##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-11-04 r88984)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* 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 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 ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
  Code: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 FALSE, filename = "plots.pdf")
  Docs: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 TRUE, filename = "plots.pdf")
  Mismatches in argument default values:
    Name: 'plots' Code: FALSE Docs: TRUE

* 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      19.129  0.876  20.532
corr_plot     19.015  0.934  20.547
var_imp       18.644  0.933  20.430
pred_ensembel  6.435  0.126   6.183
enrichfindP    0.194  0.036  13.501
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 WARNING, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.1’
** 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 Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 110.666195 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.508797 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.148674 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.575308 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.316866 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.780688 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.255726 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.091390 
iter  10 value 93.994012
iter  10 value 93.994012
iter  10 value 93.994012
final  value 93.994012 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.041434 
iter  10 value 90.192046
final  value 90.175439 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.720199 
iter  10 value 90.828915
final  value 90.745185 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.411026 
iter  10 value 93.854212
iter  20 value 88.273052
iter  30 value 88.258611
iter  30 value 88.258611
iter  30 value 88.258611
final  value 88.258611 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.993763 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.519795 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.261619 
final  value 94.043243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.038364 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.774980 
iter  10 value 94.057968
iter  20 value 94.029803
iter  30 value 93.203843
iter  40 value 88.345827
iter  50 value 86.689169
iter  60 value 81.892847
iter  70 value 81.030066
iter  80 value 80.820598
iter  90 value 80.719065
final  value 80.719028 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.956849 
iter  10 value 94.070265
iter  20 value 84.404416
iter  30 value 83.340455
iter  40 value 82.693562
iter  50 value 81.778149
iter  60 value 81.355894
iter  70 value 80.973474
final  value 80.971019 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.146380 
iter  10 value 94.049876
iter  20 value 93.489420
iter  30 value 88.598500
iter  40 value 84.581498
iter  50 value 84.012257
iter  60 value 80.562984
iter  70 value 79.813680
iter  80 value 79.176732
iter  90 value 78.784516
iter 100 value 78.738430
final  value 78.738430 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.665561 
iter  10 value 94.108504
iter  20 value 94.057116
iter  30 value 93.750109
iter  40 value 87.148535
iter  50 value 86.358252
iter  60 value 85.047690
iter  70 value 82.114704
iter  80 value 81.251988
iter  90 value 80.854643
iter 100 value 80.812954
final  value 80.812954 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.239963 
iter  10 value 94.067119
iter  20 value 94.044426
iter  30 value 93.698441
iter  40 value 93.599888
iter  50 value 91.262350
iter  60 value 90.024131
iter  70 value 89.854443
iter  80 value 89.738991
final  value 89.738978 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.652819 
iter  10 value 94.094257
iter  20 value 94.002847
iter  30 value 87.982417
iter  40 value 83.224114
iter  50 value 80.100318
iter  60 value 79.827339
iter  70 value 78.385419
iter  80 value 77.671368
iter  90 value 77.271470
iter 100 value 77.106420
final  value 77.106420 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.381371 
iter  10 value 94.053867
iter  20 value 82.759751
iter  30 value 82.160975
iter  40 value 82.016126
iter  50 value 81.914787
iter  60 value 81.424752
iter  70 value 79.720856
iter  80 value 77.175892
iter  90 value 76.897575
iter 100 value 76.398095
final  value 76.398095 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.256881 
iter  10 value 94.124876
iter  20 value 90.246882
iter  30 value 81.438469
iter  40 value 78.330498
iter  50 value 77.685606
iter  60 value 77.227757
iter  70 value 77.143750
iter  80 value 77.124613
iter  90 value 76.968800
iter 100 value 76.518208
final  value 76.518208 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.572335 
iter  10 value 91.206261
iter  20 value 87.739910
iter  30 value 83.744850
iter  40 value 82.383683
iter  50 value 79.744957
iter  60 value 78.699840
iter  70 value 78.097876
iter  80 value 77.815640
iter  90 value 77.135828
iter 100 value 76.808089
final  value 76.808089 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.539156 
iter  10 value 94.233436
iter  20 value 94.003677
iter  30 value 91.625871
iter  40 value 88.461097
iter  50 value 86.204603
iter  60 value 83.040518
iter  70 value 82.585070
iter  80 value 81.260227
iter  90 value 79.702984
iter 100 value 79.566607
final  value 79.566607 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.492471 
iter  10 value 94.135627
iter  20 value 93.576876
iter  30 value 91.065761
iter  40 value 90.574620
iter  50 value 89.567085
iter  60 value 87.229006
iter  70 value 81.432774
iter  80 value 80.912909
iter  90 value 79.836569
iter 100 value 79.054610
final  value 79.054610 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.493022 
iter  10 value 94.854697
iter  20 value 91.000366
iter  30 value 87.307172
iter  40 value 86.633677
iter  50 value 86.166261
iter  60 value 85.973856
iter  70 value 83.180283
iter  80 value 80.074165
iter  90 value 77.823801
iter 100 value 77.516674
final  value 77.516674 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.993665 
iter  10 value 94.222423
iter  20 value 82.908968
iter  30 value 82.536280
iter  40 value 82.027912
iter  50 value 80.594316
