##############################################################################
##############################################################################
###
### 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) (2024-11-20 r87352)
* 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 12.7.6
* 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
var_imp       33.441  1.634  35.446
FSmethod      32.856  1.587  34.745
corr_plot     32.774  1.615  34.643
pred_ensembel 13.798  0.442  12.262
enrichfindP    0.464  0.060   9.507
* 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-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 Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences"
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 99.534785 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.695204 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.432105 
iter  10 value 94.017442
final  value 94.017143 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.337861 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 93.847471 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.947044 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.379688 
iter  10 value 87.846200
iter  20 value 87.422846
iter  30 value 87.396216
final  value 87.396208 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.254709 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.559970 
iter  10 value 92.616821
iter  20 value 92.293926
final  value 92.293924 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.635033 
iter  10 value 93.711172
iter  20 value 93.709153
final  value 93.709151 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.335529 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.565377 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.464662 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.306021 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.362559 
iter  10 value 89.315460
iter  20 value 88.353568
iter  30 value 88.073211
iter  40 value 87.932734
final  value 87.932635 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.869705 
iter  10 value 94.087211
iter  20 value 93.985684
iter  30 value 89.621278
iter  40 value 88.545541
iter  50 value 87.025971
iter  60 value 85.627675
iter  70 value 85.167449
iter  80 value 83.881462
iter  90 value 83.184943
iter 100 value 83.116955
final  value 83.116955 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.339280 
iter  10 value 94.054965
iter  20 value 93.752598
iter  30 value 93.684517
iter  40 value 93.684030
iter  50 value 92.904429
iter  60 value 87.426425
iter  70 value 86.834793
iter  80 value 86.437447
iter  90 value 86.210802
iter 100 value 84.915666
final  value 84.915666 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 108.636663 
iter  10 value 92.226590
iter  20 value 87.279075
iter  30 value 86.634923
iter  40 value 86.320772
iter  50 value 86.120516
iter  60 value 85.798293
iter  70 value 85.678019
iter  80 value 85.665875
final  value 85.665862 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.311995 
iter  10 value 94.609266
iter  20 value 94.041668
iter  30 value 91.090992
iter  40 value 86.314397
iter  50 value 85.510833
iter  60 value 85.386691
iter  70 value 84.390893
iter  80 value 83.340593
iter  90 value 83.309220
iter 100 value 83.293160
final  value 83.293160 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.391947 
iter  10 value 94.056673
iter  20 value 93.845043
iter  30 value 93.712394
iter  40 value 93.688931
iter  50 value 93.431366
iter  60 value 90.147698
iter  70 value 86.844753
iter  80 value 86.327482
iter  90 value 85.392545
iter 100 value 85.372845
final  value 85.372845 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.620959 
iter  10 value 93.961686
iter  20 value 93.705756
iter  30 value 93.547706
iter  40 value 91.679660
iter  50 value 87.247156
iter  60 value 86.027132
iter  70 value 83.387007
iter  80 value 82.858113
iter  90 value 82.786102
iter 100 value 82.728135
final  value 82.728135 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.013693 
iter  10 value 93.981768
iter  20 value 87.747354
iter  30 value 86.996211
iter  40 value 86.497686
iter  50 value 86.087330
iter  60 value 83.422702
iter  70 value 82.233128
iter  80 value 81.924167
iter  90 value 81.809199
iter 100 value 81.772466
final  value 81.772466 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.681444 
iter  10 value 94.004403
iter  20 value 93.253319
iter  30 value 92.555447
iter  40 value 88.936406
iter  50 value 85.945953
iter  60 value 85.133042
iter  70 value 83.946137
iter  80 value 83.206181
iter  90 value 82.275207
iter 100 value 81.985393
final  value 81.985393 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.042563 
iter  10 value 94.287024
iter  20 value 92.997344
iter  30 value 88.642639
iter  40 value 87.956697
iter  50 value 86.802956
iter  60 value 84.654101
iter  70 value 83.267200
iter  80 value 82.481636
