##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-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 04:59:33 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* 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
FSmethod      33.841  0.459  34.371
var_imp       33.584  0.685  34.295
corr_plot     33.627  0.474  34.177
pred_ensembel 12.802  0.237  11.718
enrichfindP    0.557  0.038   9.869
* 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-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.18.0’
** 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 96.359717 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.891695 
iter  10 value 94.483943
iter  20 value 94.470201
final  value 94.461538 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.393113 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.636177 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.042006 
iter  10 value 92.636535
iter  20 value 92.635858
final  value 92.635856 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.635355 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 122.903636 
iter  10 value 92.390616
iter  20 value 86.511771
iter  30 value 86.401210
final  value 86.401202 
converged
Fitting Repeat 3 

# weights:  305
initial  value 117.806850 
iter  10 value 94.315790
iter  10 value 94.315790
iter  10 value 94.315790
final  value 94.315790 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.054061 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.173976 
iter  10 value 93.724683
iter  10 value 93.724683
iter  10 value 93.724683
final  value 93.724683 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.217998 
iter  10 value 93.778444
iter  20 value 93.707014
final  value 93.707007 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.546995 
iter  10 value 87.626690
iter  20 value 85.318880
iter  30 value 85.216176
iter  40 value 85.188324
final  value 85.188212 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.507476 
iter  10 value 89.932865
iter  20 value 82.647558
iter  30 value 82.085198
iter  40 value 81.710102
iter  50 value 81.702941
final  value 81.702930 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.382682 
iter  10 value 91.511713
iter  10 value 91.511713
final  value 91.511688 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.932790 
iter  10 value 94.485306
iter  20 value 94.484212
iter  20 value 94.484211
iter  20 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.130541 
iter  10 value 94.486863
iter  20 value 94.121505
iter  30 value 92.981233
iter  40 value 92.969037
iter  50 value 92.207436
iter  60 value 85.165842
iter  70 value 84.416568
iter  80 value 83.589557
iter  90 value 82.412196
iter 100 value 82.074806
final  value 82.074806 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.128959 
iter  10 value 94.488032
iter  20 value 93.926973
iter  30 value 92.544710
iter  40 value 92.074733
iter  50 value 91.848705
iter  60 value 86.064279
iter  70 value 84.070844
iter  80 value 83.715477
iter  90 value 81.727146
iter 100 value 81.181676
final  value 81.181676 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.192823 
iter  10 value 93.670164
iter  20 value 88.515071
iter  30 value 88.076186
iter  40 value 87.625829
iter  50 value 84.037126
iter  60 value 83.389263
iter  70 value 82.356996
iter  80 value 82.248216
iter  90 value 82.245641
iter  90 value 82.245641
iter  90 value 82.245641
final  value 82.245641 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.701625 
iter  10 value 94.479298
iter  20 value 91.660462
iter  30 value 88.977750
iter  40 value 88.566535
iter  50 value 85.565134
iter  60 value 84.130842
iter  70 value 83.464179
iter  80 value 83.340907
final  value 83.336569 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.496227 
iter  10 value 94.647060
iter  20 value 93.203280
iter  30 value 93.178364
iter  40 value 90.992396
iter  50 value 84.174831
iter  60 value 82.245353
iter  70 value 81.480847
iter  80 value 81.377204
iter  90 value 81.131910
final  value 81.058154 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.205711 
iter  10 value 94.593869
iter  20 value 93.013320
iter  30 value 90.072856
iter  40 value 88.129125
iter  50 value 85.132048
iter  60 value 83.364214
iter  70 value 83.043627
iter  80 value 80.737201
iter  90 value 80.282086
iter 100 value 80.098946
final  value 80.098946 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.996677 
iter  10 value 93.674265
iter  20 value 92.727584
iter  30 value 88.928273
iter  40 value 86.780309
iter  50 value 85.037405
iter  60 value 83.353563
iter  70 value 82.365739
iter  80 value 81.261811
iter  90 value 80.925892
iter 100 value 80.356432
final  value 80.356432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.411951 
iter  10 value 92.774282
iter  20 value 88.873435
iter  30 value 86.970122
iter  40 value 84.405064
iter  50 value 82.862160
iter  60 value 82.522293
iter  70 value 81.557367
iter  80 value 80.443356
iter  90 value 79.853717
iter 100 value 79.721568
final  value 79.721568 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.368998 
iter  10 value 93.723065
iter  20 value 88.623323
iter  30 value 86.169139
iter  40 value 85.501895
iter  50 value 84.223659
iter  60 value 80.928267
iter  70 value 80.215087
iter  80 value 79.624135
iter  90 value 79.408550
iter 100 value 79.328039
final  value 79.328039 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.342081 
iter  10 value 94.422155
iter  20 value 85.839363
iter  30 value 84.889785
iter  40 value 84.150382
iter  50 value 83.523305
iter  60 value 82.976574
iter  70 value 82.475418
iter  80 value 81.081698
iter  90 value 80.192512
iter 100 value 79.898979
final  value 79.898979 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.493361 
iter  10 value 95.055944
iter  20 value 86.587468
iter  30 value 84.502941
iter  40 value 83.733695
iter  50 value 82.529164
iter  60 value 82.246559
iter  70 value 82.194967
iter  80 value 82.118092
iter  90 value 81.585357
iter 100 value 80.233213
final  value 80.233213 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.365096 
iter  10 value 94.778259
iter  20 value 94.466882
iter  30 value 93.121948
iter  40 value 92.938367
iter  50 value 87.878343
iter  60 value 84.301585
iter  70 value 82.265162
