##############################################################################
##############################################################################
###
### 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      19.221  0.924  20.887
corr_plot     19.081  0.895  20.714
var_imp       18.581  0.988  20.961
pred_ensembel  6.528  0.112   6.341
enrichfindP    0.194  0.038  12.521
getFASTA       0.031  0.007   5.236
* 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 94.486828 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.235560 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.305312 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.929514 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.076315 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.135538 
iter  10 value 94.424931
final  value 94.423548 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.764599 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.028381 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.121684 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.994779 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.639900 
iter  10 value 94.338747
final  value 94.338745 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.008173 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.246587 
iter  10 value 94.356092
iter  20 value 94.354287
iter  20 value 94.354287
iter  20 value 94.354287
final  value 94.354287 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.542632 
iter  10 value 83.771489
iter  20 value 83.240692
iter  30 value 83.239653
iter  40 value 83.239526
final  value 83.239521 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.199232 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.073524 
iter  10 value 94.533602
iter  20 value 90.854083
iter  30 value 90.125949
iter  40 value 89.595019
iter  50 value 87.533240
iter  60 value 83.769099
iter  70 value 83.694120
iter  80 value 83.687061
final  value 83.684617 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.237253 
iter  10 value 93.939959
iter  20 value 88.183344
iter  30 value 87.167440
iter  40 value 85.641915
iter  50 value 85.340088
iter  60 value 84.484604
iter  70 value 84.234770
iter  80 value 84.217690
final  value 84.217673 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.431939 
iter  10 value 94.490232
iter  20 value 94.346970
iter  30 value 94.159036
iter  40 value 92.084463
iter  50 value 91.609394
iter  60 value 91.571360
iter  70 value 86.309787
iter  80 value 84.972686
iter  90 value 84.571367
iter 100 value 84.013777
final  value 84.013777 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.919653 
iter  10 value 94.488592
iter  20 value 91.476611
iter  30 value 88.694699
iter  40 value 88.088114
iter  50 value 87.586615
iter  60 value 85.230140
iter  70 value 83.834111
iter  80 value 83.740486
iter  90 value 83.642421
iter 100 value 83.602193
final  value 83.602193 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.174165 
iter  10 value 93.862925
iter  20 value 86.637934
iter  30 value 85.376152
iter  40 value 85.180519
iter  50 value 85.150803
iter  60 value 85.138274
iter  70 value 85.052014
iter  80 value 84.441323
iter  90 value 84.218034
final  value 84.217673 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.517916 
iter  10 value 91.597653
iter  20 value 89.202119
iter  30 value 86.585499
iter  40 value 85.108504
iter  50 value 83.760384
iter  60 value 82.891505
iter  70 value 82.320622
iter  80 value 81.896208
iter  90 value 81.606183
iter 100 value 81.492510
final  value 81.492510 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.313956 
iter  10 value 94.809165
iter  20 value 94.543409
iter  30 value 94.358121
iter  40 value 91.680799
iter  50 value 87.500012
iter  60 value 86.588269
iter  70 value 84.807247
iter  80 value 84.540123
iter  90 value 84.239083
iter 100 value 83.927865
final  value 83.927865 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.872297 
iter  10 value 94.550695
iter  20 value 94.104022
iter  30 value 90.728532
iter  40 value 87.428217
iter  50 value 87.044786
iter  60 value 84.684222
iter  70 value 84.221415
iter  80 value 82.892039
iter  90 value 82.739277
iter 100 value 82.666700
final  value 82.666700 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.792638 
iter  10 value 91.384854
iter  20 value 85.924166
iter  30 value 84.145479
iter  40 value 83.735175
iter  50 value 83.680000
iter  60 value 83.544093
iter  70 value 83.173848
iter  80 value 82.374062
iter  90 value 82.216337
iter 100 value 82.051155
final  value 82.051155 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.940499 
iter  10 value 94.719195
iter  20 value 93.965142
iter  30 value 93.778995
iter  40 value 93.710483
iter  50 value 85.748891
iter  60 value 85.333803
iter  70 value 84.624485
iter  80 value 84.374929
iter  90 value 84.344875
iter 100 value 84.249172
final  value 84.249172 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.867543 
iter  10 value 88.947868
iter  20 value 86.826663
iter  30 value 85.250338
iter  40 value 84.444487
iter  50 value 83.274362
iter  60 value 82.958251
iter  70 value 82.665401
iter  80 value 82.557638
iter  90 value 82.421673
iter 100 value 82.193114
final  value 82.193114 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.595433 
iter  10 value 94.490034
iter  20 value 89.752753
iter  30 value 86.736513
iter  40 value 86.275450
iter  50 value 84.976348
iter  60 value 84.102954
iter  70 value 83.534524
iter  80 value 82.677746
iter  90 value 82.272149
iter 100 value 81.810578
final  value 81.810578 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.235493 
iter  10 value 94.525710
iter  20 value 93.862480
iter  30 value 87.020593
iter  40 value 85.518656
iter  50 value 84.490830
iter  60 value 83.966994
iter  70 value 83.947742
iter  80 value 83.919189
iter  90 value 83.896537
iter 100 value 83.789494
final  value 83.789494 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.900699 
iter  10 value 94.557391
iter  20 value 94.107844
