##############################################################################
##############################################################################
###
### 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_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.4
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* 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 ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       53.266  1.966  68.086
corr_plot     51.643  1.898  62.563
FSmethod      51.116  1.849  60.971
pred_ensembel 25.407  0.554  25.550
calculateTC    4.852  0.460   6.169
enrichfindP    0.926  0.088  15.386
getFASTA       0.124  0.017   9.077
* 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: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.19-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/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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 96.165035 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.922619 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.554525 
final  value 93.890110 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.704476 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.408411 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.082058 
iter  10 value 93.159794
iter  20 value 93.080000
iter  30 value 92.551079
iter  40 value 92.550875
final  value 92.550869 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.941879 
iter  10 value 85.425812
iter  20 value 85.194570
iter  30 value 85.155839
final  value 85.155772 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.853557 
iter  10 value 87.498981
final  value 87.150800 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.169630 
final  value 93.604520 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.699372 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.788046 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.606497 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.788569 
iter  10 value 91.408529
iter  20 value 84.434755
iter  30 value 83.856133
iter  40 value 83.853646
final  value 83.853641 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.560655 
iter  10 value 93.406503
final  value 93.328073 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.624761 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.328666 
iter  10 value 94.066089
iter  20 value 93.871277
iter  30 value 93.627420
iter  40 value 90.456648
iter  50 value 89.921886
iter  60 value 84.906010
iter  70 value 84.324238
iter  80 value 84.017712
iter  90 value 83.905520
iter 100 value 83.891106
final  value 83.891106 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.890947 
iter  10 value 94.086009
iter  20 value 94.057356
iter  30 value 93.739580
iter  40 value 92.907326
iter  50 value 90.104048
iter  60 value 85.754054
iter  70 value 85.623288
iter  80 value 85.216217
iter  90 value 84.071161
iter 100 value 83.639611
final  value 83.639611 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.080364 
iter  10 value 94.205315
iter  20 value 93.996718
iter  30 value 92.784134
iter  40 value 89.585924
iter  50 value 88.314363
iter  60 value 87.857564
iter  70 value 84.328528
iter  80 value 82.807761
iter  90 value 82.446296
iter 100 value 82.431047
final  value 82.431047 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.749653 
iter  10 value 94.082224
iter  20 value 92.874299
iter  30 value 88.514180
iter  40 value 88.267523
iter  50 value 86.521433
iter  60 value 84.758827
iter  70 value 84.682919
iter  80 value 84.228707
iter  90 value 83.921155
final  value 83.891106 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.616885 
iter  10 value 93.987351
iter  20 value 87.407045
iter  30 value 85.184186
iter  40 value 84.317259
iter  50 value 84.059507
iter  60 value 83.329068
iter  70 value 83.121715
iter  80 value 82.589103
iter  90 value 82.503703
iter 100 value 82.282253
final  value 82.282253 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.642474 
iter  10 value 93.981885
iter  20 value 87.286168
iter  30 value 86.000218
iter  40 value 84.697055
iter  50 value 82.572387
iter  60 value 82.258597
iter  70 value 81.895474
iter  80 value 81.365490
iter  90 value 81.022865
iter 100 value 80.699830
final  value 80.699830 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.407829 
iter  10 value 95.069159
iter  20 value 91.997178
iter  30 value 85.185531
iter  40 value 84.782061
iter  50 value 84.549411
iter  60 value 84.029330
iter  70 value 82.467856
iter  80 value 81.481075
iter  90 value 81.209060
iter 100 value 81.085003
final  value 81.085003 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.174550 
iter  10 value 87.174733
iter  20 value 86.034981
iter  30 value 84.963248
iter  40 value 83.734481
iter  50 value 82.481939
iter  60 value 81.783131
iter  70 value 81.278850
iter  80 value 80.926168
iter  90 value 80.838541
iter 100 value 80.766411
final  value 80.766411 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.066927 
iter  10 value 94.183534
iter  20 value 90.491544
iter  30 value 85.110607
iter  40 value 84.096512
iter  50 value 83.744922
iter  60 value 83.693445
iter  70 value 83.536185
iter  80 value 82.120408
iter  90 value 81.711460
iter 100 value 81.593619
final  value 81.593619 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.095838 
iter  10 value 92.989463
iter  20 value 86.823460
iter  30 value 84.498821
iter  40 value 84.100361
iter  50 value 83.756596
iter  60 value 83.315651
iter  70 value 83.005158
iter  80 value 82.316275
iter  90 value 82.120324
iter 100 value 82.020985
final  value 82.020985 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.412812 
iter  10 value 93.791071
iter  20 value 90.510019
iter  30 value 84.952452
iter  40 value 83.807630
iter  50 value 82.321728
iter  60 value 81.575998
iter  70 value 81.382949
iter  80 value 80.370241
iter  90 value 80.171674
iter 100 value 80.137957
final  value 80.137957 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.678441 
iter  10 value 97.339325
iter  20 value 88.619853
iter  30 value 84.989689
