##############################################################################
##############################################################################
###
### 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_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-03-02 r87868)
* 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 ‘1.13.0’
* 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
FSmethod      18.057  0.793  19.167
var_imp       17.901  0.647  18.560
corr_plot     17.758  0.736  18.717
pred_ensembel  5.425  0.094   4.921
enrichfindP    0.163  0.025   8.509
* 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 ‘1.13.0’
** 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 Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 99.410493 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.216222 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.570489 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.054764 
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.555676 
iter  10 value 93.394935
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.930786 
iter  10 value 93.220099
iter  20 value 93.219812
final  value 93.219807 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.295432 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.440003 
iter  10 value 93.394942
final  value 93.394928 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.491995 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.669275 
iter  10 value 90.626259
iter  20 value 88.221978
iter  30 value 88.213084
final  value 88.209464 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.290469 
iter  10 value 94.448025
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.547837 
iter  10 value 94.448069
final  value 94.448053 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.497711 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 133.165050 
iter  10 value 93.407084
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.039200 
final  value 93.911765 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.654891 
iter  10 value 94.299107
iter  20 value 88.222942
iter  30 value 83.971411
iter  40 value 82.849593
iter  50 value 82.361258
iter  60 value 81.844104
iter  70 value 81.801183
final  value 81.789110 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.598991 
iter  10 value 94.487316
iter  20 value 94.236613
iter  30 value 93.677068
iter  40 value 93.615257
iter  50 value 88.061580
iter  60 value 84.037164
iter  70 value 83.033833
iter  80 value 82.138794
iter  90 value 82.046297
iter 100 value 82.015846
final  value 82.015846 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.265560 
iter  10 value 92.233678
iter  20 value 91.289292
iter  30 value 88.709093
iter  40 value 87.169509
iter  50 value 84.187331
iter  60 value 82.748834
iter  70 value 82.218049
iter  80 value 82.052429
iter  90 value 82.015854
final  value 82.015843 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.140406 
iter  10 value 93.744756
iter  20 value 91.265039
iter  30 value 86.435778
iter  40 value 86.171693
iter  50 value 85.803526
iter  60 value 85.337871
iter  70 value 85.279164
iter  80 value 84.863742
iter  90 value 84.532475
final  value 84.527595 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.530412 
iter  10 value 94.488317
iter  20 value 93.747973
iter  30 value 93.563948
iter  40 value 92.749005
iter  50 value 86.696143
iter  60 value 84.867832
iter  70 value 83.931297
iter  80 value 83.691176
iter  90 value 83.546974
iter 100 value 82.609303
final  value 82.609303 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.140212 
iter  10 value 94.477917
iter  20 value 93.577665
iter  30 value 91.467872
iter  40 value 87.505269
iter  50 value 87.209280
iter  60 value 86.666894
iter  70 value 85.221825
iter  80 value 84.054812
iter  90 value 83.965520
iter 100 value 83.457803
final  value 83.457803 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.976931 
iter  10 value 94.104690
iter  20 value 92.877091
iter  30 value 88.788176
iter  40 value 85.912086
iter  50 value 83.995133
iter  60 value 81.107885
iter  70 value 80.350599
iter  80 value 80.151828
iter  90 value 80.114882
iter 100 value 80.068932
final  value 80.068932 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.526186 
iter  10 value 94.432651
iter  20 value 89.204973
iter  30 value 84.604722
iter  40 value 83.728454
iter  50 value 83.102529
iter  60 value 82.739226
iter  70 value 82.370169
iter  80 value 81.472493
iter  90 value 80.901558
iter 100 value 80.755297
final  value 80.755297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.936229 
iter  10 value 93.998684
iter  20 value 93.622095
iter  30 value 87.276956
iter  40 value 85.851429
iter  50 value 84.978542
iter  60 value 84.481760
iter  70 value 84.206175
iter  80 value 84.083932
iter  90 value 82.384213
iter 100 value 81.617625
final  value 81.617625 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.409111 
iter  10 value 94.564228
iter  20 value 94.197577
iter  30 value 86.116596
iter  40 value 85.477884
iter  50 value 84.964689
iter  60 value 82.985577
iter  70 value 81.680244
iter  80 value 81.209496
iter  90 value 80.935195
iter 100 value 80.871969
final  value 80.871969 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.417146 
iter  10 value 94.555321
iter  20 value 91.360114
iter  30 value 89.109141
iter  40 value 86.822777
iter  50 value 85.894304
iter  60 value 81.661228
iter  70 value 81.256809
iter  80 value 80.718835
iter  90 value 80.463113
iter 100 value 80.349328
final  value 80.349328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.589288 
iter  10 value 96.366412
iter  20 value 93.278705
iter  30 value 89.061811
iter  40 value 86.369629
iter  50 value 85.593934
iter  60 value 83.522273
iter  70 value 81.545864
iter  80 value 80.741946
iter  90 value 80.618560
iter 100 value 80.458043
final  value 80.458043 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.173339 
iter  10 value 94.302716
iter  20 value 87.875700
iter  30 value 87.508379
iter  40 value 86.622166
iter  50 value 84.818769
iter  60 value 82.963402