iter  30 value 92.656518
iter  40 value 88.877764
iter  50 value 87.875475
iter  60 value 87.366202
iter  70 value 85.841365
iter  80 value 84.192549
iter  90 value 83.495867
iter 100 value 83.388934
final  value 83.388934 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.793980 
iter  10 value 96.677967
iter  20 value 94.764499
iter  30 value 87.498253
iter  40 value 86.246739
iter  50 value 85.156479
iter  60 value 83.992936
iter  70 value 82.547373
iter  80 value 81.596948
iter  90 value 81.405021
iter 100 value 81.395836
final  value 81.395836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.009076 
final  value 94.485785 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.901020 
final  value 94.485759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.418644 
iter  10 value 94.485769
iter  20 value 94.484163
iter  30 value 93.715584
iter  40 value 86.380931
iter  50 value 86.340998
iter  60 value 86.329409
iter  70 value 86.327540
iter  80 value 86.324044
iter  90 value 86.131108
final  value 86.130965 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.254702 
final  value 94.485950 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.501556 
iter  10 value 94.485907
iter  20 value 94.481931
iter  30 value 86.054558
iter  40 value 85.659131
iter  50 value 85.477569
iter  60 value 85.366447
iter  70 value 85.286483
iter  80 value 85.225287
iter  90 value 85.221305
iter 100 value 85.217094
final  value 85.217094 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.141939 
iter  10 value 94.488836
final  value 94.484628 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.690432 
iter  10 value 94.487628
iter  20 value 94.369892
iter  30 value 92.838697
iter  40 value 92.794904
iter  50 value 92.574882
iter  60 value 90.328997
iter  70 value 90.114233
iter  80 value 90.111884
iter  90 value 90.104135
iter 100 value 85.145214
final  value 85.145214 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.579694 
iter  10 value 94.156943
iter  20 value 94.057099
iter  30 value 94.052260
iter  40 value 89.044914
iter  50 value 85.119071
iter  60 value 85.114011
iter  70 value 85.112609
iter  80 value 85.108385
iter  90 value 85.104636
iter 100 value 85.102420
final  value 85.102420 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.887289 
iter  10 value 94.083619
iter  20 value 94.080279
iter  30 value 89.771141
iter  40 value 84.124282
iter  50 value 84.051757
final  value 84.051444 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.051617 
iter  10 value 94.488947
final  value 94.484224 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.417970 
iter  10 value 94.492292
iter  20 value 94.475589
iter  30 value 94.331104
iter  30 value 94.331103
iter  30 value 94.331103
final  value 94.331103 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.465538 
iter  10 value 94.490271
iter  20 value 94.347462
iter  30 value 94.283797
iter  40 value 90.726899
iter  50 value 87.200211
iter  60 value 86.860381
iter  70 value 86.749828
iter  80 value 86.749167
iter  90 value 86.747623
iter 100 value 86.741077
final  value 86.741077 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.060718 
iter  10 value 94.487644
iter  20 value 87.415971
iter  30 value 85.439914
iter  40 value 85.129605
iter  50 value 84.868621
iter  60 value 83.746642
iter  70 value 81.858288
iter  80 value 79.827221
iter  90 value 79.724695
iter 100 value 79.678034
final  value 79.678034 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.399825 
iter  10 value 94.491366
iter  20 value 94.170625
final  value 94.089076 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.212087 
iter  10 value 94.475169
iter  20 value 93.595308
iter  30 value 87.595350
iter  40 value 87.246311
iter  50 value 86.314905
iter  60 value 86.306194
iter  70 value 85.974556
iter  80 value 84.413142
iter  90 value 84.405395
iter 100 value 84.405057
final  value 84.405057 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.137071 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.429411 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.736580 
iter  10 value 86.765762
final  value 86.376990 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.106247 
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.009460 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.082419 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.340586 
iter  10 value 93.715893
final  value 93.697143 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.126243 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.142020 
iter  10 value 93.485056
final  value 93.481484 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.343389 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.827055 
iter  10 value 87.955578
iter  20 value 85.509322
iter  30 value 85.033672
final  value 84.988767 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.738847 
iter  10 value 93.916550
iter  20 value 93.915749
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.590373 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.095257 
iter  10 value 93.341347
iter  10 value 93.341346
iter  10 value 93.341346
final  value 93.341346 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.763521 
iter  10 value 93.723568
final  value 93.713370 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.472113 
iter  10 value 94.056755
iter  20 value 92.566722
iter  30 value 83.549849
iter  40 value 82.463187
iter  50 value 81.974548
iter  60 value 81.826112
iter  70 value 81.647744
iter  80 value 81.030706
iter  90 value 80.374413
iter 100 value 80.250747
final  value 80.250747 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.325286 
iter  10 value 94.041064
iter  20 value 85.301065
iter  30 value 84.957485
iter  40 value 84.688100
iter  50 value 84.404442
iter  60 value 83.932194
iter  70 value 83.300868
iter  80 value 83.180708
final  value 83.158535 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.596272 
iter  10 value 85.276665
iter  20 value 83.659156
iter  30 value 83.038202
iter  40 value 82.627429