iter  40 value 82.067812
iter  50 value 81.289930
iter  60 value 81.121968
iter  70 value 80.991719
iter  80 value 80.673583
iter  90 value 80.534410
iter 100 value 80.433138
final  value 80.433138 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.817609 
iter  10 value 94.053579
iter  20 value 87.203529
iter  30 value 85.322826
iter  40 value 84.730219
iter  50 value 84.289034
iter  60 value 82.497622
iter  70 value 81.311302
iter  80 value 80.965781
iter  90 value 80.889090
iter 100 value 80.769650
final  value 80.769650 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.819611 
iter  10 value 94.376766
iter  20 value 88.942707
iter  30 value 84.292855
iter  40 value 82.185413
iter  50 value 81.347989
iter  60 value 80.718019
iter  70 value 80.577491
iter  80 value 80.510483
iter  90 value 80.438850
iter 100 value 80.303940
final  value 80.303940 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.361716 
iter  10 value 94.341989
iter  20 value 89.469129
iter  30 value 85.618013
iter  40 value 83.609381
iter  50 value 81.477234
iter  60 value 81.043297
iter  70 value 81.007922
iter  80 value 80.919054
iter  90 value 80.863501
iter 100 value 80.828367
final  value 80.828367 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 122.421191 
final  value 94.054308 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.874557 
final  value 94.054571 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.591702 
final  value 94.054612 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.578128 
final  value 94.054380 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.772449 
final  value 94.055299 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.072920 
iter  10 value 92.792861
iter  20 value 91.387129
iter  30 value 91.386467
iter  30 value 91.386467
iter  30 value 91.386467
final  value 91.386467 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.820352 
iter  10 value 94.107533
iter  20 value 88.908366
iter  30 value 85.407658
iter  40 value 85.112544
iter  50 value 85.106976
iter  60 value 85.076729
final  value 85.076176 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.259532 
iter  10 value 94.014989
iter  20 value 94.011059
final  value 94.010851 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.677202 
iter  10 value 94.057452
iter  20 value 93.420403
iter  30 value 88.208778
iter  40 value 85.872307
iter  50 value 84.026140
iter  60 value 83.377893
iter  70 value 81.842725
iter  80 value 81.812080
iter  90 value 81.808281
iter 100 value 81.806735
final  value 81.806735 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 92.547525 
iter  10 value 89.479737
iter  20 value 88.802059
iter  30 value 87.154995
iter  40 value 85.260475
iter  50 value 84.269771
iter  60 value 83.597553
iter  70 value 83.596878
iter  80 value 83.594751
iter  80 value 83.594751
iter  80 value 83.594751
final  value 83.594751 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.804211 
iter  10 value 94.036196
iter  20 value 94.032404
iter  30 value 91.816895
iter  40 value 85.555758
iter  50 value 84.708647
iter  60 value 82.656566
iter  70 value 82.261397
iter  80 value 82.255274
iter  90 value 82.254940
iter 100 value 82.254829
final  value 82.254829 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.275979 
iter  10 value 94.134667
iter  20 value 93.624296
iter  30 value 93.495740
iter  40 value 93.120336
iter  50 value 85.261665
iter  60 value 85.258682
iter  70 value 85.254339
iter  80 value 83.419701
iter  90 value 80.384922
iter 100 value 80.114463
final  value 80.114463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.041527 
iter  10 value 93.511736
iter  20 value 84.314130
final  value 84.310489 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.054476 
iter  10 value 94.060189
iter  20 value 93.643776
iter  30 value 93.480705
iter  40 value 87.525692
iter  50 value 84.250979
iter  60 value 83.710133
iter  70 value 83.266756
iter  80 value 82.286942
iter  90 value 82.253938
iter 100 value 82.252660
final  value 82.252660 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.629669 
final  value 94.041191 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.516238 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.894608 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.649534 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.862434 
final  value 94.484137 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.605463 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.296328 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.991829 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.931128 
iter  10 value 93.175524
iter  20 value 85.593531
iter  30 value 85.484906
final  value 85.484692 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.228409 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.381185 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.378647 
iter  10 value 91.077887
iter  20 value 87.400819
iter  30 value 87.389563
final  value 87.389291 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.561245 
final  value 94.484137 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.595088 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.157495 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.907415 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.942427 
iter  10 value 94.466655
iter  20 value 93.946596
iter  30 value 85.430602
iter  40 value 84.284972
iter  50 value 84.082303
iter  60 value 83.793989
iter  70 value 82.377065
iter  80 value 82.083402
iter  90 value 81.525556
final  value 81.459276 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.193203 
iter  10 value 90.367906
iter  20 value 85.674975
iter  30 value 85.102810
iter  40 value 84.666688
iter  50 value 84.129597
iter  60 value 83.865147
final  value 83.863466 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.897126 
iter  10 value 94.383734
iter  20 value 92.935198
iter  30 value 90.659255
iter  40 value 90.601599
iter  50 value 90.413111
iter  60 value 90.312513
iter  70 value 90.291468
final  value 90.291451 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.411758 
