##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-06 04:43:55 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       36.228  0.454  36.883
FSmethod      34.086  0.469  34.558
corr_plot     34.085  0.384  34.511
pred_ensembel 12.870  0.084  11.632
enrichfindP    0.547  0.038  15.197
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** 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 version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 97.118999 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.397092 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.728681 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.062894 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.605010 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.013429 
iter  10 value 94.043953
iter  20 value 93.819421
final  value 93.818716 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.166124 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.532522 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.660383 
final  value 93.991525 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.200827 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.914913 
iter  10 value 92.345745
final  value 92.244445 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.920080 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.085566 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.037860 
iter  10 value 93.969045
final  value 93.969040 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.928566 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.310414 
iter  10 value 94.064140
iter  20 value 93.226060
iter  30 value 89.264249
iter  40 value 87.683148
iter  50 value 86.411181
iter  60 value 85.874393
iter  70 value 85.758977
iter  80 value 85.741965
final  value 85.738928 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.756160 
iter  10 value 93.706873
iter  20 value 90.038457
iter  30 value 87.674205
iter  40 value 86.520851
iter  50 value 85.870645
iter  60 value 84.339832
iter  70 value 84.265634
iter  80 value 84.220583
iter  90 value 84.054980
iter 100 value 84.023029
final  value 84.023029 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.799270 
iter  10 value 86.711413
iter  20 value 84.779909
iter  30 value 83.405875
iter  40 value 81.872265
iter  50 value 81.492811
iter  60 value 81.358180
iter  70 value 81.199193
final  value 81.191265 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.687889 
iter  10 value 94.056825
iter  20 value 93.825386
iter  30 value 87.117300
iter  40 value 85.187640
iter  50 value 84.820815
iter  60 value 84.741124
iter  70 value 84.459991
iter  80 value 83.915283
iter  90 value 83.811544
iter 100 value 83.770947
final  value 83.770947 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.357155 
iter  10 value 95.467088
iter  20 value 94.049232
iter  30 value 90.398624
iter  40 value 88.449574
iter  50 value 85.741204
iter  60 value 83.136808
iter  70 value 82.055724
iter  80 value 81.872132
iter  90 value 81.541612
iter 100 value 81.438716
final  value 81.438716 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.814249 
iter  10 value 94.114076
iter  20 value 93.380086
iter  30 value 87.349017
iter  40 value 86.415580
iter  50 value 83.883936
iter  60 value 80.954520
iter  70 value 80.227766
iter  80 value 79.970478
iter  90 value 79.910538
iter 100 value 79.892037
final  value 79.892037 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.061815 
iter  10 value 94.193259
iter  20 value 91.657431
iter  30 value 88.773362
iter  40 value 84.800605
iter  50 value 84.077607
iter  60 value 81.340153
iter  70 value 80.508505
iter  80 value 80.105061
iter  90 value 80.029603
iter 100 value 79.967256
final  value 79.967256 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.215236 
iter  10 value 95.310179
iter  20 value 88.838339
iter  30 value 87.632468
iter  40 value 85.256167
iter  50 value 83.636562
iter  60 value 82.691587
iter  70 value 81.630475
iter  80 value 81.283761
iter  90 value 81.064139
iter 100 value 80.982387
final  value 80.982387 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.253587 
iter  10 value 94.049444
iter  20 value 93.769145
iter  30 value 93.551218
iter  40 value 87.329788
iter  50 value 84.048500
iter  60 value 82.759936
iter  70 value 81.367254
iter  80 value 80.934543
iter  90 value 80.777002
iter 100 value 80.627475
final  value 80.627475 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.388843 
iter  10 value 94.136100
iter  20 value 94.060190
iter  30 value 93.885181
iter  40 value 88.460148
iter  50 value 84.373439
iter  60 value 83.559828
iter  70 value 83.241944
iter  80 value 82.859792
iter  90 value 81.567550
iter 100 value 80.981471
final  value 80.981471 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.245057 
iter  10 value 94.791192
iter  20 value 88.348033
iter  30 value 86.612209
iter  40 value 84.684522
iter  50 value 83.138126
iter  60 value 81.339024
iter  70 value 80.990881
iter  80 value 80.723791
iter  90 value 80.631941
iter 100 value 80.612088
final  value 80.612088 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.816266 
iter  10 value 94.071610
iter  20 value 89.579680
iter  30 value 85.307412
iter  40 value 83.980284
iter  50 value 82.508016
iter  60 value 82.002513
iter  70 value 81.207643
iter  80 value 80.462989
iter  90 value 80.206082
iter 100 value 80.008365
final  value 80.008365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.280541 
iter  10 value 94.301330
iter  20 value 92.762928
iter  30 value 89.914208
iter  40 value 82.325836
iter  50 value 81.134570
iter  60 value 80.914919
iter  70 value 80.789285
iter  80 value 80.519959
iter  90 value 80.467578
iter 100 value 80.446785
final  value 80.446785 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.457052 
iter  10 value 93.941992
iter  20 value 93.798160
iter  30 value 88.698965
iter  40 value 85.905894
iter  50 value 82.430625
iter  60 value 81.521084
iter  70 value 81.350518
iter  80 value 80.828686
iter  90 value 80.536411