iter  90 value 82.139737
iter 100 value 81.809488
final  value 81.809488 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.651060 
iter  10 value 94.048480
iter  20 value 88.499531
iter  30 value 86.723477
iter  40 value 85.565973
iter  50 value 84.383937
iter  60 value 83.336915
iter  70 value 83.223073
iter  80 value 83.052892
iter  90 value 83.004597
iter 100 value 82.635791
final  value 82.635791 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.763954 
iter  10 value 95.806247
iter  20 value 91.661583
iter  30 value 89.116063
iter  40 value 86.240444
iter  50 value 85.015594
iter  60 value 83.065043
iter  70 value 82.704212
iter  80 value 82.473191
iter  90 value 82.220967
iter 100 value 82.136271
final  value 82.136271 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.752024 
iter  10 value 93.410705
iter  20 value 87.074491
iter  30 value 85.665699
iter  40 value 84.526057
iter  50 value 83.079998
iter  60 value 82.099561
iter  70 value 81.941472
iter  80 value 81.708629
iter  90 value 81.627786
iter 100 value 81.573242
final  value 81.573242 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.834798 
iter  10 value 94.375884
iter  20 value 93.289329
iter  30 value 92.529862
iter  40 value 91.810129
iter  50 value 90.027899
iter  60 value 87.572862
iter  70 value 86.031338
iter  80 value 85.463553
iter  90 value 84.542720
iter 100 value 83.210485
final  value 83.210485 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.561509 
iter  10 value 94.024873
iter  20 value 89.975505
iter  30 value 87.318947
iter  40 value 87.011377
iter  50 value 85.822250
iter  60 value 85.126795
iter  70 value 83.364235
iter  80 value 82.680848
iter  90 value 82.505212
iter 100 value 82.313901
final  value 82.313901 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.267423 
iter  10 value 94.270300
iter  20 value 92.839370
iter  30 value 89.330820
iter  40 value 87.217330
iter  50 value 86.803294
iter  60 value 86.013112
iter  70 value 84.167920
iter  80 value 82.910016
iter  90 value 82.558570
iter 100 value 82.449898
final  value 82.449898 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.855744 
iter  10 value 93.358821
iter  20 value 93.349109
final  value 93.342318 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.879104 
final  value 94.054923 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.601455 
final  value 94.054513 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.113931 
final  value 94.054793 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.117111 
final  value 94.055359 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.902657 
iter  10 value 93.586943
iter  20 value 93.582929
final  value 93.582833 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.080572 
iter  10 value 93.587575
iter  20 value 93.575842
iter  30 value 89.709233
iter  40 value 86.459882
iter  50 value 85.722983
iter  60 value 85.030469
final  value 85.030444 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.127609 
iter  10 value 94.057705
iter  20 value 93.926475
iter  30 value 90.228125
iter  40 value 86.145346
iter  50 value 85.662620
iter  60 value 85.506166
final  value 85.506122 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.771149 
iter  10 value 93.587188
iter  20 value 93.353648
iter  30 value 93.342306
final  value 93.342206 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.681242 
iter  10 value 94.057728
final  value 94.053170 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.965551 
iter  10 value 93.590770
iter  20 value 93.584133
iter  30 value 87.536754
iter  40 value 86.800348
iter  50 value 86.505312
iter  60 value 85.622571
iter  70 value 84.471770
iter  80 value 84.083308
iter  90 value 84.063088
iter 100 value 84.055480
final  value 84.055480 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.975562 
iter  10 value 93.590493
iter  20 value 93.585217
iter  30 value 93.584235
iter  40 value 93.566190
iter  50 value 89.264245
iter  60 value 86.154400
iter  70 value 85.773195
iter  80 value 85.670041
final  value 85.669823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.793548 
iter  10 value 94.061513
iter  20 value 91.724205
iter  30 value 88.945223
iter  40 value 88.925967
final  value 88.925901 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.730053 
iter  10 value 94.060518
iter  20 value 93.541519
iter  30 value 93.342127
iter  40 value 87.177273
iter  50 value 86.262125
iter  60 value 84.616673
iter  70 value 82.988565
iter  80 value 81.621012
iter  90 value 81.324453
iter 100 value 81.312722
final  value 81.312722 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.291167 
iter  10 value 93.847723
iter  20 value 91.751360
iter  30 value 86.877531
iter  40 value 86.723139
iter  50 value 86.722463
iter  60 value 86.713150
final  value 86.711998 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.062395 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.259453 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.171916 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.616070 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.785360 