iter  10 value 94.523945
iter  20 value 94.489155
iter  30 value 88.891932
iter  40 value 86.815620
iter  50 value 83.404083
iter  60 value 82.614349
iter  70 value 82.144583
iter  80 value 81.964954
iter  90 value 81.887569
iter 100 value 81.466720
final  value 81.466720 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.623075 
iter  10 value 94.479852
iter  20 value 91.930538
iter  30 value 87.935365
iter  40 value 86.710665
iter  50 value 85.311566
iter  60 value 84.793981
iter  70 value 84.732388
final  value 84.732368 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.500119 
iter  10 value 94.464133
iter  20 value 88.543376
iter  30 value 85.920211
iter  40 value 84.284164
iter  50 value 83.383514
iter  60 value 82.711791
iter  70 value 81.805868
iter  80 value 81.700442
iter  90 value 81.669233
iter 100 value 81.586130
final  value 81.586130 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.949880 
iter  10 value 94.878604
iter  20 value 92.314529
iter  30 value 90.763476
iter  40 value 86.117264
iter  50 value 82.962825
iter  60 value 82.030536
iter  70 value 81.183523
iter  80 value 80.791226
iter  90 value 80.666270
iter 100 value 80.333113
final  value 80.333113 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.090552 
iter  10 value 94.477692
iter  20 value 90.449090
iter  30 value 85.102174
iter  40 value 82.278054
iter  50 value 81.777303
iter  60 value 81.385746
iter  70 value 81.121421
iter  80 value 80.774916
iter  90 value 80.125669
iter 100 value 79.831514
final  value 79.831514 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.570538 
iter  10 value 94.384360
iter  20 value 86.690782
iter  30 value 85.405627
iter  40 value 84.702563
iter  50 value 83.262762
iter  60 value 82.384721
iter  70 value 81.889894
iter  80 value 81.622310
iter  90 value 81.210079
iter 100 value 81.055498
final  value 81.055498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.224029 
iter  10 value 94.391205
iter  20 value 85.716708
iter  30 value 85.069787
iter  40 value 83.992341
iter  50 value 83.629536
iter  60 value 83.139290
iter  70 value 82.353907
iter  80 value 81.762519
iter  90 value 81.421194
iter 100 value 81.224739
final  value 81.224739 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.067730 
iter  10 value 94.008690
iter  20 value 91.333177
iter  30 value 87.757632
iter  40 value 83.628539
iter  50 value 83.207819
iter  60 value 82.591565
iter  70 value 81.564763
iter  80 value 80.579667
iter  90 value 80.239518
iter 100 value 80.073601
final  value 80.073601 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.173150 
iter  10 value 94.475754
iter  20 value 89.256420
iter  30 value 86.294820
iter  40 value 84.310338
iter  50 value 83.770385
iter  60 value 83.342082
iter  70 value 82.988236
iter  80 value 82.350704
iter  90 value 81.393759
iter 100 value 80.174356
final  value 80.174356 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.551268 
iter  10 value 94.410835
iter  20 value 90.973241
iter  30 value 86.654958
iter  40 value 85.183876
iter  50 value 84.455188
iter  60 value 82.812043
iter  70 value 80.225599
iter  80 value 79.727464
iter  90 value 79.551453
iter 100 value 79.438673
final  value 79.438673 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.849142 
iter  10 value 95.049337
iter  20 value 94.541506
iter  30 value 93.690134
iter  40 value 90.664230
iter  50 value 90.338663
iter  60 value 88.878540
iter  70 value 84.203308
iter  80 value 82.904483
iter  90 value 82.608282
iter 100 value 82.471340
final  value 82.471340 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.190382 
iter  10 value 95.293357
iter  20 value 85.587439
iter  30 value 82.682616
iter  40 value 80.372092
iter  50 value 80.203048
iter  60 value 80.045630
iter  70 value 79.829335
iter  80 value 79.712845
iter  90 value 79.605763
iter 100 value 79.547842
final  value 79.547842 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.325444 
iter  10 value 94.485719
iter  20 value 94.484249
iter  30 value 94.335328
iter  40 value 85.689111
final  value 85.121179 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.250694 
final  value 94.486223 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.406452 
final  value 94.485957 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.258688 
final  value 94.485704 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.325533 
final  value 94.485883 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.547046 
iter  10 value 93.475925
iter  20 value 93.411938
iter  30 value 93.003858
iter  40 value 92.885485
iter  50 value 92.885372
iter  60 value 92.317697
iter  70 value 91.878186
final  value 91.877912 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.613779 
iter  10 value 93.810904
iter  20 value 93.779286
iter  30 value 93.209344
iter  40 value 93.168885
iter  50 value 93.165443
iter  60 value 93.164765
iter  70 value 92.579394
iter  80 value 92.577488
iter  90 value 92.192101
iter 100 value 92.128082
final  value 92.128082 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.934510 
iter  10 value 94.471903
iter  20 value 93.638768
iter  30 value 85.365317
final  value 85.182376 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.046617 
iter  10 value 94.489156
iter  20 value 94.484223
iter  30 value 90.685541
iter  40 value 84.637646
iter  50 value 84.496824
iter  60 value 84.281570
iter  70 value 82.514588
iter  80 value 82.513966
iter  90 value 82.511821
iter 100 value 82.508336
final  value 82.508336 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.594254 
iter  10 value 94.488310
iter  20 value 93.472838
iter  30 value 87.592401
final  value 87.592371 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.076805 
iter  10 value 94.475888
iter  20 value 94.474367
iter  30 value 94.471990
iter  40 value 88.680552
iter  50 value 85.258049
iter  60 value 84.512808
final  value 84.511705 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.128758 
iter  10 value 94.491893
iter  20 value 94.383278
iter  30 value 88.500632
iter  40 value 88.161333
iter  50 value 86.312766
iter  60 value 83.680925
iter  70 value 83.223907
