##############################################################################
##############################################################################
###
### 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_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R version 4.5.0 RC (2025-04-04 r88126)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       18.505  0.855  19.416
FSmethod      17.938  0.870  19.023
corr_plot     17.615  0.687  18.533
pred_ensembel  5.470  0.115   5.178
enrichfindP    0.167  0.030   9.456
* 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: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.21-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/4.5-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
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 103.397143 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.167782 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.287687 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.782951 
final  value 94.052448 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.239730 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.974545 
final  value 93.671509 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.620895 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.536552 
iter  10 value 93.329959
iter  20 value 93.320547
final  value 93.320441 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.023357 
iter  10 value 94.032329
iter  10 value 94.032329
iter  10 value 94.032329
final  value 94.032329 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.333376 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.042779 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.557488 
final  value 94.052909 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.686430 
iter  10 value 93.925551
iter  20 value 92.199646
iter  30 value 92.197763
iter  40 value 92.177988
final  value 92.177986 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.270560 
iter  10 value 93.582422
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.333775 
iter  10 value 93.301910
iter  20 value 86.942629
iter  30 value 86.797060
iter  40 value 86.796910
final  value 86.796909 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.763655 
iter  10 value 94.041103
iter  20 value 92.914049
iter  30 value 89.509878
iter  40 value 87.694754
iter  50 value 87.524779
iter  60 value 86.600004
iter  70 value 85.857321
iter  80 value 80.459945
iter  90 value 79.758448
iter 100 value 78.630566
final  value 78.630566 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.735294 
iter  10 value 94.057124
iter  20 value 89.294796
iter  30 value 84.222398
iter  40 value 80.354590
iter  50 value 80.003450
iter  60 value 79.591944
iter  70 value 79.090828
iter  80 value 78.408626
iter  90 value 77.822584
iter 100 value 77.816259
final  value 77.816259 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.000122 
iter  10 value 93.917010
iter  20 value 82.040920
iter  30 value 81.530169
iter  40 value 81.421388
iter  50 value 80.806656
iter  60 value 80.168432
iter  70 value 79.866429
final  value 79.866427 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.830378 
iter  10 value 94.057145
iter  20 value 93.767272
iter  30 value 93.692768
iter  40 value 93.685961
iter  50 value 93.684929
iter  60 value 87.162461
iter  70 value 80.437916
iter  80 value 79.644078
iter  90 value 78.236719
iter 100 value 77.784607
final  value 77.784607 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.235890 
iter  10 value 93.930712
iter  20 value 86.108883
iter  30 value 83.772411
iter  40 value 83.364618
iter  50 value 83.000996
iter  60 value 82.522620
iter  70 value 82.399119
iter  80 value 82.397220
final  value 82.397215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.645065 
iter  10 value 94.035840
iter  20 value 93.658789
iter  30 value 91.183552
iter  40 value 86.751454
iter  50 value 83.384756
iter  60 value 83.016786
iter  70 value 81.300914
iter  80 value 79.311177
iter  90 value 78.679076
iter 100 value 78.492597
final  value 78.492597 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.841850 
iter  10 value 92.928273
iter  20 value 91.448393
iter  30 value 82.345777
iter  40 value 81.522743
iter  50 value 80.808007
iter  60 value 79.540024
iter  70 value 77.791958
iter  80 value 77.321629
iter  90 value 76.802592
iter 100 value 76.405222
final  value 76.405222 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.885916 
iter  10 value 94.352446
iter  20 value 90.998284
iter  30 value 90.639263
iter  40 value 90.477613
iter  50 value 90.195775
iter  60 value 84.071247
iter  70 value 79.265821
iter  80 value 78.836283
iter  90 value 78.629532
iter 100 value 78.164870
final  value 78.164870 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.037548 
iter  10 value 94.072656
iter  20 value 87.303023
iter  30 value 84.699535
iter  40 value 82.738490
iter  50 value 80.480032
iter  60 value 79.623335
iter  70 value 78.532544
iter  80 value 77.322887
iter  90 value 76.795552
iter 100 value 76.674887
final  value 76.674887 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.372635 
iter  10 value 94.055776
iter  20 value 86.319189
iter  30 value 81.831486
iter  40 value 80.411762
iter  50 value 80.075100
iter  60 value 79.795503
iter  70 value 78.840698
iter  80 value 77.756789
iter  90 value 76.571722
iter 100 value 76.473826
final  value 76.473826 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.019408 
iter  10 value 92.624389
iter  20 value 91.636667
iter  30 value 86.176472
iter  40 value 82.557087
iter  50 value 80.670946
iter  60 value 79.194526
iter  70 value 77.702049
iter  80 value 76.780386
iter  90 value 76.657900
iter 100 value 76.618396
final  value 76.618396 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.814192 
iter  10 value 94.022593
iter  20 value 84.534045
iter  30 value 80.460997
iter  40 value 80.034787
iter  50 value 78.301083
iter  60 value 77.625432
iter  70 value 77.474127
iter  80 value 77.079186
iter  90 value 76.899587
iter 100 value 76.703574