iter  10 value 94.486435
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.340101 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.109775 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.147587 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.906610 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.088403 
iter  10 value 94.354413
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.878087 
iter  10 value 94.494272
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.585976 
final  value 94.088889 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.710349 
iter  10 value 93.290145
iter  20 value 91.150963
iter  30 value 91.003008
final  value 91.001940 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.539794 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.714825 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.144551 
iter  10 value 94.487753
iter  20 value 93.272145
iter  30 value 88.803859
iter  40 value 87.059607
iter  50 value 86.147008
iter  60 value 85.976692
iter  70 value 85.885383
iter  80 value 84.423225
iter  90 value 84.328055
final  value 84.327934 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.718208 
iter  10 value 94.486440
final  value 94.486428 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.018061 
iter  10 value 94.754427
iter  20 value 94.488324
iter  30 value 94.277330
iter  40 value 94.113884
iter  50 value 94.098271
iter  60 value 94.097119
iter  70 value 89.323216
iter  80 value 88.281776
iter  90 value 88.183810
iter 100 value 86.910049
final  value 86.910049 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.199508 
iter  10 value 96.153437
iter  20 value 94.488871
iter  30 value 94.240630
iter  40 value 90.791815
iter  50 value 88.996764
iter  60 value 88.785186
iter  70 value 88.240584
iter  80 value 87.696932
iter  90 value 87.209113
iter 100 value 85.245254
final  value 85.245254 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.460406 
iter  10 value 94.497951
iter  20 value 94.489706
iter  30 value 88.964049
iter  40 value 85.930131
iter  50 value 85.727982
iter  60 value 85.100526
iter  70 value 84.313024
iter  80 value 84.194758
final  value 84.194623 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.373665 
iter  10 value 93.601362
iter  20 value 89.709704
iter  30 value 88.490914
iter  40 value 87.669946
iter  50 value 87.471595
iter  60 value 84.606079
iter  70 value 83.754009
iter  80 value 83.701325
iter  90 value 83.634980
iter 100 value 83.410744
final  value 83.410744 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.386255 
iter  10 value 90.861794
iter  20 value 87.765111
iter  30 value 87.687777
iter  40 value 87.012033
iter  50 value 85.151720
iter  60 value 83.011564
iter  70 value 82.732526
iter  80 value 82.608178
iter  90 value 82.379730
iter 100 value 81.913579
final  value 81.913579 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.161789 
iter  10 value 94.500517
iter  20 value 89.243896
iter  30 value 89.062938
iter  40 value 88.236790
iter  50 value 87.547350
iter  60 value 85.421509
iter  70 value 84.941128
iter  80 value 84.289340
iter  90 value 83.164197
iter 100 value 82.584189
final  value 82.584189 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.645655 
iter  10 value 94.443668
iter  20 value 92.168800
iter  30 value 90.099963
iter  40 value 89.373807
iter  50 value 87.876023
iter  60 value 85.714133
iter  70 value 85.213497
iter  80 value 84.235686
iter  90 value 83.760258
iter 100 value 83.385391
final  value 83.385391 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.447234 
iter  10 value 91.559999
iter  20 value 90.015734
iter  30 value 87.747750
iter  40 value 87.654425
iter  50 value 87.184593
iter  60 value 86.809364
iter  70 value 84.857257
iter  80 value 83.418718
iter  90 value 83.063925
iter 100 value 82.994195
final  value 82.994195 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.692217 
iter  10 value 88.226123
iter  20 value 85.918450
iter  30 value 84.636439
iter  40 value 84.498806
iter  50 value 84.457684
iter  60 value 84.336334
iter  70 value 84.127045
iter  80 value 83.636900
iter  90 value 83.239043
iter 100 value 83.190864
final  value 83.190864 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.448903 
iter  10 value 94.823065
iter  20 value 90.324420
iter  30 value 84.983698
iter  40 value 83.040634
iter  50 value 82.253181
iter  60 value 82.162407
iter  70 value 81.925277
iter  80 value 81.596747
iter  90 value 81.523435
iter 100 value 81.483470
final  value 81.483470 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.532705 
iter  10 value 96.292866
iter  20 value 94.301695
iter  30 value 90.997083
iter  40 value 89.981581
iter  50 value 86.954159
iter  60 value 85.969244
iter  70 value 85.548039
iter  80 value 84.733334
iter  90 value 84.323651
