##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... 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
corr_plot     34.270  0.482  34.765
var_imp       33.371  0.444  33.819
FSmethod      32.604  0.590  33.195
pred_ensembel 12.811  0.128  11.549
enrichfindP    0.565  0.037  14.364
getFASTA       0.479  0.008   6.768
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

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

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


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.1’
** 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) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 97.759128 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.495818 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.455701 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.627305 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.357192 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.475093 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.242149 
iter  10 value 93.839506
iter  10 value 93.839506
iter  10 value 93.839506
final  value 93.839506 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.416839 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.531822 
final  value 94.012725 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.045045 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.235995 
iter  10 value 94.025289
iter  10 value 94.025289
iter  10 value 94.025289
final  value 94.025289 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.114947 
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.780849 
iter  10 value 91.756562
iter  20 value 90.804168
iter  30 value 90.800061
final  value 90.800001 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.721452 
iter  10 value 94.038251
iter  10 value 94.038251
iter  10 value 94.038251
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.272145 
iter  10 value 91.813483
iter  20 value 91.812660
final  value 91.809803 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.958539 
iter  10 value 93.432525
iter  20 value 86.222971
iter  30 value 83.726871
iter  40 value 83.519502
iter  50 value 83.387378
iter  60 value 83.025924
iter  70 value 82.991533
final  value 82.991529 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.711844 
iter  10 value 94.052500
iter  20 value 92.005107
iter  30 value 85.196137
iter  40 value 84.896151
iter  50 value 84.343806
iter  60 value 84.202767
iter  70 value 83.452854
iter  80 value 83.245367
iter  90 value 82.998877
final  value 82.991529 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.576675 
iter  10 value 93.725151
iter  20 value 87.596444
iter  30 value 86.223190
iter  40 value 85.953391
iter  50 value 83.287640
iter  60 value 81.033115
iter  70 value 80.872800
iter  80 value 80.196323
iter  90 value 80.017320
final  value 80.017049 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.820044 
iter  10 value 93.876903
iter  20 value 89.671102
iter  30 value 86.362721
iter  40 value 86.217183
iter  50 value 85.892123
iter  60 value 84.844685
iter  70 value 83.367103
iter  80 value 83.062833
iter  90 value 82.991747
final  value 82.991529 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.926259 
iter  10 value 94.107459
iter  20 value 91.607683
iter  30 value 84.352596
iter  40 value 83.739705
iter  50 value 83.566666
iter  60 value 83.255397
iter  70 value 83.119697
iter  80 value 83.000028
final  value 82.991529 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.924781 
iter  10 value 93.718573
iter  20 value 84.445409
iter  30 value 83.555215
iter  40 value 80.958245
iter  50 value 80.012446
iter  60 value 79.658286
iter  70 value 79.233232
iter  80 value 79.212387
iter  90 value 79.203802
iter 100 value 79.184192
final  value 79.184192 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.572142 
iter  10 value 94.100292
iter  20 value 87.587205
iter  30 value 84.078511
iter  40 value 83.316758
iter  50 value 82.938363
iter  60 value 82.728713
iter  70 value 82.618983
iter  80 value 82.583001
iter  90 value 81.156812
iter 100 value 80.571862
final  value 80.571862 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.573404 
iter  10 value 94.438286
iter  20 value 93.518295
iter  30 value 92.616887
iter  40 value 85.217841
iter  50 value 80.209553
iter  60 value 79.638770
iter  70 value 79.476645
iter  80 value 79.270964
iter  90 value 79.187097
iter 100 value 79.131057
final  value 79.131057 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.264546 
iter  10 value 94.073017
iter  20 value 87.367050
iter  30 value 86.568843
iter  40 value 85.270989
iter  50 value 84.442324
iter  60 value 83.258253
iter  70 value 82.738102
iter  80 value 81.209851
iter  90 value 80.844768
iter 100 value 80.465900
final  value 80.465900 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.926821 
iter  10 value 94.207944
iter  20 value 94.020227
iter  30 value 86.989856
iter  40 value 84.979203
iter  50 value 83.152262
iter  60 value 79.849151
iter  70 value 79.189613
iter  80 value 78.698629
iter  90 value 78.472334
iter 100 value 78.453336
final  value 78.453336 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.513874 
iter  10 value 93.396684
iter  20 value 87.269127
iter  30 value 83.569470
iter  40 value 81.219308
iter  50 value 80.058868
iter  60 value 79.380153
iter  70 value 79.127713
iter  80 value 78.828049
iter  90 value 78.650395
iter 100 value 78.565822
final  value 78.565822 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.456082 
iter  10 value 93.527758
iter  20 value 88.633993
iter  30 value 84.343721
iter  40 value 82.252743
iter  50 value 80.745664
iter  60 value 80.155357
iter  70 value 79.517098
iter  80 value 79.367799
iter  90 value 79.189512
iter 100 value 78.746316
final  value 78.746316 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.649266 
iter  10 value 94.075660
iter  20 value 88.973035
iter  30 value 86.636091
iter  40 value 83.565527