final  value 76.703574 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.684058 
iter  10 value 94.094943
iter  20 value 88.551174
iter  30 value 84.488053
iter  40 value 83.083731
iter  50 value 81.040315
iter  60 value 79.007060
iter  70 value 77.841085
iter  80 value 77.567946
iter  90 value 77.227215
iter 100 value 76.558292
final  value 76.558292 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.662036 
iter  10 value 94.297075
iter  20 value 89.508728
iter  30 value 84.095379
iter  40 value 83.077285
iter  50 value 82.465316
iter  60 value 82.348319
iter  70 value 82.173554
iter  80 value 79.726080
iter  90 value 77.674177
iter 100 value 77.109181
final  value 77.109181 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.640331 
iter  10 value 93.722608
iter  20 value 86.829061
iter  30 value 81.902622
iter  40 value 81.573166
iter  50 value 80.764688
iter  60 value 80.215935
iter  70 value 78.830188
iter  80 value 77.098624
iter  90 value 76.584977
iter 100 value 76.351326
final  value 76.351326 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.444260 
iter  10 value 94.054574
final  value 94.052912 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.701250 
final  value 94.054456 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.703082 
final  value 94.054909 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.048353 
final  value 94.054784 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.349408 
iter  10 value 94.054950
final  value 94.053157 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.889862 
iter  10 value 94.057975
iter  20 value 94.052910
iter  30 value 93.580434
iter  40 value 92.810094
final  value 92.803996 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.239179 
iter  10 value 94.057245
iter  20 value 94.052646
iter  30 value 93.664238
final  value 93.583182 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.651203 
iter  10 value 93.464666
iter  20 value 93.197047
iter  30 value 93.194591
final  value 93.194294 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.468734 
iter  10 value 94.058316
iter  20 value 93.955939
iter  30 value 84.848194
final  value 84.745885 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.223802 
iter  10 value 94.057038
iter  20 value 94.052946
final  value 94.052916 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.325088 
iter  10 value 94.061461
iter  20 value 92.543324
iter  30 value 81.823816
iter  40 value 79.495736
iter  50 value 79.204485
iter  60 value 79.199798
iter  70 value 78.710928
iter  80 value 77.594874
iter  90 value 75.846498
iter 100 value 75.790993
final  value 75.790993 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.386737 
iter  10 value 94.061477
iter  20 value 94.016116
iter  30 value 92.862092
iter  30 value 92.862092
iter  30 value 92.862092
final  value 92.862092 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.711377 
iter  10 value 92.854443
iter  20 value 92.812371
iter  30 value 92.809211
iter  40 value 92.804427
iter  50 value 92.804339
iter  60 value 92.692725
iter  70 value 92.307924
iter  80 value 89.382946
iter  90 value 78.869347
iter 100 value 76.677023
final  value 76.677023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.229809 
iter  10 value 94.055122
iter  20 value 93.715270
iter  30 value 87.619572
iter  40 value 87.085280
iter  50 value 86.933876
iter  60 value 86.931343
iter  70 value 85.005982
iter  80 value 84.933061
iter  90 value 84.932558
final  value 84.932556 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.661684 
iter  10 value 87.627893
iter  20 value 85.205766
final  value 85.202729 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.178925 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.000336 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.521619 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.061083 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.975895 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.822139 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.163767 
iter  10 value 94.227298
iter  20 value 91.717281
iter  30 value 91.527710
final  value 91.527452 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.457695 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.892860 
iter  10 value 94.202038
iter  10 value 94.202037
iter  10 value 94.202037
final  value 94.202037 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.056725 
final  value 94.448052 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.304912 
iter  10 value 93.786590
iter  20 value 93.696363
final  value 93.696359 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.603393 
iter  10 value 93.674449
iter  20 value 93.668311
iter  30 value 93.634576
final  value 93.633783 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.667555 
final  value 94.484212 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.690886 
iter  10 value 94.355491
iter  20 value 94.354287
iter  20 value 94.354287
iter  20 value 94.354286
final  value 94.354286 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.544669 
final  value 94.088889 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.356242 
iter  10 value 94.441259
iter  20 value 94.199577
iter  30 value 94.161815
final  value 94.161779 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.062634 
iter  10 value 94.421836
iter  20 value 94.126195
iter  30 value 94.125952
iter  40 value 91.618217
iter  50 value 87.745229
iter  60 value 87.445767
iter  70 value 87.161548
iter  80 value 86.025887
iter  90 value 84.336523
iter 100 value 84.099071
final  value 84.099071 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.773723 
iter  10 value 94.475197
iter  20 value 94.203622
iter  30 value 94.141434
iter  40 value 90.354247
iter  50 value 85.588864
iter  60 value 84.725762
iter  70 value 84.599307
iter  80 value 84.464552
iter  90 value 84.444155
iter 100 value 84.443859
final  value 84.443859 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 107.468934 
iter  10 value 94.208846
iter  20 value 92.651966
iter  30 value 92.287215
iter  40 value 92.285218