iter  50 value 82.613881
iter  60 value 82.589334
final  value 82.588290 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.120890 
iter  10 value 94.042473
iter  20 value 87.472830
iter  30 value 85.440437
iter  40 value 82.591702
iter  50 value 82.475358
iter  60 value 82.441591
iter  70 value 82.421250
final  value 82.419849 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.308717 
iter  10 value 94.063733
iter  20 value 90.504200
iter  30 value 84.506494
iter  40 value 83.571620
iter  50 value 83.018323
iter  60 value 82.860112
final  value 82.847361 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.391798 
iter  10 value 94.139704
iter  20 value 93.672935
iter  30 value 85.155383
iter  40 value 84.580414
iter  50 value 81.432898
iter  60 value 80.921851
iter  70 value 79.893147
iter  80 value 79.295131
iter  90 value 79.255680
iter 100 value 79.250162
final  value 79.250162 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.326631 
iter  10 value 88.998915
iter  20 value 86.048769
iter  30 value 82.026167
iter  40 value 81.244376
iter  50 value 80.408499
iter  60 value 79.778168
iter  70 value 79.708479
iter  80 value 79.338594
iter  90 value 78.859370
iter 100 value 78.753641
final  value 78.753641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.211879 
iter  10 value 94.008973
iter  20 value 84.974284
iter  30 value 84.092064
iter  40 value 82.748049
iter  50 value 82.249568
iter  60 value 80.648485
iter  70 value 79.504465
iter  80 value 78.946994
iter  90 value 78.777979
iter 100 value 78.716265
final  value 78.716265 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.230584 
iter  10 value 93.268462
iter  20 value 86.843258
iter  30 value 85.333682
iter  40 value 81.964669
iter  50 value 81.289426
iter  60 value 80.755836
iter  70 value 79.521304
iter  80 value 79.345598
iter  90 value 79.317394
iter 100 value 79.279447
final  value 79.279447 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.370223 
iter  10 value 94.108573
iter  20 value 89.265470
iter  30 value 87.831643
iter  40 value 84.813719
iter  50 value 82.601563
iter  60 value 81.312789
iter  70 value 79.835176
iter  80 value 79.134954
iter  90 value 78.771954
iter 100 value 78.441421
final  value 78.441421 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.462074 
iter  10 value 92.923445
iter  20 value 83.774500
iter  30 value 81.972153
iter  40 value 81.178140
iter  50 value 80.738013
iter  60 value 79.490247
iter  70 value 78.495876
iter  80 value 78.328549
iter  90 value 78.150111
iter 100 value 77.997480
final  value 77.997480 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.936224 
iter  10 value 94.396717
iter  20 value 86.934495
iter  30 value 85.615022
iter  40 value 83.712365
iter  50 value 82.021560
iter  60 value 81.666576
iter  70 value 81.201657
iter  80 value 80.761403
iter  90 value 80.638941
iter 100 value 80.614943
final  value 80.614943 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.301315 
iter  10 value 94.237643
iter  20 value 93.590196
iter  30 value 92.338673
iter  40 value 84.317988
iter  50 value 82.974851
iter  60 value 82.604952
iter  70 value 82.138735
iter  80 value 82.092196
iter  90 value 82.075073
iter 100 value 82.006229
final  value 82.006229 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.948239 
iter  10 value 95.254026
iter  20 value 94.893813
iter  30 value 94.057421
iter  40 value 84.177548
iter  50 value 82.515927
iter  60 value 82.005955
iter  70 value 81.606823
iter  80 value 80.789510
iter  90 value 80.079222
iter 100 value 79.984807
final  value 79.984807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.733839 
iter  10 value 93.402461
iter  20 value 83.827732
iter  30 value 82.098270
iter  40 value 81.745680
iter  50 value 81.526783
iter  60 value 81.388164
iter  70 value 81.046252
iter  80 value 80.683195
iter  90 value 79.906715
iter 100 value 79.398800
final  value 79.398800 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.389260 
iter  10 value 93.937039
iter  20 value 93.748681
iter  30 value 93.483227
final  value 93.482556 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.787370 
iter  10 value 93.698723
iter  20 value 93.698477
iter  30 value 93.481720
iter  30 value 93.481720
iter  30 value 93.481720
final  value 93.481720 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.461063 
final  value 93.630188 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.393437 
final  value 94.054600 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.489865 
final  value 94.054552 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.772174 
iter  10 value 94.057933
iter  20 value 94.053231
iter  30 value 93.635721
iter  40 value 93.482835
iter  50 value 93.482251
iter  60 value 84.599650
iter  70 value 84.092782
iter  80 value 84.047907
final  value 84.046880 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.129633 
iter  10 value 89.367053
iter  20 value 85.616038
iter  30 value 85.612410
iter  40 value 85.608959
iter  50 value 85.357508
iter  60 value 85.266591
iter  70 value 85.266216
final  value 85.265777 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.909897 
iter  10 value 92.422984
iter  20 value 91.405370
iter  30 value 91.338478
iter  40 value 91.334011
iter  50 value 91.333522
iter  50 value 91.333521
final  value 91.333521 
converged
Fitting Repeat 4 

# weights:  305
initial  value 127.862696 
iter  10 value 94.057672
iter  20 value 94.053202
iter  30 value 93.481900
final  value 93.481631 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.716485 
iter  10 value 94.057441
final  value 94.053045 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.645320 
iter  10 value 94.054078
iter  20 value 94.042208
iter  30 value 84.170110
iter  40 value 82.416807
final  value 82.416791 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.745074 
iter  10 value 93.244185
iter  20 value 92.115000
iter  30 value 92.092811
final  value 92.092138 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.611277 
iter  10 value 94.061357