iter  70 value 81.628950
iter  80 value 81.370083
iter  90 value 81.135280
iter 100 value 81.091534
final  value 81.091534 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.313648 
iter  10 value 94.959836
iter  20 value 94.080313
iter  30 value 86.683943
iter  40 value 85.625286
iter  50 value 85.384515
iter  60 value 84.854268
iter  70 value 81.858549
iter  80 value 81.485655
iter  90 value 81.139240
iter 100 value 80.730364
final  value 80.730364 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.738322 
iter  10 value 92.631610
iter  20 value 83.632463
iter  30 value 82.330225
iter  40 value 82.132740
iter  50 value 82.118840
iter  60 value 81.958756
iter  70 value 81.635441
iter  80 value 81.055942
iter  90 value 80.865422
iter 100 value 80.702667
final  value 80.702667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.088024 
final  value 94.485874 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.228579 
final  value 94.485930 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.057725 
iter  10 value 94.484782
final  value 94.484543 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.370395 
iter  10 value 94.485958
iter  20 value 94.484269
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.161060 
final  value 94.485861 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.869118 
iter  10 value 94.408438
iter  20 value 94.406767
iter  30 value 93.933889
final  value 93.872020 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.556811 
iter  10 value 94.009056
iter  20 value 93.876768
iter  30 value 93.762347
iter  40 value 93.344137
iter  50 value 93.341886
iter  60 value 92.174675
iter  70 value 85.950482
iter  80 value 84.423738
iter  90 value 83.651210
iter 100 value 83.522074
final  value 83.522074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.995368 
iter  10 value 93.400124
iter  20 value 93.397649
iter  30 value 93.342415
iter  40 value 93.342104
iter  50 value 91.799060
iter  60 value 89.465312
iter  70 value 87.458356
iter  80 value 86.775120
iter  90 value 86.691645
final  value 86.691643 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.972864 
iter  10 value 93.400121
iter  20 value 93.396733
iter  30 value 93.395437
final  value 93.395431 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.425502 
iter  10 value 93.400428
iter  20 value 93.396963
iter  30 value 93.336349
final  value 93.336144 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.175787 
iter  10 value 94.492733
iter  20 value 94.484025
iter  30 value 93.174719
iter  40 value 86.344507
iter  50 value 85.929170
iter  60 value 85.764559
iter  70 value 85.756956
iter  80 value 85.581939
iter  90 value 84.691399
iter 100 value 84.619649
final  value 84.619649 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.965940 
iter  10 value 94.462325
iter  20 value 94.455555
iter  30 value 94.451973
iter  40 value 94.451546
iter  50 value 94.438931
iter  60 value 93.875546
iter  70 value 93.872187
iter  80 value 93.862334
final  value 93.851934 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.383077 
iter  10 value 88.940395
iter  20 value 87.730195
iter  30 value 87.654653
iter  40 value 87.653004
iter  50 value 86.961347
iter  60 value 86.777599
iter  70 value 86.777129
final  value 86.776826 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.319305 
iter  10 value 94.492065
iter  20 value 94.366390
iter  30 value 85.278828
iter  40 value 83.577512
iter  50 value 83.558427
iter  60 value 83.558188
final  value 83.558174 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.101362 
iter  10 value 93.920060
iter  20 value 93.912859
iter  30 value 93.726446
iter  40 value 93.341724
iter  50 value 93.276131
iter  50 value 93.276130
iter  50 value 93.276130
final  value 93.276130 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.619156 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.925851 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.242178 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.704605 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.850323 
iter  10 value 90.994725
iter  20 value 85.880607
iter  30 value 85.876041
final  value 85.875862 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.700566 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.045833 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.602508 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.860107 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.377014 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.050119 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.955558 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.799788 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.633670 
iter  10 value 94.431535
final  value 94.427726 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.536127 
iter  10 value 92.356488
iter  20 value 88.696654
final  value 88.529084 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.509140 
iter  10 value 94.502302
iter  20 value 91.232762
iter  30 value 85.845888
iter  40 value 85.241589
iter  50 value 84.878668
iter  60 value 84.092040
iter  70 value 83.632083
iter  80 value 83.598543
iter  90 value 83.598334
final  value 83.598283 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.161152 
iter  10 value 94.173720
iter  20 value 87.037423
iter  30 value 84.783721
iter  40 value 84.622622
iter  50 value 84.191932
iter  60 value 83.817106
final  value 83.813039 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.926207 
iter  10 value 94.499256
iter  20 value 93.720775
iter  30 value 86.739600
iter  40 value 84.431903
iter  50 value 84.109392
iter  60 value 83.467424
iter  70 value 83.384596
final  value 83.384541 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.798343 
iter  10 value 94.488309
iter  20 value 94.417711
iter  30 value 90.478059
iter  40 value 89.683896
iter  50 value 89.401089
iter  60 value 83.938057
iter  70 value 81.299102
iter  80 value 80.852282
iter  90 value 80.843062
final  value 80.842883 
converged
Fitting Repeat 5 

# weights:  103
initial  value 117.205200 
iter  10 value 94.266550
iter  20 value 86.221985