iter 100 value 84.052062
final  value 84.052062 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.975877 
iter  10 value 95.851054
iter  20 value 92.844208
iter  30 value 91.418705
iter  40 value 90.028149
iter  50 value 85.921288
iter  60 value 85.010391
iter  70 value 84.840833
iter  80 value 84.300324
iter  90 value 84.009029
iter 100 value 83.803992
final  value 83.803992 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.331769 
iter  10 value 94.804661
iter  20 value 94.700136
iter  30 value 88.013671
iter  40 value 85.429982
iter  50 value 84.344467
iter  60 value 83.271431
iter  70 value 82.726903
iter  80 value 82.503729
iter  90 value 81.929846
iter 100 value 81.767880
final  value 81.767880 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.618607 
iter  10 value 94.356012
iter  20 value 94.355084
final  value 94.354799 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.048209 
final  value 94.486034 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.109582 
iter  10 value 94.356222
iter  20 value 94.316004
iter  30 value 87.325157
iter  40 value 87.321421
iter  50 value 87.308783
iter  60 value 87.307996
iter  70 value 87.305299
final  value 87.305289 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.399946 
final  value 94.485812 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.072539 
iter  10 value 94.451162
iter  20 value 94.364432
iter  30 value 91.796272
iter  40 value 91.506854
iter  50 value 91.491948
final  value 91.491937 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.321476 
iter  10 value 93.132469
iter  20 value 90.847274
iter  30 value 90.844272
iter  40 value 88.982152
iter  50 value 87.968142
iter  60 value 87.966071
iter  70 value 87.965722
iter  80 value 87.965336
iter  90 value 87.826144
iter  90 value 87.826143
iter  90 value 87.826143
final  value 87.826143 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.402049 
iter  10 value 94.488833
iter  20 value 94.478604
final  value 94.354651 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.352861 
iter  10 value 89.150347
iter  20 value 89.149375
iter  30 value 89.033491
iter  40 value 88.011051
iter  50 value 87.937038
iter  60 value 87.834769
iter  70 value 87.830062
iter  80 value 87.827053
iter  90 value 87.826968
iter 100 value 87.810304
final  value 87.810304 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.857403 
iter  10 value 94.489412
iter  20 value 94.356999
iter  30 value 91.814930
final  value 91.166494 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.609877 
iter  10 value 94.489121
iter  20 value 92.562347
iter  30 value 91.154996
iter  40 value 91.151702
iter  50 value 90.745203
iter  60 value 90.552200
iter  70 value 90.223119
iter  80 value 85.258318
iter  90 value 85.064397
iter 100 value 85.062596
final  value 85.062596 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.778378 
iter  10 value 94.362624
iter  20 value 93.615368
iter  30 value 86.526693
iter  40 value 85.339783
iter  50 value 85.257930
iter  60 value 84.561487
iter  70 value 82.208642
iter  80 value 81.914894
iter  90 value 81.911965
iter 100 value 81.909547
final  value 81.909547 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.058985 
iter  10 value 94.491461
iter  20 value 94.357187
iter  30 value 94.086455
iter  40 value 88.954162
iter  50 value 88.614032
iter  60 value 88.593665
iter  60 value 88.593664
final  value 88.593664 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.484817 
iter  10 value 94.362602
final  value 94.360815 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.044530 
iter  10 value 94.491072
iter  20 value 91.627658
iter  30 value 91.499415
final  value 91.498815 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.762158 
iter  10 value 87.144664
iter  20 value 86.912603
iter  30 value 86.911706
iter  40 value 86.635154
iter  50 value 86.614216
iter  60 value 86.610159
iter  70 value 86.608558
iter  80 value 86.130384
iter  90 value 85.798257
iter 100 value 85.558295
final  value 85.558295 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.283737 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.571702 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.265056 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.180031 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.258509 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.090387 
final  value 94.043244 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.376727 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.182704 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.124263 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.125908 
final  value 94.017143 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.725405 
final  value 94.039949 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.192174 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.863587 
iter  10 value 94.043355
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.278437 