iter  80 value 81.746431
iter  90 value 80.379053
iter 100 value 80.021410
final  value 80.021410 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.706622 
iter  10 value 94.585634
iter  20 value 93.117690
iter  30 value 92.898384
iter  40 value 85.831909
iter  50 value 81.018174
iter  60 value 80.211960
iter  70 value 79.950785
iter  80 value 79.577386
iter  90 value 79.406620
iter 100 value 79.174582
final  value 79.174582 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.926189 
iter  10 value 94.470362
iter  20 value 89.047071
iter  30 value 85.662672
iter  40 value 84.276685
iter  50 value 83.952695
iter  60 value 83.503639
iter  70 value 81.395945
iter  80 value 80.030082
iter  90 value 79.620306
iter 100 value 79.549243
final  value 79.549243 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.233085 
iter  10 value 88.180525
iter  20 value 85.531721
iter  30 value 83.675015
iter  40 value 82.413561
iter  50 value 81.728258
iter  60 value 81.635022
iter  70 value 81.359450
iter  80 value 80.834270
iter  90 value 80.630263
iter 100 value 80.525092
final  value 80.525092 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.609074 
final  value 94.486104 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.405672 
final  value 94.485741 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.168146 
iter  10 value 92.932527
iter  20 value 92.930122
iter  30 value 85.847035
iter  40 value 85.241763
iter  50 value 85.190166
final  value 85.189557 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.632412 
iter  10 value 94.485722
iter  20 value 94.411195
final  value 94.026849 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.965673 
final  value 94.485778 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.411172 
iter  10 value 94.489056
iter  20 value 94.207320
iter  30 value 88.566163
iter  40 value 88.560213
iter  50 value 88.442996
iter  60 value 83.695182
iter  70 value 83.161786
iter  80 value 83.158468
iter  90 value 83.157368
iter 100 value 82.904032
final  value 82.904032 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.673501 
iter  10 value 93.846144
iter  20 value 92.643027
iter  30 value 92.638260
iter  40 value 92.636624
iter  50 value 87.622204
iter  60 value 87.547149
iter  70 value 83.700133
iter  80 value 83.444471
iter  90 value 82.996414
iter 100 value 82.893305
final  value 82.893305 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.240922 
iter  10 value 94.487232
iter  20 value 94.416327
iter  30 value 87.564744
iter  40 value 86.717622
iter  50 value 84.220840
final  value 84.220803 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.626252 
iter  10 value 94.489229
iter  20 value 94.484753
iter  30 value 94.105095
iter  40 value 87.192650
iter  50 value 84.107042
iter  60 value 83.303009
iter  70 value 81.972746
final  value 81.835096 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.481965 
iter  10 value 94.489278
iter  20 value 94.483816
iter  30 value 88.014051
iter  40 value 87.099172
iter  50 value 82.281957
iter  60 value 82.199751
iter  70 value 81.820004
iter  80 value 81.505848
iter  90 value 81.258344
iter 100 value 81.256954
final  value 81.256954 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.442913 
iter  10 value 93.999758
iter  20 value 93.358497
iter  30 value 92.637998
iter  40 value 92.636863
iter  50 value 92.543631
iter  60 value 86.557819
iter  70 value 84.131112
iter  80 value 84.125808
iter  90 value 84.124935
iter 100 value 83.855716
final  value 83.855716 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.148256 
iter  10 value 94.033943
iter  20 value 93.496863
iter  30 value 91.604704
iter  40 value 85.769032
iter  50 value 85.733915
iter  60 value 85.659960
iter  70 value 85.041702
iter  80 value 85.021286
iter  90 value 85.016732
iter 100 value 83.223384
final  value 83.223384 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.729037 
iter  10 value 94.494298
iter  20 value 94.448585
iter  30 value 86.008412
iter  40 value 83.511107
iter  50 value 83.311419
iter  60 value 83.279551
iter  70 value 83.275623
iter  80 value 83.164229
iter  90 value 83.052196
final  value 83.048144 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.676516 
iter  10 value 94.492718
iter  20 value 94.101008
iter  30 value 85.863988
iter  40 value 81.237826
iter  50 value 80.733431
iter  60 value 80.676175
iter  70 value 80.675927
iter  80 value 80.514333
iter  90 value 80.511383
iter 100 value 80.127079
final  value 80.127079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.941095 
iter  10 value 94.469776
iter  20 value 92.845609
iter  30 value 92.840235
final  value 92.089758 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.260297 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.489839 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.624350 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.240128 
iter  10 value 93.328261
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.398389 
iter  10 value 93.070039
final  value 93.014053 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.888824 
iter  10 value 81.108308
iter  20 value 80.732389
iter  30 value 80.659432
final  value 80.659269 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.241621 
iter  10 value 93.714288
final  value 93.714286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.725165 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.579071 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.275251 
iter  10 value 85.675584
iter  20 value 85.510013
iter  30 value 85.507049
iter  40 value 85.506553
final  value 85.506548 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.333979 
iter  10 value 93.111130
final  value 93.111023 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.536594 
iter  10 value 93.328262
final  value 93.328261 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.615129 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.928231 
iter  10 value 91.762792
iter  20 value 91.543412
final  value 91.543410 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.245256 
iter  10 value 93.328265
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.645074 
iter  10 value 93.890605
iter  20 value 90.190659
iter  30 value 89.559611
iter  40 value 83.719247