final  value 92.285205 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.731647 
iter  10 value 94.486457
iter  20 value 94.146656
iter  30 value 94.126017
iter  40 value 93.843778
iter  50 value 86.364927
iter  60 value 85.085579
iter  70 value 84.623751
iter  80 value 84.533575
iter  90 value 84.427748
iter 100 value 84.216809
final  value 84.216809 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.803910 
iter  10 value 94.461486
iter  20 value 93.300945
iter  30 value 87.372629
iter  40 value 86.817036
iter  50 value 86.634003
iter  60 value 84.616718
iter  70 value 83.759819
iter  80 value 83.612735
iter  90 value 83.488159
iter 100 value 82.784699
final  value 82.784699 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.049909 
iter  10 value 89.028176
iter  20 value 85.292666
iter  30 value 85.166392
iter  40 value 84.850678
iter  50 value 84.352235
iter  60 value 84.210566
iter  70 value 83.844392
iter  80 value 82.399191
iter  90 value 81.346789
iter 100 value 81.240042
final  value 81.240042 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.653766 
iter  10 value 94.519827
iter  20 value 88.354000
iter  30 value 85.878194
iter  40 value 85.409147
iter  50 value 84.801098
iter  60 value 83.513639
iter  70 value 81.990502
iter  80 value 81.776182
iter  90 value 81.538298
iter 100 value 81.336134
final  value 81.336134 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.394448 
iter  10 value 94.462242
iter  20 value 86.481864
iter  30 value 85.720527
iter  40 value 85.208020
iter  50 value 84.446298
iter  60 value 82.658976
iter  70 value 81.472677
iter  80 value 81.333433
iter  90 value 81.204537
iter 100 value 81.025398
final  value 81.025398 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.317111 
iter  10 value 94.583471
iter  20 value 94.509658
iter  30 value 94.481290
iter  40 value 92.426419
iter  50 value 87.954501
iter  60 value 87.478115
iter  70 value 84.507997
iter  80 value 82.702872
iter  90 value 82.439991
iter 100 value 82.274194
final  value 82.274194 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.282124 
iter  10 value 95.157012
iter  20 value 94.312063
iter  30 value 94.133845
iter  40 value 92.337473
iter  50 value 88.352692
iter  60 value 86.564553
iter  70 value 85.152881
iter  80 value 83.480819
iter  90 value 82.533980
iter 100 value 81.902786
final  value 81.902786 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.117710 
iter  10 value 95.034940
iter  20 value 94.830989
iter  30 value 86.213660
iter  40 value 85.414318
iter  50 value 84.604475
iter  60 value 84.250106
iter  70 value 84.070054
iter  80 value 83.990852
iter  90 value 83.961779
iter 100 value 83.951864
final  value 83.951864 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.311416 
iter  10 value 94.649192
iter  20 value 92.461276
iter  30 value 88.376245
iter  40 value 87.340868
iter  50 value 86.285464
iter  60 value 84.123993
iter  70 value 83.017510
iter  80 value 81.668653
iter  90 value 81.313869
iter 100 value 81.095206
final  value 81.095206 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.863073 
iter  10 value 94.882703
iter  20 value 94.051363
iter  30 value 93.995723
iter  40 value 93.946555
iter  50 value 89.205399
iter  60 value 88.085877
iter  70 value 85.775480
iter  80 value 84.782377
iter  90 value 84.350670
iter 100 value 83.592744
final  value 83.592744 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.813790 
iter  10 value 85.631025
iter  20 value 84.726934
iter  30 value 83.335307
iter  40 value 82.253082
iter  50 value 82.108527
iter  60 value 81.926014
iter  70 value 81.490745
iter  80 value 81.139009
iter  90 value 81.029534
iter 100 value 80.859178
final  value 80.859178 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.309554 
final  value 94.485676 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.186493 
final  value 94.485953 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.169772 
iter  10 value 94.485930
final  value 94.485406 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.728977 
final  value 94.028597 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.684453 
iter  10 value 94.449829
iter  20 value 94.448567
final  value 94.448099 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.501781 
iter  10 value 94.031633
iter  20 value 94.011503
iter  30 value 92.542687
iter  40 value 88.792867
iter  50 value 88.501778
final  value 88.496746 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.593362 
iter  10 value 94.494168
iter  20 value 94.465117
iter  30 value 88.450457
iter  40 value 87.597568
iter  50 value 87.407858
iter  60 value 84.417547
iter  70 value 84.407145
iter  80 value 84.404785
iter  90 value 83.311163
iter 100 value 82.840255
final  value 82.840255 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.361767 
iter  10 value 94.031503
iter  20 value 93.943745
iter  30 value 86.341460
iter  40 value 84.439105
iter  50 value 84.380150
iter  60 value 84.379540
iter  70 value 84.379488
iter  80 value 84.379102
final  value 84.377628 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.847165 
iter  10 value 94.489428
iter  20 value 94.481699
iter  30 value 94.030088
iter  40 value 94.028069
iter  50 value 93.979408
final  value 93.975597 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.386984 
iter  10 value 94.485726
iter  20 value 94.423534
iter  30 value 94.021494
iter  40 value 91.339946
iter  50 value 87.150712
iter  60 value 87.037768
iter  70 value 86.943755
iter  80 value 86.930469
iter  90 value 84.360685
iter 100 value 83.059178
final  value 83.059178 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.040897 
iter  10 value 93.677288
iter  20 value 93.675146
iter  30 value 86.198101
iter  40 value 86.183722
iter  50 value 86.176308
iter  60 value 86.174382
iter  70 value 86.110831
iter  80 value 86.109522
final  value 86.109508 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.556273 
iter  10 value 93.800906
iter  20 value 93.796544
iter  30 value 93.791508
iter  40 value 93.226290
iter  50 value 89.373864
iter  60 value 85.106683
iter  70 value 85.068455