iter  60 value 77.964805
iter  70 value 77.289769
iter  80 value 76.939482
iter  90 value 76.618634
iter 100 value 76.534184
final  value 76.534184 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.173957 
iter  10 value 94.849200
iter  20 value 92.698653
iter  30 value 86.421281
iter  40 value 83.458855
iter  50 value 82.237530
iter  60 value 81.337782
iter  70 value 79.912546
iter  80 value 78.851215
iter  90 value 77.370568
iter 100 value 77.041889
final  value 77.041889 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.315977 
iter  10 value 94.913435
iter  20 value 94.058257
iter  30 value 89.025616
iter  40 value 82.408038
iter  50 value 82.063301
iter  60 value 80.523827
iter  70 value 78.297108
iter  80 value 77.192559
iter  90 value 77.087208
iter 100 value 77.060993
final  value 77.060993 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.808997 
final  value 94.054398 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.874517 
iter  10 value 87.171975
iter  20 value 84.358200
iter  30 value 82.371842
iter  40 value 82.360208
iter  50 value 82.359943
iter  60 value 82.359645
iter  70 value 81.485549
iter  80 value 80.821388
iter  90 value 80.804562
iter 100 value 80.626280
final  value 80.626280 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.951333 
iter  10 value 94.054566
iter  20 value 94.052942
iter  30 value 81.907800
iter  40 value 81.897700
iter  50 value 81.897404
iter  60 value 81.866377
iter  70 value 81.712448
iter  80 value 81.712096
iter  90 value 81.711949
iter 100 value 81.711426
final  value 81.711426 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 120.731947 
iter  10 value 94.044999
iter  20 value 94.043494
iter  30 value 91.661987
iter  40 value 84.269379
iter  50 value 82.695236
iter  60 value 81.796349
iter  70 value 81.758606
final  value 81.758253 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.639506 
final  value 94.054733 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.468519 
iter  10 value 94.047569
iter  20 value 92.852576
iter  30 value 92.164304
iter  40 value 90.243018
iter  50 value 88.626302
iter  60 value 87.799103
iter  70 value 82.241973
iter  80 value 82.159602
iter  90 value 82.156533
iter 100 value 82.152932
final  value 82.152932 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.958135 
iter  10 value 94.058404
iter  20 value 94.053544
iter  30 value 91.286620
iter  40 value 85.083505
iter  50 value 84.860530
iter  60 value 84.853736
iter  70 value 84.851515
iter  80 value 84.850138
final  value 84.849258 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.468642 
iter  10 value 94.057139
iter  20 value 92.889932
iter  30 value 91.242884
iter  40 value 83.316139
iter  50 value 82.867312
iter  60 value 81.237633
iter  70 value 81.224982
iter  80 value 81.224839
final  value 81.224618 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.619793 
iter  10 value 94.048146
iter  20 value 94.043403
iter  30 value 93.915023
iter  40 value 83.733727
iter  50 value 78.753612
iter  60 value 77.947535
iter  70 value 77.588871
iter  80 value 75.894204
iter  90 value 75.850582
iter 100 value 75.820580
final  value 75.820580 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.571168 
iter  10 value 94.056560
iter  20 value 91.158937
iter  30 value 90.913334
iter  40 value 90.912982
iter  50 value 90.911986
iter  60 value 87.170370
iter  70 value 81.516273
iter  80 value 81.497774
iter  90 value 81.138215
iter 100 value 80.973273
final  value 80.973273 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.422630 
iter  10 value 89.450001
iter  20 value 80.296809
iter  30 value 78.807264
iter  40 value 76.364354
iter  50 value 75.398514
iter  60 value 75.371027
iter  70 value 75.370704
iter  80 value 75.366239
final  value 75.364081 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.231736 
iter  10 value 93.975514
iter  20 value 93.170817
iter  30 value 90.934763
iter  40 value 90.928278
iter  50 value 90.924207
final  value 90.922518 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.068660 
iter  10 value 93.665685
iter  20 value 91.687993
iter  30 value 82.349646
iter  40 value 81.895299
iter  50 value 81.895131
iter  60 value 81.895079
final  value 81.895077 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.739568 
iter  10 value 94.051528
iter  20 value 94.042738
iter  30 value 93.848593
iter  40 value 91.471908
iter  50 value 81.109775
iter  60 value 79.226754
iter  70 value 78.785080
iter  80 value 78.774226
iter  90 value 78.737956
iter 100 value 78.734487
final  value 78.734487 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.438252 
iter  10 value 94.057191
iter  20 value 92.660465
iter  30 value 91.207737
iter  40 value 87.242531
iter  50 value 86.188307
iter  60 value 86.166192
iter  70 value 86.144163
iter  80 value 86.131013
iter  90 value 85.379953
iter 100 value 85.365503
final  value 85.365503 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.213471 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.967178 
iter  10 value 94.275432
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.304598 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.533488 
final  value 94.275363 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.840806 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.480481 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.572223 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.812323 
iter  10 value 94.230279
final  value 94.229692 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.426600 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.562396 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.117510 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.698006 
iter  10 value 84.497490
iter  20 value 83.902359
final  value 83.885614 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.572481 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.893086 
iter  10 value 94.275379
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.292289 
final  value 94.305882 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.205320 
iter  10 value 94.488667
iter  20 value 94.422799
iter  30 value 94.342447
iter  40 value 94.334123
iter  50 value 94.068457
iter  60 value 92.429148
iter  70 value 85.613206