iter  30 value 85.492679
iter  40 value 84.609627
iter  50 value 84.095627
iter  60 value 83.983001
iter  70 value 83.943598
iter  80 value 83.829787
iter  90 value 83.813126
final  value 83.813039 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.796743 
iter  10 value 94.493047
iter  20 value 94.456592
iter  30 value 92.407352
iter  40 value 90.319045
iter  50 value 88.122864
iter  60 value 85.631912
iter  70 value 83.582732
iter  80 value 82.224057
iter  90 value 81.822350
iter 100 value 81.446975
final  value 81.446975 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.678562 
iter  10 value 94.466998
iter  20 value 88.970204
iter  30 value 85.749324
iter  40 value 84.662838
iter  50 value 83.655853
iter  60 value 81.717783
iter  70 value 81.131669
iter  80 value 80.757582
iter  90 value 80.269920
iter 100 value 80.096264
final  value 80.096264 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.379190 
iter  10 value 94.660258
iter  20 value 94.274815
iter  30 value 93.962343
iter  40 value 91.617266
iter  50 value 86.893886
iter  60 value 85.931357
iter  70 value 84.703921
iter  80 value 81.950264
iter  90 value 80.708027
iter 100 value 80.540229
final  value 80.540229 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.970064 
iter  10 value 95.628890
iter  20 value 95.339708
iter  30 value 94.691151
iter  40 value 91.503978
iter  50 value 90.472549
iter  60 value 88.325473
iter  70 value 84.998743
iter  80 value 82.441311
iter  90 value 80.892669
iter 100 value 79.576203
final  value 79.576203 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.720590 
iter  10 value 94.496408
iter  20 value 88.965315
iter  30 value 85.893018
iter  40 value 85.602337
iter  50 value 84.162835
iter  60 value 83.515121
iter  70 value 82.181694
iter  80 value 81.842553
iter  90 value 81.579501
iter 100 value 80.881447
final  value 80.881447 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.877890 
iter  10 value 94.739962
iter  20 value 94.065028
iter  30 value 92.989921
iter  40 value 85.491244
iter  50 value 81.447851
iter  60 value 80.692643
iter  70 value 80.199649
iter  80 value 79.568113
iter  90 value 79.481795
iter 100 value 79.437207
final  value 79.437207 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.574395 
iter  10 value 94.446822
iter  20 value 87.267201
iter  30 value 85.754124
iter  40 value 84.647373
iter  50 value 82.022035
iter  60 value 81.548017
iter  70 value 81.503512
iter  80 value 81.356949
iter  90 value 80.937400
iter 100 value 80.396618
final  value 80.396618 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.718859 
iter  10 value 94.470672
iter  20 value 90.738512
iter  30 value 87.199925
iter  40 value 84.005075
iter  50 value 82.852758
iter  60 value 82.381154
iter  70 value 82.190168
iter  80 value 81.690686
iter  90 value 81.051352
iter 100 value 80.451628
final  value 80.451628 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.560201 
iter  10 value 92.174507
iter  20 value 89.759981
iter  30 value 84.599048
iter  40 value 83.763932
iter  50 value 83.354720
iter  60 value 83.092138
iter  70 value 82.936710
iter  80 value 82.106171
iter  90 value 81.380270
iter 100 value 80.792982
final  value 80.792982 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.189575 
iter  10 value 94.515827
iter  20 value 94.464502
iter  30 value 94.156785
iter  40 value 85.953998
iter  50 value 85.310067
iter  60 value 84.586265
iter  70 value 83.306718
iter  80 value 80.399520
iter  90 value 80.038661
iter 100 value 79.688810
final  value 79.688810 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.709239 
final  value 94.485893 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.867150 
iter  10 value 94.485940
iter  20 value 94.460554
iter  30 value 90.831309
iter  40 value 85.883465
iter  50 value 85.878101
iter  60 value 85.757845
iter  60 value 85.757845
iter  60 value 85.757845
final  value 85.757845 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.192471 
final  value 94.485743 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.534763 
final  value 94.090678 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.128640 
final  value 94.485910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.541895 
iter  10 value 94.489518
iter  20 value 93.467461
iter  30 value 85.915809
iter  40 value 85.880545
iter  50 value 85.879600
iter  60 value 85.879308
iter  70 value 85.835931
iter  80 value 84.980242
iter  90 value 84.979431
iter 100 value 84.976919
final  value 84.976919 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.029297 
iter  10 value 94.094626
iter  20 value 94.092467
iter  30 value 94.089721
iter  40 value 93.519063
iter  50 value 84.417641
iter  60 value 83.018420
iter  70 value 82.448861
final  value 82.343638 
converged
Fitting Repeat 3 

# weights:  305
initial  value 117.939812 
iter  10 value 94.489251
iter  20 value 94.140791
iter  30 value 91.046655
iter  40 value 91.008450
iter  50 value 87.344525
iter  60 value 87.335192
iter  70 value 87.333970
iter  80 value 83.820415
iter  90 value 83.674606
iter 100 value 83.589211
final  value 83.589211 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.500857 
iter  10 value 94.122097
iter  20 value 94.115906
iter  30 value 94.001175
iter  40 value 93.999573
iter  50 value 93.996602
iter  60 value 93.952564
iter  70 value 90.872616
iter  80 value 87.620420
iter  90 value 87.193384
iter 100 value 87.190406
final  value 87.190406 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.713274 
iter  10 value 94.472410
iter  20 value 94.467377
final  value 94.467070 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.436623 
iter  10 value 94.195282
iter  20 value 94.189688
iter  30 value 94.188851
iter  40 value 94.188720
iter  50 value 88.394875
iter  60 value 83.241665
iter  70 value 81.339818
iter  80 value 80.360951
iter  90 value 79.871230
iter 100 value 79.630599
final  value 79.630599 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.615329 
iter  10 value 94.474589
iter  20 value 94.429669
iter  30 value 94.428244
final  value 94.428198 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.810681 