iter  10 value 87.608864
final  value 87.571429 
converged
Fitting Repeat 5 

# weights:  507
initial  value 141.060291 
iter  10 value 86.251987
iter  20 value 85.256867
final  value 85.256865 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.306721 
iter  10 value 93.783206
iter  20 value 85.446928
iter  30 value 84.219227
iter  40 value 82.391471
iter  50 value 81.792073
iter  60 value 81.277681
iter  70 value 81.262482
final  value 81.260027 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.629854 
iter  10 value 93.593834
iter  20 value 84.962369
iter  30 value 84.456974
iter  40 value 83.321358
iter  50 value 82.506678
iter  60 value 82.368821
iter  70 value 81.924278
iter  80 value 81.678922
iter  90 value 81.650949
iter 100 value 81.649093
final  value 81.649093 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.453951 
iter  10 value 94.009228
iter  20 value 85.304977
iter  30 value 82.581203
iter  40 value 81.982437
iter  50 value 81.740040
iter  60 value 81.243715
iter  70 value 80.838861
iter  80 value 80.794279
iter  90 value 80.678595
final  value 80.677344 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.942200 
iter  10 value 93.848409
iter  20 value 87.698547
iter  30 value 82.330783
iter  40 value 81.911724
iter  50 value 81.293585
iter  60 value 81.169497
iter  70 value 80.789239
iter  80 value 80.607414
iter  90 value 80.602438
final  value 80.602363 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.700641 
iter  10 value 94.069207
iter  20 value 92.056848
iter  30 value 85.520424
iter  40 value 82.847006
iter  50 value 82.630221
iter  60 value 82.187244
iter  70 value 81.917067
iter  80 value 81.289082
iter  90 value 81.260027
iter  90 value 81.260027
iter  90 value 81.260027
final  value 81.260027 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.613945 
iter  10 value 94.082495
iter  20 value 92.270029
iter  30 value 89.874892
iter  40 value 85.950726
iter  50 value 85.058920
iter  60 value 81.418091
iter  70 value 79.389953
iter  80 value 79.062839
iter  90 value 79.008120
iter 100 value 78.556546
final  value 78.556546 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.176046 
iter  10 value 93.929037
iter  20 value 85.546175
iter  30 value 83.546184
iter  40 value 83.105310
iter  50 value 81.478231
iter  60 value 81.391331
iter  70 value 81.365621
iter  80 value 81.304643
iter  90 value 80.982643
iter 100 value 79.220333
final  value 79.220333 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.635723 
iter  10 value 91.411435
iter  20 value 85.494280
iter  30 value 82.051454
iter  40 value 81.640776
iter  50 value 80.554870
iter  60 value 80.028325
iter  70 value 79.706393
iter  80 value 79.673211
iter  90 value 79.604568
iter 100 value 79.496484
final  value 79.496484 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.926522 
iter  10 value 93.694609
iter  20 value 88.669216
iter  30 value 88.401765
iter  40 value 88.097552
iter  50 value 82.970166
iter  60 value 81.298927
iter  70 value 80.170304
iter  80 value 78.390255
iter  90 value 78.065048
iter 100 value 77.972627
final  value 77.972627 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.902219 
iter  10 value 94.333661
iter  20 value 85.790367
iter  30 value 85.252964
iter  40 value 83.685630
iter  50 value 83.001160
iter  60 value 81.464279
iter  70 value 80.224276
iter  80 value 79.488032
iter  90 value 79.079582
iter 100 value 78.978638
final  value 78.978638 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.806558 
iter  10 value 94.089432
iter  20 value 90.198664
iter  30 value 88.558060
iter  40 value 81.927904
iter  50 value 79.162000
iter  60 value 78.202949
iter  70 value 77.851493
iter  80 value 77.571144
iter  90 value 77.393202
iter 100 value 77.240523
final  value 77.240523 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.468022 
iter  10 value 94.005043
iter  20 value 81.600230
iter  30 value 81.006094
iter  40 value 80.938924
iter  50 value 80.775099
iter  60 value 79.397874
iter  70 value 78.428746
iter  80 value 77.555569
iter  90 value 77.419298
iter 100 value 77.356214
final  value 77.356214 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.397448 
iter  10 value 90.335849
iter  20 value 80.967495
iter  30 value 79.764119
iter  40 value 78.940323
iter  50 value 78.570920
iter  60 value 77.835197
iter  70 value 77.663826
iter  80 value 77.461251
iter  90 value 77.236776
iter 100 value 77.158864
final  value 77.158864 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.883981 
iter  10 value 93.947862
iter  20 value 87.672826
iter  30 value 83.638392
iter  40 value 82.136747
iter  50 value 81.569742
iter  60 value 80.474567
iter  70 value 79.270480
iter  80 value 79.043288
iter  90 value 78.408194
iter 100 value 78.005019
final  value 78.005019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.513756 
iter  10 value 94.169856
iter  20 value 83.154614
iter  30 value 82.651118
iter  40 value 81.385847