iter  80 value 85.005001
iter  90 value 84.247194
iter 100 value 84.129386
final  value 84.129386 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.319453 
iter  10 value 94.482024
iter  20 value 94.068721
iter  30 value 94.062561
iter  40 value 94.056295
iter  50 value 93.791901
iter  60 value 88.785162
iter  70 value 86.636185
iter  80 value 85.998925
iter  90 value 85.961168
final  value 85.952882 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.643091 
iter  10 value 94.788498
iter  20 value 94.490052
iter  30 value 94.147213
iter  40 value 94.062285
iter  50 value 91.237129
iter  60 value 89.935109
iter  70 value 89.882563
iter  80 value 87.084974
iter  90 value 85.013813
iter 100 value 84.666394
final  value 84.666394 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 110.729287 
iter  10 value 96.231631
iter  20 value 94.488717
iter  30 value 94.456204
iter  40 value 93.769675
iter  50 value 92.338199
iter  60 value 92.306232
iter  70 value 92.303628
iter  80 value 92.051073
iter  90 value 92.040979
final  value 92.040975 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.054353 
iter  10 value 94.487829
iter  20 value 93.721677
iter  30 value 86.953746
iter  40 value 84.924887
iter  50 value 84.077453
iter  60 value 83.887169
iter  70 value 83.474355
iter  80 value 83.443759
iter  90 value 83.436174
iter 100 value 83.403031
final  value 83.403031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.165602 
iter  10 value 94.216915
iter  20 value 93.354081
iter  30 value 85.958774
iter  40 value 85.495499
iter  50 value 85.229666
iter  60 value 84.304284
iter  70 value 83.768648
iter  80 value 82.656790
iter  90 value 82.245162
iter 100 value 81.874594
final  value 81.874594 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.723921 
iter  10 value 94.848680
iter  20 value 88.760116
iter  30 value 86.563674
iter  40 value 85.529742
iter  50 value 85.036660
iter  60 value 84.297805
iter  70 value 83.147994
iter  80 value 82.919508
iter  90 value 82.629549
iter 100 value 82.559409
final  value 82.559409 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.044204 
iter  10 value 91.020012
iter  20 value 86.284899
iter  30 value 84.249953
iter  40 value 83.553942
iter  50 value 82.889025
iter  60 value 82.658583
iter  70 value 82.520483
iter  80 value 82.362455
iter  90 value 82.295157
iter 100 value 82.261275
final  value 82.261275 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.641681 
iter  10 value 94.474096
iter  20 value 93.919124
iter  30 value 88.825452
iter  40 value 87.532275
iter  50 value 86.787147
iter  60 value 85.256525
iter  70 value 84.223937
iter  80 value 82.828052
iter  90 value 82.416982
iter 100 value 82.271185
final  value 82.271185 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.186496 
iter  10 value 94.598868
iter  20 value 92.381996
iter  30 value 89.010323
iter  40 value 87.960221
iter  50 value 87.638916
iter  60 value 87.441281
iter  70 value 86.689937
iter  80 value 86.271791
iter  90 value 84.791986
iter 100 value 83.223456
final  value 83.223456 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.818311 
iter  10 value 94.533869
iter  20 value 94.448577
iter  30 value 94.148457
iter  40 value 93.714332
iter  50 value 91.862526
iter  60 value 85.266707
iter  70 value 83.637511
iter  80 value 82.605957
iter  90 value 82.407890
iter 100 value 82.322031
final  value 82.322031 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.720039 
iter  10 value 94.548927
iter  20 value 88.656622
iter  30 value 86.603498
iter  40 value 86.318369
iter  50 value 86.253310
iter  60 value 86.098021
iter  70 value 84.720176
iter  80 value 82.661950
iter  90 value 81.898005
iter 100 value 81.599631
final  value 81.599631 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.413477 
iter  10 value 94.458124
iter  20 value 92.753012
iter  30 value 88.228167
iter  40 value 85.082000
iter  50 value 84.584494
iter  60 value 84.062356
iter  70 value 83.748973
iter  80 value 83.615209
iter  90 value 83.412451
iter 100 value 83.294307
final  value 83.294307 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.743392 
iter  10 value 94.925826
iter  20 value 94.379890
iter  30 value 85.124553
iter  40 value 83.621337
iter  50 value 83.259248
iter  60 value 83.019264
iter  70 value 82.935562
iter  80 value 82.786064
iter  90 value 82.442940
iter 100 value 81.923801
final  value 81.923801 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.490278 
iter  10 value 94.050206
iter  20 value 88.165729
iter  30 value 86.123513
iter  40 value 84.893804
iter  50 value 83.647780
iter  60 value 83.158039
iter  70 value 83.095512
iter  80 value 82.593324
iter  90 value 82.475107
iter 100 value 82.419955
final  value 82.419955 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.078314 
iter  10 value 85.498433
iter  20 value 84.757847
iter  30 value 84.756918
iter  40 value 84.756348
iter  50 value 84.382245
final  value 84.382150 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.225297 
final  value 94.485972 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.389952 
final  value 94.485742 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.895511 
final  value 94.485946 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.318639 
final  value 94.496054 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.480834 
iter  10 value 93.428108
iter  20 value 93.424072
iter  30 value 93.423643
iter  40 value 91.862740
iter  50 value 88.208412
iter  60 value 83.319873
iter  70 value 82.871644
iter  80 value 82.278067
final  value 82.214287 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.443194 
iter  10 value 94.457518
iter  20 value 94.453002
iter  30 value 94.449436
iter  40 value 94.449335
iter  50 value 94.448189
iter  60 value 94.140886
iter  70 value 94.112826
final  value 94.112725 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.958851 
iter  10 value 94.489131
iter  20 value 94.402379
iter  30 value 89.768682
iter  40 value 89.438028
iter  50 value 87.450199
iter  60 value 84.483410
iter  70 value 83.463298
iter  80 value 83.164527
iter  90 value 82.075943
iter 100 value 81.953298
final  value 81.953298 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.867154 
iter  10 value 94.488845
iter  20 value 94.479465