iter  80 value 84.869073
iter  90 value 84.695184
iter 100 value 84.674790
final  value 84.674790 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.376505 
iter  10 value 94.485268
iter  20 value 93.320630
iter  30 value 83.425223
iter  40 value 82.829625
iter  50 value 82.557041
final  value 82.556849 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.302711 
iter  10 value 94.495249
iter  20 value 94.486620
iter  30 value 94.236557
iter  40 value 92.465425
iter  50 value 92.110351
iter  60 value 92.109090
iter  70 value 88.433249
iter  80 value 83.156448
iter  90 value 82.799509
iter 100 value 82.567278
final  value 82.567278 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.698578 
iter  10 value 94.485382
iter  20 value 93.346266
iter  30 value 92.605542
iter  40 value 91.977712
iter  50 value 87.580255
iter  60 value 87.529888
iter  70 value 87.100198
iter  80 value 87.095628
iter  80 value 87.095628
final  value 87.095628 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.342097 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.050645 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.115582 
iter  10 value 90.110983
iter  20 value 86.307333
iter  30 value 86.120102
iter  40 value 86.108297
iter  50 value 86.033314
iter  60 value 85.943423
final  value 85.942126 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.164373 
iter  10 value 88.757917
iter  20 value 86.193330
iter  30 value 85.962100
iter  40 value 85.960530
iter  40 value 85.960529
iter  40 value 85.960529
final  value 85.960529 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.431493 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.802166 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.329905 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.553577 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 93.416893 
iter  10 value 88.166968
iter  20 value 86.316401
iter  30 value 86.088392
iter  40 value 85.939953
final  value 85.939856 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.018159 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.875185 
final  value 93.874286 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.963051 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.489508 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.609894 
iter  10 value 92.487607
iter  20 value 89.216322
iter  30 value 89.131840
iter  40 value 89.125490
final  value 89.125064 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.799673 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.897790 
iter  10 value 90.578664
iter  20 value 87.750920
iter  30 value 84.862691
iter  40 value 84.803880
iter  50 value 84.794607
iter  60 value 84.763162
iter  70 value 84.678546
iter  80 value 84.612228
final  value 84.604455 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.144078 
iter  10 value 94.056842
iter  20 value 94.054701
iter  30 value 91.192759
iter  40 value 86.764781
iter  50 value 86.397926
iter  60 value 85.829565
iter  70 value 85.742656
iter  80 value 84.565691
iter  90 value 83.810291
iter 100 value 83.098839
final  value 83.098839 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.842902 
iter  10 value 94.054892
iter  20 value 89.638829
iter  30 value 88.500086
iter  40 value 85.873371
iter  50 value 85.156048
iter  60 value 85.101774
iter  70 value 84.793094
iter  80 value 84.647220
iter  90 value 84.612777
iter 100 value 84.607381
final  value 84.607381 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.223862 
iter  10 value 94.005430
iter  20 value 86.134128
iter  30 value 85.943530
iter  40 value 85.217842
iter  50 value 84.679076
iter  60 value 84.433972
iter  70 value 83.326630
iter  80 value 82.791200
final  value 82.790918 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.016605 
iter  10 value 94.211396
iter  20 value 91.888945
iter  30 value 87.480737
iter  40 value 86.772640
iter  50 value 85.802758
iter  60 value 85.352690
iter  70 value 85.120740
iter  80 value 83.657995
iter  90 value 82.818040
iter 100 value 82.790952
final  value 82.790952 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.026861 
iter  10 value 94.112615
iter  20 value 92.027649
iter  30 value 85.416830
iter  40 value 84.677912
iter  50 value 84.226737
iter  60 value 84.176630
iter  70 value 83.978609
iter  80 value 83.268879
iter  90 value 82.637018
iter 100 value 82.274388
final  value 82.274388 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.073102 
iter  10 value 94.119822
iter  20 value 94.045617
iter  30 value 92.877328
iter  40 value 86.670294
iter  50 value 86.393751
iter  60 value 84.827446
iter  70 value 84.043082
iter  80 value 83.483861
iter  90 value 83.455281
iter 100 value 83.228679
final  value 83.228679 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.594927 
iter  10 value 94.018803
iter  20 value 92.967959
iter  30 value 92.791021
iter  40 value 92.409933
iter  50 value 92.136429
iter  60 value 86.894896
iter  70 value 86.121779
iter  80 value 84.928056
iter  90 value 83.878545
iter 100 value 83.541298
final  value 83.541298 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.177839 
iter  10 value 94.246361
iter  20 value 89.853771
iter  30 value 85.973603
iter  40 value 85.459299
iter  50 value 84.737416
iter  60 value 84.434158
iter  70 value 84.125508
iter  80 value 82.684763
iter  90 value 82.453851
iter 100 value 81.789312
final  value 81.789312 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.136717 
iter  10 value 93.934209
iter  20 value 92.652478
iter  30 value 89.121629
iter  40 value 88.109657
iter  50 value 85.205402
iter  60 value 83.245099
iter  70 value 82.800150
iter  80 value 82.596691
iter  90 value 82.473534
iter 100 value 82.406653
final  value 82.406653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 144.373062 
iter  10 value 94.057670
iter  20 value 93.887991
iter  30 value 89.956591
iter  40 value 87.112962
iter  50 value 86.562181
iter  60 value 85.421944
iter  70 value 83.743658
iter  80 value 83.394630
iter  90 value 83.254278
iter 100 value 82.826099
