##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* 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
corr_plot     34.571  0.462  35.095
var_imp       33.863  0.678  34.564
FSmethod      33.492  0.523  34.015
pred_ensembel 13.335  0.282  12.276
enrichfindP    0.580  0.037  10.105
* 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-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.16.1’
** 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 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 95.208552 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.900526 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.037083 
iter  10 value 93.234390
iter  20 value 93.233385
iter  20 value 93.233384
iter  20 value 93.233384
final  value 93.233384 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.559053 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.598575 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.128605 
iter  10 value 92.999221
iter  20 value 92.717727
iter  30 value 92.651636
final  value 92.651629 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.635997 
iter  10 value 93.836067
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.423782 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.573950 
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.873434 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.826671 
iter  10 value 92.148283
iter  20 value 88.321040
iter  30 value 88.313973
final  value 88.313950 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.905798 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.673150 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.836085 
iter  10 value 92.632807
iter  20 value 92.211112
iter  20 value 92.211111
iter  20 value 92.211111
final  value 92.211111 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.962494 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.017383 
iter  10 value 93.817346
iter  20 value 92.131199
iter  30 value 85.618942
iter  40 value 85.225420
iter  50 value 85.192944
final  value 85.192936 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.484664 
iter  10 value 94.032419
iter  20 value 92.812238
iter  30 value 85.834597
iter  40 value 84.989277
iter  50 value 83.001584
iter  60 value 82.500517
iter  70 value 82.493645
final  value 82.493632 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.602529 
iter  10 value 93.920697
iter  20 value 89.151161
iter  30 value 86.485003
iter  40 value 85.727838
iter  50 value 85.439604
iter  60 value 85.415653
iter  70 value 85.407490
iter  70 value 85.407490
iter  70 value 85.407490
final  value 85.407490 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.427983 
iter  10 value 93.924545
iter  20 value 93.211354
iter  30 value 93.139305
iter  40 value 91.817118
iter  50 value 85.608967
iter  60 value 83.848629
iter  70 value 83.616723
iter  80 value 83.496787
iter  90 value 83.372597
iter 100 value 83.080038
final  value 83.080038 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.527694 
iter  10 value 94.027808
iter  20 value 87.083067
iter  30 value 85.375725
iter  40 value 85.210512
iter  50 value 84.974202
iter  60 value 84.837520
iter  70 value 84.832737
final  value 84.832711 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.023436 
iter  10 value 94.054416
iter  20 value 93.481998
iter  30 value 90.202022
iter  40 value 87.635862
iter  50 value 86.446927
iter  60 value 85.722534
iter  70 value 85.638226
iter  80 value 83.493527
iter  90 value 82.575661
iter 100 value 82.279494
final  value 82.279494 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.176006 
iter  10 value 94.393691
iter  20 value 93.775715
iter  30 value 92.425836
iter  40 value 88.936855
iter  50 value 85.400591
iter  60 value 84.526368
iter  70 value 84.134435
iter  80 value 83.923202
iter  90 value 83.886868
iter 100 value 83.585859
final  value 83.585859 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.442397 
iter  10 value 93.955803
iter  20 value 93.103503
iter  30 value 89.909890
iter  40 value 84.723346
iter  50 value 82.877749
iter  60 value 82.320970
iter  70 value 81.960664
iter  80 value 81.714614
iter  90 value 81.618270
iter 100 value 81.416707
final  value 81.416707 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.515416 
iter  10 value 94.016961
iter  20 value 93.566360
iter  30 value 91.806899
iter  40 value 87.784336
iter  50 value 83.511054
iter  60 value 82.418017
iter  70 value 82.204264
iter  80 value 81.763966
iter  90 value 81.497330
iter 100 value 81.336349
final  value 81.336349 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.352385 
iter  10 value 94.123880
iter  20 value 93.696435
iter  30 value 93.282546
iter  40 value 89.272616
iter  50 value 87.297835
iter  60 value 85.322514
iter  70 value 84.773442
iter  80 value 82.425825
iter  90 value 81.834736
iter 100 value 81.646653
final  value 81.646653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.573629 
iter  10 value 94.506769
iter  20 value 89.018697
iter  30 value 85.709967
iter  40 value 84.775856
iter  50 value 84.228314
iter  60 value 83.741668
iter  70 value 83.112712
iter  80 value 81.893301
iter  90 value 81.574217
iter 100 value 81.235225
final  value 81.235225 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.307790 
iter  10 value 95.646073
iter  20 value 87.604902
iter  30 value 85.635618
iter  40 value 85.403286
iter  50 value 85.190022
iter  60 value 84.827258
iter  70 value 84.645614
iter  80 value 83.754552
iter  90 value 82.698604
iter 100 value 82.144022
final  value 82.144022 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.716342 
iter  10 value 94.484061
iter  20 value 87.521106
iter  30 value 85.861126
iter  40 value 85.739172
iter  50 value 84.447756
iter  60 value 82.087954
iter  70 value 81.719444
iter  80 value 81.273260
iter  90 value 81.033100
iter 100 value 80.968229
final  value 80.968229 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.882710 
iter  10 value 94.790591
iter  20 value 92.769110
iter  30 value 87.616583
iter  40 value 86.440663
iter  50 value 85.950246
iter  60 value 85.301620
iter  70 value 85.123117
iter  80 value 83.969292