iter 100 value 80.285774
final  value 80.285774 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.014032 
iter  10 value 94.013542
iter  20 value 86.358096
iter  30 value 86.051429
iter  40 value 85.839423
iter  50 value 84.742672
iter  60 value 83.886087
iter  70 value 83.777871
iter  80 value 83.483155
iter  90 value 83.390541
iter 100 value 83.341144
final  value 83.341144 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.214708 
final  value 94.054581 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.106981 
final  value 94.054591 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.105611 
final  value 94.054560 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.083168 
iter  10 value 94.054411
iter  20 value 94.052969
iter  30 value 94.030806
iter  40 value 93.370798
iter  50 value 91.641480
iter  60 value 91.558621
iter  70 value 91.557071
final  value 91.557058 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.680500 
final  value 93.970378 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.474656 
iter  10 value 93.974134
iter  20 value 93.855386
iter  30 value 93.805406
iter  40 value 93.805278
final  value 93.805231 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.797521 
iter  10 value 94.058153
iter  20 value 94.026204
iter  30 value 87.243975
iter  40 value 86.993904
final  value 86.993834 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.288774 
iter  10 value 94.057387
iter  20 value 89.726199
iter  30 value 86.999907
iter  40 value 86.946226
iter  50 value 86.866122
iter  60 value 86.864958
final  value 86.864821 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.599382 
iter  10 value 92.448071
iter  20 value 86.439366
final  value 86.438274 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.002414 
iter  10 value 94.038270
iter  20 value 94.033344
final  value 94.033313 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.004459 
iter  10 value 94.064145
iter  20 value 94.056544
iter  30 value 93.450226
iter  40 value 86.243641
iter  50 value 85.723754
iter  60 value 85.027904
iter  70 value 84.356398
iter  80 value 82.462766
iter  90 value 81.797322
iter 100 value 81.539934
final  value 81.539934 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.804787 
iter  10 value 93.819680
iter  20 value 93.813974
iter  30 value 93.734561
iter  40 value 93.733971
final  value 93.733948 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.772803 
iter  10 value 94.041962
iter  20 value 94.033992
iter  30 value 92.356529
iter  40 value 85.200020
iter  50 value 81.883536
iter  60 value 81.766163
iter  70 value 81.764156
iter  80 value 81.762743
iter  90 value 81.758717
iter 100 value 81.591599
final  value 81.591599 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.667130 
iter  10 value 94.062770
iter  20 value 94.010037
iter  30 value 85.250870
iter  40 value 84.925373
iter  50 value 84.910256
iter  60 value 84.054090
iter  70 value 83.953356
iter  80 value 83.942642
iter  90 value 83.906667
iter 100 value 83.903903
final  value 83.903903 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.621524 
iter  10 value 94.041194
iter  20 value 93.549940
iter  30 value 86.884287
iter  40 value 86.011419
iter  50 value 85.040428
iter  60 value 85.021790
iter  70 value 85.000085
iter  80 value 84.971730
final  value 84.971612 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.447024 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.836191 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.061398 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.051572 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.594311 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.171025 
iter  10 value 93.394941
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.004102 
iter  10 value 93.659480
iter  10 value 93.659479
iter  10 value 93.659479
final  value 93.659479 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.922448 
iter  10 value 90.179851
iter  20 value 89.176650
final  value 89.175000 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.626656 
iter  10 value 93.394932
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.903563 
iter  10 value 93.394928
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.019220 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.491175 
iter  10 value 85.294664
iter  20 value 84.773626
final  value 84.773447 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.603587 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.228517 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.499252 
iter  10 value 94.443189
final  value 94.443182 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.736471 
iter  10 value 93.604527
iter  20 value 93.375663
iter  30 value 87.878848
iter  40 value 87.006017
iter  50 value 81.761415
iter  60 value 80.371493
iter  70 value 80.223255
final  value 80.223253 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.704674 
iter  10 value 94.488551
iter  20 value 91.361639
iter  30 value 85.695786
iter  40 value 83.929918
iter  50 value 82.978059
iter  60 value 82.908409
iter  70 value 82.907858
iter  70 value 82.907858
iter  70 value 82.907858
final  value 82.907858 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.877008 
iter  10 value 94.449133
iter  20 value 91.963955
iter  30 value 86.282815
iter  40 value 85.134833
iter  50 value 83.332263
iter  60 value 82.910755
iter  70 value 82.910084
final  value 82.907858 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.369815 
iter  10 value 93.939013
iter  20 value 93.743244
iter  30 value 87.283907
iter  40 value 83.677016
iter  50 value 83.269982
iter  60 value 83.069262
final  value 83.064945 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.819663 
iter  10 value 94.586065
iter  20 value 94.467514
iter  30 value 93.905600
iter  40 value 84.782626
iter  50 value 84.207935
iter  60 value 84.094624
iter  70 value 83.809924
iter  80 value 83.135507
iter  90 value 81.122192
iter 100 value 81.102978
final  value 81.102978 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.170009 