iter  20 value 94.045811
iter  20 value 94.045811
iter  30 value 93.458453
iter  40 value 83.816782
iter  50 value 81.907249
final  value 81.906847 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.578994 
iter  10 value 94.061521
iter  20 value 94.054396
iter  30 value 88.533081
iter  40 value 86.610978
iter  50 value 84.158497
iter  60 value 80.763365
iter  70 value 78.493401
iter  80 value 78.330190
iter  90 value 78.315458
iter 100 value 78.306792
final  value 78.306792 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.494645 
iter  10 value 93.923908
iter  20 value 91.932965
iter  30 value 91.827272
iter  40 value 91.286131
iter  50 value 91.278857
iter  60 value 91.278484
iter  70 value 91.278339
final  value 91.278320 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.778619 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.005201 
final  value 94.264858 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.030185 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.906460 
final  value 94.457914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.070095 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.834799 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.311348 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.001530 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.155427 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.222885 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.430018 
iter  10 value 94.448378
iter  20 value 94.031520
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.590396 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.985928 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.536586 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.305157 
final  value 94.020991 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.678488 
iter  10 value 94.468604
iter  20 value 93.853988
iter  30 value 89.074118
iter  40 value 86.657330
iter  50 value 84.854702
iter  60 value 84.338665
iter  70 value 84.162485
iter  80 value 84.055487
final  value 84.054378 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.840336 
iter  10 value 94.063396
iter  20 value 90.796309
iter  30 value 90.080045
iter  40 value 89.190229
iter  50 value 88.195219
iter  60 value 86.607696
iter  70 value 82.556212
iter  80 value 82.167058
iter  90 value 81.896867
final  value 81.892454 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.988229 
iter  10 value 94.248730
iter  20 value 86.494303
iter  30 value 85.497124
iter  40 value 85.123517
iter  50 value 82.758050
iter  60 value 82.250347
iter  70 value 81.902661
final  value 81.892454 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.006682 
iter  10 value 94.493380
iter  20 value 94.487179
iter  30 value 93.526790
iter  40 value 87.115680
iter  50 value 85.964421
iter  60 value 84.387400
iter  70 value 84.083365
iter  80 value 84.059853
final  value 84.054378 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.179457 
iter  10 value 94.488620
iter  20 value 94.022997
iter  30 value 93.903282
iter  40 value 93.889491
iter  50 value 89.612245
iter  60 value 87.589544
iter  70 value 86.368365
iter  80 value 84.735154
iter  90 value 84.255704
iter 100 value 84.185614
final  value 84.185614 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.956860 
iter  10 value 94.714931
iter  20 value 94.450425
iter  30 value 92.467883
iter  40 value 87.562623
iter  50 value 85.579847
iter  60 value 84.790249
iter  70 value 82.732933
iter  80 value 81.565030
iter  90 value 81.480616
iter 100 value 81.422402
final  value 81.422402 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.138856 
iter  10 value 94.235879
iter  20 value 93.897555
iter  30 value 93.091939
iter  40 value 89.093411
iter  50 value 88.258585
iter  60 value 84.822901
iter  70 value 84.053142
iter  80 value 83.739421
iter  90 value 82.392869
iter 100 value 81.507755
final  value 81.507755 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.784906 
iter  10 value 95.372181
iter  20 value 88.654541
iter  30 value 84.664775
iter  40 value 82.708206
iter  50 value 81.547587
iter  60 value 80.956926
iter  70 value 80.788462
iter  80 value 80.686725
iter  90 value 80.662643
iter 100 value 80.625839
final  value 80.625839 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.281863 
iter  10 value 94.619045
iter  20 value 87.399898
iter  30 value 86.641559
iter  40 value 84.493194
iter  50 value 83.179429
iter  60 value 82.792509
iter  70 value 82.550272
iter  80 value 81.888566
iter  90 value 81.777288
iter 100 value 81.743030
final  value 81.743030 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.195244 
iter  10 value 95.206579
iter  20 value 94.220616
iter  30 value 88.146979
iter  40 value 83.821596
iter  50 value 83.217867
iter  60 value 83.065136
iter  70 value 82.684173
iter  80 value 82.612933
iter  90 value 82.152905
iter 100 value 81.516902
final  value 81.516902 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.178314 
iter  10 value 93.122463
iter  20 value 88.779297
iter  30 value 87.416518
iter  40 value 85.793761
iter  50 value 84.589202
iter  60 value 84.375752
iter  70 value 83.290306
iter  80 value 81.790779
iter  90 value 80.950231
iter 100 value 80.792832
final  value 80.792832 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.180720 
iter  10 value 95.012800
iter  20 value 88.353485
iter  30 value 86.592350
iter  40 value 84.859378
iter  50 value 84.503677
iter  60 value 83.704333
iter  70 value 83.507807
iter  80 value 83.044466
iter  90 value 81.054556
iter 100 value 80.865829
final  value 80.865829 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.934359 
iter  10 value 94.525941
iter  20 value 92.195823
iter  30 value 86.161294
iter  40 value 84.922478
iter  50 value 83.957884
iter  60 value 83.844323
iter  70 value 83.375304
iter  80 value 81.383028
iter  90 value 80.611277
iter 100 value 80.105768
final  value 80.105768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.353537 
iter  10 value 95.067699
iter  20 value 94.419631