iter  50 value 83.321892
iter  60 value 83.208142
iter  70 value 82.967847
iter  80 value 82.929785
final  value 82.927978 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.958717 
iter  10 value 93.535247
iter  20 value 92.573865
iter  30 value 89.288919
iter  40 value 84.380887
iter  50 value 83.282344
iter  60 value 82.768741
iter  70 value 81.196344
iter  80 value 79.250571
final  value 79.246018 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.570941 
iter  10 value 94.055653
iter  20 value 93.624304
iter  30 value 93.242389
iter  40 value 93.234378
iter  50 value 93.231023
iter  60 value 83.415971
iter  70 value 80.205155
iter  80 value 80.126870
iter  90 value 80.073240
iter 100 value 79.432054
final  value 79.432054 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.750674 
iter  10 value 94.056163
iter  20 value 94.055023
iter  30 value 93.551867
iter  40 value 93.424805
iter  50 value 93.232063
final  value 93.230213 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.348448 
iter  10 value 93.894504
iter  20 value 87.187601
iter  30 value 84.652258
iter  40 value 84.514107
iter  50 value 83.698219
iter  60 value 83.239795
iter  70 value 83.106933
iter  80 value 82.937508
iter  90 value 82.928017
final  value 82.927977 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.714163 
iter  10 value 93.482769
iter  20 value 86.336122
iter  30 value 82.244596
iter  40 value 80.749233
iter  50 value 79.258505
iter  60 value 78.935672
iter  70 value 78.930706
iter  80 value 78.878010
iter  90 value 78.720041
iter 100 value 78.374211
final  value 78.374211 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.162607 
iter  10 value 94.006780
iter  20 value 88.177913
iter  30 value 82.357379
iter  40 value 80.398574
iter  50 value 78.763936
iter  60 value 78.566338
iter  70 value 78.148093
iter  80 value 78.051190
iter  90 value 77.808856
iter 100 value 77.709916
final  value 77.709916 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.292617 
iter  10 value 94.127214
iter  20 value 93.000119
iter  30 value 92.320544
iter  40 value 88.849564
iter  50 value 82.690592
iter  60 value 81.667430
iter  70 value 81.186688
iter  80 value 81.155563
iter  90 value 80.955032
iter 100 value 80.157435
final  value 80.157435 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.193782 
iter  10 value 93.629554
iter  20 value 90.860379
iter  30 value 90.421081
iter  40 value 89.601043
iter  50 value 86.021999
iter  60 value 80.102478
iter  70 value 79.768306
iter  80 value 79.694097
iter  90 value 79.388365
iter 100 value 79.369105
final  value 79.369105 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.026599 
iter  10 value 93.289379
iter  20 value 83.467758
iter  30 value 82.919188
iter  40 value 82.667074
iter  50 value 82.628541
iter  60 value 82.264554
iter  70 value 81.610092
iter  80 value 79.731045
iter  90 value 79.104321
iter 100 value 79.021086
final  value 79.021086 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.445688 
iter  10 value 88.409437
iter  20 value 83.635448
iter  30 value 79.847108
iter  40 value 79.304451
iter  50 value 78.949282
iter  60 value 78.841244
iter  70 value 78.773846
iter  80 value 78.594032
iter  90 value 78.164526
iter 100 value 78.052260
final  value 78.052260 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.027193 
iter  10 value 93.390133
iter  20 value 91.208556
iter  30 value 89.267721
iter  40 value 88.834763
iter  50 value 86.494843
iter  60 value 84.911751
iter  70 value 84.123425
iter  80 value 81.606645
iter  90 value 80.146514
iter 100 value 79.075665
final  value 79.075665 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.730708 
iter  10 value 94.313180
iter  20 value 93.865617
iter  30 value 93.522150
iter  40 value 89.538006
iter  50 value 82.064420
iter  60 value 80.925246
iter  70 value 80.296918
iter  80 value 79.696830
iter  90 value 79.447482
iter 100 value 79.056396
final  value 79.056396 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.557631 
iter  10 value 93.105719
iter  20 value 84.122935
iter  30 value 82.218086
iter  40 value 81.559904
iter  50 value 80.241069
iter  60 value 79.767546
iter  70 value 79.136774
iter  80 value 78.526877
iter  90 value 78.206466
iter 100 value 78.105199
final  value 78.105199 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.272692 
iter  10 value 93.571641
iter  20 value 91.266222
iter  30 value 85.305584
iter  40 value 82.828828
iter  50 value 81.878374
iter  60 value 80.531928
iter  70 value 79.819438
iter  80 value 79.388492
iter  90 value 78.797388
iter 100 value 78.585849
final  value 78.585849 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.218836 
final  value 94.054661 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.023288 
final  value 94.055298 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.636242 
final  value 94.054507 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.810000 
iter  10 value 93.412502
iter  20 value 93.312178
final  value 93.185261 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.051965 
iter  10 value 93.330581
iter  20 value 93.330202
iter  30 value 93.270040
iter  40 value 93.129753
iter  50 value 83.279897
iter  60 value 82.968513
iter  70 value 82.012235
iter  80 value 81.690607
iter  90 value 81.690396
final  value 81.689013 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.387192 
iter  10 value 94.055521
iter  20 value 93.433014
iter  30 value 93.330435
iter  40 value 93.328645
iter  50 value 85.476281
iter  60 value 80.901596
iter  70 value 80.637893
final  value 80.634826 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.740649 
iter  10 value 94.056616
iter  20 value 93.987683
iter  30 value 91.456651
iter  40 value 88.681869
iter  50 value 88.636716
iter  60 value 88.153166
iter  70 value 85.856389
iter  80 value 81.872352
iter  90 value 81.703859
iter 100 value 81.703144
final  value 81.703144 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.797713 
iter  10 value 94.040618
iter  20 value 94.013351
iter  30 value 94.009375
iter  40 value 84.930057
iter  50 value 84.876421
iter  60 value 83.672182
iter  70 value 83.589050
iter  80 value 82.336370
iter  90 value 80.549186
iter 100 value 80.338970
final  value 80.338970 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.488473 