iter  10 value 94.348533
iter  20 value 93.789790
iter  30 value 90.957348
iter  40 value 89.938895
iter  50 value 89.629324
iter  60 value 86.785410
iter  70 value 83.089291
iter  80 value 82.289111
iter  90 value 82.228444
iter 100 value 81.992402
final  value 81.992402 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.353118 
iter  10 value 96.250931
iter  20 value 93.506162
iter  30 value 91.498686
iter  40 value 87.382969
iter  50 value 86.762121
iter  60 value 83.203924
iter  70 value 80.477108
iter  80 value 80.335748
iter  90 value 80.299884
iter 100 value 79.595896
final  value 79.595896 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.359294 
iter  10 value 94.468080
iter  20 value 93.859206
iter  30 value 93.597753
iter  40 value 89.783049
iter  50 value 87.176731
iter  60 value 86.837867
iter  70 value 85.994667
iter  80 value 81.396858
iter  90 value 79.966846
iter 100 value 79.410287
final  value 79.410287 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.038195 
iter  10 value 94.534178
iter  20 value 93.573352
iter  30 value 91.589100
iter  40 value 86.385276
iter  50 value 84.185743
iter  60 value 83.459598
iter  70 value 82.859091
iter  80 value 80.739458
iter  90 value 79.236016
iter 100 value 78.859947
final  value 78.859947 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.767671 
iter  10 value 94.497177
iter  20 value 91.702499
iter  30 value 91.462920
iter  40 value 88.525599
iter  50 value 86.151147
iter  60 value 85.317974
iter  70 value 83.579379
iter  80 value 82.093192
iter  90 value 81.951108
iter 100 value 80.645151
final  value 80.645151 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.143689 
iter  10 value 94.682145
iter  20 value 93.951306
iter  30 value 88.842151
iter  40 value 83.754398
iter  50 value 81.823263
iter  60 value 79.669068
iter  70 value 79.471090
iter  80 value 79.157665
iter  90 value 79.030579
iter 100 value 79.018325
final  value 79.018325 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.176459 
iter  10 value 94.410306
iter  20 value 85.458744
iter  30 value 83.079886
iter  40 value 82.241274
iter  50 value 79.858844
iter  60 value 79.468805
iter  70 value 79.334565
iter  80 value 79.214411
iter  90 value 79.177894
iter 100 value 79.093594
final  value 79.093594 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.902924 
iter  10 value 95.885140
iter  20 value 88.498031
iter  30 value 87.482756
iter  40 value 86.633801
iter  50 value 84.197835
iter  60 value 82.705067
iter  70 value 81.117708
iter  80 value 80.576867
iter  90 value 80.496703
iter 100 value 80.146692
final  value 80.146692 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.027728 
iter  10 value 97.094731
iter  20 value 90.008981
iter  30 value 83.811768
iter  40 value 83.127183
iter  50 value 82.648418
iter  60 value 82.545905
iter  70 value 82.403039
iter  80 value 81.533734
iter  90 value 79.999792
iter 100 value 79.725878
final  value 79.725878 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.935462 
iter  10 value 95.078355
iter  20 value 91.400292
iter  30 value 84.404195
iter  40 value 81.801246
iter  50 value 80.115314
iter  60 value 79.338657
iter  70 value 79.093624
iter  80 value 79.018128
iter  90 value 78.862933
iter 100 value 78.307455
final  value 78.307455 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 114.277484 
iter  10 value 93.397703
iter  20 value 93.396900
iter  30 value 93.155173
iter  40 value 93.154638
iter  50 value 91.210297
iter  60 value 87.095745
iter  70 value 85.883369
iter  80 value 85.766887
final  value 85.766858 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.503408 
final  value 94.485849 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.915075 
iter  10 value 94.059793
iter  20 value 93.397959
iter  30 value 93.396860
iter  40 value 93.396304
final  value 93.395942 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.075055 
final  value 94.485704 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.027275 
final  value 94.485845 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.249570 
iter  10 value 94.485445
iter  20 value 93.999710
iter  30 value 86.676128
iter  40 value 86.515244
iter  50 value 86.503765
iter  60 value 85.068089
iter  70 value 84.191379
iter  80 value 84.119016
iter  90 value 84.117373
iter 100 value 84.116151
final  value 84.116151 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.054877 
iter  10 value 93.114869
iter  20 value 86.405765
iter  30 value 82.439749
iter  40 value 82.118988
iter  50 value 82.086532
final  value 82.086505 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.385413 
iter  10 value 93.403131
iter  20 value 93.399645
iter  30 value 91.744023
iter  40 value 85.137599
iter  50 value 84.982424
iter  60 value 84.980009
final  value 84.979772 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.572880 
iter  10 value 94.488478
iter  20 value 90.644669
iter  30 value 88.934337
iter  40 value 88.927261
iter  50 value 88.925849
iter  60 value 88.923781
iter  70 value 88.923395
iter  70 value 88.923395
iter  70 value 88.923395
final  value 88.923395 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.919052 
iter  10 value 93.400540
iter  20 value 93.399601
iter  30 value 93.337000
final  value 93.336579 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.671325 
iter  10 value 94.492461
iter  20 value 94.484263
iter  30 value 84.858214
iter  40 value 84.632500
final  value 84.632253 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.266626 
iter  10 value 93.404104
iter  20 value 93.402911
iter  30 value 93.343628
iter  40 value 87.149470
iter  50 value 81.623729
iter  60 value 81.208079
iter  70 value 80.994949
iter  80 value 79.876289
iter  90 value 79.679562
iter 100 value 79.672560
final  value 79.672560 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.990870 
iter  10 value 93.404565
iter  20 value 93.403828
iter  30 value 93.402812
iter  40 value 93.345093
iter  50 value 93.337520
iter  60 value 93.335483
iter  70 value 83.163651