iter  50 value 82.976443
iter  60 value 82.101958
iter  70 value 80.439103
iter  80 value 80.391205
iter  90 value 80.354789
iter 100 value 79.861038
final  value 79.861038 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.656909 
iter  10 value 92.089020
iter  20 value 83.914744
iter  30 value 82.677796
iter  40 value 82.161365
iter  50 value 80.645623
iter  60 value 80.109080
iter  70 value 79.557831
iter  80 value 79.319604
iter  90 value 78.956244
iter 100 value 78.601067
final  value 78.601067 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 152.084890 
iter  10 value 95.746055
iter  20 value 88.644710
iter  30 value 87.583719
iter  40 value 86.002754
iter  50 value 83.380568
iter  60 value 82.139683
iter  70 value 81.846036
iter  80 value 81.236801
iter  90 value 80.452091
iter 100 value 79.316543
final  value 79.316543 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.549904 
final  value 94.054308 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.961163 
final  value 94.054610 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.047004 
final  value 94.054805 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.012449 
final  value 94.054618 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.789233 
final  value 94.040043 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.453287 
iter  10 value 94.058054
iter  20 value 94.052923
iter  30 value 93.487158
iter  40 value 84.529833
iter  50 value 83.487149
iter  60 value 82.722949
iter  70 value 82.718929
iter  80 value 80.807472
iter  90 value 80.613431
iter 100 value 80.489520
final  value 80.489520 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.044653 
iter  10 value 94.057404
iter  20 value 94.052928
iter  30 value 94.051518
iter  40 value 88.571364
iter  50 value 86.587724
iter  60 value 86.586385
iter  60 value 86.586384
iter  60 value 86.586384
final  value 86.586384 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.213315 
iter  10 value 94.057357
iter  20 value 93.919848
iter  30 value 92.117684
iter  40 value 84.561371
iter  50 value 83.925872
iter  60 value 83.891113
final  value 83.888229 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.833141 
iter  10 value 94.056219
iter  20 value 92.297957
iter  30 value 87.050539
iter  40 value 87.047393
iter  50 value 87.045126
iter  60 value 87.044691
iter  70 value 86.741122
final  value 86.741005 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.023002 
iter  10 value 94.057707
iter  20 value 93.021397
iter  30 value 86.308485
iter  40 value 85.978162
final  value 85.977999 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.485467 
iter  10 value 94.060893
iter  20 value 94.045822
iter  30 value 94.025652
final  value 94.025608 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.117994 
iter  10 value 94.059634
iter  20 value 93.952757
iter  30 value 89.876039
iter  40 value 83.270888
iter  50 value 82.555981
iter  60 value 81.893388
iter  70 value 80.964323
iter  80 value 80.920150
iter  90 value 80.815863
iter 100 value 80.814776
final  value 80.814776 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.453820 
iter  10 value 94.061346
iter  20 value 94.046134
iter  30 value 91.610631
iter  40 value 83.447857
iter  50 value 82.971403
iter  60 value 82.702096
iter  70 value 79.558835
iter  80 value 79.176339
iter  90 value 78.526556
iter 100 value 78.173991
final  value 78.173991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.736912 
iter  10 value 93.818459
iter  20 value 93.760716
iter  30 value 93.159384
final  value 92.820703 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.255820 
iter  10 value 94.046549
iter  20 value 93.553530
iter  30 value 85.041756
iter  40 value 82.733761
iter  50 value 82.430031
iter  60 value 79.484396
iter  70 value 78.299410
iter  80 value 78.067221
iter  90 value 78.004727
iter 100 value 77.977288
final  value 77.977288 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.357317 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.234812 
iter  10 value 94.354810
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.850273 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.222104 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.763271 
final  value 94.484212 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.464120 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.360762 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.111160 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.532936 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.761754 
final  value 94.484212 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.715352 
iter  10 value 94.240481
final  value 94.093952 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.068213 
iter  10 value 93.477765
iter  20 value 93.475616
final  value 93.475602 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.695104 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.640791 
iter  10 value 92.709433
iter  20 value 85.358075
iter  30 value 85.355260
final  value 85.355257 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.810966 
iter  10 value 89.710418
final  value 88.800000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.229479 
iter  10 value 94.409338
iter  20 value 93.877526
iter  30 value 90.711196
iter  40 value 89.299694
iter  50 value 88.576418
iter  60 value 87.238525
iter  70 value 86.219979
iter  80 value 85.367988
iter  90 value 85.326297
final  value 85.323952 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.119637 
iter  10 value 94.487095
iter  20 value 93.298201
iter  30 value 86.672603
iter  40 value 86.370527
iter  50 value 86.255248
iter  60 value 85.484939
iter  70 value 85.324808
final  value 85.323952 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.340580 
iter  10 value 94.494552
iter  20 value 94.446215
iter  30 value 87.908643
iter  40 value 87.499748
iter  50 value 87.173288
iter  60 value 84.543153
iter  70 value 84.534877
iter  70 value 84.534877