iter  80 value 82.243614
iter  90 value 81.785636
iter 100 value 81.350650
final  value 81.350650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.356157 
iter  10 value 94.492496
iter  20 value 94.448590
iter  30 value 89.092644
iter  40 value 84.988220
iter  50 value 80.549116
iter  60 value 78.967391
iter  70 value 78.619769
iter  80 value 78.500713
iter  90 value 77.978045
iter 100 value 77.971173
final  value 77.971173 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.138881 
iter  10 value 91.951601
iter  20 value 91.883908
iter  30 value 91.813111
iter  40 value 91.811900
iter  50 value 91.655354
iter  60 value 91.477412
iter  70 value 91.474140
iter  80 value 91.471940
iter  90 value 91.308065
iter 100 value 91.057075
final  value 91.057075 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.891013 
iter  10 value 94.490625
iter  20 value 94.483884
iter  30 value 94.029348
iter  40 value 90.901774
iter  50 value 90.848938
iter  60 value 90.839530
iter  70 value 90.791318
iter  80 value 90.618840
iter  90 value 90.457763
iter 100 value 90.419874
final  value 90.419874 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.151398 
final  value 94.291892 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.853303 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.305123 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.980999 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.419893 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.005931 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.019953 
iter  10 value 93.754644
iter  20 value 93.584573
iter  30 value 93.584204
final  value 93.584197 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.247412 
iter  10 value 93.889845
iter  20 value 92.803720
iter  30 value 92.739811
iter  40 value 92.739486
final  value 92.739340 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.851438 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.382626 
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.067809 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.132467 
final  value 93.833616 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.478512 
iter  10 value 91.585015
iter  20 value 86.456006
iter  30 value 86.088471
iter  40 value 84.352985
iter  50 value 84.006261
iter  60 value 83.999188
iter  70 value 83.998986
final  value 83.998969 
converged
Fitting Repeat 4 

# weights:  507
initial  value 136.040388 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.010788 
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.107933 
iter  10 value 94.486459
iter  20 value 94.326514
iter  30 value 92.971944
iter  40 value 86.738481
iter  50 value 84.909097
iter  60 value 84.283477
iter  70 value 83.860537
iter  80 value 83.777780
final  value 83.777756 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.938902 
iter  10 value 92.758021
iter  20 value 92.114876
iter  30 value 92.063270
iter  40 value 92.062438
final  value 92.062437 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.555256 
iter  10 value 94.385825
iter  20 value 94.051841
iter  30 value 93.091009
iter  40 value 86.581295
iter  50 value 85.686996
iter  60 value 84.503360
iter  70 value 84.286437
iter  80 value 83.818425
iter  90 value 83.746971
final  value 83.746965 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.101433 
iter  10 value 94.358634
iter  20 value 90.302420
iter  30 value 88.519786
iter  40 value 85.855249
iter  50 value 84.860682
iter  60 value 84.526399
iter  70 value 84.322124
iter  80 value 83.917936
iter  90 value 82.426053
iter 100 value 82.152376
final  value 82.152376 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.092807 
iter  10 value 94.488495
iter  20 value 94.341823
iter  30 value 86.832781
iter  40 value 85.701486
iter  50 value 84.485061
iter  60 value 84.304915
iter  70 value 84.292493
iter  80 value 84.292193
final  value 84.291796 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.721111 
iter  10 value 94.430962
iter  20 value 92.046425
iter  30 value 87.932911
iter  40 value 86.033225
iter  50 value 85.686338
iter  60 value 85.498365
iter  70 value 85.040086
iter  80 value 84.956633
iter  90 value 84.647457
iter 100 value 82.453173
final  value 82.453173 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.639165 
iter  10 value 94.513373
iter  20 value 92.414319
iter  30 value 90.071475
iter  40 value 87.887154
iter  50 value 86.910879
iter  60 value 85.463902
iter  70 value 85.004161
iter  80 value 84.621514
iter  90 value 83.651058
iter 100 value 81.937592
final  value 81.937592 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.105466 
iter  10 value 94.390188
iter  20 value 90.779238
iter  30 value 86.445236
iter  40 value 84.049381
iter  50 value 82.211559
iter  60 value 81.994616
iter  70 value 81.368206
iter  80 value 80.410855
iter  90 value 79.997561
iter 100 value 79.912113
final  value 79.912113 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.593684 
iter  10 value 94.413529
iter  20 value 90.695742
iter  30 value 86.564612
iter  40 value 85.287057
iter  50 value 84.976493
iter  60 value 84.614745
iter  70 value 83.835713
iter  80 value 83.318672
iter  90 value 82.141546
iter 100 value 80.972305
final  value 80.972305 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.832185 
iter  10 value 94.159995
iter  20 value 88.721189
iter  30 value 84.646598
iter  40 value 82.642639
iter  50 value 81.618379
iter  60 value 80.995602
iter  70 value 80.398726
iter  80 value 80.305652
iter  90 value 80.089640
iter 100 value 79.942327
final  value 79.942327 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.048948 
iter  10 value 94.240824
iter  20 value 87.692225
iter  30 value 86.579513
iter  40 value 83.848719
iter  50 value 82.595438
iter  60 value 82.052979
iter  70 value 81.600980
iter  80 value 81.366481
iter  90 value 81.139771
iter 100 value 80.823240
final  value 80.823240 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.914545 
iter  10 value 94.467094
iter  20 value 88.015067
iter  30 value 86.779711
iter  40 value 84.875772
iter  50 value 82.613214
iter  60 value 81.819892