final  value 82.826099 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.598791 
iter  10 value 93.994931
iter  20 value 92.002332
iter  30 value 91.598765
iter  40 value 89.222134
iter  50 value 86.814466
iter  60 value 86.004228
iter  70 value 84.622950
iter  80 value 83.720971
iter  90 value 83.424803
iter 100 value 82.998537
final  value 82.998537 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.843479 
iter  10 value 94.334353
iter  20 value 94.235978
iter  30 value 93.664584
iter  40 value 92.631880
iter  50 value 91.737309
iter  60 value 87.941086
iter  70 value 85.233673
iter  80 value 83.732345
iter  90 value 83.298575
iter 100 value 83.258040
final  value 83.258040 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.424226 
iter  10 value 94.218320
iter  20 value 94.043618
iter  30 value 92.322585
iter  40 value 86.819768
iter  50 value 86.192813
iter  60 value 84.277151
iter  70 value 83.351712
iter  80 value 82.535684
iter  90 value 81.976272
iter 100 value 81.643615
final  value 81.643615 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.959603 
iter  10 value 94.039088
iter  20 value 87.422345
iter  30 value 85.545849
iter  40 value 82.735456
iter  50 value 82.502285
iter  60 value 82.394409
iter  70 value 82.257475
iter  80 value 82.080345
iter  90 value 81.841679
iter 100 value 81.725968
final  value 81.725968 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.858339 
final  value 94.054672 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.067128 
iter  10 value 94.054316
iter  20 value 93.921535
iter  30 value 85.617670
final  value 85.600350 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.135148 
final  value 94.054528 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.817902 
final  value 94.054348 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.001714 
final  value 94.054537 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.368996 
iter  10 value 94.038065
iter  20 value 94.034688
iter  30 value 93.805916
iter  40 value 87.056557
iter  50 value 85.327593
iter  60 value 84.751316
final  value 84.736616 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.279352 
iter  10 value 93.278237
iter  20 value 91.597023
iter  30 value 91.536478
iter  40 value 91.517853
iter  50 value 91.474648
iter  60 value 91.184129
final  value 91.182278 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.330903 
iter  10 value 94.026445
iter  20 value 90.386738
iter  30 value 86.048698
iter  40 value 85.457486
iter  40 value 85.457485
iter  40 value 85.457485
final  value 85.457485 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.181820 
iter  10 value 93.918600
iter  20 value 93.901654
iter  30 value 93.858341
iter  40 value 93.853939
final  value 93.852218 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.414844 
iter  10 value 94.057634
iter  20 value 94.036337
iter  30 value 93.377603
iter  40 value 93.141432
iter  50 value 91.147698
iter  60 value 85.561850
iter  70 value 85.542150
iter  80 value 85.541807
iter  90 value 85.472565
iter 100 value 85.470119
final  value 85.470119 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.644630 
iter  10 value 94.041107
iter  20 value 93.433416
iter  30 value 86.636823
iter  30 value 86.636822
iter  30 value 86.636822
final  value 86.636822 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.623806 
iter  10 value 93.883320
iter  20 value 90.235293
iter  30 value 89.012739
iter  40 value 84.875009
iter  50 value 83.776292
iter  60 value 83.733881
iter  70 value 82.989716
iter  80 value 82.895448
iter  90 value 82.858039
iter 100 value 82.837323
final  value 82.837323 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.683034 
iter  10 value 94.061120
iter  20 value 94.053163
iter  30 value 93.542599
iter  40 value 93.539819
final  value 93.539801 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.665070 
iter  10 value 94.060730
iter  20 value 93.201317
iter  30 value 86.550246
iter  40 value 85.908591
iter  50 value 85.886326
iter  60 value 83.470599
iter  70 value 83.397941
iter  80 value 83.396041
iter  90 value 83.392577
iter 100 value 83.390508
final  value 83.390508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.622063 
iter  10 value 84.197391
iter  20 value 83.728440
iter  30 value 82.929802
iter  40 value 81.443693
iter  50 value 81.218743
iter  60 value 80.727437
iter  70 value 80.651345
iter  80 value 80.568077
iter  90 value 80.311967
iter 100 value 80.178350
final  value 80.178350 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.996587 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.008911 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.674829 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.189879 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.407044 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.480910 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.880600 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.157780 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.639135 
final  value 94.132871 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.704652 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.006814 
iter  10 value 94.275183
iter  20 value 94.057031
iter  30 value 94.051994
final  value 94.051984 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.722857 
final  value 94.312038 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.352546 
iter  10 value 91.200167
iter  20 value 91.120763
iter  30 value 91.119871
final  value 91.119852 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.238956 
iter  10 value 94.432863
final  value 94.409639 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.627131 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.875352 
iter  10 value 94.486576
iter  20 value 94.358634
iter  30 value 89.272009
iter  40 value 88.861667
iter  50 value 81.310976
iter  60 value 81.042089
iter  70 value 80.187963
iter  80 value 79.673165
iter  90 value 79.566381
iter 100 value 79.555875
final  value 79.555875 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.219848 
iter  10 value 94.362790
iter  20 value 88.723050