iter  30 value 93.214604
iter  40 value 93.206398
iter  50 value 93.205653
iter  60 value 93.205444
final  value 93.205411 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.190562 
iter  10 value 94.285122
iter  20 value 94.268838
iter  30 value 94.234093
iter  40 value 93.739000
iter  50 value 89.902227
iter  60 value 89.882583
iter  70 value 89.872211
iter  80 value 89.871898
iter  90 value 89.871696
iter 100 value 89.791408
final  value 89.791408 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.882254 
iter  10 value 94.003347
iter  20 value 93.997001
iter  30 value 93.976284
iter  40 value 91.797081
iter  50 value 87.737926
iter  60 value 86.824591
iter  70 value 86.732670
iter  80 value 84.767968
iter  90 value 83.168707
iter 100 value 82.432180
final  value 82.432180 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.314116 
iter  10 value 94.239993
iter  20 value 94.237151
iter  30 value 94.073680
iter  40 value 94.072987
iter  50 value 94.059526
iter  60 value 93.943191
iter  70 value 92.704840
iter  80 value 84.871526
iter  90 value 82.850443
iter 100 value 81.913049
final  value 81.913049 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.518048 
iter  10 value 94.492620
iter  20 value 94.387176
iter  30 value 92.613515
iter  40 value 88.965746
iter  50 value 88.954237
iter  60 value 88.953572
final  value 88.953559 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.091720 
iter  10 value 94.283911
iter  20 value 94.276791
iter  30 value 91.928630
iter  40 value 87.516473
final  value 87.512851 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.681758 
iter  10 value 94.288057
iter  20 value 94.282316
iter  20 value 94.282316
iter  30 value 94.281843
final  value 94.281836 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.091555 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.433622 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 93.999444 
iter  10 value 87.858208
iter  20 value 87.821698
final  value 87.821656 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.755961 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.926764 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.784205 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.917077 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.920061 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.597613 
iter  10 value 91.621941
iter  20 value 90.215324
iter  30 value 90.175696
iter  40 value 90.175360
iter  50 value 82.575155
iter  60 value 81.347819
iter  70 value 81.329847
final  value 81.329117 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.930185 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.731952 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.344235 
iter  10 value 93.856425
iter  20 value 93.745510
iter  30 value 93.745359
final  value 93.745355 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.274004 
iter  10 value 93.915747
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.060649 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.587716 
iter  10 value 86.424972
iter  20 value 81.329392
iter  30 value 81.159822
final  value 81.158333 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.288635 
iter  10 value 93.855850
iter  20 value 93.794304
iter  30 value 84.739195
iter  40 value 84.228886
iter  50 value 83.963216
iter  60 value 82.258746
iter  70 value 82.008599
iter  80 value 81.989265
iter  90 value 81.987429
iter  90 value 81.987429
iter  90 value 81.987429
final  value 81.987429 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.045166 
iter  10 value 94.055086
iter  20 value 93.849501
iter  30 value 89.685446
iter  40 value 84.765674
iter  50 value 83.255669
iter  60 value 82.069135
iter  70 value 81.577690
iter  80 value 80.942596
iter  90 value 80.809900
iter 100 value 80.799151
final  value 80.799151 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 110.728162 
iter  10 value 93.428217
iter  20 value 83.307517
iter  30 value 82.861289
iter  40 value 82.524748
iter  50 value 82.041058
iter  60 value 82.013423
iter  70 value 81.988033
final  value 81.987429 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.318398 
iter  10 value 93.859776
iter  20 value 87.318637
iter  30 value 86.738933
iter  40 value 86.075437
iter  50 value 85.334428
iter  60 value 84.948254
iter  70 value 84.892696
iter  80 value 84.858990
final  value 84.858976 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.504257 
iter  10 value 93.950066
iter  20 value 93.234326
iter  30 value 84.783927
iter  40 value 83.596559
iter  50 value 82.539483
iter  60 value 82.010133
iter  70 value 80.802350
iter  80 value 80.730391
final  value 80.671314 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.379326 
iter  10 value 94.977428
iter  20 value 92.757081
iter  30 value 91.928244
iter  40 value 89.823962
iter  50 value 86.377613
iter  60 value 85.292743
iter  70 value 80.936074
iter  80 value 80.026928
iter  90 value 79.882801
iter 100 value 79.753105
final  value 79.753105 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.428170 
iter  10 value 94.099606
iter  20 value 89.288009
iter  30 value 84.423725
iter  40 value 83.388562
iter  50 value 82.180868
iter  60 value 80.490636
iter  70 value 80.116960
iter  80 value 79.882301
iter  90 value 79.801815
iter 100 value 79.543832
final  value 79.543832 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.415441 
iter  10 value 90.801325
iter  20 value 85.463781
iter  30 value 83.003252
iter  40 value 82.344220
iter  50 value 81.536173
iter  60 value 80.926541
iter  70 value 80.791611
iter  80 value 80.376007
iter  90 value 79.365682
iter 100 value 79.300577
final  value 79.300577 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.093581 
iter  10 value 94.089560
iter  20 value 90.901981
iter  30 value 82.718702
iter  40 value 82.371414
iter  50 value 81.358827
iter  60 value 80.182133
iter  70 value 79.928518
iter  80 value 79.775001
iter  90 value 79.642913
iter 100 value 79.496934
final  value 79.496934 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.476175 
iter  10 value 94.063588
iter  20 value 94.054095
iter  30 value 89.025459
iter  40 value 85.962529
iter  50 value 85.470855
iter  60 value 84.000705
iter  70 value 81.936025
iter  80 value 81.228982
iter  90 value 81.011327