iter  90 value 83.168690
iter 100 value 82.938731
final  value 82.938731 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.389563 
iter  10 value 93.940504
iter  20 value 88.995174
iter  30 value 88.251016
iter  40 value 86.632194
iter  50 value 83.879501
iter  60 value 83.485105
iter  70 value 82.484421
iter  80 value 82.288116
iter  90 value 82.202781
iter 100 value 82.128132
final  value 82.128132 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.916564 
final  value 94.054870 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.282113 
final  value 94.054325 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.042139 
final  value 94.054593 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.550485 
final  value 94.054453 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.713323 
final  value 94.054683 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.734888 
iter  10 value 93.834154
iter  20 value 90.568279
iter  30 value 87.613467
iter  40 value 85.822342
iter  50 value 85.061974
iter  60 value 85.022392
iter  70 value 84.842836
iter  80 value 83.753141
iter  90 value 82.074665
iter 100 value 81.624361
final  value 81.624361 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.405848 
iter  10 value 94.057671
iter  20 value 94.052922
iter  30 value 93.467818
iter  40 value 93.369295
iter  50 value 89.316986
iter  60 value 89.237550
iter  70 value 84.999001
iter  80 value 83.009835
iter  90 value 82.351339
iter 100 value 82.349861
final  value 82.349861 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.369098 
iter  10 value 93.637770
iter  20 value 93.388948
iter  30 value 93.382665
iter  40 value 93.381402
final  value 93.378691 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.779963 
iter  10 value 93.840768
iter  20 value 93.378289
iter  30 value 93.377955
final  value 93.377790 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.228542 
iter  10 value 94.057812
iter  20 value 93.909245
iter  30 value 88.972034
iter  40 value 86.253401
iter  50 value 86.251393
iter  60 value 85.639165
iter  70 value 85.453095
iter  80 value 85.250139
iter  90 value 85.080304
iter 100 value 85.014956
final  value 85.014956 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.958474 
iter  10 value 94.063476
iter  20 value 94.055748
final  value 94.055745 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.762571 
iter  10 value 94.059762
iter  20 value 87.461889
iter  30 value 87.047995
iter  40 value 86.604983
iter  50 value 85.329835
iter  60 value 84.832581
iter  70 value 84.014984
iter  80 value 81.334329
iter  90 value 81.124134
iter 100 value 81.122011
final  value 81.122011 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.083498 
iter  10 value 85.739118
iter  20 value 85.022843
iter  30 value 85.016107
iter  40 value 85.012959
iter  50 value 85.012194
iter  60 value 84.924952
iter  70 value 84.883815
final  value 84.882426 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.568302 
iter  10 value 94.061201
iter  20 value 94.042737
iter  30 value 86.717871
iter  40 value 84.740519
iter  50 value 81.285868
iter  60 value 80.234830
iter  70 value 79.757364
iter  80 value 79.633286
iter  90 value 79.600918
iter 100 value 79.597993
final  value 79.597993 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.495601 
iter  10 value 87.217354
iter  20 value 85.526366
iter  30 value 85.424365
iter  40 value 85.287464
iter  50 value 85.282999
iter  60 value 84.369542
iter  70 value 82.655526
iter  80 value 80.737139
iter  90 value 80.512038
iter 100 value 80.511546
final  value 80.511546 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.417544 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 117.188905 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.398135 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.622727 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.445603 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.690549 
iter  10 value 93.807659
iter  20 value 93.714288
iter  20 value 93.714288
iter  20 value 93.714288
final  value 93.714288 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.266951 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.800805 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.694579 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.382614 
final  value 93.582417 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.034332 
final  value 92.861582 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.669534 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.069250 
iter  10 value 93.523810
iter  10 value 93.523810
iter  10 value 93.523810
final  value 93.523810 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.463718 
iter  10 value 93.714293
final  value 93.714286 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.183484 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.581570 
iter  10 value 94.053006
iter  20 value 85.762464
iter  30 value 85.430947
iter  40 value 84.770110
iter  50 value 84.602671
final  value 84.601693 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.872547 
iter  10 value 94.060047
iter  20 value 91.869274
iter  30 value 90.116088
iter  40 value 84.878440
iter  50 value 84.639284
iter  60 value 84.047370
iter  70 value 83.104471
iter  80 value 83.071264
iter  90 value 82.989069
iter 100 value 82.906306
final  value 82.906306 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.507028 
iter  10 value 94.031121
iter  20 value 93.316653
iter  30 value 93.218071
iter  40 value 93.120571
iter  50 value 92.689847
iter  60 value 88.747617
iter  70 value 88.274960
iter  80 value 85.926779
iter  90 value 83.393345
iter 100 value 83.035594
final  value 83.035594 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.051417 
iter  10 value 92.605028
iter  20 value 85.973542
iter  30 value 85.465807
iter  40 value 84.989560
iter  50 value 83.735617
iter  60 value 82.942650
iter  70 value 82.904920
final  value 82.904816 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.429554 
iter  10 value 94.227898
iter  20 value 93.202650
iter  30 value 86.765832
iter  40 value 85.210105
iter  50 value 84.899458