iter  10 value 83.646474
iter  20 value 83.260270
iter  30 value 83.258381
iter  40 value 83.256059
iter  50 value 83.199218
final  value 83.198227 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.684618 
iter  10 value 93.333512
iter  20 value 93.330971
iter  30 value 90.650816
iter  40 value 81.605293
iter  50 value 81.512931
iter  60 value 81.503491
iter  70 value 81.494477
iter  80 value 81.487613
final  value 81.487430 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.298184 
iter  10 value 85.697283
iter  20 value 85.515637
iter  30 value 85.301103
iter  40 value 84.812391
iter  50 value 84.812239
final  value 84.812230 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.118277 
iter  10 value 93.436315
iter  20 value 93.099617
iter  30 value 93.089428
iter  40 value 93.018216
iter  50 value 93.015560
iter  60 value 85.815569
iter  70 value 80.634895
final  value 80.634580 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.577472 
iter  10 value 93.337088
iter  20 value 93.334403
iter  30 value 93.259450
iter  40 value 83.301984
final  value 83.246829 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.772243 
iter  10 value 85.577643
iter  20 value 85.521695
iter  30 value 85.460807
iter  40 value 84.988391
iter  50 value 79.206028
iter  60 value 78.559398
iter  70 value 78.495648
iter  80 value 78.441199
iter  90 value 78.434254
iter 100 value 78.351921
final  value 78.351921 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.438115 
iter  10 value 94.019442
iter  20 value 93.662262
iter  30 value 93.424752
iter  40 value 93.417791
iter  50 value 93.413553
iter  60 value 93.277919
iter  70 value 93.269530
iter  80 value 93.268517
iter  90 value 93.162385
iter 100 value 93.054156
final  value 93.054156 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.014134 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.869894 
iter  10 value 93.274501
iter  20 value 93.271106
final  value 93.271095 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.780998 
iter  10 value 86.540548
iter  20 value 86.080032
final  value 86.079546 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.513495 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 93.123051 
iter  10 value 86.862830
iter  20 value 86.590273
final  value 86.590137 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.036463 
iter  10 value 93.539502
iter  10 value 93.539501
final  value 93.539501 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.416196 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.802111 
iter  10 value 94.047619
iter  10 value 94.047619
iter  10 value 94.047619
final  value 94.047619 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.845225 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.996484 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.371848 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.048259 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.889631 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.627225 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.505110 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.518415 
iter  10 value 94.071579
iter  20 value 89.661992
iter  30 value 87.138488
iter  40 value 86.285097
iter  50 value 85.538273
iter  60 value 85.245280
iter  70 value 85.091075
final  value 85.087383 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.488056 
iter  10 value 94.056470
iter  20 value 94.050230
iter  30 value 89.891219
iter  40 value 86.677834
iter  50 value 86.400598
iter  60 value 84.536141
iter  70 value 84.397415
iter  80 value 84.171519
iter  90 value 84.063831
iter 100 value 83.779477
final  value 83.779477 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.921915 
iter  10 value 94.118319
iter  20 value 93.173753
iter  30 value 93.075815
iter  40 value 92.922879
iter  50 value 92.327234
iter  60 value 91.882289
iter  70 value 87.155125
iter  80 value 84.186637
iter  90 value 83.897480
iter 100 value 83.687201
final  value 83.687201 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.506888 
iter  10 value 93.982007
iter  20 value 93.043510
iter  30 value 88.726892
iter  40 value 88.140259
iter  50 value 85.457490
iter  60 value 85.195677
iter  70 value 84.734257
iter  80 value 84.646543
iter  90 value 84.639166
final  value 84.637417 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.695533 
iter  10 value 93.948882
iter  20 value 92.879843
iter  30 value 91.738577
iter  40 value 91.409740
iter  50 value 88.178280
iter  60 value 85.341419
iter  70 value 85.018200
iter  80 value 84.842278
final  value 84.842211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.256294 
iter  10 value 94.062110
iter  20 value 93.909716
iter  30 value 88.323093
iter  40 value 87.366216
iter  50 value 86.852099
iter  60 value 84.601435
iter  70 value 81.729851
iter  80 value 81.372009
iter  90 value 81.220584
iter 100 value 81.066863
final  value 81.066863 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.598300 
iter  10 value 94.109595
iter  20 value 90.675721
iter  30 value 88.618901
iter  40 value 87.139041
iter  50 value 86.518275
iter  60 value 85.074742
iter  70 value 84.746015
iter  80 value 84.562926
iter  90 value 83.440379
iter 100 value 81.806176
final  value 81.806176 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.632889 
iter  10 value 94.288793
iter  20 value 94.084996
iter  30 value 92.771127
iter  40 value 87.602751
iter  50 value 85.558646
iter  60 value 85.164329
iter  70 value 83.040717
iter  80 value 81.784224
iter  90 value 81.291319
iter 100 value 81.205424
final  value 81.205424 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.336393 
iter  10 value 94.039631
iter  20 value 91.462904
iter  30 value 88.619385
iter  40 value 87.025435
iter  50 value 85.596621
iter  60 value 83.383909
iter  70 value 82.121813
iter  80 value 82.067475
iter  90 value 81.835863
iter 100 value 81.044157
final  value 81.044157 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.443986 
iter  10 value 93.299477
iter  20 value 88.464677
iter  30 value 86.831964
iter  40 value 85.585458
iter  50 value 84.347278
iter  60 value 84.229090
iter  70 value 83.919888
iter  80 value 83.881436
iter  90 value 83.780401
iter 100 value 83.180995