iter  30 value 91.218902
iter  40 value 85.633974
iter  50 value 83.988071
iter  60 value 83.210491
iter  70 value 82.453103
iter  80 value 82.110079
iter  90 value 81.945511
iter 100 value 81.740390
final  value 81.740390 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.232528 
iter  10 value 94.392068
iter  20 value 93.819757
iter  30 value 88.993325
iter  40 value 88.380013
iter  50 value 87.499700
iter  60 value 86.328775
iter  70 value 86.148366
iter  80 value 85.577295
iter  90 value 83.505641
iter 100 value 82.220781
final  value 82.220781 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.949064 
iter  10 value 94.489623
final  value 94.487742 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.471708 
final  value 94.485924 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.806391 
final  value 94.485920 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.305633 
final  value 94.485919 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.891220 
final  value 94.485985 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.598338 
iter  10 value 92.477377
iter  20 value 84.337617
iter  30 value 83.494869
iter  40 value 82.372769
iter  50 value 82.053323
iter  60 value 81.978143
iter  70 value 81.414379
iter  80 value 81.241717
iter  90 value 80.414741
iter 100 value 80.316443
final  value 80.316443 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.566710 
iter  10 value 94.031498
iter  20 value 92.263710
iter  30 value 84.352930
iter  40 value 84.093206
iter  50 value 82.204594
iter  60 value 81.209912
final  value 81.153446 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.146905 
iter  10 value 94.488642
iter  20 value 94.159007
final  value 93.810009 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.014970 
iter  10 value 94.489250
iter  20 value 94.334051
iter  30 value 91.046762
iter  40 value 86.032964
iter  50 value 84.729269
iter  60 value 84.728035
final  value 84.727987 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.820329 
iter  10 value 90.870453
iter  20 value 88.272157
iter  30 value 88.195588
iter  40 value 87.311875
iter  50 value 87.282626
iter  60 value 87.281560
iter  70 value 87.278645
iter  80 value 84.823815
iter  90 value 83.988331
iter 100 value 83.853399
final  value 83.853399 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.829292 
iter  10 value 93.791608
iter  20 value 88.780187
iter  30 value 87.858470
iter  40 value 87.857300
final  value 87.857085 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.675426 
iter  10 value 94.492145
iter  20 value 94.417147
iter  30 value 92.908715
iter  40 value 92.897530
final  value 92.897508 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.361795 
iter  10 value 89.175597
iter  20 value 88.429320
iter  30 value 88.397307
iter  40 value 88.225626
iter  50 value 87.268869
iter  60 value 86.933552
final  value 86.932681 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.360240 
iter  10 value 93.808611
iter  20 value 93.796640
iter  30 value 93.787440
iter  40 value 93.786798
final  value 93.786781 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.888927 
iter  10 value 94.035045
iter  20 value 94.027473
final  value 94.027025 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.432630 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.911363 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.064610 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.706024 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.916837 
iter  10 value 90.574422
iter  20 value 83.061903
final  value 83.052050 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.534091 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.666295 
final  value 93.811828 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.284564 
iter  10 value 93.811828
iter  10 value 93.811828
iter  10 value 93.811828
final  value 93.811828 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.133255 
iter  10 value 92.654232
iter  20 value 91.177708
iter  30 value 91.177422
final  value 91.177420 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.233085 
iter  10 value 84.243494
iter  20 value 84.108547
iter  30 value 83.671715
final  value 83.671595 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.254016 
iter  10 value 93.478342
final  value 93.478341 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.320391 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.959286 
iter  10 value 93.857054
iter  20 value 93.811988
iter  30 value 93.811830
final  value 93.811828 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.340747 
final  value 93.788889 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.639058 
iter  10 value 93.801477
iter  20 value 93.796571
iter  30 value 92.683934
final  value 92.683908 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.211636 
iter  10 value 93.559128
iter  20 value 84.258701
iter  30 value 83.904576
iter  40 value 82.794502
iter  50 value 82.529391
iter  60 value 82.481729
iter  70 value 81.961580
iter  80 value 81.860414
final  value 81.859821 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.132497 
iter  10 value 94.271445
iter  20 value 86.090902
iter  30 value 83.677193
iter  40 value 82.996745
iter  50 value 82.236684
iter  60 value 82.059617
iter  70 value 81.365453
iter  80 value 80.402474
iter  90 value 80.232129
iter 100 value 80.231501
final  value 80.231501 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 111.087630 
iter  10 value 94.333011
iter  20 value 84.513636
iter  30 value 83.903688
iter  40 value 82.566809
iter  50 value 82.303096
iter  60 value 81.963386
iter  70 value 81.859833
final  value 81.859822 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.087380 
iter  10 value 94.412574
iter  20 value 88.768005
iter  30 value 85.548947
iter  40 value 83.911650
iter  50 value 82.876957
iter  60 value 80.854449
iter  70 value 80.591901
iter  80 value 80.241410
iter  90 value 80.232098
iter  90 value 80.232098
final  value 80.232098 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.192579 