iter  10 value 94.489654
iter  20 value 91.494164
iter  30 value 87.632310
iter  40 value 83.022206
iter  50 value 81.856489
iter  60 value 81.853132
iter  60 value 81.853132
final  value 81.853132 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.388556 
iter  10 value 88.773433
iter  20 value 85.833443
iter  30 value 85.765102
iter  40 value 85.757976
iter  50 value 85.677329
iter  60 value 85.672000
iter  70 value 85.036980
iter  80 value 82.630977
iter  90 value 82.533578
iter 100 value 82.505770
final  value 82.505770 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.791669 
iter  10 value 94.328274
iter  20 value 94.207356
iter  30 value 88.715083
iter  40 value 85.242972
iter  50 value 83.754652
iter  60 value 83.462518
iter  70 value 83.395763
iter  80 value 83.387848
iter  90 value 83.386876
iter  90 value 83.386876
final  value 83.386876 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.861852 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.029854 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.958716 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.441108 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.800013 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.125671 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.090371 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.896436 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.237573 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.381461 
iter  10 value 93.798817
iter  10 value 93.798817
iter  10 value 93.798817
final  value 93.798817 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.563544 
iter  10 value 94.254943
iter  20 value 93.865929
iter  30 value 92.940466
iter  40 value 91.948776
iter  50 value 91.710123
final  value 91.708580 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.717383 
iter  10 value 94.336217
final  value 94.336207 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.620835 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.156630 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.097975 
final  value 94.461207 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.309252 
iter  10 value 93.964556
iter  20 value 83.083692
iter  30 value 82.376211
iter  40 value 81.902329
iter  50 value 81.531384
iter  60 value 81.354850
iter  70 value 81.047159
iter  80 value 80.586824
iter  90 value 80.582489
iter  90 value 80.582489
iter  90 value 80.582489
final  value 80.582489 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.492105 
iter  10 value 94.488620
iter  20 value 94.037834
iter  30 value 93.834709
iter  40 value 93.731583
iter  50 value 92.641605
iter  60 value 86.132337
iter  70 value 84.360269
iter  80 value 82.215947
iter  90 value 81.741136
iter 100 value 81.493418
final  value 81.493418 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.271810 
iter  10 value 94.420846
iter  20 value 91.280247
iter  30 value 85.680252
iter  40 value 85.437246
iter  50 value 84.585361
iter  60 value 84.323076
iter  70 value 84.312140
final  value 84.312115 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.067681 
iter  10 value 94.482833
iter  20 value 93.940260
iter  30 value 86.820146
iter  40 value 83.952885
iter  50 value 82.599996
iter  60 value 81.891778
iter  70 value 81.034683
iter  80 value 80.701812
iter  90 value 80.583629
final  value 80.582489 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.008129 
iter  10 value 94.477249
iter  20 value 93.848135
iter  30 value 90.056113
iter  40 value 86.594353
iter  50 value 86.409991
iter  60 value 86.042109
iter  70 value 86.027647
iter  80 value 84.064845
iter  90 value 83.867588
iter 100 value 83.847992
final  value 83.847992 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.988573 
iter  10 value 94.566184
iter  20 value 86.012248
iter  30 value 84.957529
iter  40 value 83.680296
iter  50 value 80.920148
iter  60 value 80.131724
iter  70 value 79.915923
iter  80 value 79.687067
iter  90 value 79.442296
iter 100 value 79.250533
final  value 79.250533 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.515972 
iter  10 value 93.586927
iter  20 value 92.799359
iter  30 value 91.588406
iter  40 value 91.131234
iter  50 value 87.034333
iter  60 value 85.554852
iter  70 value 84.848864
iter  80 value 83.718771
iter  90 value 80.506150
iter 100 value 80.159916
final  value 80.159916 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.010856 
iter  10 value 94.642445
iter  20 value 89.250711
iter  30 value 86.702457
iter  40 value 85.528212
iter  50 value 83.258869
iter  60 value 81.918635
iter  70 value 80.720866
iter  80 value 80.006833
iter  90 value 79.616669
iter 100 value 79.498840
final  value 79.498840 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.015906 
iter  10 value 94.416206
iter  20 value 94.251005
iter  30 value 90.842600
iter  40 value 85.649173
iter  50 value 84.068575
iter  60 value 83.513139
iter  70 value 82.982236
iter  80 value 82.182161
iter  90 value 81.164038
iter 100 value 80.040225
final  value 80.040225 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.502944 
iter  10 value 95.186408
iter  20 value 93.849097
iter  30 value 87.314892
iter  40 value 83.199075
iter  50 value 81.537678
iter  60 value 81.016148
iter  70 value 80.795109
iter  80 value 80.509823
iter  90 value 80.302748
iter 100 value 79.983645
final  value 79.983645 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.059664 
iter  10 value 94.536748
iter  20 value 91.817620
iter  30 value 86.321305
iter  40 value 83.815155
iter  50 value 82.218159
iter  60 value 81.825345
iter  70 value 80.997409
iter  80 value 79.688157
iter  90 value 79.170648
iter 100 value 78.953661
final  value 78.953661 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.929217 
iter  10 value 94.374970
iter  20 value 91.461435
iter  30 value 87.775407
iter  40 value 84.856450
iter  50 value 82.400115
iter  60 value 82.049874
iter  70 value 81.466890
iter  80 value 80.424937
iter  90 value 79.553076
iter 100 value 79.433075
final  value 79.433075 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.087894 