iter  70 value 84.534877
final  value 84.534877 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.536048 
iter  10 value 94.471431
iter  20 value 94.113924
iter  30 value 94.088345
iter  40 value 92.309040
iter  50 value 87.242656
iter  60 value 86.533673
iter  70 value 85.792524
iter  80 value 84.417832
iter  90 value 84.019436
iter 100 value 83.216736
final  value 83.216736 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.702803 
iter  10 value 95.586503
iter  20 value 94.488577
iter  30 value 94.204849
iter  40 value 86.910914
iter  50 value 84.841484
iter  60 value 84.609618
iter  70 value 84.543389
iter  80 value 84.360837
iter  90 value 82.884654
iter 100 value 82.597117
final  value 82.597117 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.263481 
iter  10 value 94.405069
iter  20 value 94.074159
iter  30 value 92.482292
iter  40 value 86.822552
iter  50 value 84.700078
iter  60 value 84.458774
iter  70 value 82.884825
iter  80 value 82.700557
iter  90 value 82.597343
iter 100 value 82.572367
final  value 82.572367 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.601370 
iter  10 value 94.462425
iter  20 value 94.151698
iter  30 value 94.005852
iter  40 value 87.015001
iter  50 value 85.786464
iter  60 value 85.059244
iter  70 value 83.620594
iter  80 value 82.184418
iter  90 value 81.865575
iter 100 value 81.738831
final  value 81.738831 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 132.581013 
iter  10 value 94.546506
iter  20 value 90.858232
iter  30 value 88.167421
iter  40 value 84.553618
iter  50 value 83.514912
iter  60 value 83.030741
iter  70 value 82.533661
iter  80 value 82.337480
iter  90 value 82.156156
iter 100 value 82.051176
final  value 82.051176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.165348 
iter  10 value 94.285042
iter  20 value 88.263105
iter  30 value 85.455987
iter  40 value 84.504077
iter  50 value 84.070676
iter  60 value 83.014541
iter  70 value 82.372267
iter  80 value 82.041057
iter  90 value 81.912382
iter 100 value 81.713078
final  value 81.713078 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.931374 
iter  10 value 94.130951
iter  20 value 89.511994
iter  30 value 88.674564
iter  40 value 87.845159
iter  50 value 85.265351
iter  60 value 82.514214
iter  70 value 82.241358
iter  80 value 82.088409
iter  90 value 82.017095
iter 100 value 81.715971
final  value 81.715971 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.624562 
iter  10 value 93.825108
iter  20 value 86.931122
iter  30 value 86.387565
iter  40 value 85.957604
iter  50 value 84.929845
iter  60 value 84.172165
iter  70 value 83.394730
iter  80 value 82.636989
iter  90 value 81.370222
iter 100 value 81.050899
final  value 81.050899 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.787132 
iter  10 value 97.098426
iter  20 value 91.941875
iter  30 value 87.517711
iter  40 value 85.856119
iter  50 value 82.522564
iter  60 value 82.355068
iter  70 value 82.079859
iter  80 value 82.015358
iter  90 value 81.941822
iter 100 value 81.912208
final  value 81.912208 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.232243 
iter  10 value 93.477364
iter  20 value 85.543974
iter  30 value 85.187719
iter  40 value 84.996619
iter  50 value 83.857980
iter  60 value 83.209800
iter  70 value 81.812837
iter  80 value 81.482852
iter  90 value 81.123878
iter 100 value 81.006457
final  value 81.006457 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.938869 
iter  10 value 96.220788
iter  20 value 92.752756
iter  30 value 86.884987
iter  40 value 85.315885
iter  50 value 83.986866
iter  60 value 83.309357
iter  70 value 82.407880
iter  80 value 81.781949
iter  90 value 81.505959
iter 100 value 81.456751
final  value 81.456751 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.664242 
iter  10 value 94.212189
iter  20 value 87.191210
iter  30 value 86.629037
iter  40 value 86.412378
iter  50 value 85.219492
iter  60 value 83.334728
iter  70 value 82.700866
iter  80 value 82.637050
iter  90 value 82.346641
iter 100 value 81.495634
final  value 81.495634 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.908531 
final  value 94.485904 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.715913 
final  value 94.486091 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.931030 
final  value 94.355973 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.153976 
final  value 94.485836 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.955431 
final  value 94.485760 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.833063 
iter  10 value 94.362874
iter  20 value 94.358202
iter  30 value 94.355110
final  value 94.354670 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.870742 
iter  10 value 94.359687
iter  20 value 94.125124
iter  30 value 92.632033
final  value 92.631449 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.165495 
iter  10 value 94.359881
iter  20 value 94.078748
iter  30 value 92.616089
final  value 92.616086 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.313523 
iter  10 value 94.109270
iter  20 value 94.106234
iter  30 value 94.105627
iter  40 value 94.104821
iter  50 value 94.104178
iter  60 value 91.704076
iter  70 value 88.523188
iter  80 value 87.681060
iter  90 value 85.356305
iter 100 value 83.531802
final  value 83.531802 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.145464 
iter  10 value 94.483406
iter  20 value 90.106611
iter  30 value 85.838459
iter  40 value 83.940248
final  value 83.939063 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.634760 
iter  10 value 94.491654
iter  20 value 94.114488
iter  30 value 94.109113
iter  40 value 94.107654
iter  50 value 94.106920
iter  60 value 94.095381
iter  70 value 90.291329
iter  80 value 87.813425
iter  90 value 86.304006
iter 100 value 83.836253
final  value 83.836253 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.201811 
iter  10 value 93.661560
iter  20 value 92.568223
iter  30 value 92.547384