iter  80 value 83.002249
iter  90 value 82.979136
final  value 82.978935 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.905272 
iter  10 value 93.722816
iter  20 value 93.715251
iter  30 value 90.536318
iter  40 value 82.749038
iter  50 value 82.608316
iter  60 value 82.586360
final  value 82.584841 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.494865 
iter  10 value 93.118299
iter  20 value 93.113984
iter  30 value 87.418515
iter  40 value 83.710597
iter  50 value 81.670529
iter  60 value 81.646940
iter  70 value 81.646550
iter  80 value 81.588780
iter  90 value 81.217137
iter 100 value 78.353649
final  value 78.353649 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.965577 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.988996 
iter  10 value 93.912797
iter  20 value 93.891999
final  value 93.890821 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.672131 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.531959 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.135264 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.082049 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.109871 
iter  10 value 93.565062
final  value 93.564928 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.876965 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.806914 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.425028 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.329683 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.260564 
iter  10 value 85.896249
iter  20 value 85.871904
final  value 85.871899 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.097480 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.325178 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.193800 
iter  10 value 93.728449
iter  20 value 93.551606
final  value 93.551243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.937153 
iter  10 value 93.643730
iter  20 value 86.701175
iter  30 value 84.873034
iter  40 value 84.673689
iter  50 value 84.388931
iter  60 value 83.892631
final  value 83.883376 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.132699 
iter  10 value 94.056890
iter  20 value 94.056597
iter  30 value 87.879965
iter  40 value 86.012268
iter  50 value 85.773861
iter  60 value 84.087334
iter  70 value 83.927590
iter  80 value 82.844588
iter  90 value 81.979294
iter 100 value 81.701729
final  value 81.701729 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.254919 
iter  10 value 94.055681
iter  20 value 92.843494
iter  30 value 88.047521
iter  40 value 86.899804
iter  50 value 86.581064
iter  60 value 85.633637
iter  70 value 84.520368
iter  80 value 84.301460
iter  90 value 83.832534
iter 100 value 83.503319
final  value 83.503319 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.693178 
iter  10 value 94.186725
iter  20 value 93.432704
iter  30 value 88.161797
iter  40 value 87.226199
iter  50 value 84.936522
iter  60 value 84.594609
iter  70 value 84.251908
iter  80 value 83.887066
final  value 83.883376 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.671286 
iter  10 value 94.089455
iter  20 value 94.050336
iter  30 value 93.880243
iter  40 value 93.831744
iter  50 value 93.815229
iter  60 value 93.813877
iter  70 value 90.333137
iter  80 value 84.716861
iter  90 value 83.817586
iter 100 value 83.437690
final  value 83.437690 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.772036 
iter  10 value 93.849677
iter  20 value 85.123494
iter  30 value 82.403015
iter  40 value 81.665379
iter  50 value 81.519236
iter  60 value 81.235222
iter  70 value 81.200813
iter  80 value 81.149758
iter  90 value 81.080818
iter 100 value 80.972121
final  value 80.972121 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.143471 
iter  10 value 93.230671
iter  20 value 86.874995
iter  30 value 86.790606
iter  40 value 85.610353
iter  50 value 83.640344
iter  60 value 83.147969
iter  70 value 82.948671
iter  80 value 82.851624
iter  90 value 81.970237
iter 100 value 81.239319
final  value 81.239319 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.207137 
iter  10 value 93.991532
iter  20 value 88.185961
iter  30 value 85.979910
iter  40 value 85.537748
iter  50 value 84.363198
iter  60 value 83.702961
iter  70 value 83.570764
iter  80 value 83.551793
iter  90 value 83.289411
iter 100 value 83.133722
final  value 83.133722 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.313127 
iter  10 value 94.059340
iter  20 value 88.701103
iter  30 value 85.088348
iter  40 value 84.134737
iter  50 value 83.074782
iter  60 value 82.230643
iter  70 value 81.881873
iter  80 value 81.851936
iter  90 value 81.738062
iter 100 value 81.348361
final  value 81.348361 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.106621 
iter  10 value 94.030683
iter  20 value 93.546591
iter  30 value 89.186181
iter  40 value 83.287899
iter  50 value 82.255214
iter  60 value 81.943362
iter  70 value 81.416925
iter  80 value 81.297898
iter  90 value 80.975158
iter 100 value 80.782938
final  value 80.782938 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.406149 
iter  10 value 93.838332
iter  20 value 91.802517
iter  30 value 88.255337
iter  40 value 84.627033
iter  50 value 83.380827
iter  60 value 83.135291
iter  70 value 83.009586
iter  80 value 82.413691
iter  90 value 81.763258
iter 100 value 80.840408
final  value 80.840408 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.301656 
iter  10 value 94.310125
iter  20 value 93.949723
iter  30 value 86.927383
iter  40 value 86.745458
iter  50 value 86.664208
iter  60 value 86.264493
iter  70 value 84.323385
iter  80 value 83.056321
iter  90 value 81.204213
iter 100 value 80.354358
final  value 80.354358 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.611979 
iter  10 value 94.233149
iter  20 value 94.053799
iter  30 value 88.385771
iter  40 value 85.398977
iter  50 value 83.673147
iter  60 value 83.124060
iter  70 value 82.768817
iter  80 value 82.396459
iter  90 value 81.439288
iter 100 value 80.903409
final  value 80.903409 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.784188 