iter  70 value 81.064917
iter  80 value 80.845769
iter  90 value 80.633811
iter 100 value 80.436587
final  value 80.436587 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.311172 
iter  10 value 94.480518
iter  20 value 91.067027
iter  30 value 90.052827
iter  40 value 84.514885
iter  50 value 83.754818
iter  60 value 82.311084
iter  70 value 81.328712
iter  80 value 80.721444
iter  90 value 80.553748
iter 100 value 80.526906
final  value 80.526906 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.096609 
iter  10 value 95.703242
iter  20 value 93.465206
iter  30 value 88.097746
iter  40 value 86.569982
iter  50 value 85.265199
iter  60 value 83.736511
iter  70 value 81.938452
iter  80 value 81.306760
iter  90 value 81.052326
iter 100 value 80.895041
final  value 80.895041 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.943770 
iter  10 value 94.063907
iter  20 value 87.677267
iter  30 value 86.341465
iter  40 value 83.938426
iter  50 value 82.481592
iter  60 value 81.679014
iter  70 value 81.199647
iter  80 value 81.055897
iter  90 value 80.858608
iter 100 value 80.426366
final  value 80.426366 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.175921 
iter  10 value 94.485683
iter  20 value 94.484238
final  value 94.484215 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.322034 
final  value 94.485763 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.794182 
final  value 94.486057 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.229073 
final  value 94.485911 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.672664 
iter  10 value 94.486091
iter  20 value 94.484226
iter  30 value 93.824972
iter  40 value 92.286343
iter  50 value 91.913660
iter  50 value 91.913659
iter  50 value 91.913658
final  value 91.913658 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.547187 
iter  10 value 94.483484
iter  20 value 94.280494
iter  30 value 94.276961
iter  40 value 93.976845
iter  50 value 93.836285
final  value 93.834329 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.279987 
iter  10 value 94.296462
iter  20 value 94.292667
final  value 94.292152 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.759446 
iter  10 value 94.488811
iter  20 value 94.484225
iter  30 value 94.187267
iter  40 value 87.050825
iter  50 value 86.961207
iter  60 value 86.957535
iter  70 value 86.248390
iter  80 value 85.917132
iter  90 value 85.917047
final  value 85.917015 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.523091 
iter  10 value 94.489333
iter  20 value 94.023135
iter  30 value 86.371759
iter  40 value 86.296628
iter  50 value 86.294595
final  value 86.294297 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.236458 
iter  10 value 94.099699
iter  20 value 94.096480
iter  30 value 94.095100
iter  40 value 93.940757
iter  50 value 85.489199
iter  60 value 84.050893
iter  70 value 83.457650
iter  80 value 83.392226
iter  90 value 83.281459
iter 100 value 83.232486
final  value 83.232486 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.458358 
iter  10 value 94.769289
iter  20 value 93.835580
iter  30 value 93.833660
iter  40 value 91.406657
iter  50 value 91.071320
iter  60 value 91.071068
iter  70 value 81.949281
iter  80 value 81.584283
iter  90 value 81.129376
iter 100 value 80.329121
final  value 80.329121 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.346072 
iter  10 value 94.492650
iter  20 value 94.425813
iter  30 value 89.737373
iter  40 value 86.458989
iter  50 value 85.200954
iter  60 value 85.133757
iter  70 value 82.082389
iter  80 value 82.012734
iter  90 value 82.007854
iter 100 value 81.916968
final  value 81.916968 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.981354 
iter  10 value 94.298092
iter  20 value 93.634977
iter  30 value 92.511111
iter  40 value 91.906380
iter  50 value 91.758695
iter  60 value 91.758323
final  value 91.758322 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.160218 
iter  10 value 94.300093
iter  20 value 94.292625
final  value 94.292324 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.053022 
iter  10 value 94.300901
iter  20 value 94.278135
iter  30 value 93.223409
iter  40 value 86.751601
iter  50 value 85.901849
iter  60 value 84.343234
iter  70 value 84.285879
iter  70 value 84.285878
iter  70 value 84.285878
final  value 84.285878 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.076522 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.418322 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.728278 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.585739 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.447064 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.691824 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.177088 
iter  10 value 93.394931
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.393309 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.955048 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.547769 
iter  10 value 93.394935
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.136902 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.792279 
iter  10 value 93.484047
iter  20 value 91.212173
final  value 91.212122 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.966568 
iter  10 value 93.394928
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.861378 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 124.973918 
iter  10 value 93.394951
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.156737 
iter  10 value 94.494321
iter  20 value 93.938144
iter  30 value 93.711227
iter  40 value 93.311477
iter  50 value 88.403841
iter  60 value 84.636251
iter  70 value 83.391080
iter  80 value 81.898417
iter  90 value 81.329916
iter 100 value 80.926975
final  value 80.926975 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.662012 
iter  10 value 94.542223
iter  20 value 94.386620
iter  30 value 85.016891
iter  40 value 84.049137
iter  50 value 83.652025
iter  60 value 83.163365
iter  70 value 82.926362
iter  80 value 82.895021
iter  90 value 82.880253
iter 100 value 82.877220