iter  60 value 84.556301
iter  70 value 82.743393
iter  80 value 82.001675
iter  90 value 81.312836
iter 100 value 81.283746
final  value 81.283746 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.966134 
iter  10 value 94.069512
iter  20 value 91.288889
iter  30 value 87.108385
iter  40 value 86.675345
iter  50 value 84.767450
iter  60 value 83.817616
iter  70 value 82.762470
iter  80 value 82.147003
iter  90 value 81.520841
iter 100 value 81.106237
final  value 81.106237 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.564799 
iter  10 value 93.993155
iter  20 value 88.672023
iter  30 value 86.969565
iter  40 value 83.318538
iter  50 value 82.616592
iter  60 value 82.178072
iter  70 value 80.751116
iter  80 value 80.235406
iter  90 value 80.142937
iter 100 value 80.101778
final  value 80.101778 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.339038 
iter  10 value 94.072782
iter  20 value 87.345773
iter  30 value 86.441152
iter  40 value 83.091814
iter  50 value 81.714540
iter  60 value 80.921159
iter  70 value 80.739961
iter  80 value 80.279727
iter  90 value 79.829632
iter 100 value 79.591355
final  value 79.591355 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.575520 
iter  10 value 94.492701
iter  20 value 94.033567
iter  30 value 93.438289
iter  40 value 92.646000
iter  50 value 89.946304
iter  60 value 87.226948
iter  70 value 85.751426
iter  80 value 83.545668
iter  90 value 80.742182
iter 100 value 80.203870
final  value 80.203870 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.030192 
iter  10 value 94.114407
iter  20 value 93.707003
iter  30 value 93.170620
iter  40 value 91.270959
iter  50 value 87.739560
iter  60 value 86.104537
iter  70 value 85.342854
iter  80 value 83.464876
iter  90 value 81.928251
iter 100 value 80.489289
final  value 80.489289 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.814850 
iter  10 value 92.905827
iter  20 value 92.281720
iter  30 value 88.050233
iter  40 value 83.271734
iter  50 value 83.152670
iter  60 value 82.472942
iter  70 value 81.556911
iter  80 value 81.215566
iter  90 value 80.813319
iter 100 value 80.241753
final  value 80.241753 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.103205 
iter  10 value 92.785205
iter  20 value 86.995662
iter  30 value 84.470398
iter  40 value 83.948911
iter  50 value 83.255284
iter  60 value 83.108836
iter  70 value 82.772939
iter  80 value 81.282566
iter  90 value 80.924128
iter 100 value 80.679787
final  value 80.679787 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.700316 
iter  10 value 93.936779
iter  20 value 92.267825
iter  30 value 85.566142
iter  40 value 83.581472
iter  50 value 81.944535
iter  60 value 81.219859
iter  70 value 80.553843
iter  80 value 80.325020
iter  90 value 80.160526
iter 100 value 79.826807
final  value 79.826807 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.910494 
iter  10 value 93.363344
iter  20 value 85.196314
iter  30 value 84.229175
iter  40 value 84.096934
iter  50 value 83.480055
iter  60 value 83.084709
iter  70 value 82.891324
iter  80 value 82.630241
iter  90 value 81.523768
iter 100 value 80.266968
final  value 80.266968 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.884698 
iter  10 value 95.190524
iter  20 value 94.124138
iter  30 value 92.259035
iter  40 value 86.495155
iter  50 value 85.349156
iter  60 value 84.306633
iter  70 value 83.334248
iter  80 value 82.200094
iter  90 value 81.540853
iter 100 value 81.241658
final  value 81.241658 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.374165 
final  value 94.054470 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.797626 
final  value 94.054489 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.644003 
iter  10 value 93.584374
iter  20 value 93.534532
iter  30 value 85.902039
iter  40 value 85.886079
iter  40 value 85.886079
final  value 85.886079 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.286656 
final  value 94.054534 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.533627 
final  value 94.054612 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.503976 
iter  10 value 93.587264
iter  20 value 93.290856
iter  30 value 85.481033
iter  40 value 85.254619
iter  50 value 85.076793
iter  60 value 84.980939
iter  70 value 83.995087
iter  80 value 83.719466
iter  90 value 83.710311
iter 100 value 83.709082
final  value 83.709082 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.212799 
iter  10 value 93.908768
iter  20 value 93.902510
iter  30 value 91.203245
iter  40 value 89.928724
iter  50 value 86.385252
iter  60 value 86.175292
iter  70 value 83.615234
iter  80 value 82.891494
final  value 82.891114 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.639974 
iter  10 value 94.057294
iter  20 value 94.045092
iter  30 value 84.391379
iter  40 value 84.335044
iter  50 value 84.122053
final  value 84.117640 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.226727 
iter  10 value 93.587379
iter  20 value 89.469366
iter  30 value 87.509616
iter  40 value 87.402329
iter  50 value 87.310610
final  value 87.308948 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.391683 
iter  10 value 94.057589
iter  20 value 93.903058
final  value 93.193059 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.489681 
iter  10 value 93.590780
iter  20 value 93.359537
iter  30 value 87.168442
iter  40 value 86.571937
final  value 86.571885 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.590578 
iter  10 value 94.060871
iter  20 value 94.044891
iter  30 value 93.193863
iter  30 value 93.193862
iter  30 value 93.193862
final  value 93.193862 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.485208 
iter  10 value 94.060734
iter  20 value 93.779552
final  value 93.192698 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.421251 
iter  10 value 85.578243
iter  20 value 84.082083
iter  30 value 84.073916
iter  40 value 83.935058
iter  50 value 83.875147
iter  60 value 83.869167
iter  70 value 83.629346
iter  80 value 81.659629
iter  90 value 80.734190
iter 100 value 80.576995
final  value 80.576995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.403501 
iter  10 value 93.919330