iter  10 value 92.486330
iter  20 value 85.361765
iter  30 value 81.072040
iter  40 value 80.291559
iter  50 value 79.756475
iter  60 value 79.182387
iter  70 value 78.938639
iter  80 value 78.788808
iter  90 value 78.746857
iter 100 value 78.675555
final  value 78.675555 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.832464 
iter  10 value 88.470903
iter  20 value 85.600858
iter  30 value 81.492778
iter  40 value 80.914525
iter  50 value 80.206100
iter  60 value 80.057951
iter  70 value 79.466261
iter  80 value 79.422155
iter  90 value 79.274522
iter 100 value 79.128923
final  value 79.128923 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.889274 
iter  10 value 94.487251
iter  20 value 93.660051
iter  30 value 86.159772
iter  40 value 85.272828
iter  50 value 81.554010
iter  60 value 80.084944
iter  70 value 79.677361
iter  80 value 79.604914
iter  90 value 79.517954
iter 100 value 79.444803
final  value 79.444803 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 112.020756 
final  value 94.490298 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.767391 
iter  10 value 94.486011
iter  20 value 94.484255
final  value 94.484214 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.135139 
iter  10 value 94.485719
iter  20 value 94.484259
iter  30 value 94.369213
final  value 94.354650 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.603041 
final  value 94.486116 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.377488 
final  value 94.485648 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.217111 
iter  10 value 94.341427
iter  20 value 94.332680
iter  30 value 90.043179
iter  40 value 86.405227
iter  50 value 85.253607
iter  60 value 85.252781
iter  70 value 85.252000
iter  80 value 84.973384
iter  90 value 84.632194
iter 100 value 84.449239
final  value 84.449239 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.995450 
iter  10 value 94.488609
iter  20 value 86.295779
iter  30 value 84.655918
iter  40 value 84.325714
iter  50 value 84.320920
final  value 84.320809 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.520426 
iter  10 value 94.466234
iter  20 value 94.359561
iter  30 value 94.356079
iter  40 value 92.665502
iter  50 value 84.736339
iter  60 value 84.707388
iter  70 value 84.705981
iter  80 value 83.641940
iter  90 value 82.839637
iter 100 value 82.328462
final  value 82.328462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.940915 
iter  10 value 94.488643
iter  20 value 94.252314
iter  30 value 84.728610
iter  40 value 84.508890
iter  50 value 84.414740
final  value 84.413667 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.288961 
iter  10 value 94.488999
iter  20 value 88.336913
iter  30 value 86.886625
iter  40 value 84.699913
iter  50 value 80.991846
iter  60 value 80.263961
iter  70 value 79.801648
final  value 79.741953 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.046197 
iter  10 value 88.091087
iter  20 value 84.875110
iter  30 value 84.653448
iter  40 value 83.318685
iter  50 value 82.976404
iter  60 value 82.972656
iter  70 value 82.970033
iter  80 value 81.325339
iter  90 value 81.250066
iter 100 value 81.248606
final  value 81.248606 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.904236 
iter  10 value 94.491270
iter  20 value 93.736726
iter  30 value 84.984847
iter  40 value 84.108534
iter  50 value 80.953250
iter  60 value 80.816913
iter  70 value 80.815532
iter  80 value 80.812896
iter  90 value 80.178801
iter 100 value 78.838807
final  value 78.838807 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.293555 
iter  10 value 94.492586
iter  20 value 94.484370
final  value 94.484353 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.982845 
iter  10 value 94.493421
iter  20 value 94.491620
iter  30 value 94.465803
iter  40 value 86.811787
iter  50 value 84.871546
iter  60 value 84.852809
final  value 84.851934 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.604526 
iter  10 value 94.492871
iter  20 value 94.480403
iter  30 value 92.067782
iter  40 value 86.149425
iter  50 value 84.410407
iter  60 value 84.341726
iter  70 value 84.339042
iter  80 value 84.338981
iter  90 value 84.338914
final  value 84.338824 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.567694 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.064236 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.411551 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.839971 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.636661 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.563418 
final  value 93.991525 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.073968 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.312796 
final  value 93.991525 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.438678 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.256780 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.667614 
final  value 93.810010 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.968924 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.261858 
final  value 93.810010 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.373687 
final  value 92.514439 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.845532 
iter  10 value 93.793862
final  value 93.789014 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.928924 
iter  10 value 94.049858
iter  20 value 91.497158
iter  30 value 90.277899
iter  40 value 85.838989
iter  50 value 85.703057
iter  60 value 85.414548
iter  70 value 83.178722
iter  80 value 83.138089
iter  90 value 83.121542
iter 100 value 83.116012
final  value 83.116012 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.663538 
iter  10 value 94.057572
iter  20 value 93.942827
iter  30 value 93.891465
iter  40 value 93.863597
iter  50 value 91.856920
iter  60 value 90.086600
iter  70 value 89.820988
iter  80 value 89.808023
final  value 89.808010 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.346877 
iter  10 value 94.069855
iter  20 value 92.602856
iter  30 value 83.605607
iter  40 value 83.524071
iter  50 value 83.502224
iter  60 value 83.480513