final  value 82.877220 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.699705 
iter  10 value 94.362819
iter  20 value 93.133765
iter  30 value 91.583531
iter  40 value 84.422129
iter  50 value 83.893483
iter  60 value 82.704486
iter  70 value 81.255539
iter  80 value 80.879024
iter  90 value 80.719698
iter 100 value 80.706332
final  value 80.706332 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.520499 
iter  10 value 94.498492
iter  20 value 91.932660
iter  30 value 87.695259
iter  40 value 86.961559
iter  50 value 86.679989
iter  60 value 86.661244
iter  70 value 86.650501
final  value 86.650295 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.573643 
iter  10 value 94.611292
iter  20 value 92.575761
iter  30 value 84.051275
iter  40 value 83.244520
iter  50 value 82.762913
iter  60 value 82.509490
iter  70 value 82.433688
iter  80 value 82.422017
final  value 82.422009 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.118424 
iter  10 value 93.404416
iter  20 value 86.312780
iter  30 value 85.185961
iter  40 value 83.400019
iter  50 value 82.527826
iter  60 value 82.378691
iter  70 value 82.241290
iter  80 value 81.522555
iter  90 value 80.234008
iter 100 value 80.198395
final  value 80.198395 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.693398 
iter  10 value 94.990475
iter  20 value 93.666887
iter  30 value 93.487499
iter  40 value 87.983181
iter  50 value 85.879725
iter  60 value 85.343731
iter  70 value 84.968871
iter  80 value 84.771128
iter  90 value 84.073225
iter 100 value 83.035658
final  value 83.035658 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.157869 
iter  10 value 93.869655
iter  20 value 91.663393
iter  30 value 87.640328
iter  40 value 83.407829
iter  50 value 82.073702
iter  60 value 81.240564
iter  70 value 80.752565
iter  80 value 79.750845
iter  90 value 79.557282
iter 100 value 79.348756
final  value 79.348756 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.522501 
iter  10 value 94.039912
iter  20 value 93.641340
iter  30 value 91.038109
iter  40 value 84.448382
iter  50 value 83.471782
iter  60 value 83.088724
iter  70 value 82.636463
iter  80 value 82.179109
iter  90 value 82.086306
iter 100 value 81.929284
final  value 81.929284 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.814532 
iter  10 value 91.458693
iter  20 value 87.201694
iter  30 value 83.474352
iter  40 value 83.291918
iter  50 value 83.199500
iter  60 value 82.781612
iter  70 value 82.198689
iter  80 value 82.087936
iter  90 value 80.883091
iter 100 value 79.943635
final  value 79.943635 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.077568 
iter  10 value 94.619996
iter  20 value 92.127631
iter  30 value 86.988097
iter  40 value 82.452356
iter  50 value 80.157807
iter  60 value 79.928087
iter  70 value 79.726846
iter  80 value 79.646084
iter  90 value 79.633205
iter 100 value 79.624633
final  value 79.624633 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.956623 
iter  10 value 93.981258
iter  20 value 92.077551
iter  30 value 84.980645
iter  40 value 84.503478
iter  50 value 82.887606
iter  60 value 80.725610
iter  70 value 80.393218
iter  80 value 79.570867
iter  90 value 79.000251
iter 100 value 78.925886
final  value 78.925886 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.440789 
iter  10 value 94.557893
iter  20 value 89.509960
iter  30 value 83.748041
iter  40 value 83.160684
iter  50 value 82.794982
iter  60 value 82.133112
iter  70 value 80.234826
iter  80 value 79.518593
iter  90 value 79.418695
iter 100 value 79.281452
final  value 79.281452 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.216462 
iter  10 value 94.189768
iter  20 value 94.017573
iter  30 value 93.366621
iter  40 value 93.287095
iter  50 value 92.677942
iter  60 value 87.282050
iter  70 value 84.422770
iter  80 value 83.606522
iter  90 value 81.689951
iter 100 value 80.920879
final  value 80.920879 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.903006 
iter  10 value 94.498483
iter  20 value 88.037174
iter  30 value 82.620622
iter  40 value 81.707880
iter  50 value 81.365123
iter  60 value 80.795223
iter  70 value 80.446430
iter  80 value 80.190566
iter  90 value 79.454743
iter 100 value 79.186274
final  value 79.186274 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.859804 
iter  10 value 94.485862
iter  20 value 94.484228
iter  20 value 94.484227
iter  20 value 94.484227
final  value 94.484227 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.250512 
iter  10 value 94.563966
iter  20 value 94.551687
iter  30 value 94.486299
iter  40 value 92.293992
iter  50 value 92.281038
iter  60 value 92.184699
iter  70 value 92.083307
iter  80 value 92.082965
iter  90 value 92.081669
iter  90 value 92.081668
iter  90 value 92.081668
final  value 92.081668 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.305913 
iter  10 value 86.383491
iter  20 value 85.650557
iter  30 value 85.612740
iter  40 value 85.166162
iter  50 value 85.147349
final  value 85.147312 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.595739 
final  value 94.485746 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.977824 
iter  10 value 93.397732
iter  20 value 93.397450
iter  30 value 93.167529
iter  40 value 82.904634
iter  50 value 82.901563
iter  60 value 82.867929
final  value 82.836466 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.223971 
iter  10 value 94.488808
iter  20 value 94.484429
iter  30 value 94.310762
iter  40 value 87.042348
iter  50 value 82.558937
iter  60 value 82.396113
iter  70 value 82.395553
iter  80 value 82.306822
iter  90 value 81.508140
iter 100 value 81.268889
final  value 81.268889 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.232585 
iter  10 value 93.401017
iter  20 value 93.398038
iter  30 value 93.168286
iter  40 value 93.103335
iter  50 value 91.646697
iter  60 value 90.883555
iter  70 value 90.867253
final  value 90.866533 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.236635 
iter  10 value 94.453013
iter  20 value 94.239130
final  value 94.227432 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.470167 
iter  10 value 93.403893
iter  20 value 93.231842