iter 100 value 80.814919
final  value 80.814919 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.142161 
iter  10 value 94.222081
iter  20 value 93.196039
iter  30 value 87.126441
iter  40 value 84.036140
iter  50 value 81.631630
iter  60 value 80.822801
iter  70 value 80.034741
iter  80 value 79.552461
iter  90 value 79.266626
iter 100 value 79.223423
final  value 79.223423 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.826684 
iter  10 value 95.496754
iter  20 value 94.251796
iter  30 value 93.713611
iter  40 value 85.109975
iter  50 value 81.800423
iter  60 value 80.888845
iter  70 value 79.721578
iter  80 value 79.643337
iter  90 value 79.519370
iter 100 value 79.473268
final  value 79.473268 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.671982 
iter  10 value 94.385870
iter  20 value 90.351328
iter  30 value 86.678801
iter  40 value 82.274977
iter  50 value 81.112484
iter  60 value 80.081688
iter  70 value 79.650454
iter  80 value 79.430052
iter  90 value 79.323290
iter 100 value 79.193812
final  value 79.193812 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.396717 
iter  10 value 93.904650
iter  20 value 88.899147
iter  30 value 84.829450
iter  40 value 82.338068
iter  50 value 81.881277
iter  60 value 80.906920
iter  70 value 80.442792
iter  80 value 79.745010
iter  90 value 79.339342
iter 100 value 79.128955
final  value 79.128955 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.916626 
iter  10 value 94.349354
iter  20 value 93.623829
iter  30 value 85.506125
iter  40 value 84.047795
iter  50 value 83.865495
iter  60 value 83.221786
iter  70 value 81.658749
iter  80 value 81.273648
iter  90 value 80.289960
iter 100 value 79.711177
final  value 79.711177 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.237818 
final  value 94.054503 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.539427 
final  value 94.054682 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.679464 
iter  10 value 86.310837
iter  20 value 86.270718
iter  30 value 86.270002
iter  40 value 86.261149
iter  50 value 86.189038
iter  60 value 83.924549
iter  70 value 82.874509
iter  80 value 82.766761
iter  90 value 82.747925
iter 100 value 82.740117
final  value 82.740117 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.032412 
iter  10 value 94.061630
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.366188 
final  value 94.054589 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.852922 
iter  10 value 93.921183
iter  20 value 93.030762
iter  30 value 83.075190
final  value 83.032046 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.621742 
iter  10 value 88.543608
iter  20 value 86.103212
iter  30 value 85.941367
iter  40 value 85.938454
iter  50 value 85.935737
final  value 85.935333 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.002110 
iter  10 value 94.058210
iter  20 value 94.046724
iter  30 value 87.659684
final  value 86.380724 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.812503 
iter  10 value 93.920713
iter  20 value 93.904014
iter  30 value 90.363658
iter  40 value 84.793188
iter  50 value 84.791191
iter  60 value 84.790656
iter  60 value 84.790656
iter  60 value 84.790656
final  value 84.790656 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.301929 
iter  10 value 94.016214
iter  20 value 93.827645
iter  30 value 93.773713
iter  40 value 93.773257
final  value 93.773255 
converged
Fitting Repeat 1 

# weights:  507
initial  value 89.032908 
iter  10 value 81.397049
iter  20 value 81.370819
iter  30 value 81.211286
iter  40 value 80.646660
iter  50 value 80.353967
iter  60 value 80.348414
iter  70 value 80.280733
iter  80 value 80.190975
iter  90 value 80.189102
iter 100 value 80.188100
final  value 80.188100 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.072450 
iter  10 value 93.761206
iter  20 value 93.755468
iter  30 value 92.916563
iter  40 value 87.542840
iter  50 value 87.284935
iter  60 value 85.594291
iter  70 value 85.537481
final  value 85.531824 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.936767 
iter  10 value 92.672760
iter  20 value 92.584868
iter  30 value 92.580799
iter  40 value 92.577536
iter  50 value 92.577416
final  value 92.577005 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.755907 
iter  10 value 94.061567
iter  20 value 94.052428
iter  30 value 93.930464
iter  40 value 93.795547
final  value 93.753066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.888783 
iter  10 value 93.924009
iter  20 value 93.916928
iter  30 value 85.466996
iter  40 value 84.851606
iter  50 value 82.234579
iter  60 value 80.701058
iter  70 value 80.642223
iter  80 value 80.629326
iter  90 value 80.099862
iter 100 value 80.094533
final  value 80.094533 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.379560 
iter  10 value 94.028022
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.436808 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.995137 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.550465 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.383507 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.319707 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.203206 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.724248 
iter  10 value 94.369912
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.015149 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.196239 
iter  10 value 93.887795
iter  10 value 93.887794
iter  10 value 93.887794
final  value 93.887794 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.490714 
iter  10 value 94.019843
final  value 94.019154 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.502393 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.054775 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.112196 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.898470 
iter  10 value 94.307757
iter  20 value 93.962229
final  value 93.940759 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.155900 
iter  10 value 94.487413
iter  20 value 92.803905
iter  30 value 88.969059
iter  40 value 87.288356
iter  50 value 85.084726
iter  60 value 83.940672
iter  70 value 83.627133
iter  80 value 83.599441
iter  90 value 83.582347
final  value 83.582343 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.506289 