final  value 83.479284 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.712591 
iter  10 value 94.042827
iter  20 value 91.377202
iter  30 value 91.264041
iter  40 value 91.261820
final  value 91.261813 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.679677 
iter  10 value 93.960800
iter  20 value 86.565516
iter  30 value 86.217054
iter  40 value 86.133271
iter  50 value 83.604213
iter  60 value 83.523060
iter  70 value 83.518815
iter  80 value 83.496529
iter  90 value 83.479288
final  value 83.479284 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.273835 
iter  10 value 94.041846
iter  20 value 86.778039
iter  30 value 84.712798
iter  40 value 83.276901
iter  50 value 82.851023
iter  60 value 81.786619
iter  70 value 80.443365
iter  80 value 79.899541
iter  90 value 79.761817
iter 100 value 79.706154
final  value 79.706154 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.463318 
iter  10 value 92.282900
iter  20 value 86.034215
iter  30 value 83.281783
iter  40 value 82.902834
iter  50 value 82.562974
iter  60 value 81.536380
iter  70 value 79.782950
iter  80 value 79.140293
iter  90 value 78.980080
iter 100 value 78.941463
final  value 78.941463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.235719 
iter  10 value 93.402245
iter  20 value 85.981169
iter  30 value 83.569396
iter  40 value 82.681352
iter  50 value 82.262185
iter  60 value 81.549752
iter  70 value 80.714709
iter  80 value 80.342475
iter  90 value 80.093047
iter 100 value 80.033251
final  value 80.033251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.892833 
iter  10 value 95.031279
iter  20 value 94.352414
iter  30 value 86.276097
iter  40 value 83.189974
iter  50 value 83.151307
iter  60 value 83.113065
iter  70 value 82.326521
iter  80 value 81.353426
iter  90 value 80.474930
iter 100 value 80.025039
final  value 80.025039 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.239689 
iter  10 value 94.220826
iter  20 value 94.097011
iter  30 value 87.069007
iter  40 value 85.014965
iter  50 value 82.335855
iter  60 value 81.801391
iter  70 value 81.371594
iter  80 value 80.984959
iter  90 value 80.395655
iter 100 value 79.850852
final  value 79.850852 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.875404 
iter  10 value 94.119830
iter  20 value 88.499352
iter  30 value 85.100261
iter  40 value 83.851838
iter  50 value 82.699372
iter  60 value 81.861869
iter  70 value 81.430210
iter  80 value 81.227411
iter  90 value 80.535825
iter 100 value 80.226703
final  value 80.226703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.415044 
iter  10 value 94.078319
iter  20 value 91.862382
iter  30 value 86.168459
iter  40 value 84.127480
iter  50 value 81.207394
iter  60 value 80.457262
iter  70 value 80.305088
iter  80 value 80.071094
iter  90 value 79.774980
iter 100 value 79.576313
final  value 79.576313 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.653528 
iter  10 value 94.334664
iter  20 value 93.592537
iter  30 value 84.306403
iter  40 value 83.259836
iter  50 value 83.067106
iter  60 value 82.294205
iter  70 value 81.115586
iter  80 value 80.638287
iter  90 value 80.108195
iter 100 value 79.799133
final  value 79.799133 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.564067 
iter  10 value 93.842065
iter  20 value 83.689265
iter  30 value 83.000863
iter  40 value 81.562660
iter  50 value 81.217646
iter  60 value 80.467290
iter  70 value 80.420942
iter  80 value 80.329087
iter  90 value 80.140964
iter 100 value 79.717322
final  value 79.717322 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.249395 
iter  10 value 94.540722
iter  20 value 93.590891
iter  30 value 84.887546
iter  40 value 83.332603
iter  50 value 82.712264
iter  60 value 82.603857
iter  70 value 82.560580
iter  80 value 82.264574
iter  90 value 81.534196
iter 100 value 81.200783
final  value 81.200783 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.172114 
final  value 94.054592 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.772685 
final  value 94.054294 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.444345 
final  value 93.820481 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.119710 
iter  10 value 94.052955
final  value 94.052912 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.564803 
final  value 94.054574 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.677948 
iter  10 value 94.057542
iter  20 value 94.052924
iter  30 value 93.971993
iter  40 value 90.418035
iter  50 value 83.978500
iter  60 value 83.789016
iter  70 value 83.781435
iter  80 value 83.781064
iter  90 value 83.779005
iter 100 value 83.773935
final  value 83.773935 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.837746 
iter  10 value 94.060255
iter  20 value 93.695287
iter  30 value 90.173487
iter  40 value 84.173819
iter  50 value 84.154631
iter  60 value 84.102833
iter  70 value 84.101306
iter  80 value 82.888452
iter  90 value 82.658434
iter 100 value 82.054615
final  value 82.054615 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.501345 
iter  10 value 93.720060
iter  20 value 92.891561
iter  30 value 92.706998
iter  40 value 84.891566
iter  50 value 84.832050
iter  60 value 82.206050
iter  70 value 82.180450
final  value 82.180430 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.293842 
iter  10 value 94.057741
iter  20 value 94.053201
iter  30 value 94.031391
iter  40 value 93.511540
iter  50 value 93.008265
iter  60 value 92.993779
iter  70 value 92.726372
iter  80 value 92.719048
final  value 92.718995 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.111377 
iter  10 value 94.057868
iter  20 value 94.052941
iter  30 value 92.702182
final  value 92.702180 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.834055 
iter  10 value 93.448087
iter  20 value 86.208326
iter  30 value 85.827653
iter  40 value 85.576484
iter  50 value 84.580120
iter  60 value 84.537905
iter  70 value 84.536684
iter  80 value 84.287366
iter  90 value 83.603407
iter 100 value 83.553264
final  value 83.553264 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.193166 
iter  10 value 93.727489
iter  20 value 93.712942