iter  10 value 95.230628
iter  20 value 94.143990
iter  30 value 93.954014
iter  40 value 93.276621
iter  50 value 90.404751
iter  60 value 84.879188
iter  70 value 83.894603
iter  80 value 82.194882
iter  90 value 81.889012
iter 100 value 81.074113
final  value 81.074113 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.399374 
iter  10 value 93.367484
iter  20 value 86.877749
iter  30 value 86.247621
iter  40 value 84.637780
iter  50 value 84.348180
iter  60 value 84.283643
iter  70 value 83.797641
iter  80 value 83.663928
iter  90 value 83.591588
iter 100 value 83.551793
final  value 83.551793 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.728706 
final  value 94.054507 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.379898 
final  value 94.054375 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.446362 
final  value 94.055299 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.260205 
iter  10 value 94.040353
iter  20 value 94.039342
iter  30 value 94.038838
iter  40 value 94.038409
final  value 94.038397 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.012813 
iter  10 value 93.774237
iter  20 value 93.767436
iter  30 value 93.607117
iter  40 value 93.600613
iter  50 value 93.600185
iter  60 value 93.599788
iter  70 value 90.552657
iter  80 value 87.682495
iter  90 value 87.622705
iter 100 value 87.408521
final  value 87.408521 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 97.680549 
iter  10 value 94.057500
iter  20 value 94.022829
iter  30 value 93.760432
iter  40 value 90.169943
iter  50 value 85.402202
iter  60 value 85.377919
iter  70 value 84.973469
iter  80 value 84.819721
iter  90 value 84.662516
iter 100 value 84.233971
final  value 84.233971 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.682012 
iter  10 value 94.045152
iter  20 value 94.028984
iter  30 value 92.978008
iter  40 value 92.976747
iter  50 value 92.976080
iter  60 value 91.881234
iter  70 value 91.850731
iter  80 value 91.709557
final  value 91.684091 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.122435 
iter  10 value 94.042644
iter  20 value 93.977020
iter  30 value 92.472809
iter  40 value 92.392442
iter  50 value 92.390806
iter  60 value 92.390602
iter  70 value 86.902506
iter  80 value 85.686266
iter  90 value 84.987117
iter 100 value 84.676258
final  value 84.676258 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.674260 
iter  10 value 89.343511
iter  20 value 86.756824
iter  30 value 85.843155
iter  40 value 85.493554
iter  50 value 85.492385
iter  60 value 85.366869
iter  70 value 85.353311
iter  80 value 85.349785
iter  90 value 85.258304
iter 100 value 84.075707
final  value 84.075707 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.006056 
iter  10 value 85.633147
iter  20 value 85.610616
iter  30 value 85.606958
iter  40 value 84.890321
iter  50 value 83.030674
iter  60 value 82.929749
iter  70 value 82.929643
iter  80 value 82.929518
final  value 82.929510 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.197356 
iter  10 value 93.747865
iter  20 value 92.968177
iter  30 value 92.248741
iter  40 value 92.220836
iter  50 value 92.217977
iter  60 value 91.937650
iter  70 value 91.884080
iter  80 value 91.879140
final  value 91.878667 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.728680 
iter  10 value 88.964885
iter  20 value 86.890608
iter  30 value 86.847943
iter  40 value 86.739465
iter  50 value 85.105608
iter  60 value 85.066477
iter  70 value 85.063677
iter  80 value 85.059577
iter  90 value 85.012462
final  value 85.010775 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.575552 
iter  10 value 93.622873
iter  20 value 93.614756
iter  30 value 88.648172
iter  40 value 82.827383
iter  50 value 82.240117
iter  60 value 81.690020
iter  70 value 80.175261
iter  80 value 78.989059
iter  90 value 78.653414
iter 100 value 78.633382
final  value 78.633382 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.017329 
iter  10 value 94.043191
iter  20 value 94.036203
iter  30 value 93.980118
iter  40 value 93.965895
iter  50 value 86.625478
iter  60 value 84.853351
iter  70 value 84.830036
iter  80 value 84.792797
iter  90 value 83.982534
iter 100 value 83.196928
final  value 83.196928 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.707982 
iter  10 value 94.046031
iter  20 value 93.388220
iter  30 value 85.837268
final  value 85.837264 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.030428 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.019574 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.637446 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.247802 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.403245 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.088164 
final  value 94.363637 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.937961 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.436038 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.130533 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.739582 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.146526 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.210938 
iter  10 value 90.757410
iter  20 value 90.547879
iter  30 value 90.512188
iter  40 value 90.399677
final  value 90.399672 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.606716 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.865643 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.739528 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.082860 
iter  10 value 94.412354
iter  20 value 91.614909
iter  30 value 90.872700
iter  40 value 89.968557
iter  50 value 89.915460
final  value 89.915411 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.276861 
iter  10 value 94.486468
iter  20 value 93.791578
iter  30 value 86.011731
iter  40 value 85.856876
iter  50 value 85.726359
iter  60 value 84.916964
iter  70 value 84.298994
iter  80 value 84.242528
final  value 84.240249 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.803404 