iter  10 value 94.477662
iter  20 value 90.129416
iter  30 value 88.489895
iter  40 value 86.794987
iter  50 value 85.886724
iter  60 value 84.392304
iter  70 value 83.312447
iter  80 value 83.013993
iter  90 value 82.994665
iter 100 value 82.962882
final  value 82.962882 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.595591 
iter  10 value 94.377931
iter  20 value 92.082962
iter  30 value 91.749719
iter  40 value 88.189386
iter  50 value 86.048952
iter  60 value 84.894186
iter  70 value 84.784053
iter  80 value 84.692089
final  value 84.692026 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.912988 
iter  10 value 94.439758
iter  20 value 94.021475
iter  30 value 92.397069
iter  40 value 91.870221
iter  50 value 90.821905
iter  60 value 87.272256
iter  70 value 87.055976
iter  80 value 86.450150
iter  90 value 85.341834
iter 100 value 85.261701
final  value 85.261701 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.475989 
iter  10 value 94.488619
iter  20 value 91.962614
iter  30 value 87.323015
iter  40 value 85.819318
iter  50 value 85.079237
iter  60 value 84.971667
iter  70 value 84.734356
iter  80 value 84.350936
iter  90 value 84.311739
iter 100 value 84.266082
final  value 84.266082 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.756831 
iter  10 value 94.280006
iter  20 value 90.465764
iter  30 value 87.003732
iter  40 value 85.177163
iter  50 value 84.074363
iter  60 value 83.532846
iter  70 value 82.630552
iter  80 value 82.193828
iter  90 value 81.947832
iter 100 value 81.783460
final  value 81.783460 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.558538 
iter  10 value 94.522047
iter  20 value 93.914134
iter  30 value 92.558201
iter  40 value 88.025053
iter  50 value 87.395898
iter  60 value 87.184293
iter  70 value 84.966529
iter  80 value 83.878056
iter  90 value 83.101027
iter 100 value 81.981678
final  value 81.981678 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.153916 
iter  10 value 94.500560
iter  20 value 93.308398
iter  30 value 89.446032
iter  40 value 87.495503
iter  50 value 86.917017
iter  60 value 86.667225
iter  70 value 86.161487
iter  80 value 84.927426
iter  90 value 84.488377
iter 100 value 83.510700
final  value 83.510700 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.100415 
iter  10 value 93.969573
iter  20 value 88.350396
iter  30 value 87.916271
iter  40 value 86.072970
iter  50 value 85.329108
iter  60 value 83.097696
iter  70 value 81.900380
iter  80 value 81.745879
iter  90 value 81.690655
iter 100 value 81.676020
final  value 81.676020 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.522893 
iter  10 value 93.789136
iter  20 value 87.719207
iter  30 value 87.150638
iter  40 value 86.842244
iter  50 value 85.398620
iter  60 value 85.325541
iter  70 value 84.742119
iter  80 value 84.633718
iter  90 value 84.595918
iter 100 value 84.091687
final  value 84.091687 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.642054 
iter  10 value 94.302550
iter  20 value 91.616396
iter  30 value 90.169231
iter  40 value 88.550276
iter  50 value 85.532982
iter  60 value 83.146090
iter  70 value 82.507829
iter  80 value 82.164427
iter  90 value 81.944914
iter 100 value 81.928838
final  value 81.928838 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.062009 
iter  10 value 94.212293
iter  20 value 88.095777
iter  30 value 85.005778
iter  40 value 84.318601
iter  50 value 84.161882
iter  60 value 83.465933
iter  70 value 82.971155
iter  80 value 82.512255
iter  90 value 82.324624
iter 100 value 82.237002
final  value 82.237002 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.208457 
iter  10 value 94.205447
iter  20 value 91.763723
iter  30 value 86.982549
iter  40 value 85.185320
iter  50 value 83.873694
iter  60 value 82.745072
iter  70 value 82.300443
iter  80 value 82.151687
iter  90 value 82.102749
iter 100 value 81.974764
final  value 81.974764 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.556200 
iter  10 value 94.405629
iter  20 value 90.640371
iter  30 value 88.118730
iter  40 value 87.015169
iter  50 value 84.489132
iter  60 value 83.766484
iter  70 value 83.413411
iter  80 value 83.255601
iter  90 value 83.236065
iter 100 value 83.185767
final  value 83.185767 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.170785 
iter  10 value 94.696011
iter  20 value 93.127771
iter  30 value 87.628537
iter  40 value 86.720148
iter  50 value 85.089394
iter  60 value 83.087777
iter  70 value 82.579220
iter  80 value 82.194134
iter  90 value 81.838578
iter 100 value 81.666943
final  value 81.666943 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.529717 
iter  10 value 94.485883
final  value 94.484215 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.554249 
iter  10 value 94.485894
iter  20 value 94.059793
final  value 94.026754 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.171368 
final  value 94.485685 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.100682 
iter  10 value 94.486022
iter  20 value 94.484220
final  value 94.484215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.456745 
final  value 94.485678 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.570262 
final  value 94.489871 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.894602 
iter  10 value 94.033994
iter  20 value 94.027752
iter  30 value 91.746677
iter  40 value 87.485108
iter  50 value 87.100173
iter  60 value 87.093157
iter  70 value 87.093025
iter  80 value 87.092775
iter  90 value 86.899396
final  value 86.898194 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.522895 
iter  10 value 94.491349
iter  20 value 88.916982
iter  30 value 87.206898
iter  40 value 86.990043
iter  50 value 86.989731
iter  60 value 86.857290
iter  70 value 86.752267
iter  70 value 86.752267
iter  70 value 86.752267
final  value 86.752267 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.057024 
iter  10 value 94.257800
iter  20 value 94.115911
final  value 94.026922 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.572521 
iter  10 value 94.488873
iter  20 value 94.376681
iter  30 value 92.913823
iter  40 value 91.147248
iter  50 value 89.025249
iter  60 value 88.970370
iter  70 value 88.969989
iter  80 value 86.642708
iter  90 value 84.066206
iter 100 value 84.047340