final  value 83.180995 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.637904 
iter  10 value 94.089510
iter  20 value 88.526381
iter  30 value 85.253594
iter  40 value 84.821258
iter  50 value 83.549949
iter  60 value 82.227190
iter  70 value 81.668774
iter  80 value 81.066992
iter  90 value 80.927847
iter 100 value 80.766810
final  value 80.766810 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.266593 
iter  10 value 94.043265
iter  20 value 93.296577
iter  30 value 91.917341
iter  40 value 88.444982
iter  50 value 85.655090
iter  60 value 85.029871
iter  70 value 84.540546
iter  80 value 83.008981
iter  90 value 82.673782
iter 100 value 81.987614
final  value 81.987614 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.552142 
iter  10 value 94.049141
iter  20 value 91.146080
iter  30 value 87.624632
iter  40 value 86.127441
iter  50 value 85.226598
iter  60 value 85.048854
iter  70 value 83.790607
iter  80 value 83.433649
iter  90 value 83.384998
iter 100 value 83.317478
final  value 83.317478 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.872755 
iter  10 value 93.579492
iter  20 value 87.388628
iter  30 value 86.447914
iter  40 value 85.601594
iter  50 value 84.892592
iter  60 value 84.111558
iter  70 value 83.249027
iter  80 value 82.540148
iter  90 value 81.510683
iter 100 value 81.276281
final  value 81.276281 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.193979 
iter  10 value 93.034310
iter  20 value 87.868126
iter  30 value 85.852896
iter  40 value 83.491325
iter  50 value 82.348580
iter  60 value 81.979934
iter  70 value 81.544313
iter  80 value 81.296300
iter  90 value 81.231547
iter 100 value 81.225162
final  value 81.225162 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.490954 
final  value 94.054485 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.305503 
final  value 94.054702 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.571655 
final  value 94.054496 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.450919 
final  value 94.054735 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.427929 
final  value 94.049255 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.665484 
iter  10 value 94.101685
iter  20 value 94.038850
iter  30 value 93.421656
iter  40 value 89.089374
iter  50 value 85.335286
iter  60 value 85.212156
iter  70 value 85.089140
iter  80 value 85.088309
iter  80 value 85.088309
final  value 85.088309 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.240486 
iter  10 value 94.037747
iter  20 value 93.829800
iter  30 value 92.282338
iter  40 value 92.276054
iter  50 value 92.256924
final  value 92.248002 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.437279 
iter  10 value 87.947225
iter  20 value 86.582690
iter  30 value 86.580307
iter  40 value 85.613519
iter  50 value 84.168375
iter  60 value 80.589762
iter  70 value 79.383528
iter  80 value 79.187004
iter  90 value 79.186869
final  value 79.186382 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.634775 
iter  10 value 94.058744
iter  20 value 92.270978
iter  30 value 91.602562
iter  40 value 87.330292
iter  50 value 83.902074
iter  60 value 82.286778
iter  70 value 81.970886
iter  80 value 81.970623
iter  90 value 81.965050
iter 100 value 81.920861
final  value 81.920861 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.984722 
iter  10 value 94.057821
iter  20 value 93.396385
iter  30 value 87.788634
iter  40 value 85.414356
iter  50 value 84.934452
iter  60 value 84.025953
iter  70 value 83.802286
iter  80 value 83.219029
iter  90 value 83.177301
iter 100 value 83.076628
final  value 83.076628 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.889788 
iter  10 value 92.130871
iter  20 value 88.788836
iter  30 value 87.661690
iter  40 value 86.047521
iter  50 value 86.019453
iter  60 value 86.016220
iter  70 value 85.994699
iter  80 value 85.985916
iter  90 value 85.984599
iter 100 value 85.983985
final  value 85.983985 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.322460 
iter  10 value 94.042145
iter  20 value 94.024837
iter  30 value 94.017157
iter  40 value 85.786254
iter  50 value 85.116345
iter  60 value 85.091335
iter  70 value 85.091280
final  value 85.090655 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.854687 
iter  10 value 94.060509
final  value 94.053782 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.542428 
iter  10 value 93.743823
iter  20 value 91.131676
iter  30 value 86.470039
final  value 86.383166 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.834433 
iter  10 value 94.007943
iter  20 value 94.001699
iter  30 value 92.545233
iter  40 value 87.213160
iter  50 value 86.490827
iter  60 value 86.261878
iter  70 value 86.214982
final  value 86.213759 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.388560 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.144297 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.847927 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.235492 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.558070 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.138509 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.062850 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.485465 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.092582 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.445034 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.538812 
final  value 94.291892 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.625637 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.620104 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.848338 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.199094 
iter  10 value 94.291909
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.976060 
iter  10 value 94.549212
iter  20 value 94.485898
iter  30 value 94.459512
iter  40 value 93.817715
iter  50 value 93.666847
iter  60 value 85.256967
iter  70 value 83.472069
iter  80 value 82.771993
iter  90 value 82.591614
iter 100 value 82.439294
final  value 82.439294 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.388150 
iter  10 value 94.485181
iter  20 value 91.899844
iter  30 value 91.573648
iter  40 value 91.549407
iter  50 value 90.985362
iter  60 value 90.911787
iter  70 value 90.897233