iter  10 value 94.484396
iter  20 value 87.893208
iter  30 value 86.582975
iter  40 value 84.347826
iter  50 value 82.363994
iter  60 value 80.970541
iter  70 value 80.256198
iter  80 value 80.231217
iter  90 value 80.228538
iter  90 value 80.228538
final  value 80.228538 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.094275 
iter  10 value 94.906976
iter  20 value 93.405951
iter  30 value 84.644786
iter  40 value 82.870504
iter  50 value 82.502282
iter  60 value 82.382545
iter  70 value 82.305115
iter  80 value 81.941731
iter  90 value 81.886446
iter 100 value 81.866378
final  value 81.866378 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.372652 
iter  10 value 94.356792
iter  20 value 91.824042
iter  30 value 91.286301
iter  40 value 90.016836
iter  50 value 83.417408
iter  60 value 81.600766
iter  70 value 80.878859
iter  80 value 79.961259
iter  90 value 79.824632
iter 100 value 79.488296
final  value 79.488296 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.152039 
iter  10 value 94.475981
iter  20 value 91.373904
iter  30 value 83.684981
iter  40 value 80.546402
iter  50 value 79.506515
iter  60 value 78.792390
iter  70 value 78.216717
iter  80 value 77.961209
iter  90 value 77.868827
iter 100 value 77.688868
final  value 77.688868 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.885613 
iter  10 value 94.142604
iter  20 value 82.715275
iter  30 value 81.653348
iter  40 value 80.224004
iter  50 value 79.316692
iter  60 value 78.876798
iter  70 value 78.455894
iter  80 value 78.170461
iter  90 value 77.980374
iter 100 value 77.812795
final  value 77.812795 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.831885 
iter  10 value 94.492489
iter  20 value 93.310144
iter  30 value 83.955568
iter  40 value 83.056742
iter  50 value 80.402836
iter  60 value 79.597642
iter  70 value 79.189809
iter  80 value 78.425759
iter  90 value 78.100569
iter 100 value 77.935808
final  value 77.935808 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.957333 
iter  10 value 90.365586
iter  20 value 83.344714
iter  30 value 81.126131
iter  40 value 78.685973
iter  50 value 78.349829
iter  60 value 77.886477
iter  70 value 77.742302
iter  80 value 77.600051
iter  90 value 77.337450
iter 100 value 77.257073
final  value 77.257073 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.810959 
iter  10 value 91.643124
iter  20 value 86.056159
iter  30 value 84.815452
iter  40 value 82.307624
iter  50 value 82.019683
iter  60 value 79.199806
iter  70 value 78.365148
iter  80 value 77.694118
iter  90 value 77.585776
iter 100 value 77.379112
final  value 77.379112 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.359736 
iter  10 value 93.866145
iter  20 value 84.041725
iter  30 value 82.697410
iter  40 value 81.940217
iter  50 value 80.593789
iter  60 value 78.774667
iter  70 value 78.434125
iter  80 value 77.985858
iter  90 value 77.658657
iter 100 value 77.413983
final  value 77.413983 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.069533 
iter  10 value 93.610215
iter  20 value 85.534577
iter  30 value 85.046865
iter  40 value 82.515846
iter  50 value 80.876909
iter  60 value 79.598664
iter  70 value 79.550862
iter  80 value 79.277911
iter  90 value 79.147119
iter 100 value 79.048410
final  value 79.048410 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.869149 
iter  10 value 96.031981
iter  20 value 92.849975
iter  30 value 87.534984
iter  40 value 82.671981
iter  50 value 81.213270
iter  60 value 80.093989
iter  70 value 78.439775
iter  80 value 78.056242
iter  90 value 77.536766
iter 100 value 77.383462
final  value 77.383462 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.111360 
iter  10 value 89.028391
iter  20 value 88.646485
iter  30 value 86.642426
iter  40 value 86.639796
iter  50 value 85.459466
iter  60 value 85.457201
iter  70 value 85.456044
iter  80 value 84.506869
iter  90 value 83.683306
final  value 83.683291 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.813340 
final  value 94.485812 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.043748 
iter  10 value 94.485911
iter  20 value 94.480594
final  value 94.478786 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.330221 
iter  10 value 83.444031
iter  20 value 83.015955
iter  30 value 83.013528
iter  40 value 82.999912
iter  50 value 82.966785
iter  60 value 81.379303
iter  70 value 80.536550
iter  80 value 80.402214
iter  90 value 80.401787
final  value 80.401036 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.110864 
iter  10 value 94.485879
iter  20 value 94.438191
iter  30 value 92.326796
iter  40 value 92.210594
iter  50 value 91.320140
iter  60 value 90.804666
final  value 90.802573 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.137318 
iter  10 value 94.489469
iter  20 value 94.484337
iter  30 value 92.715693
iter  40 value 91.535613
iter  50 value 91.508564
final  value 91.508504 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.632519 
iter  10 value 94.489445
iter  20 value 94.474714
iter  30 value 84.157542
iter  40 value 81.629068
iter  50 value 79.824953
iter  60 value 79.591497
iter  70 value 79.323905
iter  80 value 79.259529
iter  90 value 79.238428
iter 100 value 79.183236
final  value 79.183236 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.717785 
iter  10 value 92.172392
iter  20 value 92.167661
iter  30 value 92.166066
iter  40 value 92.163270
iter  50 value 90.737786
iter  60 value 90.645066
iter  70 value 90.514694
iter  80 value 90.514361
final  value 90.513674 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.681973 
iter  10 value 93.816479
iter  20 value 93.814247
iter  30 value 93.812272
iter  40 value 93.812198
iter  40 value 93.812198
final  value 93.812198 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.764480 
iter  10 value 93.817332
iter  20 value 93.814033
iter  30 value 93.812344
final  value 93.812335 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.228003 
iter  10 value 93.820223
iter  20 value 93.816262