final  value 84.047340 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.790848 
iter  10 value 94.492734
iter  20 value 94.484801
iter  30 value 91.411065
iter  40 value 86.252976
iter  50 value 86.119181
iter  60 value 86.116804
iter  70 value 85.712960
iter  80 value 85.396987
final  value 85.395519 
converged
Fitting Repeat 2 

# weights:  507
initial  value 130.429162 
iter  10 value 94.330978
iter  20 value 94.329575
iter  30 value 93.265025
iter  40 value 86.080500
iter  50 value 86.064728
iter  60 value 86.064549
iter  70 value 84.850910
iter  80 value 84.159067
iter  90 value 83.614129
iter 100 value 83.613543
final  value 83.613543 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.809824 
iter  10 value 94.492037
iter  20 value 94.344467
final  value 94.027388 
converged
Fitting Repeat 4 

# weights:  507
initial  value 139.618333 
iter  10 value 94.491560
iter  20 value 94.485366
iter  30 value 94.027358
iter  30 value 94.027358
iter  30 value 94.027358
final  value 94.027358 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.515463 
final  value 94.492613 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.324043 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.184526 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.711650 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.123292 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.372832 
iter  10 value 90.537014
iter  20 value 89.136138
iter  30 value 89.133692
final  value 89.133690 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.629021 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.093636 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.320895 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.662834 
final  value 93.300000 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.907792 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.463555 
iter  10 value 92.830387
iter  20 value 84.762213
iter  30 value 84.134048
iter  40 value 83.510605
iter  50 value 83.163519
iter  60 value 83.162379
final  value 83.162367 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.540822 
iter  10 value 89.068411
iter  20 value 87.102700
iter  30 value 87.101125
iter  30 value 87.101124
iter  30 value 87.101124
final  value 87.101124 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.225231 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.008019 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.108746 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.523675 
iter  10 value 94.488531
iter  20 value 94.168992
iter  30 value 94.061824
iter  40 value 92.985290
iter  50 value 91.492215
iter  60 value 89.670566
iter  70 value 89.598361
final  value 89.595578 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.038169 
iter  10 value 94.573024
iter  20 value 94.486432
iter  30 value 94.123245
iter  40 value 91.609791
iter  50 value 85.480089
iter  60 value 84.924493
iter  70 value 84.891730
iter  80 value 84.760148
iter  90 value 84.685887
final  value 84.679816 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.368304 
iter  10 value 94.310757
iter  20 value 92.620372
iter  30 value 89.045870
iter  40 value 84.726564
iter  50 value 84.103100
iter  60 value 83.217273
iter  70 value 81.992529
iter  80 value 81.849512
iter  90 value 81.572861
iter 100 value 81.284092
final  value 81.284092 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.334813 
iter  10 value 94.488555
iter  20 value 94.168161
iter  30 value 93.948690
iter  40 value 93.864314
iter  50 value 91.428785
iter  60 value 89.613809
iter  70 value 89.598838
iter  80 value 89.595440
iter  90 value 89.593347
iter 100 value 89.592764
final  value 89.592764 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.266954 
iter  10 value 94.307381
iter  20 value 86.735107
iter  30 value 85.934033
iter  40 value 84.756522
final  value 84.735639 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.896651 
iter  10 value 94.482979
iter  20 value 88.557968
iter  30 value 85.160459
iter  40 value 83.304332
iter  50 value 82.693093
iter  60 value 82.532819
iter  70 value 82.256523
iter  80 value 81.377082
iter  90 value 80.532239
iter 100 value 80.295615
final  value 80.295615 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.077858 
iter  10 value 94.545021
iter  20 value 93.165581
iter  30 value 92.429598
iter  40 value 90.190871
iter  50 value 89.994147
iter  60 value 89.848835
iter  70 value 88.420938
iter  80 value 86.565023
iter  90 value 84.399994
iter 100 value 83.181576
final  value 83.181576 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.859866 
iter  10 value 94.457912
iter  20 value 91.297397
iter  30 value 86.238687
iter  40 value 81.978853
iter  50 value 81.419808
iter  60 value 81.336776
iter  70 value 81.151973
iter  80 value 80.682778
iter  90 value 80.595946
iter 100 value 80.575548
final  value 80.575548 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.201891 
iter  10 value 94.532694
iter  20 value 94.489175
iter  30 value 91.907929
iter  40 value 86.673017
iter  50 value 84.542086
iter  60 value 84.206578
iter  70 value 82.244150
iter  80 value 81.533316
iter  90 value 81.401735
iter 100 value 81.049353
final  value 81.049353 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.787970 
iter  10 value 94.489021
iter  20 value 94.003386
iter  30 value 86.469040
iter  40 value 84.592244
iter  50 value 84.023753
iter  60 value 82.907501
iter  70 value 82.358918
iter  80 value 81.707850
iter  90 value 80.914015
iter 100 value 80.708738
final  value 80.708738 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.544383 
iter  10 value 93.788264
iter  20 value 87.802622
iter  30 value 86.186825
iter  40 value 82.019372
iter  50 value 81.391801
iter  60 value 81.172639
iter  70 value 81.015503
iter  80 value 80.880749
iter  90 value 80.817130
iter 100 value 80.756566
final  value 80.756566 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.026430 
iter  10 value 94.442413
iter  20 value 92.713472
iter  30 value 87.382906
iter  40 value 83.787720
iter  50 value 82.748410
iter  60 value 81.952033
iter  70 value 80.798934
iter  80 value 80.467068
iter  90 value 80.259148
iter 100 value 80.042179
final  value 80.042179 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.801014 