final  value 90.897229 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.432457 
iter  10 value 94.494703
iter  20 value 94.458057
iter  30 value 94.352690
iter  40 value 94.277581
iter  50 value 88.102100
iter  60 value 86.480076
iter  70 value 83.582099
iter  80 value 83.091101
iter  90 value 82.862203
iter 100 value 82.768315
final  value 82.768315 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 110.158862 
iter  10 value 94.398873
iter  20 value 87.277576
iter  30 value 86.575475
iter  40 value 83.740170
iter  50 value 83.561807
iter  60 value 83.348247
iter  70 value 83.127994
iter  80 value 82.891935
iter  90 value 82.444260
iter 100 value 82.409401
final  value 82.409401 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.369549 
iter  10 value 88.861097
iter  20 value 85.223007
iter  30 value 85.075213
iter  40 value 83.441544
iter  50 value 82.621757
iter  60 value 82.410679
iter  70 value 82.409266
iter  70 value 82.409266
iter  70 value 82.409266
final  value 82.409266 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.907290 
iter  10 value 90.743444
iter  20 value 86.474581
iter  30 value 84.959470
iter  40 value 84.786516
iter  50 value 84.678930
iter  60 value 83.970753
iter  70 value 82.841933
iter  80 value 81.073958
iter  90 value 80.080162
iter 100 value 79.668312
final  value 79.668312 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.697679 
iter  10 value 94.483402
iter  20 value 94.371013
iter  30 value 93.527419
iter  40 value 86.687735
iter  50 value 81.933773
iter  60 value 81.649997
iter  70 value 81.451105
iter  80 value 81.171162
iter  90 value 80.763584
iter 100 value 79.604084
final  value 79.604084 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 130.966541 
iter  10 value 94.677513
iter  20 value 93.619854
iter  30 value 87.718418
iter  40 value 84.435368
iter  50 value 84.012962
iter  60 value 83.975965
iter  70 value 83.582743
iter  80 value 81.882568
iter  90 value 80.629757
iter 100 value 79.872572
final  value 79.872572 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.494098 
iter  10 value 93.971348
iter  20 value 91.895524
iter  30 value 83.496033
iter  40 value 81.696132
iter  50 value 80.084128
iter  60 value 79.849814
iter  70 value 79.480146
iter  80 value 79.200889
iter  90 value 78.996606
iter 100 value 78.900351
final  value 78.900351 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.221576 
iter  10 value 93.891790
iter  20 value 88.904683
iter  30 value 87.443750
iter  40 value 84.430964
iter  50 value 82.834143
iter  60 value 80.519725
iter  70 value 80.264025
iter  80 value 79.986973
iter  90 value 79.542832
iter 100 value 79.321895
final  value 79.321895 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.992145 
iter  10 value 95.093768
iter  20 value 93.364572
iter  30 value 87.678540
iter  40 value 85.262335
iter  50 value 82.537851
iter  60 value 81.056899
iter  70 value 80.196674
iter  80 value 79.766339
iter  90 value 79.688986
iter 100 value 79.476983
final  value 79.476983 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.992349 
iter  10 value 94.343692
iter  20 value 89.825647
iter  30 value 86.470868
iter  40 value 85.668649
iter  50 value 84.929298
iter  60 value 84.442140
iter  70 value 81.323959
iter  80 value 79.825166
iter  90 value 79.610303
iter 100 value 79.241954
final  value 79.241954 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.775134 
iter  10 value 94.625275
iter  20 value 94.494329
iter  30 value 91.957225
iter  40 value 88.471017
iter  50 value 85.409690
iter  60 value 82.273980
iter  70 value 81.746207
iter  80 value 81.558210
iter  90 value 81.416422
iter 100 value 81.349484
final  value 81.349484 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.015445 
iter  10 value 94.298372
iter  20 value 87.893706
iter  30 value 84.797388
iter  40 value 81.425457
iter  50 value 80.653941
iter  60 value 80.234411
iter  70 value 79.693691
iter  80 value 79.342985
iter  90 value 79.234636
iter 100 value 79.181294
final  value 79.181294 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 140.680320 
iter  10 value 92.830646
iter  20 value 89.477057
iter  30 value 85.657434
iter  40 value 85.061815
iter  50 value 84.687932
iter  60 value 84.306475
iter  70 value 83.796207
iter  80 value 81.536517
iter  90 value 80.938874
iter 100 value 80.087599
final  value 80.087599 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.527617 
iter  10 value 94.484421
iter  20 value 93.968632
iter  30 value 93.509657
iter  40 value 93.509483
iter  50 value 93.508700
final  value 93.508661 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.524082 
final  value 94.485997 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.123957 
iter  10 value 94.293832
iter  20 value 93.965088
iter  30 value 85.659876
iter  40 value 85.654149
iter  50 value 84.837360
final  value 84.764532 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.599633 
final  value 94.485776 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.903341 
final  value 94.485920 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.671441 
iter  10 value 94.592739
iter  20 value 92.508393
iter  30 value 92.507227
iter  40 value 92.463929
iter  50 value 92.462759
iter  60 value 92.460358
final  value 92.459618 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.508769 
iter  10 value 94.334140
iter  20 value 94.315814
iter  30 value 87.505303
iter  40 value 85.778489
iter  50 value 85.484548
iter  60 value 85.471845
iter  70 value 85.390049
iter  80 value 84.897014
iter  90 value 84.776136
iter 100 value 84.760534
final  value 84.760534 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.137642 
iter  10 value 94.386655
iter  20 value 94.384781
final  value 94.382840 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.277503 
iter  10 value 94.488988
iter  20 value 94.401564
iter  30 value 87.553080
iter  40 value 83.669077
iter  50 value 82.224381
iter  60 value 81.220702
iter  70 value 81.214069
iter  80 value 81.208745
iter  90 value 81.159882
iter 100 value 81.152852
final  value 81.152852 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.201739 
iter  10 value 94.297301
iter  20 value 94.293039
iter  30 value 92.709914
iter  40 value 91.952771
iter  50 value 91.663103