iter  10 value 94.490054
iter  20 value 94.448133
iter  30 value 94.296925
iter  40 value 88.026067
iter  50 value 84.863692
iter  60 value 84.460065
iter  70 value 84.172225
iter  80 value 84.092513
iter  90 value 84.091598
final  value 84.091357 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.121525 
iter  10 value 94.491852
iter  20 value 94.429107
iter  30 value 88.691561
iter  40 value 83.752113
iter  50 value 83.638239
iter  60 value 83.587376
iter  70 value 83.582655
iter  80 value 83.579900
final  value 83.579899 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.974952 
iter  10 value 94.290243
iter  20 value 91.831989
iter  30 value 90.760439
iter  40 value 90.474047
iter  50 value 90.175486
iter  60 value 84.789209
iter  70 value 83.435646
iter  80 value 83.140630
iter  90 value 81.698578
iter 100 value 80.968819
final  value 80.968819 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.748832 
iter  10 value 94.566035
iter  20 value 87.260297
iter  30 value 85.726962
iter  40 value 84.877371
iter  50 value 84.232561
iter  60 value 83.223826
iter  70 value 81.563013
iter  80 value 80.778506
iter  90 value 80.425045
iter 100 value 80.230953
final  value 80.230953 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.687043 
iter  10 value 93.749307
iter  20 value 85.489682
iter  30 value 84.741621
iter  40 value 82.687699
iter  50 value 81.699290
iter  60 value 81.379437
iter  70 value 81.341275
iter  80 value 81.250373
iter  90 value 81.229132
iter 100 value 81.172086
final  value 81.172086 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.704194 
iter  10 value 94.148675
iter  20 value 90.199032
iter  30 value 86.356030
iter  40 value 84.528903
iter  50 value 83.738261
iter  60 value 82.753511
iter  70 value 81.461255
iter  80 value 80.528718
iter  90 value 80.452783
iter 100 value 79.917740
final  value 79.917740 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 122.319093 
iter  10 value 94.406886
iter  20 value 92.262600
iter  30 value 88.249390
iter  40 value 82.195198
iter  50 value 81.564270
iter  60 value 81.244284
iter  70 value 81.058381
iter  80 value 80.933996
iter  90 value 80.681539
iter 100 value 80.357128
final  value 80.357128 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.242297 
iter  10 value 94.465069
iter  20 value 89.294650
iter  30 value 88.693426
iter  40 value 87.978206
iter  50 value 85.110655
iter  60 value 81.853455
iter  70 value 81.318425
iter  80 value 81.027051
iter  90 value 80.063023
iter 100 value 79.899549
final  value 79.899549 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.064748 
iter  10 value 98.779727
iter  20 value 95.240457
iter  30 value 87.023649
iter  40 value 82.289574
iter  50 value 81.461388
iter  60 value 80.559688
iter  70 value 79.816880
iter  80 value 79.455881
iter  90 value 79.333875
iter 100 value 79.287712
final  value 79.287712 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.305405 
iter  10 value 94.761423
iter  20 value 85.988022
iter  30 value 83.609720
iter  40 value 81.788081
iter  50 value 81.042664
iter  60 value 80.351509
iter  70 value 79.957154
iter  80 value 79.873713
iter  90 value 79.798228
iter 100 value 79.553756
final  value 79.553756 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.080368 
iter  10 value 94.455312
iter  20 value 87.719457
iter  30 value 84.472730
iter  40 value 84.135934
iter  50 value 83.050489
iter  60 value 79.952362
iter  70 value 79.227123
iter  80 value 79.006972
iter  90 value 78.852271
iter 100 value 78.816471
final  value 78.816471 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.027680 
iter  10 value 94.470578
iter  20 value 90.232800
iter  30 value 86.281496
iter  40 value 84.640542
iter  50 value 83.706152
iter  60 value 83.126749
iter  70 value 82.294521
iter  80 value 81.899924
iter  90 value 80.370069
iter 100 value 79.894965
final  value 79.894965 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.833667 
iter  10 value 94.609851
iter  20 value 93.031958
iter  30 value 92.245969
iter  40 value 91.840114
iter  50 value 90.158759
iter  60 value 83.588454
iter  70 value 81.482483
iter  80 value 80.428169
iter  90 value 79.922587
iter 100 value 79.418257
final  value 79.418257 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.577307 
final  value 94.464059 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.920317 
final  value 94.485731 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.598613 
final  value 94.485482 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.668310 
final  value 94.485741 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.135438 
iter  10 value 94.485932
iter  20 value 93.071663
iter  30 value 86.507192
iter  40 value 86.502258
final  value 86.501561 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.956496 
iter  10 value 94.489024
iter  20 value 94.428860
iter  30 value 85.870830
iter  40 value 85.704108
iter  50 value 85.701786
iter  60 value 85.642975
iter  70 value 84.151392
iter  80 value 84.132017
iter  90 value 84.131789
final  value 84.131772 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.956985 
iter  10 value 94.359545
iter  20 value 94.339558
iter  30 value 88.723929
iter  40 value 88.363181
iter  50 value 86.968170
iter  60 value 86.967401
final  value 86.927928 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.366107 
iter  10 value 94.489644
iter  20 value 94.484425
iter  30 value 94.446082
iter  40 value 86.073527
iter  50 value 82.221620
iter  60 value 79.365592
iter  70 value 78.652381
iter  80 value 78.207203
iter  90 value 78.065197
iter 100 value 78.063992
final  value 78.063992 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.917400 
iter  10 value 94.436446
iter  20 value 94.359838
iter  30 value 94.356207
iter  40 value 94.330532
iter  50 value 94.321696
final  value 94.321644 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.077378 
iter  10 value 94.359202
iter  20 value 94.355856
final  value 94.355621 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.648845 
iter  10 value 89.512521