iter  50 value 78.029646
iter  60 value 77.507968
iter  70 value 77.333305
iter  80 value 77.271894
iter  90 value 77.241151
iter 100 value 77.154518
final  value 77.154518 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.632614 
final  value 94.054742 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.213586 
iter  10 value 94.054617
iter  20 value 94.052313
final  value 94.043261 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.110038 
iter  10 value 94.023249
iter  20 value 94.019021
iter  30 value 94.018320
iter  40 value 94.017834
iter  50 value 91.657365
iter  60 value 90.330226
iter  70 value 89.526469
iter  80 value 89.469942
final  value 89.469520 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.630786 
final  value 94.054535 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.123102 
final  value 94.044924 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.398425 
iter  10 value 94.057408
iter  20 value 84.881202
iter  30 value 81.167060
iter  40 value 80.615976
iter  50 value 80.155575
iter  60 value 80.121186
final  value 80.120985 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.302384 
iter  10 value 94.057520
iter  20 value 94.047564
iter  30 value 82.913731
iter  40 value 81.669075
final  value 81.645317 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.678874 
iter  10 value 94.047979
iter  20 value 94.043999
iter  30 value 94.043293
iter  40 value 82.102885
iter  50 value 81.506669
iter  60 value 81.367117
iter  70 value 81.261692
final  value 81.257116 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.415728 
iter  10 value 94.057309
iter  20 value 93.253372
iter  30 value 92.251320
final  value 92.073591 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.161799 
iter  10 value 94.057877
iter  20 value 94.051602
iter  30 value 89.303789
iter  40 value 89.000618
final  value 89.000203 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.228984 
iter  10 value 92.964583
iter  20 value 92.940317
iter  30 value 85.943115
iter  40 value 85.510015
iter  50 value 85.508257
iter  60 value 85.054450
iter  70 value 83.713063
iter  80 value 83.539791
iter  90 value 82.975012
iter 100 value 82.784520
final  value 82.784520 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 150.978983 
iter  10 value 94.060728
iter  20 value 94.038762
iter  30 value 93.009403
iter  40 value 82.498476
iter  50 value 82.468166
iter  60 value 82.278765
iter  70 value 82.266230
iter  80 value 82.266122
final  value 82.266120 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.000571 
iter  10 value 94.060356
iter  20 value 94.042664
iter  30 value 85.580417
iter  40 value 85.508261
iter  40 value 85.508261
iter  50 value 85.490915
iter  60 value 79.603025
iter  70 value 77.708008
iter  80 value 76.958709
iter  90 value 76.746084
iter 100 value 76.508510
final  value 76.508510 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.803751 
iter  10 value 94.061928
iter  20 value 93.872151
iter  30 value 84.463502
iter  40 value 84.230660
iter  50 value 84.199560
iter  50 value 84.199560
final  value 84.199560 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.137582 
iter  10 value 94.052289
iter  20 value 94.010687
iter  30 value 94.008784
iter  40 value 94.005745
iter  50 value 94.005033
iter  60 value 93.999278
iter  70 value 85.904456
iter  80 value 85.443151
final  value 85.441770 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.542644 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.568770 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.866448 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.493197 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.010590 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.661918 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.180285 
iter  10 value 93.523633
final  value 93.520939 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.450489 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.132977 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.383023 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.049775 
iter  10 value 93.795085
final  value 93.794996 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.492251 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.648437 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.226754 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.149296 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.062055 
iter  10 value 94.488393
iter  10 value 94.488392
iter  20 value 93.638746
iter  30 value 93.615759
iter  40 value 86.311016
iter  50 value 84.979864
iter  60 value 84.664968
iter  70 value 83.720084
iter  80 value 83.128717
iter  90 value 82.593433
iter 100 value 82.071426
final  value 82.071426 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 116.414879 
iter  10 value 94.405378
iter  20 value 87.654560
iter  30 value 86.331646
iter  40 value 85.870473
iter  50 value 85.360415
iter  60 value 81.564044