iter  20 value 93.410915
iter  30 value 93.384887
iter  40 value 93.016781
iter  50 value 92.900608
iter  60 value 86.344251
iter  70 value 83.951787
iter  80 value 83.623054
iter  90 value 82.471680
iter 100 value 79.451723
final  value 79.451723 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.486404 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.162196 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.466879 
iter  10 value 93.900280
final  value 93.900041 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.297220 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.827813 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.455283 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.316883 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.428234 
final  value 94.400000 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.654679 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.819589 
iter  10 value 94.149191
iter  20 value 94.055917
final  value 94.055814 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.171544 
iter  10 value 94.390910
iter  10 value 94.390909
iter  10 value 94.390909
final  value 94.390909 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.965481 
final  value 94.473119 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.755289 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.029301 
iter  10 value 88.076521
iter  20 value 84.102414
iter  30 value 83.962481
iter  40 value 83.895333
iter  50 value 83.284485
iter  60 value 83.279621
iter  70 value 83.275650
iter  80 value 82.178087
iter  90 value 82.094791
iter 100 value 82.084452
final  value 82.084452 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.361721 
iter  10 value 94.473118
iter  10 value 94.473118
iter  10 value 94.473118
final  value 94.473118 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.110397 
iter  10 value 94.486477
iter  20 value 94.347383
iter  30 value 88.199215
iter  40 value 86.075598
iter  50 value 85.222980
iter  60 value 84.295445
iter  70 value 83.949618
final  value 83.949476 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.011681 
iter  10 value 94.482685
iter  20 value 84.711235
iter  30 value 84.344074
iter  40 value 84.106309
iter  50 value 83.200517
iter  60 value 82.976489
iter  70 value 82.942136
iter  80 value 82.938224
iter  90 value 82.936775
final  value 82.936759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.136272 
iter  10 value 94.555768
iter  20 value 94.484439
iter  30 value 94.220403
iter  40 value 94.103807
iter  50 value 94.083776
iter  60 value 94.001236
iter  70 value 89.668275
iter  80 value 87.652721
iter  90 value 87.022516
iter 100 value 84.466265
final  value 84.466265 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.545433 
iter  10 value 94.488901
iter  20 value 92.234401
iter  30 value 87.992417
iter  40 value 86.875400
iter  50 value 86.646281
iter  60 value 83.909617
iter  70 value 83.693689
iter  80 value 83.499221
iter  90 value 83.488276
iter 100 value 83.487215
final  value 83.487215 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.595312 
iter  10 value 94.442483
iter  20 value 88.213456
iter  30 value 86.997528
iter  40 value 84.914113
iter  50 value 84.269230
iter  60 value 83.951276
final  value 83.949477 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.822944 
iter  10 value 94.562458
iter  20 value 90.301941
iter  30 value 85.388709
iter  40 value 84.020925
iter  50 value 83.863017
iter  60 value 83.806096
iter  70 value 82.538378
iter  80 value 82.472394
iter  90 value 82.455575
iter 100 value 82.371262
final  value 82.371262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.129181 
iter  10 value 86.619208
iter  20 value 85.162241
iter  30 value 84.956850
iter  40 value 82.992067
iter  50 value 82.624926
iter  60 value 82.002506
iter  70 value 81.512387
iter  80 value 81.351587
iter  90 value 81.342018
iter 100 value 81.327608
final  value 81.327608 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.150377 
iter  10 value 94.412399
iter  20 value 93.058480
iter  30 value 92.413715
iter  40 value 92.194233
iter  50 value 86.624793
iter  60 value 83.012867
iter  70 value 82.498495
iter  80 value 82.149844
iter  90 value 81.961421
iter 100 value 81.731691
final  value 81.731691 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.491569 
iter  10 value 94.304433
iter  20 value 93.245907
iter  30 value 82.570897
iter  40 value 80.497642
iter  50 value 79.786023
iter  60 value 79.600712
iter  70 value 79.463636
iter  80 value 79.433745
iter  90 value 79.354159
iter 100 value 79.312663
final  value 79.312663 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.613797 
iter  10 value 94.479567
iter  20 value 91.026425
iter  30 value 89.909177
iter  40 value 86.016850
iter  50 value 83.596801
iter  60 value 83.097226
iter  70 value 82.732158
iter  80 value 82.383125
iter  90 value 80.681804
iter 100 value 80.232754
final  value 80.232754 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.233875 
iter  10 value 94.474612
iter  20 value 90.999864
iter  30 value 88.728278
iter  40 value 87.933685
iter  50 value 86.051100
iter  60 value 82.863602
iter  70 value 81.682468
iter  80 value 81.322529
iter  90 value 81.078280
iter 100 value 80.668824
final  value 80.668824 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.214045 
iter  10 value 94.290883
iter  20 value 85.312582
iter  30 value 84.247327
iter  40 value 83.795215
iter  50 value 82.139218
iter  60 value 80.788531
iter  70 value 79.997556
iter  80 value 79.768563
iter  90 value 79.659979
iter 100 value 79.409717
final  value 79.409717 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.455876 
iter  10 value 95.685985
iter  20 value 93.827508
iter  30 value 88.197109
iter  40 value 83.722282
iter  50 value 82.757093
iter  60 value 82.184501
iter  70 value 80.835974
iter  80 value 80.294007
iter  90 value 79.967041
iter 100 value 79.715639
final  value 79.715639 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.293100 
iter  10 value 94.650620
iter  20 value 86.231092
iter  30 value 84.026668
iter  40 value 83.176266
iter  50 value 82.930975
iter  60 value 82.666401