iter  30 value 93.711773
iter  40 value 89.262431
iter  50 value 82.272067
iter  60 value 82.268860
iter  70 value 82.180820
iter  80 value 82.180531
iter  90 value 80.890262
iter 100 value 79.186953
final  value 79.186953 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.067358 
iter  10 value 94.059638
iter  20 value 94.020019
iter  30 value 89.260697
iter  40 value 83.774403
iter  50 value 81.315126
iter  60 value 79.273024
iter  70 value 78.850767
iter  80 value 78.614202
iter  90 value 78.360155
iter 100 value 78.350928
final  value 78.350928 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.196073 
iter  10 value 94.060684
iter  20 value 92.191496
iter  30 value 84.349605
iter  40 value 84.341000
final  value 84.340972 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.847066 
iter  10 value 94.060450
iter  20 value 93.268708
iter  30 value 86.600932
iter  40 value 84.319894
iter  50 value 84.303649
iter  60 value 82.970966
iter  70 value 80.807722
iter  80 value 80.639293
iter  90 value 80.055658
iter 100 value 79.625256
final  value 79.625256 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.411497 
final  value 93.867392 
converged
Fitting Repeat 2 

# weights:  103
initial  value 120.318286 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.365882 
iter  10 value 93.867217
final  value 93.855558 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.682063 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.050725 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.272414 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.052499 
iter  10 value 93.701587
iter  10 value 93.701587
iter  10 value 93.701587
final  value 93.701587 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.128359 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.598701 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.527524 
iter  10 value 88.789254
iter  10 value 88.789254
iter  10 value 88.789253
final  value 88.789253 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.498246 
iter  10 value 88.988822
iter  20 value 88.969362
final  value 88.969344 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.508860 
final  value 93.867392 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.260897 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.130034 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.048818 
iter  10 value 93.555230
iter  20 value 87.048151
iter  30 value 86.468934
iter  40 value 86.468576
final  value 86.468550 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.847499 
iter  10 value 93.626532
iter  20 value 86.649516
iter  30 value 85.249706
iter  40 value 84.443474
iter  50 value 83.958676
iter  60 value 83.890228
iter  70 value 83.878848
iter  80 value 83.865847
final  value 83.865841 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.566353 
iter  10 value 94.056560
iter  20 value 94.033642
iter  30 value 86.228026
iter  40 value 84.073062
iter  50 value 83.913778
iter  60 value 83.866998
final  value 83.865841 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.838438 
iter  10 value 93.951375
iter  20 value 92.336360
iter  30 value 92.109466
iter  40 value 86.928815
iter  50 value 84.661591
iter  60 value 84.357995
iter  70 value 84.128668
final  value 84.123995 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.448629 
iter  10 value 93.918849
iter  20 value 87.945394
iter  30 value 85.865937
iter  40 value 85.018298
iter  50 value 84.931965
final  value 84.928789 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.138827 
iter  10 value 94.073663
iter  20 value 93.866667
iter  30 value 93.310795
iter  40 value 92.845278
iter  50 value 87.588606
iter  60 value 86.307627
iter  70 value 85.653113
iter  80 value 84.844547
iter  90 value 84.122892
iter 100 value 83.961442
final  value 83.961442 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.818946 
iter  10 value 94.143083
iter  20 value 92.614391
iter  30 value 92.351241
iter  40 value 89.332814
iter  50 value 84.789587
iter  60 value 84.314651
iter  70 value 83.782066
iter  80 value 83.123969
iter  90 value 82.247337
iter 100 value 81.302877
final  value 81.302877 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.603231 
iter  10 value 94.067234
iter  20 value 87.949324
iter  30 value 85.328438
iter  40 value 84.269450
iter  50 value 84.181055
iter  60 value 84.036130
iter  70 value 83.969569
iter  80 value 83.136040
iter  90 value 81.455173
iter 100 value 80.955632
final  value 80.955632 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.366256 
iter  10 value 93.982863
iter  20 value 85.883930
iter  30 value 84.882943
iter  40 value 84.729773
iter  50 value 83.860724
iter  60 value 82.857209
iter  70 value 82.147301
iter  80 value 82.090308
iter  90 value 82.081804
iter 100 value 82.078579
final  value 82.078579 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.712060 
iter  10 value 93.942726
iter  20 value 87.101301
iter  30 value 85.107586
iter  40 value 84.816499
iter  50 value 84.737377
iter  60 value 84.644581
iter  70 value 84.155054
iter  80 value 82.689675
iter  90 value 81.353622
iter 100 value 81.047584
final  value 81.047584 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.833045 
iter  10 value 94.091341
iter  20 value 88.241904
iter  30 value 85.586050
iter  40 value 84.505817
iter  50 value 84.119651
iter  60 value 83.699143
iter  70 value 82.732877
iter  80 value 81.687473
iter  90 value 81.104277
iter 100 value 80.833681
final  value 80.833681 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.349714 
iter  10 value 94.289637
iter  20 value 90.421150
iter  30 value 85.705742
iter  40 value 82.821045
iter  50 value 82.031096
iter  60 value 81.858546
iter  70 value 81.506067
iter  80 value 81.252500
iter  90 value 81.190084
iter 100 value 80.783173
final  value 80.783173 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.713089 
iter  10 value 95.032303
iter  20 value 94.004637
iter  30 value 93.649805
iter  40 value 93.312965
iter  50 value 90.485357
iter  60 value 88.562620
iter  70 value 83.862886
iter  80 value 81.291577
iter  90 value 80.762370