iter  40 value 92.545809
iter  50 value 92.541665
iter  60 value 92.522523
iter  70 value 92.287412
iter  80 value 85.809028
iter  90 value 85.264293
iter 100 value 85.251362
final  value 85.251362 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.450991 
iter  10 value 94.492374
iter  20 value 94.403879
iter  30 value 93.387088
iter  40 value 86.306631
iter  50 value 85.521860
iter  60 value 85.492004
iter  70 value 83.651386
iter  80 value 83.455389
iter  90 value 83.451564
iter 100 value 83.451389
final  value 83.451389 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.999050 
iter  10 value 94.492798
iter  20 value 93.981843
iter  30 value 86.168325
iter  40 value 86.162846
iter  50 value 86.159846
iter  60 value 86.130854
iter  70 value 86.127545
iter  80 value 86.126934
iter  90 value 86.108671
iter 100 value 83.912623
final  value 83.912623 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.184265 
iter  10 value 94.543544
iter  20 value 93.484997
iter  30 value 93.480034
iter  40 value 90.526123
iter  50 value 84.805720
iter  60 value 84.368490
iter  70 value 84.365486
iter  80 value 84.107581
iter  90 value 82.640739
iter 100 value 81.556152
final  value 81.556152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.053592 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.250781 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.718985 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.191267 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.040049 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.134868 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.854385 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.010386 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.594569 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.794630 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.928288 
final  value 94.428839 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.147938 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.535073 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.711260 
iter  10 value 94.020205
final  value 93.976192 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.639531 
iter  10 value 93.493279
final  value 93.481595 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.664929 
iter  10 value 94.469384
iter  20 value 91.860125
iter  30 value 87.171983
iter  40 value 86.624579
iter  50 value 86.285591
iter  60 value 85.109003
iter  70 value 85.033465
final  value 85.031477 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.590114 
iter  10 value 94.499909
iter  20 value 93.156245
iter  30 value 88.278623
iter  40 value 86.657198
iter  50 value 85.880172
iter  60 value 83.507138
iter  70 value 83.364850
iter  80 value 83.048055
iter  90 value 82.596599
iter 100 value 82.535274
final  value 82.535274 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.324879 
iter  10 value 94.486540
iter  20 value 94.239584
iter  30 value 94.024710
iter  40 value 90.092400
iter  50 value 87.742231
iter  60 value 84.981271
iter  70 value 84.748855
final  value 84.747368 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.810874 
iter  10 value 94.506651
iter  20 value 94.444294
iter  30 value 92.389959
iter  40 value 92.154113
iter  50 value 92.142076
final  value 92.142004 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.582062 
iter  10 value 94.349400
iter  20 value 91.166642
iter  30 value 88.344662
iter  40 value 86.995515
iter  50 value 84.176605
iter  60 value 83.313240
iter  70 value 82.906138
iter  80 value 82.599659
iter  90 value 82.533366
iter 100 value 82.500469
final  value 82.500469 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.015803 
iter  10 value 95.301837
iter  20 value 87.821258
iter  30 value 85.605752
iter  40 value 84.224904
iter  50 value 83.486161
iter  60 value 82.728172
iter  70 value 81.882757
iter  80 value 81.500018
iter  90 value 81.213177
iter 100 value 81.134532
final  value 81.134532 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.962772 
iter  10 value 94.365374
iter  20 value 91.245762
iter  30 value 86.422408
iter  40 value 84.995274
iter  50 value 84.304798
iter  60 value 83.973180
iter  70 value 83.559024
iter  80 value 83.081828
iter  90 value 82.646832
iter 100 value 82.459420
final  value 82.459420 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.587207 
iter  10 value 94.382764
iter  20 value 90.371215
iter  30 value 84.386386
iter  40 value 83.028892
iter  50 value 82.739710
iter  60 value 82.527451
iter  70 value 82.339994
iter  80 value 82.178631
iter  90 value 81.970699
iter 100 value 81.874820
final  value 81.874820 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.428291 
iter  10 value 95.113786
iter  20 value 88.784293
iter  30 value 86.999890
iter  40 value 86.610502
iter  50 value 86.146824
iter  60 value 85.493086
iter  70 value 85.077485
iter  80 value 84.189023
iter  90 value 82.487436
iter 100 value 81.205137
final  value 81.205137 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.814684 
iter  10 value 94.799479
iter  20 value 93.491814
iter  30 value 90.729745
iter  40 value 89.451365
iter  50 value 87.601231
iter  60 value 86.289304
iter  70 value 85.830002
iter  80 value 83.326323
iter  90 value 82.172241
iter 100 value 81.459719
final  value 81.459719 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.404751 
iter  10 value 93.431398
iter  20 value 87.626165
iter  30 value 85.351501
iter  40 value 84.659302
iter  50 value 82.924072
iter  60 value 82.107768
iter  70 value 81.675985
iter  80 value 81.369266
iter  90 value 81.228431
iter 100 value 81.165889
final  value 81.165889 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.375653 
iter  10 value 95.935646
iter  20 value 87.893128
iter  30 value 85.450425
iter  40 value 84.093436
iter  50 value 83.020830
iter  60 value 82.801702
iter  70 value 82.340145
iter  80 value 82.107206
iter  90 value 82.000575
iter 100 value 81.670334