iter  70 value 82.547329
iter  80 value 82.490823
iter  90 value 82.434388
iter 100 value 82.291976
final  value 82.291976 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.444272 
iter  10 value 95.892815
iter  20 value 94.874320
iter  30 value 88.287197
iter  40 value 86.677820
iter  50 value 86.341766
iter  60 value 86.297762
iter  70 value 85.721617
iter  80 value 83.576696
iter  90 value 81.626540
iter 100 value 80.877508
final  value 80.877508 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.512366 
final  value 94.474494 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.968685 
final  value 94.485722 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.099063 
final  value 94.485687 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.066313 
final  value 94.485671 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.257459 
final  value 94.485803 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.113383 
iter  10 value 94.478241
iter  20 value 94.473770
iter  30 value 94.430352
iter  40 value 84.141489
iter  50 value 84.041434
iter  60 value 83.636398
iter  70 value 83.144896
iter  80 value 83.144264
iter  90 value 83.142488
iter 100 value 82.901029
final  value 82.901029 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.678090 
iter  10 value 94.489135
iter  20 value 94.483546
iter  30 value 90.023481
iter  40 value 85.547652
iter  50 value 85.128155
iter  60 value 82.200795
iter  70 value 82.068310
iter  80 value 81.267034
iter  90 value 80.811448
iter 100 value 80.809897
final  value 80.809897 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.331230 
iter  10 value 94.491134
iter  20 value 92.095894
iter  30 value 83.801850
iter  40 value 83.740080
iter  50 value 83.738425
iter  60 value 83.733003
iter  70 value 83.732694
iter  80 value 83.730428
iter  90 value 83.725043
final  value 83.724897 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.605947 
iter  10 value 94.488294
iter  20 value 94.449756
iter  30 value 84.494493
iter  40 value 84.021047
iter  50 value 80.842935
iter  60 value 79.150447
iter  70 value 79.146137
iter  80 value 79.116785
iter  90 value 79.103921
iter 100 value 78.843288
final  value 78.843288 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.691101 
iter  10 value 94.487382
iter  20 value 93.990765
iter  30 value 92.427756
iter  40 value 84.072345
iter  50 value 81.874020
iter  60 value 80.226530
iter  70 value 79.508071
iter  80 value 79.246890
iter  90 value 78.965938
iter 100 value 78.526173
final  value 78.526173 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.206544 
iter  10 value 94.494592
iter  20 value 94.468692
iter  30 value 94.097505
iter  40 value 94.066230
iter  50 value 94.064893
iter  60 value 93.983416
iter  70 value 89.100384
iter  80 value 85.910036
iter  90 value 82.006101
iter 100 value 80.571922
final  value 80.571922 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.868302 
iter  10 value 94.481925
iter  20 value 94.407468
iter  30 value 94.392080
iter  30 value 94.392080
iter  30 value 94.392080
final  value 94.392080 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.788708 
iter  10 value 94.241905
iter  20 value 94.239656
iter  30 value 93.588464
iter  40 value 92.811931
iter  50 value 92.811416
iter  60 value 92.702862
iter  70 value 87.688608
iter  80 value 85.090746
iter  90 value 83.762930
iter 100 value 80.698870
final  value 80.698870 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.280995 
iter  10 value 94.480981
iter  20 value 94.434519
iter  30 value 92.799053
iter  40 value 88.296402
iter  50 value 88.277242
iter  60 value 88.276706
iter  70 value 87.410951
iter  80 value 87.169366
iter  90 value 87.167516
iter 100 value 86.929905
final  value 86.929905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.347332 
iter  10 value 94.492413
final  value 94.484519 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.990167 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.202607 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.355169 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.798488 
iter  10 value 90.913859
iter  20 value 90.913052
final  value 90.913044 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.310580 
final  value 94.326054 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.405197 
iter  10 value 90.349343
iter  20 value 80.265055
final  value 80.257496 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.948921 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.179564 
iter  10 value 94.333759
final  value 94.326051 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.289161 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.261588 
iter  10 value 94.484294
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.269143 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.479738 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.351256 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.974618 
iter  10 value 88.711835
iter  20 value 88.706777
iter  30 value 88.685834
iter  40 value 88.683958
final  value 88.683951 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.392257 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.408035 
iter  10 value 86.589064
iter  20 value 81.818752
iter  30 value 81.555706
iter  40 value 81.507322
iter  50 value 81.462313
iter  60 value 80.709690
iter  70 value 78.743925
iter  80 value 77.560810
iter  90 value 77.456448
iter 100 value 77.272852
final  value 77.272852 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.352696 
iter  10 value 94.488558
iter  20 value 84.350209
iter  30 value 82.911086
iter  40 value 82.745365
iter  50 value 82.663907
iter  60 value 82.547509
iter  70 value 80.696845
iter  80 value 77.821060
iter  90 value 76.931186
iter 100 value 76.922935
final  value 76.922935 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.295933 
iter  10 value 94.488496
iter  20 value 85.311861
iter  30 value 81.975291
iter  40 value 81.623807
iter  50 value 81.134547
iter  60 value 78.365593
iter  70 value 77.862750
iter  80 value 77.802317
final  value 77.753022 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.850407 