iter  60 value 91.364806
iter  60 value 91.364805
iter  60 value 91.364805
final  value 91.364805 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.199267 
iter  10 value 94.300166
iter  20 value 94.296566
iter  30 value 94.294972
iter  40 value 94.292203
iter  50 value 92.818063
iter  60 value 82.629134
iter  70 value 82.626880
iter  80 value 82.304966
iter  90 value 82.265585
iter  90 value 82.265585
iter  90 value 82.265585
final  value 82.265585 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.559363 
iter  10 value 87.750002
iter  20 value 87.319381
iter  30 value 87.313016
iter  40 value 87.312663
iter  50 value 87.288277
iter  60 value 87.286777
iter  70 value 87.286201
iter  80 value 87.218086
iter  90 value 83.883757
iter 100 value 82.849810
final  value 82.849810 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.567618 
iter  10 value 94.493546
iter  20 value 94.456118
iter  30 value 85.975728
iter  40 value 85.964442
iter  50 value 85.953335
iter  60 value 85.927558
iter  70 value 85.925909
final  value 85.925644 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.352422 
iter  10 value 92.483274
iter  20 value 90.800710
iter  30 value 90.709678
iter  40 value 90.703090
iter  50 value 90.560400
iter  60 value 90.418083
iter  70 value 90.414679
final  value 90.411958 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.872299 
iter  10 value 94.488803
iter  20 value 94.487259
iter  30 value 85.394719
iter  40 value 83.316189
iter  50 value 83.191844
final  value 83.191397 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.825192 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.830550 
final  value 94.483810 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.270438 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 122.614909 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.101752 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.266740 
iter  10 value 94.379772
final  value 94.344733 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.298334 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.562979 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.057160 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.496266 
iter  10 value 88.929290
iter  20 value 85.881016
iter  30 value 84.966592
final  value 84.960590 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.178771 
final  value 94.052434 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.739589 
iter  10 value 93.889165
iter  20 value 93.245886
iter  30 value 92.326931
iter  40 value 88.330356
iter  50 value 88.151705
iter  60 value 88.146961
iter  70 value 88.146920
iter  70 value 88.146919
iter  70 value 88.146919
final  value 88.146919 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.956310 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 131.232492 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.291812 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.916366 
iter  10 value 94.398730
iter  20 value 90.116039
iter  30 value 88.114336
iter  40 value 84.052704
iter  50 value 83.075699
iter  60 value 82.514679
iter  70 value 82.251912
iter  80 value 82.152255
iter  90 value 82.087580
final  value 82.087519 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.628737 
iter  10 value 94.478879
iter  20 value 88.765001
iter  30 value 87.870523
iter  40 value 86.982908
iter  50 value 86.357729
iter  60 value 86.207600
iter  70 value 86.195967
iter  80 value 86.158323
final  value 86.157554 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.069490 
iter  10 value 94.531639
iter  20 value 90.544746
iter  30 value 87.601574
iter  40 value 87.185398
iter  50 value 84.830002
iter  60 value 84.754874
iter  70 value 83.440673
iter  80 value 82.230139
iter  90 value 82.088571
iter 100 value 82.087519
final  value 82.087519 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 108.188460 
iter  10 value 94.470102
iter  20 value 93.572940
iter  30 value 88.786245
iter  40 value 88.024784
iter  50 value 87.296185
iter  60 value 87.089668
iter  70 value 87.071408
iter  80 value 86.368107
iter  90 value 85.723404
final  value 85.722505 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.703745 
iter  10 value 94.490609
iter  20 value 93.886492
iter  30 value 88.076072
iter  40 value 87.739299
iter  50 value 87.549570
iter  60 value 86.567531
iter  70 value 86.151880
iter  80 value 86.013664
iter  90 value 85.583978
iter 100 value 82.455872
final  value 82.455872 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.725991 
iter  10 value 94.599492
iter  20 value 94.490241
iter  30 value 93.734903
iter  40 value 93.585648
iter  50 value 89.231489
iter  60 value 88.155964
iter  70 value 85.075764
iter  80 value 83.984268
iter  90 value 83.490454
iter 100 value 83.417126
final  value 83.417126 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.746628 
iter  10 value 94.908593
iter  20 value 89.813048
iter  30 value 85.625725
iter  40 value 82.864546
iter  50 value 82.592688
iter  60 value 82.454705
iter  70 value 82.244074
iter  80 value 82.006235
iter  90 value 81.744612
iter 100 value 81.522880
final  value 81.522880 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.526387 
iter  10 value 94.429891
iter  20 value 89.039700
iter  30 value 88.413845
iter  40 value 88.076783
iter  50 value 84.857316
iter  60 value 82.066476
iter  70 value 81.631496
iter  80 value 81.577424
iter  90 value 81.539979
iter 100 value 81.506055
final  value 81.506055 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.616562 
iter  10 value 94.585117
iter  20 value 89.911519
iter  30 value 85.922817
iter  40 value 85.056778
iter  50 value 83.678044
iter  60 value 82.100548
iter  70 value 81.846719
iter  80 value 81.521452
iter  90 value 81.265708
iter 100 value 81.001204
final  value 81.001204 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.386803 
iter  10 value 94.499100
iter  20 value 90.557795
iter  30 value 89.274352
iter  40 value 89.171732
iter  50 value 88.637367
iter  60 value 87.037221
iter  70 value 83.978649
iter  80 value 83.355884
iter  90 value 82.559768
iter 100 value 82.076189
final  value 82.076189 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.281366 
iter  10 value 94.168311
iter  20 value 93.595114
iter  30 value 85.423141