final  value 81.670334 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.125232 
iter  10 value 94.431801
iter  20 value 90.897410
iter  30 value 89.067402
iter  40 value 88.884608
iter  50 value 86.085427
iter  60 value 85.001432
iter  70 value 83.832791
iter  80 value 82.991028
iter  90 value 81.840407
iter 100 value 81.575826
final  value 81.575826 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.599897 
iter  10 value 98.372884
iter  20 value 87.310224
iter  30 value 85.000532
iter  40 value 83.897760
iter  50 value 83.397868
iter  60 value 82.866605
iter  70 value 82.734213
iter  80 value 82.299234
iter  90 value 81.402338
iter 100 value 81.062173
final  value 81.062173 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.843824 
iter  10 value 93.048882
iter  20 value 86.147199
iter  30 value 85.040732
iter  40 value 84.354853
iter  50 value 84.247057
iter  60 value 84.211186
iter  70 value 84.059899
iter  80 value 83.371464
iter  90 value 82.512355
iter 100 value 81.376095
final  value 81.376095 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.082081 
final  value 94.486014 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.334902 
final  value 94.277044 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.856066 
final  value 94.276827 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.353626 
iter  10 value 94.485827
iter  20 value 94.481441
final  value 94.275498 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.177495 
final  value 94.485809 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.993841 
iter  10 value 94.280016
iter  20 value 93.997277
iter  30 value 93.994190
iter  40 value 93.991593
iter  50 value 93.978431
iter  60 value 93.977681
iter  70 value 93.432674
iter  80 value 85.126870
iter  90 value 82.931850
iter 100 value 82.072065
final  value 82.072065 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.834016 
iter  10 value 94.476922
iter  20 value 93.020259
iter  30 value 89.438930
iter  40 value 88.410548
iter  50 value 88.348089
iter  60 value 88.345577
iter  70 value 87.092838
iter  80 value 86.719595
iter  90 value 86.531979
iter 100 value 86.115306
final  value 86.115306 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.393176 
iter  10 value 91.520893
iter  20 value 91.370682
iter  30 value 91.298771
iter  40 value 91.288839
iter  50 value 91.287840
iter  60 value 91.285233
iter  70 value 87.562318
iter  80 value 85.009451
iter  90 value 85.002611
final  value 85.001724 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.718762 
iter  10 value 94.487585
iter  20 value 93.928383
iter  30 value 93.923026
final  value 93.922887 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.728543 
iter  10 value 94.280562
iter  20 value 94.219891
iter  30 value 86.047640
iter  40 value 85.781224
iter  40 value 85.781223
iter  40 value 85.781223
final  value 85.781223 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.165388 
iter  10 value 94.492339
iter  20 value 94.482445
iter  30 value 93.974645
final  value 93.843226 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.370729 
iter  10 value 94.283282
iter  20 value 94.275617
iter  30 value 94.006998
iter  40 value 93.694263
iter  50 value 85.176804
iter  60 value 84.895937
iter  70 value 84.833935
iter  80 value 84.790874
final  value 84.789970 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.425130 
iter  10 value 94.238082
iter  20 value 93.889059
iter  30 value 93.817400
iter  40 value 93.811225
iter  50 value 93.809363
iter  60 value 89.523862
iter  70 value 88.664060
iter  80 value 88.510847
iter  90 value 88.510327
iter 100 value 87.154785
final  value 87.154785 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.389153 
iter  10 value 93.551034
iter  20 value 93.532449
iter  30 value 93.530927
iter  40 value 93.528916
iter  50 value 92.782056
iter  60 value 92.563168
iter  70 value 92.560962
iter  80 value 92.087159
iter  90 value 83.100961
iter 100 value 82.508647
final  value 82.508647 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.633982 
iter  10 value 94.492791
iter  20 value 94.432864
iter  30 value 88.841153
iter  40 value 85.456915
iter  50 value 85.449325
iter  60 value 84.892447
iter  70 value 83.999077
final  value 83.920308 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.673887 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.489570 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.929492 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.331851 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.655730 
final  value 94.484137 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.754746 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.132073 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.014859 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.889625 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.771584 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.215143 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.584698 
iter  10 value 93.849743
iter  20 value 93.847833
final  value 93.847813 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.870645 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.464980 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.629616 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.606599 
iter  10 value 94.495908
iter  20 value 91.825782
iter  30 value 84.605641
iter  40 value 83.011829
iter  50 value 82.530136
iter  60 value 82.141610
iter  70 value 81.955982
iter  80 value 81.767486
final  value 81.765159 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.006435 
iter  10 value 94.559825
iter  20 value 94.488819
iter  30 value 94.422463
iter  40 value 93.376290
iter  50 value 91.831961
iter  60 value 91.763572
iter  70 value 91.595199
iter  80 value 91.473910
iter  90 value 91.410741
iter  90 value 91.410740
iter  90 value 91.410740
final  value 91.410740 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.028594 
iter  10 value 94.508640