iter  10 value 94.488546
iter  20 value 93.977283
iter  30 value 85.957167
iter  40 value 82.254281
iter  50 value 82.187771
iter  60 value 81.510415
iter  70 value 81.470853
final  value 81.463032 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.438204 
iter  10 value 94.491494
iter  20 value 88.247014
iter  30 value 84.834399
iter  40 value 84.515862
iter  50 value 84.175780
iter  60 value 79.750436
iter  70 value 78.108299
iter  80 value 77.593144
iter  90 value 77.501141
iter 100 value 77.435818
final  value 77.435818 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.830157 
iter  10 value 89.266616
iter  20 value 84.531829
iter  30 value 80.661031
iter  40 value 78.637232
iter  50 value 77.722545
iter  60 value 76.794626
iter  70 value 76.169208
iter  80 value 75.999878
iter  90 value 75.836354
iter 100 value 75.812665
final  value 75.812665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.433196 
iter  10 value 94.617794
iter  20 value 83.264682
iter  30 value 81.118404
iter  40 value 78.548658
iter  50 value 78.300068
iter  60 value 77.644585
iter  70 value 77.352320
iter  80 value 76.756233
iter  90 value 76.592821
iter 100 value 76.241143
final  value 76.241143 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.919158 
iter  10 value 94.133555
iter  20 value 86.975111
iter  30 value 85.722227
iter  40 value 84.133483
iter  50 value 81.129708
iter  60 value 80.105261
iter  70 value 79.075008
iter  80 value 78.419230
iter  90 value 77.513846
iter 100 value 77.296388
final  value 77.296388 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.555025 
iter  10 value 94.609112
iter  20 value 93.716133
iter  30 value 82.050767
iter  40 value 80.253506
iter  50 value 78.478266
iter  60 value 77.731908
iter  70 value 76.234833
iter  80 value 76.002050
iter  90 value 75.937916
iter 100 value 75.745232
final  value 75.745232 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.924381 
iter  10 value 94.488900
iter  20 value 93.909007
iter  30 value 90.947796
iter  40 value 89.032440
iter  50 value 87.236825
iter  60 value 87.148961
iter  70 value 84.366916
iter  80 value 77.430572
iter  90 value 76.722543
iter 100 value 76.156363
final  value 76.156363 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.372145 
iter  10 value 93.876362
iter  20 value 89.264454
iter  30 value 83.749526
iter  40 value 78.954431
iter  50 value 77.724538
iter  60 value 77.243130
iter  70 value 77.058897
iter  80 value 76.945989
iter  90 value 76.926085
iter 100 value 76.884697
final  value 76.884697 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 150.395160 
iter  10 value 94.477831
iter  20 value 87.111091
iter  30 value 82.451266
iter  40 value 81.272096
iter  50 value 80.899799
iter  60 value 79.774931
iter  70 value 78.798799
iter  80 value 78.493405
iter  90 value 77.384656
iter 100 value 76.328658
final  value 76.328658 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.278177 
iter  10 value 94.632153
iter  20 value 91.999551
iter  30 value 89.410631
iter  40 value 86.905859
iter  50 value 83.951337
iter  60 value 80.590066
iter  70 value 79.660251
iter  80 value 77.765206
iter  90 value 77.047165
iter 100 value 76.983740
final  value 76.983740 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.780957 
iter  10 value 91.659915
iter  20 value 88.015252
iter  30 value 80.031927
iter  40 value 79.016476
iter  50 value 78.042678
iter  60 value 77.017017
iter  70 value 76.686586
iter  80 value 76.519701
iter  90 value 76.326213
iter 100 value 76.185339
final  value 76.185339 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.465359 
iter  10 value 94.637190
iter  20 value 93.957160
iter  30 value 83.515389
iter  40 value 82.360454
iter  50 value 79.532372
iter  60 value 78.719738
iter  70 value 77.705428
iter  80 value 76.480753
iter  90 value 76.034414
iter 100 value 75.952550
final  value 75.952550 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.066956 
iter  10 value 94.485596
iter  20 value 94.484224
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.462137 
final  value 94.486051 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.406591 
iter  10 value 90.933442
iter  20 value 90.924585
final  value 90.924088 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.056873 
final  value 94.485892 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.704193 
iter  10 value 90.148833
iter  20 value 89.984610
iter  30 value 89.983891
iter  40 value 89.954663
iter  50 value 89.953702
iter  60 value 89.953085
final  value 89.952860 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.235598 
iter  10 value 94.317238
iter  20 value 94.308776
final  value 94.308501 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.991623 
iter  10 value 94.489237
iter  20 value 94.484460
iter  30 value 88.714318
iter  40 value 81.882223
iter  50 value 81.017865
final  value 81.017457 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.151750 
iter  10 value 94.359392
iter  20 value 89.909979
iter  30 value 89.361640
iter  40 value 89.185412
iter  50 value 88.354928
iter  60 value 88.301484
iter  70 value 88.300273
iter  80 value 88.299919
iter  90 value 88.298615
iter 100 value 88.297954
final  value 88.297954 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.225193 
iter  10 value 94.359063
iter  20 value 91.872486
iter  30 value 82.102807
iter  40 value 81.466201
iter  50 value 77.912756
iter  60 value 75.844548
iter  70 value 75.824871
final  value 75.824704 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.095723 
iter  10 value 90.933562
iter  20 value 90.925525
iter  30 value 90.923047
iter  40 value 90.921197
iter  50 value 88.009085
iter  60 value 87.507251
iter  70 value 85.250930
iter  80 value 84.654655
iter  90 value 84.654284
iter  90 value 84.654283
iter  90 value 84.654283
final  value 84.654283 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.704472 
iter  10 value 90.938091
iter  20 value 90.927147
iter  30 value 90.283590
iter  40 value 85.442256
iter  50 value 84.803921
iter  60 value 84.589276
iter  70 value 75.597186
iter  80 value 75.301921
iter  90 value 75.103994
iter 100 value 75.052153
