value 85.617943
iter  60 value 84.815952
iter  70 value 84.612392
iter  80 value 84.359654
iter  90 value 83.407100
iter 100 value 82.375929
final  value 82.375929 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.692101 
iter  10 value 94.455126
iter  20 value 92.157808
iter  30 value 90.939973
iter  40 value 85.719700
iter  50 value 84.020270
iter  60 value 83.099548
iter  70 value 82.618491
iter  80 value 82.298157
iter  90 value 82.171264
final  value 82.171247 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.895055 
iter  10 value 94.528131
iter  20 value 94.489476
iter  30 value 94.404226
iter  40 value 93.927083
iter  50 value 93.388297
iter  60 value 93.313188
iter  70 value 90.347534
iter  80 value 86.569106
iter  90 value 85.422387
iter 100 value 85.020131
final  value 85.020131 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.178153 
iter  10 value 94.464206
iter  20 value 93.456277
iter  30 value 91.425267
iter  40 value 91.350443
iter  50 value 91.344945
iter  60 value 91.344826
iter  70 value 91.324632
iter  80 value 86.559595
iter  90 value 84.857293
iter 100 value 84.553907
final  value 84.553907 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.775913 
iter  10 value 94.712765
iter  20 value 94.286945
iter  30 value 91.740648
iter  40 value 90.082253
iter  50 value 89.627785
iter  60 value 89.246361
iter  70 value 86.723558
iter  80 value 85.608173
iter  90 value 82.971396
iter 100 value 81.981255
final  value 81.981255 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.049786 
iter  10 value 96.212113
iter  20 value 94.497765
iter  30 value 89.735025
iter  40 value 86.635297
iter  50 value 83.897995
iter  60 value 81.966947
iter  70 value 81.691496
iter  80 value 81.662858
iter  90 value 81.334503
iter 100 value 81.177432
final  value 81.177432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.157074 
iter  10 value 94.664289
iter  20 value 87.979684
iter  30 value 85.559035
iter  40 value 85.049641
iter  50 value 85.001462
iter  60 value 84.964878
iter  70 value 84.874520
iter  80 value 84.527136
iter  90 value 83.391149
iter 100 value 83.183144
final  value 83.183144 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.212313 
iter  10 value 94.849835
iter  20 value 94.425751
iter  30 value 86.078843
iter  40 value 85.766704
iter  50 value 83.426998
iter  60 value 81.589389
iter  70 value 81.220774
iter  80 value 81.073010
iter  90 value 80.952527
iter 100 value 80.636921
final  value 80.636921 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.631867 
iter  10 value 94.609987
iter  20 value 94.100841
iter  30 value 93.301176
iter  40 value 86.219539
iter  50 value 85.083103
iter  60 value 83.487489
iter  70 value 82.480372
iter  80 value 81.791559
iter  90 value 81.215116
iter 100 value 80.981907
final  value 80.981907 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.487380 
iter  10 value 94.390046
iter  20 value 86.967687
iter  30 value 85.760668
iter  40 value 85.587312
iter  50 value 85.232956
iter  60 value 84.944523
iter  70 value 84.696476
iter  80 value 83.583927
iter  90 value 82.467735
iter 100 value 81.772309
final  value 81.772309 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.946532 
iter  10 value 94.599399
iter  20 value 93.629735
iter  30 value 87.149715
iter  40 value 84.332573
iter  50 value 83.259047
iter  60 value 82.509119
iter  70 value 82.217608
iter  80 value 82.042965
iter  90 value 81.957555
iter 100 value 81.932277
final  value 81.932277 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.984058 
iter  10 value 96.112893
iter  20 value 91.108875
iter  30 value 88.210679
iter  40 value 82.937920
iter  50 value 81.749016
iter  60 value 81.052139
iter  70 value 80.641805
iter  80 value 80.499100
iter  90 value 80.451678
iter 100 value 80.351126
final  value 80.351126 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.757324 
iter  10 value 99.135910
iter  20 value 91.311104
iter  30 value 86.113474
iter  40 value 84.616692
iter  50 value 82.605573
iter  60 value 82.158033
iter  70 value 81.667549
iter  80 value 80.847714
iter  90 value 80.672214
iter 100 value 80.560067
final  value 80.560067 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.373131 
iter  10 value 104.069477
iter  20 value 97.486063
iter  30 value 92.142517
iter  40 value 86.415841
iter  50 value 84.201105