iter  20 value 84.970901
iter  30 value 82.369576
iter  40 value 82.355160
final  value 82.355055 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.850182 
iter  10 value 94.362645
iter  20 value 94.356928
iter  30 value 94.354454
iter  40 value 92.621476
final  value 92.620972 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.749623 
iter  10 value 94.362133
iter  20 value 94.354696
iter  30 value 93.575275
iter  40 value 91.613947
final  value 91.610032 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.665328 
iter  10 value 90.733970
iter  20 value 88.872962
iter  30 value 84.863174
iter  40 value 84.858378
iter  50 value 84.857265
iter  60 value 84.855624
iter  70 value 84.821703
iter  80 value 84.816611
iter  90 value 84.815819
iter 100 value 84.815231
final  value 84.815231 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.473076 
iter  10 value 94.317745
iter  20 value 94.315881
iter  30 value 94.311887
iter  40 value 93.269033
iter  50 value 90.529330
iter  60 value 90.499405
iter  70 value 90.496976
iter  80 value 90.394741
iter  90 value 90.353278
iter 100 value 90.352355
final  value 90.352355 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.826305 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.528815 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.727662 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.183675 
iter  10 value 94.456805
iter  20 value 94.443263
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.694136 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.013763 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.910465 
iter  10 value 94.443244
iter  10 value 94.443244
iter  10 value 94.443244
final  value 94.443244 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.096423 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.651549 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.423736 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.807361 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.419400 
final  value 94.428839 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.160120 
iter  10 value 94.391937
iter  20 value 94.385586
final  value 94.385584 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.692356 
iter  10 value 94.443245
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.489251 
iter  10 value 94.385554
iter  10 value 94.385554
iter  20 value 94.383696
final  value 94.383622 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.769108 
iter  10 value 94.464604
iter  20 value 94.239866
iter  30 value 94.191188
iter  40 value 94.190261
iter  50 value 93.007411
iter  60 value 92.661863
iter  70 value 92.410492
iter  80 value 84.475486
iter  90 value 84.202573
iter 100 value 84.096735
final  value 84.096735 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.975100 
iter  10 value 94.497114
iter  20 value 94.487602
iter  30 value 94.404194
iter  40 value 90.614913
iter  50 value 89.436404
iter  60 value 85.858787
iter  70 value 85.736069
iter  80 value 85.723298
iter  90 value 85.696639
iter 100 value 85.619523
final  value 85.619523 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.945509 
iter  10 value 94.411724
iter  20 value 91.348416
iter  30 value 85.992281
iter  40 value 85.669485
iter  50 value 85.588666
iter  60 value 85.478786
iter  70 value 85.427891
final  value 85.425811 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.296184 
iter  10 value 94.486438
iter  20 value 94.340453
iter  30 value 92.663824
iter  40 value 86.788117
iter  50 value 86.056258
iter  60 value 85.986200
iter  70 value 85.905716
iter  80 value 85.312624
iter  90 value 84.465480
iter 100 value 83.926998
final  value 83.926998 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.232532 
iter  10 value 94.487750
iter  20 value 87.131797
iter  30 value 86.472490
iter  40 value 85.829905
iter  50 value 85.545064
iter  60 value 85.497085
iter  70 value 85.425825
final  value 85.425811 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.310694 
iter  10 value 94.556227
iter  20 value 93.558947
iter  30 value 90.688231
iter  40 value 88.210002
iter  50 value 87.376903
iter  60 value 85.928786
iter  70 value 84.229437
iter  80 value 83.213844
iter  90 value 82.684834
iter 100 value 82.573222
final  value 82.573222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.991892 
iter  10 value 94.490026
iter  20 value 94.178670
iter  30 value 86.557193
iter  40 value 85.836633
iter  50 value 85.268422
iter  60 value 84.493156
iter  70 value 84.032935
iter  80 value 83.832136
iter  90 value 83.785419
iter 100 value 83.763640
final  value 83.763640 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.709939 
iter  10 value 94.602678
iter  20 value 93.696491
iter  30 value 87.651473
iter  40 value 86.468545
iter  50 value 85.692366
iter  60 value 85.332868
iter  70 value 85.259660
iter  80 value 85.200543
iter  90 value 84.283653
iter 100 value 82.831559
final  value 82.831559 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.702197 
iter  10 value 94.386568
iter  20 value 90.202894
iter  30 value 87.069728
iter  40 value 85.683326
iter  50 value 83.994405
iter  60 value 83.403351
iter  70 value 83.222364
iter  80 value 83.093253
iter  90 value 82.965019
iter 100 value 82.555758
final  value 82.555758 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.563029 
iter  10 value 94.402339
iter  20 value 86.907243
iter  30 value 86.461040
iter  40 value 85.795861
iter  50 value 83.810772
iter  60 value 82.724908
iter  70 value 82.229986
iter  80 value 81.697787
iter  90 value 81.612942
iter 100 value 81.573362
final  value 81.573362 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.358872 
iter  10 value 95.741487
iter  20 value 94.578422
iter  30 value 94.478114
iter  40 value 92.552199
iter  50 value 88.409037
iter  60 value 85.522237
iter  70 value 83.891716
iter  80 value 83.430822
iter  90 value 82.963969
iter 100 value 82.305036
final  value 82.305036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.868364 
iter  10 value 94.489408