final  value 75.052153 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.210853 
iter  10 value 87.211086
iter  20 value 85.015032
iter  30 value 84.959882
iter  40 value 82.239194
iter  50 value 78.313031
iter  60 value 76.830949
iter  70 value 76.828481
final  value 76.828310 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.383146 
iter  10 value 90.932334
iter  20 value 90.929728
iter  30 value 90.921974
iter  40 value 86.303871
iter  50 value 79.854842
iter  60 value 79.597684
iter  70 value 79.569700
iter  80 value 79.568333
final  value 79.566282 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.896335 
iter  10 value 94.362536
iter  20 value 94.356711
iter  30 value 94.310100
iter  40 value 94.309115
final  value 94.309094 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.746710 
iter  10 value 94.492961
iter  20 value 94.484262
iter  30 value 92.849689
iter  40 value 92.297399
iter  50 value 92.296458
iter  60 value 92.296165
iter  70 value 92.273078
iter  80 value 92.272136
iter  80 value 92.272136
final  value 92.272136 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.211567 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.084944 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.973759 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.022022 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.175162 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.744124 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.932666 
iter  10 value 86.101454
iter  20 value 85.673271
iter  30 value 85.665780
iter  40 value 85.117108
final  value 85.103437 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.380097 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.435210 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.756482 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.145622 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.462275 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.969969 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.163914 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.985991 
iter  10 value 92.128827
iter  20 value 84.734526
iter  30 value 84.710185
final  value 84.710063 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.332696 
iter  10 value 94.226621
iter  20 value 88.658648
iter  30 value 88.590855
iter  40 value 86.737557
iter  50 value 85.851434
iter  60 value 85.796617
iter  70 value 85.776115
iter  80 value 85.769303
iter  80 value 85.769303
iter  80 value 85.769303
final  value 85.769303 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.689869 
iter  10 value 94.487434
iter  20 value 87.719201
iter  30 value 87.065415
iter  40 value 86.151395
iter  50 value 85.573249
iter  60 value 85.123682
iter  70 value 84.938830
iter  80 value 84.919346
final  value 84.919344 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.032215 
iter  10 value 94.453083
iter  20 value 93.862942
iter  30 value 87.418667
iter  40 value 85.580763
iter  50 value 85.174907
iter  60 value 84.883304
iter  70 value 84.780826
final  value 84.780678 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.364443 
iter  10 value 94.498435
iter  20 value 94.436070
iter  30 value 93.208775
iter  40 value 92.770300
iter  50 value 87.670339
iter  60 value 86.467660
iter  70 value 85.966939
iter  80 value 85.278287
iter  90 value 84.201006
iter 100 value 84.062155
final  value 84.062155 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.541651 
iter  10 value 93.927281
iter  20 value 87.036420
iter  30 value 86.277462
iter  40 value 85.560063
iter  50 value 84.957095
iter  60 value 84.889018
final  value 84.888164 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.046394 
iter  10 value 95.363358
iter  20 value 92.361446
iter  30 value 91.866700
iter  40 value 87.444777
iter  50 value 85.135659
iter  60 value 84.964233
iter  70 value 84.121459
iter  80 value 83.128378
iter  90 value 83.061687
iter 100 value 82.778507
final  value 82.778507 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.485834 
iter  10 value 95.330702
iter  20 value 94.687501
iter  30 value 93.805949
iter  40 value 92.460690
iter  50 value 90.690596
iter  60 value 90.641136
iter  70 value 90.111332
iter  80 value 86.512026
iter  90 value 83.850188
iter 100 value 82.696698
final  value 82.696698 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.784708 
iter  10 value 96.244952
iter  20 value 90.724837
iter  30 value 90.419307
iter  40 value 88.629257
iter  50 value 87.423480
iter  60 value 85.610987
iter  70 value 84.505806
iter  80 value 83.697214
iter  90 value 83.357642
iter 100 value 83.245894
final  value 83.245894 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.285102 
iter  10 value 94.367173
iter  20 value 90.590437
iter  30 value 86.264227
iter  40 value 85.935692
iter  50 value 85.664612
iter  60 value 85.443401
iter  70 value 84.463198
iter  80 value 83.009488
iter  90 value 82.896387
iter 100 value 82.762668
final  value 82.762668 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.724383 
iter  10 value 92.220169
iter  20 value 90.635444
iter  30 value 88.464337
iter  40 value 85.059538
iter  50 value 84.500539
iter  60 value 84.223970
iter  70 value 83.830973
iter  80 value 83.567959
iter  90 value 83.433411
iter 100 value 83.051093
final  value 83.051093 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.675036 
iter  10 value 94.423014
iter  20 value 91.856589
iter  30 value 90.385421
iter  40 value 85.912726
iter  50 value 85.424854
iter  60 value 84.476255
iter  70 value 84.025665
iter  80 value 83.312233
iter  90 value 83.227577
iter 100 value 83.116420
final  value 83.116420 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.053488 
iter  10 value 92.166358
iter  20 value 88.805344
iter  30 value 86.994757
iter  40 value 85.184278
iter  50 value 83.813867
iter  60 value 83.422959
iter  70 value 82.898517
iter  80 value 82.700790
iter  90 value 82.564859
iter 100 value 82.462151
final  value 82.462151 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.365987 
iter  10 value 93.922783
iter  20 value 87.775965
iter  30 value 87.465517
iter  40 value 86.384256
iter  50 value 83.952201