iter  30 value 84.333056
iter  40 value 83.714393
iter  50 value 83.032801
iter  60 value 82.559990
iter  70 value 82.141161
iter  80 value 82.115161
final  value 82.109848 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.462865 
iter  10 value 94.247602
iter  20 value 91.911639
iter  30 value 90.155224
iter  40 value 90.003293
iter  50 value 89.687764
iter  60 value 89.654270
iter  70 value 83.595709
iter  80 value 81.651000
iter  90 value 80.940905
iter 100 value 80.620574
final  value 80.620574 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.608145 
iter  10 value 94.498108
iter  20 value 94.456631
iter  30 value 94.192138
iter  40 value 94.100496
iter  50 value 94.089710
iter  60 value 90.565517
iter  70 value 85.707302
iter  80 value 84.089555
iter  90 value 83.319011
iter 100 value 82.947491
final  value 82.947491 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.903459 
iter  10 value 94.345714
iter  20 value 91.852735
iter  30 value 91.622611
iter  40 value 91.609429
iter  50 value 91.543603
iter  60 value 89.909048
iter  70 value 89.665859
iter  80 value 89.653248
iter  90 value 84.824597
iter 100 value 82.043673
final  value 82.043673 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.681755 
iter  10 value 94.491295
iter  20 value 90.848493
iter  30 value 87.708713
iter  40 value 84.424483
iter  50 value 83.297340
iter  60 value 81.153910
iter  70 value 80.745441
iter  80 value 80.098612
iter  90 value 79.578689
iter 100 value 78.718202
final  value 78.718202 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.440727 
iter  10 value 94.600282
iter  20 value 94.496093
iter  30 value 93.453131
iter  40 value 86.586849
iter  50 value 81.219227
iter  60 value 80.882433
iter  70 value 80.830532
iter  80 value 80.236297
iter  90 value 79.278043
iter 100 value 78.342729
final  value 78.342729 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.531361 
iter  10 value 94.327390
iter  20 value 83.733387
iter  30 value 80.694578
iter  40 value 80.118269
iter  50 value 79.013878
iter  60 value 78.726741
iter  70 value 78.430701
iter  80 value 78.266164
iter  90 value 78.196963
iter 100 value 78.163892
final  value 78.163892 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.111912 
iter  10 value 94.774320
iter  20 value 94.492521
iter  30 value 94.450111
iter  40 value 90.426634
iter  50 value 87.491512
iter  60 value 83.984109
iter  70 value 83.110861
iter  80 value 80.286059
iter  90 value 79.636662
iter 100 value 79.302262
final  value 79.302262 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.900414 
iter  10 value 94.523369
iter  20 value 87.541078
iter  30 value 83.551638
iter  40 value 83.244965
iter  50 value 81.714642
iter  60 value 80.347883
iter  70 value 79.115939
iter  80 value 78.867187
iter  90 value 78.610470
iter 100 value 78.108743
final  value 78.108743 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.447854 
iter  10 value 94.498176
iter  20 value 87.807066
iter  30 value 84.738955
iter  40 value 81.989059
iter  50 value 81.646740
iter  60 value 80.512974
iter  70 value 79.925466
iter  80 value 79.309774
iter  90 value 78.869684
iter 100 value 78.715711
final  value 78.715711 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.268297 
iter  10 value 93.870369
iter  20 value 85.863260
iter  30 value 83.704617
iter  40 value 83.321019
iter  50 value 81.374938
iter  60 value 80.524486
iter  70 value 79.268380
iter  80 value 78.996711
iter  90 value 78.735916
iter 100 value 78.610060
final  value 78.610060 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.850853 
iter  10 value 95.151411
iter  20 value 92.733224
iter  30 value 84.765077
iter  40 value 83.846944
iter  50 value 83.171949
iter  60 value 82.408891
iter  70 value 81.441222
iter  80 value 80.804070
iter  90 value 80.669812
iter 100 value 80.341928
final  value 80.341928 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.964872 
iter  10 value 102.410921
iter  20 value 93.561749
iter  30 value 87.803687
iter  40 value 85.275935
iter  50 value 84.849923
iter  60 value 83.298221
iter  70 value 82.036324
iter  80 value 80.382269
iter  90 value 79.620921
iter 100 value 79.181852
final  value 79.181852 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.818178 
iter  10 value 94.331257
iter  20 value 85.370179
iter  30 value 83.974110
iter  40 value 82.181469
iter  50 value 81.435470
iter  60 value 80.882415
iter  70 value 80.542905
iter  80 value 80.420121
iter  90 value 79.983957
iter 100 value 79.369980
final  value 79.369980 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.208992 
iter  10 value 94.485872
iter  20 value 94.484271
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.222357 
iter  10 value 94.445047
iter  20 value 94.443368
iter  30 value 94.209711
iter  40 value 94.057850
final  value 94.057463 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.825515 
iter  10 value 85.886915
iter  20 value 84.360516
iter  30 value 83.711348
iter  40 value 83.693636
iter  50 value 83.692995
final  value 83.692908 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.516907 
final  value 94.485691 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.192624 
final  value 94.485706 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.732953 
iter  10 value 94.488566
iter  20 value 94.461764
iter  30 value 85.989832
iter  40 value 83.841500
iter  50 value 83.837484
final  value 83.837465 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.431106 
iter  10 value 94.487686
iter  20 value 88.198190
iter  30 value 87.084555
iter  40 value 86.414308
iter  50 value 86.410757
iter  60 value 86.352975
iter  70 value 85.981420
iter  80 value 85.977839
iter  90 value 85.976955
iter 100 value 85.439898
final  value 85.439898 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.901966 
iter  10 value 94.490940
iter  20 value 90.005354
iter  30 value 87.816574
iter  40 value 87.363148
iter  50 value 86.098072
final  value 86.097726 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.502605 
iter  10 value 94.489052
iter  20 value 94.484341
iter  30 value 94.465590