iter  20 value 90.464844
iter  30 value 86.953023
iter  40 value 84.500302
iter  50 value 83.667759
iter  60 value 82.632977
iter  70 value 82.104786
iter  80 value 81.907002
iter  90 value 81.607965
iter 100 value 81.568701
final  value 81.568701 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.926668 
iter  10 value 96.154247
iter  20 value 91.873568
iter  30 value 89.495422
iter  40 value 88.689674
iter  50 value 88.538919
iter  60 value 87.660733
iter  70 value 84.095377
iter  80 value 83.609857
iter  90 value 83.038034
iter 100 value 82.762013
final  value 82.762013 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.552838 
iter  10 value 94.920247
iter  20 value 90.977837
iter  30 value 86.449913
iter  40 value 85.110089
iter  50 value 84.449431
iter  60 value 84.010253
iter  70 value 83.883687
iter  80 value 83.787989
iter  90 value 83.766966
iter 100 value 83.763912
final  value 83.763912 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.473382 
iter  10 value 95.929581
iter  20 value 89.195571
iter  30 value 87.939712
iter  40 value 87.095398
iter  50 value 83.114557
iter  60 value 82.233826
iter  70 value 82.023837
iter  80 value 81.775686
iter  90 value 81.633420
iter 100 value 81.442596
final  value 81.442596 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.991424 
final  value 94.485795 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.649327 
final  value 94.485836 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.723035 
iter  10 value 94.385047
final  value 94.385042 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.114316 
iter  10 value 94.307747
iter  20 value 94.306109
iter  30 value 94.305649
iter  40 value 94.289283
iter  40 value 94.289283
iter  40 value 94.289283
final  value 94.289283 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.842672 
final  value 94.485793 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.822425 
iter  10 value 94.391278
iter  20 value 94.384136
iter  30 value 87.058017
iter  40 value 85.415463
iter  50 value 85.409537
iter  60 value 85.408853
iter  70 value 85.408041
final  value 84.849799 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.442760 
iter  10 value 94.448326
iter  20 value 94.443856
iter  30 value 94.113279
iter  40 value 90.989785
iter  50 value 87.975988
iter  60 value 86.322515
iter  70 value 86.275940
iter  80 value 86.275679
final  value 86.275122 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.047178 
iter  10 value 94.488133
iter  20 value 92.519255
iter  30 value 87.958332
iter  40 value 87.954622
iter  50 value 86.760530
iter  60 value 86.636002
iter  70 value 86.627730
iter  80 value 86.625406
iter  90 value 86.563597
iter 100 value 86.456198
final  value 86.456198 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.258935 
iter  10 value 94.489059
iter  20 value 94.484222
iter  30 value 94.318683
iter  40 value 93.973737
iter  50 value 87.740537
iter  60 value 87.740189
final  value 87.740181 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.988939 
iter  10 value 94.365667
iter  20 value 94.359336
iter  30 value 94.359121
iter  40 value 94.298288
iter  50 value 94.293051
iter  60 value 94.291516
iter  70 value 94.258857
iter  80 value 85.866993
iter  90 value 84.006664
iter 100 value 83.876085
final  value 83.876085 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.339740 
iter  10 value 94.436519
iter  20 value 91.394666
iter  30 value 85.824202
iter  40 value 85.807115
iter  50 value 85.802660
iter  60 value 85.684245
iter  70 value 85.682874
iter  80 value 85.222333
iter  90 value 84.690659
final  value 84.689262 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.160751 
iter  10 value 90.857977
iter  20 value 88.912837
iter  30 value 88.827593
iter  40 value 88.479728
iter  50 value 83.952104
iter  60 value 82.520524
iter  70 value 82.188836
iter  80 value 81.669140
iter  90 value 81.487381
iter 100 value 81.466446
final  value 81.466446 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.029564 
iter  10 value 94.492768
iter  20 value 94.135918
iter  30 value 87.370685
iter  40 value 86.263558
iter  50 value 86.133388
iter  60 value 86.019591
final  value 86.018262 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.401716 
iter  10 value 94.491921
iter  20 value 94.449247
iter  30 value 94.239759
final  value 87.953063 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.404175 
iter  10 value 94.492485
iter  20 value 94.392650
iter  30 value 89.827239
final  value 89.715970 
converged
Fitting Repeat 1 

# weights:  507
initial  value 136.850985 
iter  10 value 117.767302
iter  20 value 117.548907
iter  30 value 103.395038
iter  40 value 102.696356
iter  50 value 101.801974
iter  60 value 100.938896
iter  70 value 100.903023
iter  70 value 100.903022
iter  70 value 100.903022
final  value 100.903022 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.837319 
iter  10 value 117.897843
iter  20 value 117.719601
iter  30 value 109.680160
iter  40 value 102.026248
iter  50 value 101.897156
iter  60 value 101.811841
iter  70 value 101.811386
iter  80 value 101.773595
iter  90 value 101.689282
iter 100 value 101.267575
final  value 101.267575 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.776503 
iter  10 value 117.873950
iter  20 value 117.873307
iter  30 value 117.795995
final  value 117.729113 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.084697 
iter  10 value 117.891319
iter  20 value 107.611212
iter  30 value 106.793293
iter  40 value 106.738362
iter  50 value 105.481377
iter  60 value 105.450050
iter  70 value 105.226263
iter  80 value 105.224260
iter  90 value 105.220011
final  value 105.219842 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.415788 
iter  10 value 117.898271
iter  20 value 117.337878
iter  30 value 110.838337
iter  40 value 110.169194
iter  50 value 107.479332
final  value 107.479329 
converged
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 -- Wed May  6 00:49:07 2026 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 40.019   1.082  81.322