iter  30 value 91.197553
iter  40 value 86.033970
iter  50 value 84.827030
iter  60 value 82.230719
iter  70 value 82.086136
final  value 82.085780 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.429329 
iter  10 value 92.262818
iter  20 value 91.723926
iter  30 value 89.569733
iter  40 value 88.254126
iter  50 value 87.431784
iter  60 value 87.392898
iter  60 value 87.392897
final  value 87.392896 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.385945 
iter  10 value 94.492485
iter  20 value 94.343266
iter  30 value 93.773643
iter  30 value 93.773642
final  value 93.773637 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.099840 
iter  10 value 94.677121
iter  20 value 88.540205
iter  30 value 88.502749
iter  40 value 88.502302
iter  50 value 88.500824
iter  60 value 88.499778
iter  70 value 88.455950
iter  80 value 85.421640
iter  90 value 85.197407
iter 100 value 85.173209
final  value 85.173209 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.379485 
iter  10 value 93.819937
iter  20 value 93.816489
iter  30 value 90.957821
iter  40 value 90.321169
iter  50 value 90.318867
iter  60 value 90.318540
iter  70 value 90.318003
final  value 90.317888 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.746148 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.803227 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.295145 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.228216 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.704634 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.253811 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.838702 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.460241 
iter  10 value 92.945357
iter  20 value 92.822296
final  value 92.822222 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.750144 
final  value 93.601516 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.347832 
iter  10 value 94.053296
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.298095 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.984910 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.889308 
iter  10 value 93.582819
iter  20 value 92.071974
iter  30 value 90.909302
final  value 90.909125 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.947043 
iter  10 value 92.945402
final  value 92.945355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.539173 
iter  10 value 92.313239
iter  20 value 90.266450
final  value 90.262441 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.897604 
iter  10 value 93.985645
iter  20 value 93.231466
iter  30 value 93.060821
iter  40 value 86.722217
iter  50 value 85.629059
iter  60 value 84.778308
iter  70 value 84.490456
iter  80 value 82.691449
iter  90 value 82.367104
iter 100 value 82.141803
final  value 82.141803 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 93.427906 
iter  10 value 86.366614
iter  20 value 85.828625
iter  30 value 83.770495
iter  40 value 82.443447
iter  50 value 82.124166
iter  60 value 82.087795
final  value 82.087772 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.722615 
iter  10 value 94.025764
iter  20 value 90.932381
iter  30 value 88.398905
iter  40 value 85.330855
iter  50 value 84.073917
iter  60 value 83.945749
final  value 83.941619 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.263110 
iter  10 value 94.038185
iter  20 value 87.924715
iter  30 value 87.323923
iter  40 value 86.843366
iter  50 value 86.559006
iter  60 value 86.333170
final  value 86.318202 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.680460 
iter  10 value 94.056621
iter  20 value 93.396433
iter  30 value 93.240466
iter  40 value 93.160295
iter  50 value 92.879382
iter  60 value 88.264258
iter  70 value 84.589292
iter  80 value 84.177407
iter  90 value 84.085774
iter 100 value 84.047998
final  value 84.047998 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.139347 
iter  10 value 92.267358
iter  20 value 86.325384
iter  30 value 85.786379
iter  40 value 83.997427
iter  50 value 83.539917
iter  60 value 83.256915
iter  70 value 83.043587
iter  80 value 82.962201
iter  90 value 82.957430
iter  90 value 82.957429
final  value 82.957428 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.143223 
iter  10 value 95.763919
iter  20 value 89.053726
iter  30 value 86.773599
iter  40 value 85.690150
iter  50 value 82.636620
iter  60 value 82.306517
iter  70 value 82.177618
iter  80 value 81.992171
iter  90 value 81.943674
iter 100 value 81.912333
final  value 81.912333 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.487927 
iter  10 value 94.037000
iter  20 value 93.380507
iter  30 value 93.076375
iter  40 value 92.331224
iter  50 value 90.332895
iter  60 value 87.189831
iter  70 value 83.645767
iter  80 value 82.357176
iter  90 value 81.566822
iter 100 value 81.433866
final  value 81.433866 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.307424 
iter  10 value 94.030711
iter  20 value 92.200998
iter  30 value 91.052450
iter  40 value 88.438266
iter  50 value 83.752078
iter  60 value 82.819129
iter  70 value 82.190930
iter  80 value 81.886471
iter  90 value 81.640547
iter 100 value 81.270595
final  value 81.270595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.824698 
iter  10 value 94.021913
iter  20 value 92.984484
iter  30 value 89.150250
iter  40 value 87.163863
iter  50 value 86.838033
iter  60 value 86.601712
iter  70 value 86.441099
iter  80 value 84.423291
iter  90 value 83.191257
iter 100 value 81.815950
final  value 81.815950 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 134.417210 
iter  10 value 94.596473
iter  20 value 94.136688
iter  30 value 93.393080
iter  40 value 86.081590
iter  50 value 85.756728
iter  60 value 85.527154
iter  70 value 84.665461
iter  80 value 83.513211
iter  90 value 82.754312
iter 100 value 81.818686
final  value 81.818686 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.575590 
iter  10 value 91.385044
iter  20 value 88.980467
iter  30 value 88.598829
iter  40 value 83.701319
iter  50 value 83.011836