iter  30 value 92.487707
iter  40 value 88.320081
iter  50 value 87.871257
iter  60 value 87.870432
iter  70 value 86.005393
iter  80 value 81.234511
iter  90 value 80.486681
iter 100 value 79.794872
final  value 79.794872 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.795640 
iter  10 value 94.488863
iter  20 value 94.484427
final  value 94.484233 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.061071 
iter  10 value 94.492691
iter  20 value 93.406986
final  value 93.395574 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.688505 
iter  10 value 93.403440
iter  20 value 93.396593
iter  30 value 93.382762
iter  40 value 91.610305
iter  50 value 89.172117
iter  60 value 83.425075
iter  70 value 82.919556
iter  80 value 82.771496
iter  90 value 82.513715
iter 100 value 82.492770
final  value 82.492770 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.206656 
iter  10 value 94.492399
iter  20 value 94.294066
iter  30 value 93.503666
final  value 93.502242 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.465121 
iter  10 value 94.493928
iter  20 value 94.485879
iter  30 value 93.396571
final  value 93.396543 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.479473 
iter  10 value 93.404002
iter  20 value 93.400562
iter  30 value 93.137757
iter  40 value 86.425943
iter  50 value 85.408386
iter  60 value 85.403118
iter  60 value 85.403117
iter  70 value 85.402846
final  value 85.402781 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.427000 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.488217 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.655670 
iter  10 value 93.582455
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.079205 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.566516 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.106042 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.663891 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.793955 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.497052 
final  value 92.892737 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.826784 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.871800 
iter  10 value 93.680765
iter  20 value 91.065238
iter  30 value 87.830603
iter  40 value 84.045814
iter  50 value 83.724207
iter  60 value 83.717165
iter  70 value 83.715470
final  value 83.715468 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.731018 
iter  10 value 92.892738
iter  10 value 92.892737
iter  10 value 92.892737
final  value 92.892737 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.946188 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.481530 
final  value 94.052830 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.046565 
iter  10 value 93.326169
iter  20 value 93.282767
final  value 93.282717 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.355286 
iter  10 value 94.039612
iter  20 value 93.631974
iter  30 value 87.579559
iter  40 value 86.983601
iter  50 value 85.730633
iter  60 value 84.122557
iter  70 value 83.393297
iter  80 value 82.950493
iter  90 value 82.306927
iter 100 value 82.181514
final  value 82.181514 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.342944 
iter  10 value 93.976859
iter  20 value 91.160277
iter  30 value 90.243586
iter  40 value 85.952592
iter  50 value 82.584244
iter  60 value 82.283654
iter  70 value 82.206204
iter  80 value 82.193236
final  value 82.193235 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.379219 
iter  10 value 94.055623
iter  20 value 93.381314
iter  30 value 90.802057
iter  40 value 89.550360
iter  50 value 84.783937
iter  60 value 83.031575
iter  70 value 82.597009
iter  80 value 82.304682
final  value 82.304193 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.704548 
iter  10 value 94.047729
iter  20 value 91.279209
iter  30 value 89.952488
iter  40 value 86.930554
iter  50 value 84.583299
iter  60 value 84.499168
iter  70 value 84.337966
iter  80 value 84.285696
final  value 84.285053 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.718330 
iter  10 value 94.058117
iter  20 value 93.654828
iter  30 value 89.367291
iter  40 value 85.573060
iter  50 value 84.903025
iter  60 value 84.286902
iter  70 value 83.203013
iter  80 value 82.927784
iter  90 value 82.845304
iter 100 value 82.135333
final  value 82.135333 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.665456 
iter  10 value 93.964359
iter  20 value 88.379248
iter  30 value 86.270622
iter  40 value 84.970322
iter  50 value 82.479915
iter  60 value 81.566111
iter  70 value 81.335231
iter  80 value 81.270514
iter  90 value 81.202678
iter 100 value 81.096232
final  value 81.096232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.740047 
iter  10 value 94.086855
iter  20 value 93.979433
iter  30 value 87.995922
iter  40 value 86.806906
iter  50 value 85.155175
iter  60 value 83.609789
iter  70 value 82.969048
iter  80 value 81.958832
iter  90 value 81.496194
iter 100 value 81.262052
final  value 81.262052 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.716887 
iter  10 value 93.647514
iter  20 value 93.398542
iter  30 value 88.531454
iter  40 value 86.664624
iter  50 value 86.524995
iter  60 value 85.990178
iter  70 value 83.291226
iter  80 value 81.970151
iter  90 value 81.417057
iter 100 value 80.855143
final  value 80.855143 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.204553 
iter  10 value 94.745767
iter  20 value 94.058465
iter  30 value 93.130051
iter  40 value 91.517956
iter  50 value 90.326721
iter  60 value 86.795276
iter  70 value 85.040192
iter  80 value 84.740256
iter  90 value 84.447952
iter 100 value 83.394043
final  value 83.394043 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.698379 
iter  10 value 94.111781
iter  20 value 93.978452
iter  30 value 93.506522
iter  40 value 89.947268
iter  50 value 83.550223
iter  60 value 82.539059
iter  70 value 82.300647
iter  80 value 82.009887
iter  90 value 81.646630
iter 100 value 81.416941
final  value 81.416941 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.410712 
iter  10 value 91.929660
iter  20 value 84.721736