iter  20 value 94.486924
iter  30 value 93.168787
iter  40 value 88.657221
iter  50 value 87.094912
iter  60 value 85.332614
iter  70 value 84.633442
iter  80 value 84.627461
final  value 84.627257 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.669485 
iter  10 value 94.484388
iter  20 value 93.294422
iter  30 value 90.875419
iter  40 value 90.771934
iter  50 value 85.589829
iter  60 value 85.087101
iter  70 value 84.731450
iter  80 value 84.629101
final  value 84.629065 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.111832 
iter  10 value 94.227289
iter  20 value 87.213854
iter  30 value 86.504972
iter  40 value 86.105245
iter  50 value 84.724770
iter  60 value 83.971128
iter  70 value 83.590227
iter  80 value 83.106898
iter  90 value 83.076358
iter  90 value 83.076357
iter  90 value 83.076357
final  value 83.076357 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.102881 
iter  10 value 94.476387
iter  20 value 87.127772
iter  30 value 85.213340
iter  40 value 83.835322
iter  50 value 83.500400
iter  60 value 83.266511
iter  70 value 82.311287
iter  80 value 81.591420
iter  90 value 81.582534
iter 100 value 81.444873
final  value 81.444873 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.025052 
iter  10 value 94.726916
iter  20 value 88.442578
iter  30 value 87.714855
iter  40 value 87.459327
iter  50 value 87.219557
iter  60 value 87.092028
iter  70 value 86.737324
iter  80 value 83.960441
iter  90 value 81.729726
iter 100 value 81.333926
final  value 81.333926 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.607294 
iter  10 value 94.055477
iter  20 value 87.481189
iter  30 value 84.504093
iter  40 value 83.861397
iter  50 value 80.946417
iter  60 value 79.962570
iter  70 value 79.790830
iter  80 value 79.701714
iter  90 value 79.626901
iter 100 value 79.538240
final  value 79.538240 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.167833 
iter  10 value 94.622669
iter  20 value 94.506346
iter  30 value 94.222526
iter  40 value 92.974750
iter  50 value 92.567460
iter  60 value 89.313540
iter  70 value 88.166115
iter  80 value 87.748372
iter  90 value 87.188890
iter 100 value 83.455722
final  value 83.455722 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.057119 
iter  10 value 94.524712
iter  20 value 94.391635
iter  30 value 94.286698
iter  40 value 88.638393
iter  50 value 86.481477
iter  60 value 82.914157
iter  70 value 80.791967
iter  80 value 80.385766
iter  90 value 80.313158
iter 100 value 80.082473
final  value 80.082473 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.165315 
iter  10 value 95.247361
iter  20 value 90.734030
iter  30 value 88.838775
iter  40 value 88.052202
iter  50 value 86.530368
iter  60 value 86.302143
iter  70 value 85.212779
iter  80 value 82.259222
iter  90 value 81.177931
iter 100 value 80.977052
final  value 80.977052 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.015238 
iter  10 value 94.176276
iter  20 value 93.847628
iter  30 value 86.699770
iter  40 value 83.368519
iter  50 value 81.979350
iter  60 value 81.126002
iter  70 value 80.200661
iter  80 value 79.844225
iter  90 value 79.511041
iter 100 value 79.192076
final  value 79.192076 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.539445 
iter  10 value 94.748940
iter  20 value 86.204580
iter  30 value 85.134442
iter  40 value 83.823980
iter  50 value 83.248284
iter  60 value 82.046783
iter  70 value 81.353486
iter  80 value 81.288675
iter  90 value 80.968192
iter 100 value 80.574177
final  value 80.574177 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.287656 
iter  10 value 93.837200
iter  20 value 86.068828
iter  30 value 84.358317
iter  40 value 81.838575
iter  50 value 81.337992
iter  60 value 80.880741
iter  70 value 80.315939
iter  80 value 80.064184
iter  90 value 79.813381
iter 100 value 79.561768
final  value 79.561768 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.203417 
iter  10 value 95.066433
iter  20 value 86.691640
iter  30 value 85.792346
iter  40 value 84.694578
iter  50 value 84.543916
iter  60 value 84.334742
iter  70 value 83.747453
iter  80 value 82.543378
iter  90 value 81.804921
iter 100 value 81.261298
final  value 81.261298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.817051 
final  value 94.484946 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.273470 
final  value 94.485848 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.915255 
final  value 94.485641 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.538181 
final  value 94.485830 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.709265 
final  value 94.485733 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.918386 
iter  10 value 94.359428
iter  20 value 94.355488
iter  30 value 94.355204
iter  40 value 94.354790
final  value 94.354787 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.747870 
iter  10 value 94.211465
iter  20 value 87.656448
iter  30 value 85.707070
iter  40 value 85.706783
iter  50 value 85.148559
iter  60 value 83.614429
iter  70 value 82.767145
iter  80 value 82.761833
iter  90 value 82.761528
iter 100 value 82.752100
final  value 82.752100 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.868524 
iter  10 value 94.358473
iter  20 value 94.354171
final  value 94.354054 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.463373 
iter  10 value 93.245237
iter  20 value 93.213216
iter  30 value 93.209206
iter  40 value 92.820714
iter  50 value 92.242756
iter  60 value 92.129064
iter  70 value 92.128918
final  value 92.128908 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.440923 
iter  10 value 94.489484
iter  20 value 94.484298
iter  30 value 93.480353
iter  40 value 84.888844
iter  50 value 84.844341
iter  60 value 84.538735
iter  70 value 84.382097
iter  80 value 81.831974
iter  90 value 81.054574
iter 100 value 80.965101
final  value 80.965101 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.009132 
iter  10 value 94.495263
iter  20 value 94.214653