iter  60 value 84.018394
iter  70 value 83.729403
iter  80 value 82.265871
iter  90 value 81.679944
iter 100 value 81.040560
final  value 81.040560 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.508495 
final  value 94.485728 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.218112 
final  value 94.486079 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.504624 
final  value 94.468457 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.208633 
final  value 94.485722 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.903223 
final  value 94.487093 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.027224 
iter  10 value 94.488684
iter  20 value 93.947587
final  value 93.637749 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.443728 
iter  10 value 94.471638
iter  20 value 93.940120
iter  30 value 90.778619
iter  40 value 90.778323
iter  50 value 89.782105
iter  60 value 85.194505
iter  70 value 85.192645
final  value 85.192634 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.369117 
iter  10 value 93.879733
iter  20 value 93.872780
iter  30 value 92.905789
final  value 92.736354 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.755097 
iter  10 value 94.488622
iter  20 value 94.483343
iter  30 value 93.583506
final  value 93.573255 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.782828 
iter  10 value 94.453300
iter  20 value 94.243915
iter  30 value 89.679811
iter  40 value 89.320291
iter  50 value 87.049079
iter  60 value 82.731839
iter  70 value 82.509197
iter  80 value 82.499109
iter  90 value 82.498064
iter 100 value 82.495983
final  value 82.495983 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.278903 
iter  10 value 94.492222
iter  20 value 94.445440
iter  30 value 89.268967
iter  40 value 88.942872
iter  50 value 88.501878
iter  60 value 81.791575
iter  70 value 81.510464
iter  80 value 81.504426
final  value 81.504207 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.878130 
iter  10 value 94.475111
iter  20 value 94.472112
iter  30 value 94.471802
iter  40 value 94.020863
iter  50 value 90.981290
iter  60 value 86.375283
iter  70 value 85.909593
iter  80 value 85.550245
iter  90 value 84.631398
iter 100 value 84.277791
final  value 84.277791 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.789425 
iter  10 value 94.476327
iter  20 value 94.469125
iter  30 value 90.526495
final  value 90.474546 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.372235 
iter  10 value 93.880485
iter  20 value 93.751740
iter  30 value 93.574100
iter  40 value 93.572984
iter  50 value 93.572497
iter  50 value 93.572497
final  value 93.572497 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.641710 
iter  10 value 94.475454
iter  20 value 94.430232
iter  30 value 93.877601
iter  40 value 93.741720
final  value 93.573039 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.730859 
iter  10 value 117.766968
iter  20 value 117.604604
iter  30 value 107.400842
iter  40 value 106.856329
iter  50 value 106.832937
final  value 106.832920 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.836371 
iter  10 value 117.688065
iter  20 value 117.545373
iter  30 value 117.542831
iter  40 value 117.501849
iter  50 value 116.670422
iter  60 value 110.887660
iter  70 value 106.857813
iter  80 value 106.663483
iter  90 value 106.629656
final  value 106.629560 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.542444 
iter  10 value 117.766857
iter  20 value 117.760456
iter  30 value 117.599307
iter  40 value 117.595608
final  value 117.595576 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.756820 
iter  10 value 115.263297
iter  20 value 109.041872
iter  30 value 106.979681
iter  40 value 106.832379
iter  50 value 106.829947
iter  60 value 106.402399
iter  70 value 106.077435
iter  80 value 106.070706
final  value 106.070620 
converged
Fitting Repeat 5 

# weights:  507
initial  value 131.812196 
iter  10 value 117.507580
iter  20 value 117.500350
iter  30 value 117.499768
iter  40 value 113.354119
iter  50 value 108.396441
iter  60 value 104.704573
iter  70 value 103.907558
iter  80 value 103.901701
iter  90 value 103.409389
iter 100 value 102.604225
final  value 102.604225 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Mon Mar 17 07:28:59 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 
 53.521   1.333 143.123