iter  10 value 94.840852
iter  20 value 92.548597
iter  30 value 90.911995
iter  40 value 86.022320
iter  50 value 83.947609
iter  60 value 83.196740
iter  70 value 82.231662
iter  80 value 81.802592
iter  90 value 81.315369
iter 100 value 80.607503
final  value 80.607503 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.676566 
iter  10 value 95.963631
iter  20 value 92.360528
iter  30 value 91.691721
iter  40 value 87.028417
iter  50 value 82.439081
iter  60 value 80.924289
iter  70 value 80.469665
iter  80 value 79.831650
iter  90 value 79.601845
iter 100 value 79.566756
final  value 79.566756 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.228243 
iter  10 value 97.421319
iter  20 value 86.804963
iter  30 value 84.784109
iter  40 value 84.694264
iter  50 value 84.500994
iter  60 value 83.793567
iter  70 value 82.435383
iter  80 value 81.862089
iter  90 value 80.708851
iter 100 value 80.059224
final  value 80.059224 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.891376 
iter  10 value 94.410928
final  value 94.410923 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.775689 
iter  10 value 94.468694
iter  20 value 94.466845
iter  20 value 94.466845
iter  20 value 94.466845
final  value 94.466845 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.666930 
final  value 94.485887 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.547706 
final  value 94.486177 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.924732 
final  value 94.485769 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.957527 
iter  10 value 86.712815
iter  20 value 86.022272
iter  30 value 84.560304
iter  40 value 84.558104
iter  50 value 83.948834
iter  60 value 83.677146
iter  70 value 83.631065
iter  80 value 83.629987
iter  90 value 83.629464
final  value 83.629265 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.091787 
iter  10 value 94.413183
iter  20 value 94.408702
iter  30 value 94.013479
iter  40 value 83.763843
iter  50 value 83.557738
final  value 83.554076 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.918380 
iter  10 value 94.471749
iter  20 value 94.466891
iter  30 value 91.574756
iter  40 value 82.383069
iter  50 value 80.390632
iter  60 value 80.045082
iter  70 value 79.470245
iter  80 value 79.359924
iter  90 value 79.357299
iter 100 value 79.356025
final  value 79.356025 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.497275 
iter  10 value 94.433869
iter  20 value 94.414628
iter  30 value 89.217463
iter  40 value 88.935579
iter  50 value 88.925256
iter  60 value 85.747594
iter  70 value 85.743996
iter  80 value 85.743485
iter  90 value 83.738330
final  value 83.663306 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.610573 
iter  10 value 94.433424
iter  20 value 94.428978
iter  30 value 93.984562
iter  40 value 86.201990
iter  50 value 83.438785
iter  60 value 79.388643
iter  70 value 79.006541
iter  80 value 78.541822
iter  90 value 78.481364
iter 100 value 78.362541
final  value 78.362541 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.737036 
iter  10 value 87.944719
iter  20 value 84.875292
iter  30 value 84.869985
iter  40 value 84.868068
iter  50 value 83.919435
iter  60 value 83.866185
iter  70 value 83.862409
iter  80 value 83.861709
iter  90 value 83.858097
iter 100 value 83.226375
final  value 83.226375 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.196751 
iter  10 value 93.349498
iter  20 value 93.307904
iter  30 value 93.305936
iter  40 value 93.302175
iter  50 value 91.265212
iter  60 value 91.246591
iter  70 value 90.919727
iter  80 value 85.163617
iter  90 value 80.800291
iter 100 value 79.838879
final  value 79.838879 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.211983 
iter  10 value 94.492067
iter  20 value 85.326699
iter  30 value 84.639257
iter  40 value 83.815694
final  value 83.815280 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.013839 
iter  10 value 93.272856
iter  20 value 93.267546
iter  30 value 88.532842
iter  40 value 83.662960
iter  50 value 82.903664
iter  60 value 81.698491
iter  70 value 81.572224
iter  80 value 80.741468
iter  90 value 80.705736
iter 100 value 80.703733
final  value 80.703733 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.385028 
iter  10 value 93.136802
iter  20 value 91.168067
iter  30 value 90.136677
iter  40 value 89.758818
iter  50 value 89.755262
final  value 89.754951 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.018314 
iter  10 value 118.303777
iter  20 value 107.471292
iter  30 value 105.957741
iter  40 value 105.722326
iter  50 value 104.259791
iter  60 value 104.002673
iter  70 value 103.115170
iter  80 value 102.201192
iter  90 value 101.701759
iter 100 value 101.290454
final  value 101.290454 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 124.655744 
iter  10 value 118.095020
iter  20 value 116.795607
iter  30 value 112.750171
iter  40 value 107.685887
iter  50 value 104.872553
iter  60 value 104.205516
iter  70 value 102.745187
iter  80 value 102.604728
iter  90 value 102.530547
iter 100 value 102.410645
final  value 102.410645 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 137.233103 
iter  10 value 117.177000
iter  20 value 110.680413
iter  30 value 108.061840
iter  40 value 107.224153
iter  50 value 104.250375
iter  60 value 102.606131
iter  70 value 102.316947
iter  80 value 102.104322
iter  90 value 102.032340
iter 100 value 101.959925
final  value 101.959925 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 136.361389 
iter  10 value 118.013206
iter  20 value 108.937724
iter  30 value 106.936439
iter  40 value 105.916913
iter  50 value 105.397725
iter  60 value 105.290922
iter  70 value 105.172432
iter  80 value 105.005755
iter  90 value 104.621885
iter 100 value 103.354807
final  value 103.354807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 130.469951 
iter  10 value 119.284872
iter  20 value 117.628009
iter  30 value 116.523426
iter  40 value 106.475379
iter  50 value 105.089810
iter  60 value 103.896400
iter  70 value 102.390314
iter  80 value 101.176047
iter  90 value 100.830270
iter 100 value 100.722780
final  value 100.722780 
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 -- Sun Dec 21 20:16:30 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 20.239   0.476  73.624