iter  30 value 94.212000
iter  40 value 94.207335
iter  50 value 94.006335
iter  60 value 91.937013
final  value 91.916359 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.313508 
iter  10 value 94.362471
iter  20 value 94.355177
iter  30 value 94.354420
iter  40 value 93.411648
iter  50 value 86.782447
iter  60 value 86.346363
iter  70 value 85.842694
iter  80 value 84.212469
iter  90 value 83.973883
iter 100 value 83.971365
final  value 83.971365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.225696 
iter  10 value 94.492532
iter  20 value 94.427954
iter  30 value 91.099393
iter  40 value 90.661240
final  value 90.660081 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.382658 
iter  10 value 94.492856
iter  20 value 94.333868
iter  30 value 89.935248
iter  40 value 88.959441
iter  50 value 87.249501
iter  60 value 87.136387
iter  70 value 87.118665
iter  80 value 85.430266
iter  90 value 84.910506
iter 100 value 84.899985
final  value 84.899985 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.880298 
iter  10 value 94.362213
iter  20 value 94.300825
iter  30 value 88.412041
iter  40 value 88.398336
iter  50 value 85.714156
final  value 85.521296 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.858854 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.794188 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.597572 
final  value 93.672973 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.620318 
final  value 93.672973 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.248214 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.726644 
final  value 93.867392 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.897432 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 93.051933 
iter  10 value 90.240169
iter  20 value 90.050736
iter  30 value 84.527284
iter  40 value 83.475995
iter  50 value 83.475805
final  value 83.475785 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.373270 
iter  10 value 93.904546
iter  20 value 93.903449
iter  20 value 93.903449
iter  20 value 93.903449
final  value 93.903449 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.818538 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.151623 
iter  10 value 92.831594
iter  20 value 92.075658
iter  30 value 91.194491
iter  40 value 90.752993
iter  50 value 90.750377
iter  60 value 90.750329
final  value 90.750321 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.195778 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.551403 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.045737 
final  value 94.025289 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.891156 
final  value 93.994013 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.814136 
iter  10 value 94.054915
iter  20 value 93.703487
iter  30 value 93.579866
iter  40 value 93.570324
iter  50 value 93.568798
iter  50 value 93.568797
iter  50 value 93.568797
final  value 93.568797 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.054144 
iter  10 value 93.966658
iter  20 value 88.919599
iter  30 value 86.798702
iter  40 value 85.750756
iter  50 value 85.010148
iter  60 value 84.280046
iter  70 value 82.915062
iter  80 value 82.737722
iter  90 value 82.734745
final  value 82.734734 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.653771 
iter  10 value 94.057034
iter  20 value 93.922182
iter  30 value 93.678661
iter  40 value 93.661178
iter  50 value 89.132141
iter  60 value 86.490570
iter  70 value 86.037423
iter  80 value 82.837744
iter  90 value 82.226500
iter 100 value 82.133956
final  value 82.133956 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.774344 
iter  10 value 93.990362
iter  20 value 92.093698
iter  30 value 87.120189
iter  40 value 83.200300
iter  50 value 82.284176
iter  60 value 81.707220
iter  70 value 80.867471
final  value 80.817105 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.522424 
iter  10 value 93.251079
iter  20 value 90.707050
iter  30 value 88.734408
iter  40 value 84.330358
iter  50 value 82.591112
iter  60 value 81.884245
iter  70 value 81.568026
iter  80 value 81.098888
iter  90 value 80.819241
final  value 80.817105 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.174401 
iter  10 value 94.009048
iter  20 value 93.650494
iter  30 value 93.437646
iter  40 value 92.290358
iter  50 value 90.492458
iter  60 value 85.719158
iter  70 value 83.401749
iter  80 value 81.997427
iter  90 value 81.920695
iter 100 value 81.463670
final  value 81.463670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.026420 
iter  10 value 94.092260
iter  20 value 93.023169
iter  30 value 84.813109
iter  40 value 84.275228
iter  50 value 81.184458
iter  60 value 80.257072
iter  70 value 80.022628
iter  80 value 79.626046
iter  90 value 79.455311
iter 100 value 79.332392
final  value 79.332392 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.194716 
iter  10 value 92.291807
iter  20 value 88.469463
iter  30 value 87.213112
iter  40 value 83.758082
iter  50 value 83.033149
iter  60 value 82.406071
iter  70 value 81.584475
iter  80 value 80.850218
iter  90 value 80.015229
iter 100 value 79.302129
final  value 79.302129 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.158618 
iter  10 value 94.096957
iter  20 value 88.461990
iter  30 value 86.494715
iter  40 value 84.916458
iter  50 value 82.842612
iter  60 value 80.457449
iter  70 value 80.102242
iter  80 value 80.066551
iter  90 value 79.981278
iter 100 value 79.933758
final  value 79.933758 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.885322 
iter  10 value 93.872220
iter  20 value 89.548026
iter  30 value 87.289948
iter  40 value 85.066167
iter  50 value 84.767839
iter  60 value 81.580353
iter  70 value 80.097596
iter  80 value 79.847614
iter  90 value 79.575386
iter 100 value 79.315747
final  value 79.315747 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.804421 
iter  10 value 93.941403
iter  20 value 90.709722
iter  30 value 85.243279
iter  40 value 81.963632