iter  40 value 94.058668
iter  50 value 94.057759
final  value 94.057735 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.069057 
iter  10 value 94.316716
iter  20 value 94.312264
iter  30 value 94.162952
iter  40 value 94.052151
iter  50 value 90.747071
iter  60 value 83.498615
iter  70 value 83.498228
iter  80 value 83.481297
iter  90 value 83.405709
iter 100 value 82.037930
final  value 82.037930 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.904178 
iter  10 value 94.243513
iter  20 value 84.360088
iter  30 value 82.872026
iter  40 value 82.719176
iter  50 value 82.714605
iter  60 value 82.711565
iter  70 value 82.710310
iter  80 value 82.698027
iter  90 value 82.627078
iter 100 value 81.946016
final  value 81.946016 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.921918 
iter  10 value 94.491308
iter  20 value 94.473721
iter  30 value 83.644357
iter  40 value 81.434795
iter  50 value 80.542384
iter  60 value 80.535809
iter  70 value 79.706913
iter  80 value 78.976015
iter  90 value 78.970459
iter 100 value 78.829601
final  value 78.829601 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.437692 
iter  10 value 88.176255
iter  20 value 88.155781
iter  30 value 86.595596
iter  40 value 86.593952
iter  50 value 86.012017
iter  60 value 83.891898
iter  70 value 80.929806
iter  80 value 80.923929
iter  90 value 80.457491
iter 100 value 78.891608
final  value 78.891608 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.162595 
iter  10 value 94.451872
iter  20 value 94.428055
iter  30 value 93.131294
iter  40 value 84.063376
iter  50 value 82.008649
iter  60 value 81.410060
final  value 81.404722 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.183152 
iter  10 value 86.727472
iter  20 value 86.242854
iter  30 value 86.242404
iter  40 value 85.746920
iter  50 value 85.055172
iter  60 value 85.054964
final  value 85.054784 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.963873 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.600049 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.216226 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.695489 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.980440 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.038039 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.845574 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.728300 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.645907 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.986964 
iter  10 value 94.443270
final  value 94.443265 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.120647 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.839811 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.332060 
iter  10 value 94.484193
iter  20 value 94.473946
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.143646 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.132595 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.805845 
iter  10 value 94.216542
iter  20 value 88.999559
iter  30 value 86.536928
iter  40 value 85.763336
iter  50 value 85.598314
iter  60 value 85.568085
iter  70 value 85.540754
iter  80 value 85.532692
final  value 85.531180 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.770725 
iter  10 value 94.312509
iter  20 value 92.894480
iter  30 value 91.855605
iter  40 value 90.972073
iter  50 value 89.503898
iter  60 value 84.784396
iter  70 value 83.724914
iter  80 value 83.632259
final  value 83.632143 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.974923 
iter  10 value 94.436481
iter  20 value 88.433863
iter  30 value 86.080701
iter  40 value 85.939250
iter  50 value 85.915561
iter  60 value 85.901254
final  value 85.901121 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.375445 
iter  10 value 94.414090
iter  20 value 93.394444
iter  30 value 91.140519
iter  40 value 90.922933
iter  50 value 87.071587
iter  60 value 86.066818
iter  70 value 85.976474
final  value 85.976109 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.378256 
iter  10 value 94.388109
iter  20 value 87.158800
iter  30 value 85.191258
iter  40 value 84.845468
iter  50 value 84.611920
iter  60 value 84.393099
final  value 84.390892 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.551655 
iter  10 value 94.411902
iter  20 value 87.051667
iter  30 value 86.931608
iter  40 value 86.746728
iter  50 value 85.630185
iter  60 value 85.528623
iter  70 value 85.481299
iter  80 value 84.943016
iter  90 value 84.682435
iter 100 value 83.805505
final  value 83.805505 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.857140 
iter  10 value 94.464563
iter  20 value 92.418309
iter  30 value 90.801266
iter  40 value 90.025946
iter  50 value 89.401807
iter  60 value 88.342890
iter  70 value 85.659786
iter  80 value 85.052392
iter  90 value 84.655696
iter 100 value 84.469741
final  value 84.469741 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.629290 
iter  10 value 94.030415
iter  20 value 87.754201
iter  30 value 85.523017
iter  40 value 84.630372
iter  50 value 84.176055
iter  60 value 83.928443
iter  70 value 83.589061
iter  80 value 82.789770
iter  90 value 82.725600
iter 100 value 82.720816
final  value 82.720816 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.199160 
iter  10 value 94.276131
iter  20 value 87.448354
iter  30 value 86.056309
iter  40 value 85.629647
iter  50 value 85.419760
iter  60 value 85.367235
iter  70 value 84.460561
iter  80 value 83.456713
iter  90 value 83.123562
iter 100 value 82.750484
final  value 82.750484 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.706429 
iter  10 value 94.657163
iter  20 value 94.513187
iter  30 value 91.882824
iter  40 value 89.652869
iter  50 value 88.230888
iter  60 value 87.532839
iter  70 value 86.349196
iter  80 value 86.022959
iter  90 value 85.950802
iter 100 value 85.725891
final  value 85.725891 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.328278 
iter  10 value 94.675631
iter  20 value 94.502176
iter  30 value 88.373722
iter  40 value 86.334681
iter  50 value 85.740291
iter  60 value 85.115870