iter  40 value 82.842267
iter  50 value 82.087789
iter  60 value 81.099241
iter  70 value 80.741175
iter  80 value 80.662656
iter  90 value 80.617713
iter 100 value 80.448316
final  value 80.448316 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.440265 
iter  10 value 96.685973
iter  20 value 95.559132
iter  30 value 88.245720
iter  40 value 83.635738
iter  50 value 81.629560
iter  60 value 81.503332
iter  70 value 80.934121
iter  80 value 80.478430
iter  90 value 80.249928
iter 100 value 80.195517
final  value 80.195517 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.888132 
iter  10 value 95.099160
iter  20 value 93.783074
iter  30 value 93.392069
iter  40 value 88.595377
iter  50 value 86.502462
iter  60 value 83.725266
iter  70 value 82.908195
iter  80 value 82.084168
iter  90 value 81.990998
iter 100 value 81.955559
final  value 81.955559 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.272319 
iter  10 value 94.027249
iter  20 value 88.284238
iter  30 value 87.006536
iter  40 value 86.593129
iter  50 value 85.307085
iter  60 value 82.584287
iter  70 value 81.947081
iter  80 value 81.722817
iter  90 value 81.270816
iter 100 value 81.082954
final  value 81.082954 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.681276 
iter  10 value 94.519493
iter  20 value 93.940934
iter  30 value 90.082080
iter  40 value 88.578180
iter  50 value 87.117680
iter  60 value 86.798859
iter  70 value 86.224110
iter  80 value 83.597571
iter  90 value 82.347792
iter 100 value 81.112600
final  value 81.112600 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.852189 
final  value 94.485918 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.730391 
final  value 94.485803 
converged
Fitting Repeat 3 

# weights:  103
initial  value 93.200567 
iter  10 value 85.933892
iter  20 value 85.821395
iter  30 value 85.816822
iter  40 value 85.815906
iter  50 value 85.565870
iter  60 value 85.153632
iter  70 value 84.966614
iter  80 value 84.965559
iter  90 value 84.505181
final  value 84.481117 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.665339 
final  value 94.485989 
converged
Fitting Repeat 5 

# weights:  103
initial  value 119.173793 
final  value 94.485849 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.980479 
iter  10 value 94.489055
iter  20 value 94.484236
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.599555 
iter  10 value 94.489453
iter  20 value 94.484574
iter  30 value 94.484497
final  value 94.484301 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.261099 
iter  10 value 91.760398
iter  20 value 91.126103
iter  30 value 89.405427
iter  40 value 86.367449
iter  50 value 86.114907
iter  60 value 85.919982
iter  70 value 85.784272
final  value 85.784252 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.653593 
iter  10 value 94.489366
iter  20 value 94.484426
iter  30 value 93.692418
iter  40 value 87.928319
final  value 87.923531 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.887578 
iter  10 value 94.359974
iter  20 value 93.988430
iter  30 value 93.912417
final  value 93.912312 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.386998 
iter  10 value 94.491959
iter  20 value 93.033450
iter  30 value 86.340840
iter  40 value 86.203648
iter  50 value 85.848691
iter  60 value 84.151584
iter  70 value 81.199167
iter  80 value 79.979297
iter  90 value 79.945501
iter 100 value 79.943169
final  value 79.943169 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.263293 
iter  10 value 94.491829
iter  20 value 93.806400
final  value 93.660522 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.239237 
iter  10 value 94.492171
iter  20 value 94.338038
iter  30 value 93.913183
iter  40 value 93.642038
iter  50 value 92.226292
iter  60 value 89.334619
iter  70 value 88.267249
iter  80 value 87.523812
iter  90 value 87.521209
iter 100 value 87.239991
final  value 87.239991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.653580 
iter  10 value 94.153353
iter  20 value 94.003506
iter  30 value 93.816980
iter  40 value 88.389602
iter  50 value 87.243810
iter  60 value 87.234405
iter  70 value 87.234268
iter  70 value 87.234268
final  value 87.234268 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.337150 
iter  10 value 91.964885
iter  20 value 89.642865
iter  30 value 87.601760
iter  40 value 87.597571
iter  50 value 87.587693
iter  60 value 87.228618
iter  70 value 87.214675
iter  80 value 87.212088
iter  90 value 87.209506
iter 100 value 86.993322
final  value 86.993322 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 129.910831 
iter  10 value 113.425730
iter  20 value 112.859262
iter  30 value 112.815997
iter  40 value 111.387841
iter  50 value 111.387028
iter  60 value 109.353537
iter  70 value 108.328630
iter  80 value 108.283859
iter  90 value 105.087738
iter 100 value 104.940172
final  value 104.940172 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 129.033490 
iter  10 value 117.870771
iter  20 value 117.673724
iter  30 value 106.061757
iter  40 value 105.037477
iter  50 value 104.836513
final  value 104.829181 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.622476 
iter  10 value 117.894642
iter  20 value 117.828771
iter  30 value 111.649945
iter  40 value 111.543936
iter  50 value 111.542108
iter  60 value 110.508931
iter  70 value 110.448214
iter  80 value 110.438447
iter  90 value 110.437442
iter 100 value 110.436541
final  value 110.436541 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.256531 
iter  10 value 107.459576
iter  20 value 107.168248
iter  30 value 107.162364
iter  40 value 106.477902
iter  50 value 103.584410
iter  60 value 102.910899
iter  70 value 102.904436
iter  80 value 102.765326
iter  90 value 102.126530
iter 100 value 101.625948
final  value 101.625948 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.408900 
iter  10 value 117.763491
iter  20 value 113.346497
iter  30 value 107.220140
iter  40 value 107.165976
iter  50 value 107.162172
iter  60 value 105.956728
iter  70 value 104.693352
iter  80 value 104.679152
iter  90 value 104.643474
iter 100 value 103.476372
final  value 103.476372 
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 -- Wed May  6 01:04:49 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 
 40.335   1.259  91.653