iter  50 value 80.592902
iter  60 value 80.281069
iter  70 value 79.974637
iter  80 value 79.770160
iter  90 value 79.399612
iter 100 value 79.174050
final  value 79.174050 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.819434 
iter  10 value 86.793811
iter  20 value 83.438387
iter  30 value 82.506452
iter  40 value 81.191744
iter  50 value 80.691864
iter  60 value 79.955838
iter  70 value 79.614574
iter  80 value 79.430221
iter  90 value 79.209234
iter 100 value 78.999409
final  value 78.999409 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.203951 
iter  10 value 93.998487
iter  20 value 93.152495
iter  30 value 87.450819
iter  40 value 86.451613
iter  50 value 83.972329
iter  60 value 83.174308
iter  70 value 82.551203
iter  80 value 81.200753
iter  90 value 80.213358
iter 100 value 79.507629
final  value 79.507629 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.511718 
iter  10 value 93.915024
iter  20 value 89.892370
iter  30 value 87.548455
iter  40 value 85.990584
iter  50 value 82.324575
iter  60 value 81.831419
iter  70 value 80.871417
iter  80 value 79.832869
iter  90 value 79.253680
iter 100 value 79.057477
final  value 79.057477 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.401458 
iter  10 value 94.887638
iter  20 value 86.853363
iter  30 value 83.880670
iter  40 value 83.135782
iter  50 value 80.641995
iter  60 value 79.548284
iter  70 value 79.299951
iter  80 value 79.256795
iter  90 value 79.193834
iter 100 value 79.176003
final  value 79.176003 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.313200 
final  value 94.054658 
converged
Fitting Repeat 2 

# weights:  103
initial  value 124.129310 
final  value 94.054461 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.659498 
final  value 94.054513 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.210745 
final  value 94.054246 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.505301 
iter  10 value 93.726720
iter  20 value 93.722031
iter  30 value 92.909853
iter  40 value 91.946723
iter  50 value 89.412075
iter  60 value 82.769144
final  value 82.769121 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.809913 
iter  10 value 93.929990
iter  20 value 93.664248
iter  30 value 93.477041
iter  40 value 91.156861
iter  50 value 84.248678
final  value 84.246273 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.475588 
iter  10 value 94.057944
iter  20 value 94.052943
iter  30 value 93.673363
final  value 93.673245 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.858304 
iter  10 value 94.057944
iter  20 value 93.854297
iter  30 value 89.722764
iter  40 value 88.692974
iter  50 value 88.347132
final  value 88.346208 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.436715 
iter  10 value 94.057850
iter  20 value 94.053840
iter  30 value 93.980307
iter  40 value 92.311866
iter  50 value 92.218741
iter  60 value 92.218323
iter  70 value 92.218132
iter  80 value 91.137588
iter  90 value 85.607954
iter 100 value 85.607081
final  value 85.607081 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.382477 
iter  10 value 94.057136
iter  20 value 93.957764
iter  30 value 93.513204
iter  40 value 87.617511
iter  50 value 87.616066
iter  60 value 87.615018
iter  70 value 86.346996
final  value 86.336210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.818111 
iter  10 value 93.448546
iter  20 value 93.447810
final  value 93.447492 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.664264 
iter  10 value 86.131716
iter  20 value 84.689448
iter  30 value 84.431655
iter  40 value 84.327306
iter  50 value 84.326773
iter  60 value 84.325921
iter  70 value 84.321909
final  value 84.319645 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.930195 
iter  10 value 94.033460
iter  20 value 93.891212
iter  30 value 93.800835
iter  40 value 91.572119
iter  50 value 84.838606
iter  60 value 83.151557
iter  70 value 80.733853
iter  80 value 78.924665
iter  90 value 78.788478
iter 100 value 78.714234
final  value 78.714234 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.805160 
iter  10 value 93.681037
iter  20 value 93.676116
iter  30 value 84.458431
iter  40 value 82.483136
iter  50 value 82.482177
final  value 82.482005 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.127817 
iter  10 value 93.659114
iter  20 value 92.623738
iter  30 value 86.434102
iter  40 value 86.407739
iter  50 value 84.502895
iter  60 value 84.495783
iter  70 value 84.343525
iter  80 value 84.090138
iter  90 value 84.087231
iter 100 value 83.998597
final  value 83.998597 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.555092 
iter  10 value 117.763791
iter  20 value 117.759332
iter  20 value 117.759331
final  value 117.759138 
converged
Fitting Repeat 2 

# weights:  305
initial  value 135.356479 
iter  10 value 117.896040
iter  20 value 117.888512
iter  30 value 113.118615
iter  40 value 112.059884
iter  50 value 112.008424
iter  60 value 109.865341
iter  70 value 109.083806
iter  80 value 109.079251
iter  90 value 109.070301
iter 100 value 108.963538
final  value 108.963538 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.599752 
iter  10 value 117.210779
iter  20 value 114.075320
iter  30 value 113.637055
iter  40 value 113.353537
iter  50 value 113.352571
final  value 113.352103 
converged
Fitting Repeat 4 

# weights:  305
initial  value 128.705997 
iter  10 value 117.529066
iter  20 value 116.945052
iter  30 value 116.943657
iter  40 value 116.940361
final  value 116.940102 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.754008 
iter  10 value 117.895006
iter  20 value 117.693307
iter  30 value 110.805041
iter  40 value 110.338566
iter  50 value 108.759356
iter  60 value 108.723190
iter  70 value 108.721801
iter  80 value 108.720361
iter  90 value 106.462194
iter 100 value 105.936322
final  value 105.936322 
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 -- Mon Dec  1 00:40:48 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 
 40.486   1.194  83.803