iter 100 value 80.736634
final  value 80.736634 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.994392 
iter  10 value 91.769742
iter  20 value 85.472266
iter  30 value 84.842929
iter  40 value 83.870744
iter  50 value 81.334988
iter  60 value 80.990893
iter  70 value 80.707544
iter  80 value 80.608441
iter  90 value 80.555285
iter 100 value 80.525418
final  value 80.525418 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.206853 
iter  10 value 95.638739
iter  20 value 86.840431
iter  30 value 85.601540
iter  40 value 83.609451
iter  50 value 82.998923
iter  60 value 82.378725
iter  70 value 81.372107
iter  80 value 80.878212
iter  90 value 80.715238
iter 100 value 80.658479
final  value 80.658479 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.206225 
iter  10 value 94.690939
iter  20 value 93.957130
iter  30 value 87.549000
iter  40 value 86.707209
iter  50 value 85.969721
iter  60 value 83.536253
iter  70 value 82.076743
iter  80 value 81.247928
iter  90 value 80.842822
iter 100 value 80.651746
final  value 80.651746 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.949491 
iter  10 value 87.271952
iter  20 value 84.997441
iter  30 value 84.995754
iter  40 value 83.934621
iter  50 value 83.927163
iter  60 value 83.918755
iter  70 value 83.833968
final  value 83.833557 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.400540 
final  value 94.054602 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.648024 
final  value 94.054706 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.141867 
iter  10 value 94.044692
iter  10 value 94.044691
iter  10 value 94.044691
final  value 94.044691 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.123872 
final  value 94.054521 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.022846 
iter  10 value 94.057973
iter  20 value 94.006305
iter  30 value 92.610074
iter  40 value 92.594830
iter  50 value 92.594716
iter  50 value 92.594715
final  value 92.594713 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.734537 
iter  10 value 94.030052
iter  20 value 93.872080
iter  30 value 85.289846
iter  40 value 84.910348
iter  50 value 84.901847
final  value 84.901747 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.026691 
iter  10 value 93.381766
iter  20 value 86.278647
iter  30 value 81.188309
iter  40 value 79.381637
iter  50 value 79.075627
iter  60 value 78.949373
iter  70 value 78.946650
iter  80 value 78.944352
final  value 78.942284 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.596269 
iter  10 value 94.057593
iter  20 value 93.438708
iter  30 value 91.219088
iter  40 value 91.153044
final  value 91.153003 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.891627 
iter  10 value 94.057131
iter  20 value 93.991477
iter  30 value 89.953660
iter  40 value 85.680192
iter  50 value 84.906796
iter  60 value 84.684696
iter  70 value 84.682951
iter  80 value 84.682538
final  value 84.682365 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.401471 
iter  10 value 88.345522
iter  20 value 87.650339
iter  30 value 87.604935
iter  40 value 87.577741
iter  50 value 87.572814
iter  60 value 87.565153
iter  70 value 87.563371
iter  80 value 87.563007
iter  90 value 87.481667
iter 100 value 86.559198
final  value 86.559198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.873423 
iter  10 value 94.034304
iter  20 value 94.031458
iter  30 value 87.489836
iter  40 value 84.445943
iter  50 value 83.308765
iter  60 value 81.926977
iter  70 value 80.724951
iter  80 value 80.704023
final  value 80.703716 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.912902 
iter  10 value 94.056098
iter  20 value 93.975996
final  value 93.868640 
converged
Fitting Repeat 4 

# weights:  507
initial  value 135.015561 
iter  10 value 94.061232
iter  20 value 94.047170
iter  30 value 93.819868
iter  40 value 91.350776
iter  50 value 89.968829
iter  60 value 85.733001
iter  70 value 84.138103
iter  80 value 83.755847
iter  90 value 83.493499
iter 100 value 82.838444
final  value 82.838444 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.898981 
iter  10 value 94.060112
iter  20 value 94.052212
iter  30 value 85.167172
iter  40 value 84.676702
iter  50 value 84.656387
final  value 84.655540 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.712228 
iter  10 value 120.265278
iter  20 value 118.271182
iter  30 value 117.713691
iter  40 value 117.070201
iter  50 value 113.370733
iter  60 value 110.709599
iter  70 value 106.474621
iter  80 value 105.108039
iter  90 value 102.962613
iter 100 value 101.766399
final  value 101.766399 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.985659 
iter  10 value 119.695190
iter  20 value 108.470359
iter  30 value 108.065943
iter  40 value 107.514910
iter  50 value 106.245296
iter  60 value 104.956021
iter  70 value 103.019769
iter  80 value 102.277856
iter  90 value 102.208571
iter 100 value 102.184987
final  value 102.184987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.572298 
iter  10 value 117.915769
iter  20 value 117.453750
iter  30 value 108.448755
iter  40 value 107.488387
iter  50 value 105.094350
iter  60 value 102.296663
iter  70 value 101.302365
iter  80 value 100.682148
iter  90 value 100.529617
iter 100 value 100.485391
final  value 100.485391 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 150.291757 
iter  10 value 118.372367
iter  20 value 111.422392
iter  30 value 105.997527
iter  40 value 105.592375
iter  50 value 105.054868
iter  60 value 103.775123
iter  70 value 103.480660
iter  80 value 103.422075
iter  90 value 103.296845
iter 100 value 102.552986
final  value 102.552986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.650243 
iter  10 value 120.904612
iter  20 value 117.784295
iter  30 value 117.242117
iter  40 value 109.302106
iter  50 value 105.630611
iter  60 value 104.136780
iter  70 value 103.024237
iter  80 value 102.177332
iter  90 value 101.741693
iter 100 value 101.555346
final  value 101.555346 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Mar 18 19:51:26 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 
 17.640   0.421  84.024