iter  70 value 84.435585
iter  80 value 83.106097
iter  90 value 82.463729
iter 100 value 82.412180
final  value 82.412180 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.068943 
iter  10 value 94.835276
iter  20 value 91.064129
iter  30 value 88.162275
iter  40 value 86.811124
iter  50 value 86.552058
iter  60 value 84.780111
iter  70 value 83.779999
iter  80 value 82.784531
iter  90 value 82.378156
iter 100 value 82.163641
final  value 82.163641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.449115 
iter  10 value 95.029859
iter  20 value 90.111447
iter  30 value 86.168836
iter  40 value 85.817231
iter  50 value 85.602029
iter  60 value 85.453223
iter  70 value 84.722059
iter  80 value 83.376951
iter  90 value 82.951984
iter 100 value 82.459103
final  value 82.459103 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.445848 
iter  10 value 94.763088
iter  20 value 94.546032
iter  30 value 94.374304
iter  40 value 93.235285
iter  50 value 92.973668
iter  60 value 92.261423
iter  70 value 92.169631
iter  80 value 90.563424
iter  90 value 89.235800
iter 100 value 88.552046
final  value 88.552046 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.453235 
iter  10 value 94.536032
iter  20 value 93.741214
iter  30 value 87.433783
iter  40 value 85.182810
iter  50 value 84.601065
iter  60 value 84.451202
iter  70 value 84.325465
iter  80 value 83.512071
iter  90 value 82.846998
iter 100 value 82.658584
final  value 82.658584 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.044577 
final  value 94.469049 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.796753 
final  value 94.485789 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.866582 
iter  10 value 94.485741
iter  20 value 94.484271
iter  30 value 94.410242
iter  40 value 93.773400
final  value 93.773391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.093618 
final  value 94.468621 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.705073 
final  value 94.485833 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.449434 
iter  10 value 94.487764
iter  20 value 94.474553
iter  30 value 94.105455
final  value 94.105351 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.080381 
iter  10 value 94.487094
iter  20 value 92.401932
iter  30 value 89.467747
iter  40 value 88.826759
iter  50 value 88.735837
iter  60 value 88.470201
iter  70 value 88.464687
iter  80 value 88.355945
iter  90 value 88.195389
final  value 88.195203 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.463763 
iter  10 value 94.489021
iter  20 value 94.412983
iter  30 value 89.968774
iter  40 value 84.986865
iter  50 value 84.970061
final  value 84.967988 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.717413 
iter  10 value 94.488695
iter  20 value 94.444871
iter  30 value 87.049215
iter  40 value 86.931068
iter  50 value 86.612142
iter  60 value 86.507132
iter  70 value 86.372679
final  value 86.370864 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.322344 
iter  10 value 94.489260
iter  20 value 94.481924
iter  30 value 88.439729
iter  40 value 86.221683
iter  50 value 86.185597
iter  60 value 86.154435
iter  70 value 85.912452
iter  80 value 85.887882
final  value 85.887826 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.654432 
iter  10 value 94.490568
iter  20 value 94.347672
iter  30 value 92.715145
iter  40 value 90.441414
iter  50 value 86.219542
iter  60 value 86.195470
iter  70 value 86.188441
iter  80 value 86.186270
iter  90 value 86.163815
iter 100 value 85.419474
final  value 85.419474 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.573763 
iter  10 value 94.488912
iter  20 value 94.172677
iter  30 value 93.459234
iter  40 value 93.407239
iter  50 value 92.956781
iter  60 value 90.006269
iter  70 value 89.586930
iter  80 value 89.547021
final  value 89.546285 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.574640 
iter  10 value 94.160901
iter  20 value 92.421542
iter  30 value 85.853659
iter  40 value 84.917991
iter  50 value 81.981810
iter  60 value 81.720652
iter  70 value 81.719810
final  value 81.718941 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.288497 
iter  10 value 94.483995
iter  20 value 94.467964
iter  30 value 94.448466
iter  40 value 94.448275
final  value 94.448233 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.098405 
iter  10 value 94.492804
iter  20 value 94.198867
iter  30 value 86.546517
iter  40 value 86.334966
iter  50 value 84.547845
iter  60 value 84.154194
iter  70 value 84.151364
iter  80 value 84.145182
iter  80 value 84.145182
final  value 84.145182 
converged
Fitting Repeat 1 

# weights:  305
initial  value 130.890093 
iter  10 value 117.895204
iter  20 value 117.890544
iter  30 value 117.574090
iter  40 value 105.870816
iter  50 value 105.530126
final  value 105.529989 
converged
Fitting Repeat 2 

# weights:  305
initial  value 129.099745 
iter  10 value 117.763907
iter  20 value 117.616116
iter  30 value 114.535607
iter  40 value 111.492842
iter  50 value 111.474067
iter  60 value 111.298591
iter  70 value 111.291031
iter  80 value 111.289433
iter  90 value 111.288706
iter 100 value 111.282885
final  value 111.282885 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 138.642476 
iter  10 value 117.895067
iter  20 value 117.736993
iter  30 value 107.050886
iter  40 value 106.487387
iter  50 value 106.414671
iter  60 value 106.413531
iter  70 value 106.412385
iter  80 value 105.131342
iter  90 value 100.963500
iter 100 value 100.294022
final  value 100.294022 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 134.767372 
iter  10 value 117.894731
iter  20 value 111.447953
iter  30 value 104.639030
iter  40 value 103.231720
iter  50 value 102.870748
iter  60 value 102.009039
final  value 101.432752 
converged
Fitting Repeat 5 

# weights:  305
initial  value 129.293701 
iter  10 value 117.805977
iter  20 value 117.748070
iter  30 value 117.518048
final  value 117.512041 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Mon Apr 21 19:54:11 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 
 17.208   0.453  78.260