iter  30 value 84.233817
iter  40 value 83.902858
iter  50 value 83.882024
iter  60 value 83.866569
iter  70 value 83.583105
iter  80 value 83.180901
iter  90 value 82.155603
iter 100 value 81.873947
final  value 81.873947 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.495546 
iter  10 value 94.385303
iter  20 value 93.589680
iter  30 value 93.517734
iter  40 value 88.601212
iter  50 value 85.097183
iter  60 value 84.735443
iter  70 value 84.324553
iter  80 value 81.705602
iter  90 value 80.650043
iter 100 value 80.359255
final  value 80.359255 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.572074 
iter  10 value 94.073178
iter  20 value 92.787243
iter  30 value 86.566397
iter  40 value 84.963599
iter  50 value 84.160958
iter  60 value 83.888639
iter  70 value 83.832234
iter  80 value 83.492740
iter  90 value 81.876020
iter 100 value 81.106665
final  value 81.106665 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.531454 
iter  10 value 94.035859
iter  20 value 85.129333
iter  30 value 84.560029
iter  40 value 84.440425
iter  50 value 83.919503
iter  60 value 83.819925
iter  70 value 83.643175
iter  80 value 83.303163
iter  90 value 81.645934
iter 100 value 80.634621
final  value 80.634621 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.527662 
iter  10 value 94.750873
iter  20 value 87.949572
iter  30 value 86.666050
iter  40 value 84.227687
iter  50 value 82.551463
iter  60 value 81.577171
iter  70 value 81.294101
iter  80 value 80.788313
iter  90 value 80.712259
iter 100 value 80.657450
final  value 80.657450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.921195 
iter  10 value 94.054726
iter  20 value 94.052963
final  value 94.052915 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.317354 
final  value 94.054539 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.792386 
iter  10 value 92.894720
iter  20 value 92.891607
iter  30 value 88.000102
iter  40 value 83.729793
iter  50 value 83.296172
iter  60 value 82.893954
iter  70 value 82.829303
final  value 82.822430 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.819019 
iter  10 value 94.054616
final  value 94.052925 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.187429 
final  value 94.054787 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.883808 
iter  10 value 93.941924
iter  20 value 93.939561
iter  30 value 93.938818
iter  40 value 93.937727
iter  50 value 93.936837
iter  60 value 93.936766
iter  70 value 93.936104
iter  70 value 93.936103
iter  70 value 93.936103
final  value 93.936103 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.457981 
iter  10 value 94.059695
iter  20 value 94.054803
iter  30 value 93.369411
iter  40 value 91.228130
iter  50 value 91.097795
iter  60 value 91.094899
final  value 91.093577 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.503616 
iter  10 value 94.057917
iter  20 value 94.052936
final  value 94.052912 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.247035 
iter  10 value 94.057878
iter  20 value 93.995317
final  value 93.582843 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.529052 
iter  10 value 94.057729
iter  20 value 93.953263
iter  30 value 93.366219
final  value 93.366213 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.892067 
iter  10 value 93.240255
iter  20 value 93.097113
iter  30 value 92.944690
final  value 92.943602 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.793934 
iter  10 value 93.590703
iter  20 value 93.583073
final  value 93.582726 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.174277 
iter  10 value 93.591231
iter  20 value 93.584013
final  value 93.583203 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.363449 
iter  10 value 94.060654
iter  20 value 93.821993
iter  30 value 93.491556
iter  40 value 85.996278
iter  50 value 85.981285
iter  60 value 85.766636
iter  70 value 85.138661
iter  80 value 81.634219
iter  90 value 81.377922
iter 100 value 81.371356
final  value 81.371356 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.144505 
iter  10 value 94.061040
iter  20 value 93.998111
iter  30 value 90.443556
iter  30 value 90.443555
iter  30 value 90.443555
final  value 90.443555 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.979049 
iter  10 value 114.122111
iter  20 value 110.935417
iter  30 value 107.489776
iter  40 value 104.803655
iter  50 value 102.088155
iter  60 value 101.695892
iter  70 value 101.604390
iter  80 value 101.428016
iter  90 value 101.401965
iter 100 value 101.345835
final  value 101.345835 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.521817 
iter  10 value 118.428526
iter  20 value 117.553252
iter  30 value 108.902084
iter  40 value 106.363067
iter  50 value 103.892598
iter  60 value 101.631285
iter  70 value 101.189739
iter  80 value 100.692065
iter  90 value 100.476738
iter 100 value 100.390115
final  value 100.390115 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 140.770732 
iter  10 value 117.849287
iter  20 value 110.624124
iter  30 value 106.264441
iter  40 value 106.151348
iter  50 value 105.191494
iter  60 value 103.820843
iter  70 value 102.567587
iter  80 value 101.675975
iter  90 value 101.270472
iter 100 value 100.782984
final  value 100.782984 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 142.909996 
iter  10 value 117.891291
iter  20 value 113.159805
iter  30 value 109.765012
iter  40 value 107.081277
iter  50 value 105.537894
iter  60 value 103.806367
iter  70 value 102.774673
iter  80 value 101.644146
iter  90 value 101.374515
iter 100 value 101.074686
final  value 101.074686 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 167.401711 
iter  10 value 117.206265
iter  20 value 116.543508
iter  30 value 111.913377
iter  40 value 109.709955
iter  50 value 107.508445
iter  60 value 106.952948
iter  70 value 105.432684
iter  80 value 104.339709
iter  90 value 103.085961
iter 100 value 102.768803
final  value 102.768803 
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 Jun 24 06:10:48 2024 
*********************************************** 
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 
 74.553   2.236  83.989