iter  60 value 83.028581
iter  70 value 82.673028
iter  80 value 82.585684
iter  90 value 82.463755
iter 100 value 82.152620
final  value 82.152620 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.728334 
iter  10 value 94.511040
iter  20 value 94.362989
iter  30 value 90.394174
iter  40 value 88.471374
iter  50 value 87.016448
iter  60 value 83.825274
iter  70 value 83.090195
iter  80 value 82.557351
iter  90 value 82.164886
iter 100 value 82.155156
final  value 82.155156 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.433933 
iter  10 value 94.383871
iter  20 value 86.280174
iter  30 value 85.363194
iter  40 value 84.664132
iter  50 value 83.880048
iter  60 value 83.196846
iter  70 value 82.681007
iter  80 value 82.384597
iter  90 value 82.115060
iter 100 value 82.023367
final  value 82.023367 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.129241 
iter  10 value 94.485889
iter  20 value 94.484295
iter  30 value 94.457226
iter  40 value 92.451831
iter  50 value 87.332110
iter  60 value 87.277733
iter  70 value 87.249972
iter  80 value 87.249560
iter  90 value 87.206726
iter 100 value 87.200086
final  value 87.200086 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.498516 
final  value 94.485824 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.461846 
final  value 94.485976 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.176494 
final  value 94.485765 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.035151 
final  value 94.486010 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.364136 
iter  10 value 94.488883
iter  20 value 94.484343
iter  30 value 87.116851
iter  40 value 85.264590
final  value 85.252793 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.936561 
iter  10 value 94.490881
iter  20 value 94.484954
iter  30 value 88.732873
iter  40 value 85.849290
iter  50 value 85.845120
iter  60 value 85.373757
iter  70 value 85.359089
iter  80 value 85.358517
iter  90 value 85.357321
final  value 85.356827 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.159358 
iter  10 value 94.488516
iter  20 value 92.427660
iter  30 value 91.470303
iter  40 value 91.468876
final  value 91.468510 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.359733 
iter  10 value 89.571043
iter  20 value 88.590100
iter  30 value 88.588548
iter  40 value 88.002191
iter  50 value 87.966440
iter  60 value 87.965711
iter  70 value 87.964476
iter  80 value 87.964387
iter  90 value 87.964164
iter 100 value 87.963941
final  value 87.963941 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.809146 
iter  10 value 94.488939
iter  20 value 94.329356
iter  30 value 93.733673
iter  40 value 93.721154
iter  50 value 91.849425
iter  60 value 91.830423
iter  60 value 91.830422
final  value 91.830420 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.909395 
iter  10 value 89.664206
iter  20 value 86.281602
iter  30 value 85.656651
iter  40 value 85.590307
iter  50 value 85.499465
iter  60 value 85.498285
iter  70 value 84.088276
iter  80 value 83.933412
iter  90 value 83.904288
iter 100 value 83.881010
final  value 83.881010 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.832928 
iter  10 value 91.167007
iter  20 value 91.146922
iter  30 value 91.136160
iter  40 value 90.845843
iter  50 value 84.115137
iter  60 value 83.527644
iter  70 value 83.517406
iter  80 value 83.515495
iter  90 value 83.382760
iter 100 value 82.852095
final  value 82.852095 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.064661 
iter  10 value 94.475027
iter  20 value 91.751471
iter  30 value 85.329878
iter  40 value 85.126822
iter  50 value 84.755217
iter  60 value 83.749913
iter  70 value 83.403578
iter  80 value 83.377154
iter  90 value 83.376951
final  value 83.376889 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.424906 
iter  10 value 94.475434
iter  20 value 94.467960
iter  30 value 94.345341
iter  40 value 91.819009
iter  50 value 91.144989
iter  60 value 86.979536
iter  70 value 86.112998
iter  80 value 85.005996
iter  90 value 84.741095
iter 100 value 84.149454
final  value 84.149454 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.438755 
iter  10 value 94.492464
iter  20 value 93.236899
iter  30 value 86.367664
iter  40 value 86.327204
final  value 86.326894 
converged
Fitting Repeat 1 

# weights:  305
initial  value 130.349040 
iter  10 value 117.832985
iter  20 value 109.721133
iter  30 value 107.805195
iter  40 value 104.245035
iter  50 value 102.056254
iter  60 value 101.789766
iter  70 value 101.640675
iter  80 value 101.390586
iter  90 value 101.135452
iter 100 value 101.049142
final  value 101.049142 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.390483 
iter  10 value 115.549772
iter  20 value 106.104006
iter  30 value 105.784751
iter  40 value 104.876703
iter  50 value 103.671697
iter  60 value 103.633185
iter  70 value 103.504494
iter  80 value 102.749808
iter  90 value 101.320782
iter 100 value 101.293405
final  value 101.293405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.873675 
iter  10 value 117.935314
iter  20 value 108.273015
iter  30 value 105.770634
iter  40 value 105.152350
iter  50 value 104.980689
iter  60 value 103.354809
iter  70 value 102.161214
iter  80 value 101.806714
iter  90 value 101.144546
iter 100 value 100.646417
final  value 100.646417 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 130.932983 
iter  10 value 119.453051
iter  20 value 117.689075
iter  30 value 117.623796
iter  40 value 108.081682
iter  50 value 105.882538
iter  60 value 105.451371
iter  70 value 104.895005
iter  80 value 103.234604
iter  90 value 102.659649
iter 100 value 101.772537
final  value 101.772537 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 139.057617 
iter  10 value 118.860025
iter  20 value 111.200233
iter  30 value 106.769519
iter  40 value 105.245249
iter  50 value 104.741734
iter  60 value 102.733302
iter  70 value 102.185322
iter  80 value 101.842854
iter  90 value 101.819188
iter 100 value 101.809242
final  value 101.809242 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Mar 31 00:25:06 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 
 41.006   1.052 104.005