iter  60 value 82.710968
iter  70 value 82.439766
iter  80 value 82.083429
iter  90 value 81.664342
iter 100 value 81.367272
final  value 81.367272 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.999852 
iter  10 value 94.028566
iter  20 value 91.863641
iter  30 value 90.367617
iter  40 value 90.075697
iter  50 value 88.004993
iter  60 value 84.847583
iter  70 value 82.841179
iter  80 value 82.385243
iter  90 value 82.078231
iter 100 value 82.050965
final  value 82.050965 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.219095 
iter  10 value 94.286204
iter  20 value 92.790090
iter  30 value 86.298390
iter  40 value 84.545988
iter  50 value 83.630894
iter  60 value 81.487553
iter  70 value 80.997822
iter  80 value 80.883883
iter  90 value 80.855980
iter 100 value 80.753705
final  value 80.753705 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.210434 
iter  10 value 94.335813
iter  20 value 86.543548
iter  30 value 86.032255
iter  40 value 83.974544
iter  50 value 82.789291
iter  60 value 82.480218
iter  70 value 82.276297
iter  80 value 82.021622
iter  90 value 81.902993
iter 100 value 81.652420
final  value 81.652420 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.903202 
final  value 94.054514 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.897590 
iter  10 value 94.054392
iter  20 value 94.052967
final  value 94.052917 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.002480 
final  value 94.056977 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.025445 
final  value 94.054223 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.319478 
final  value 94.054719 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.840490 
iter  10 value 92.952889
iter  20 value 92.938816
iter  30 value 92.937032
iter  40 value 92.838238
iter  50 value 88.965923
iter  60 value 86.958564
iter  70 value 86.574508
iter  80 value 86.570159
iter  90 value 86.269403
iter 100 value 86.051166
final  value 86.051166 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.041095 
iter  10 value 94.057661
iter  20 value 94.031908
iter  30 value 92.292654
iter  40 value 90.493044
iter  50 value 83.272748
iter  60 value 82.177447
iter  70 value 82.046217
iter  80 value 81.329023
iter  90 value 81.168932
iter 100 value 81.168626
final  value 81.168626 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.394178 
iter  10 value 92.950669
iter  20 value 92.949715
iter  30 value 92.902844
iter  40 value 88.677812
iter  50 value 85.580426
iter  60 value 84.897159
iter  70 value 84.896627
iter  80 value 84.893222
final  value 84.892118 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.497009 
iter  10 value 94.056129
iter  20 value 93.096696
iter  30 value 92.807492
final  value 92.807449 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.150270 
iter  10 value 92.952365
iter  20 value 92.935011
iter  30 value 88.597408
iter  40 value 88.471445
iter  50 value 87.283025
iter  60 value 85.881823
iter  70 value 85.733532
iter  80 value 85.718419
iter  90 value 85.618310
iter 100 value 85.614362
final  value 85.614362 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.688068 
final  value 93.636968 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.332175 
iter  10 value 94.057855
iter  20 value 92.396161
iter  30 value 87.849041
iter  40 value 87.823023
iter  50 value 87.605858
iter  60 value 86.712697
iter  70 value 86.119697
iter  80 value 86.097021
iter  90 value 86.080669
final  value 86.080447 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.608721 
iter  10 value 92.955245
iter  20 value 92.936013
iter  30 value 91.620976
iter  40 value 90.422289
iter  50 value 86.240991
iter  60 value 83.658342
iter  70 value 83.060096
iter  80 value 82.908004
iter  90 value 81.853683
iter 100 value 80.674785
final  value 80.674785 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.105756 
iter  10 value 92.954619
iter  20 value 92.952883
iter  30 value 92.941183
iter  40 value 92.933668
iter  50 value 88.953692
iter  60 value 82.729054
iter  70 value 80.485938
iter  80 value 80.420914
iter  90 value 80.415188
final  value 80.415037 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.461776 
iter  10 value 93.954769
iter  20 value 93.438394
iter  30 value 88.490313
iter  40 value 87.010105
final  value 87.009922 
converged
Fitting Repeat 1 

# weights:  305
initial  value 170.245711 
iter  10 value 117.766986
iter  20 value 114.552072
iter  30 value 110.402296
iter  40 value 109.716811
iter  50 value 109.101127
iter  60 value 108.185454
iter  70 value 103.525501
iter  80 value 103.022554
iter  90 value 102.786580
iter 100 value 102.158477
final  value 102.158477 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.801940 
iter  10 value 109.237683
iter  20 value 108.751075
iter  30 value 108.218703
iter  40 value 104.903945
iter  50 value 104.741294
iter  60 value 104.708712
iter  70 value 104.652441
iter  80 value 103.217986
iter  90 value 102.877845
iter 100 value 102.775229
final  value 102.775229 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.423363 
iter  10 value 117.706244
iter  20 value 108.668373
iter  30 value 106.273971
iter  40 value 105.543377
iter  50 value 104.120755
iter  60 value 103.792329
iter  70 value 103.500263
iter  80 value 103.376123
iter  90 value 103.279725
iter 100 value 103.139419
final  value 103.139419 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.673568 
iter  10 value 117.775816
iter  20 value 110.205827
iter  30 value 106.926145
iter  30 value 106.926144
final  value 106.926144 
converged
Fitting Repeat 5 

# weights:  305
initial  value 155.815850 
iter  10 value 116.215010
iter  20 value 114.802538
iter  30 value 112.808662
iter  40 value 107.419897
iter  50 value 106.779332
iter  60 value 106.176693
iter  70 value 105.916465
iter  80 value 105.529382
iter  90 value 104.639569
iter 100 value 104.124780
final  value 104.124780 
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 Nov 30 20:31:23 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 
 20.134   0.453  69.273