iter  70 value 80.799614
iter  80 value 80.797423
iter  90 value 80.785777
iter 100 value 80.712134
final  value 80.712134 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.984721 
iter  10 value 94.488596
iter  20 value 93.777078
iter  30 value 93.688599
iter  40 value 92.056533
iter  50 value 86.749070
iter  60 value 86.274896
iter  70 value 86.045417
iter  80 value 86.025137
iter  90 value 81.926780
iter 100 value 81.512677
final  value 81.512677 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.886733 
iter  10 value 94.349573
iter  20 value 91.510381
iter  30 value 87.302347
iter  40 value 85.118128
iter  50 value 82.850890
iter  60 value 82.226862
iter  70 value 82.041438
iter  80 value 81.659546
iter  90 value 81.511953
final  value 81.511947 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.456427 
iter  10 value 94.490332
iter  20 value 94.486809
iter  30 value 94.339166
iter  40 value 85.039315
iter  50 value 83.729135
iter  60 value 82.954922
iter  70 value 82.237874
iter  80 value 81.894931
iter  90 value 81.535690
final  value 81.511947 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.873819 
iter  10 value 93.954608
iter  20 value 85.834977
iter  30 value 83.140376
iter  40 value 81.866514
iter  50 value 81.418069
iter  60 value 81.314092
iter  70 value 80.998743
iter  80 value 79.889796
iter  90 value 79.218820
iter 100 value 79.073789
final  value 79.073789 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.659680 
iter  10 value 93.787718
iter  20 value 85.050899
iter  30 value 84.088399
iter  40 value 82.719842
iter  50 value 82.211926
iter  60 value 81.580332
iter  70 value 81.450390
iter  80 value 80.945221
iter  90 value 80.834746
iter 100 value 80.727658
final  value 80.727658 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.164773 
iter  10 value 93.960031
iter  20 value 86.641089
iter  30 value 83.897503
iter  40 value 83.132177
iter  50 value 82.197556
iter  60 value 79.760144
iter  70 value 79.525803
iter  80 value 79.425887
iter  90 value 79.347516
iter 100 value 79.289299
final  value 79.289299 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.621159 
iter  10 value 95.527420
iter  20 value 87.809634
iter  30 value 83.823745
iter  40 value 82.879775
iter  50 value 81.860607
iter  60 value 81.484118
iter  70 value 81.233196
iter  80 value 80.424120
iter  90 value 79.884564
iter 100 value 79.803467
final  value 79.803467 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.042602 
iter  10 value 95.508312
iter  20 value 84.985311
iter  30 value 84.145162
iter  40 value 83.973183
iter  50 value 82.213178
iter  60 value 80.372548
iter  70 value 79.539196
iter  80 value 79.451784
iter  90 value 79.332782
iter 100 value 78.993473
final  value 78.993473 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.608596 
iter  10 value 96.212968
iter  20 value 88.875969
iter  30 value 84.502711
iter  40 value 82.666311
iter  50 value 81.967136
iter  60 value 81.715776
iter  70 value 81.224473
iter  80 value 80.080897
iter  90 value 79.792937
iter 100 value 79.595262
final  value 79.595262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.758087 
iter  10 value 87.467495
iter  20 value 85.914689
iter  30 value 84.767055
iter  40 value 83.113267
iter  50 value 82.598470
iter  60 value 82.373330
iter  70 value 82.029917
iter  80 value 81.331754
iter  90 value 79.384847
iter 100 value 79.125274
final  value 79.125274 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.967200 
iter  10 value 95.055789
iter  20 value 94.524470
iter  30 value 93.292903
iter  40 value 90.183751
iter  50 value 89.031168
iter  60 value 86.857266
iter  70 value 86.349686
iter  80 value 85.433138
iter  90 value 85.048806
iter 100 value 84.527370
final  value 84.527370 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.847702 
iter  10 value 94.615046
iter  20 value 90.971455
iter  30 value 86.168296
iter  40 value 81.710206
iter  50 value 79.628712
iter  60 value 79.121000
iter  70 value 78.945974
iter  80 value 78.861212
iter  90 value 78.813418
iter 100 value 78.756858
final  value 78.756858 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.814844 
iter  10 value 95.165879
iter  20 value 90.113559
iter  30 value 88.173397
iter  40 value 87.330146
iter  50 value 84.704373
iter  60 value 81.983679
iter  70 value 81.531144
iter  80 value 81.144396
iter  90 value 80.710044
iter 100 value 80.434885
final  value 80.434885 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.023212 
final  value 94.485676 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.252136 
final  value 94.485898 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.318192 
final  value 94.485930 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.544842 
final  value 94.485771 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.392083 
final  value 94.485824 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.765628 
iter  10 value 93.562751
iter  20 value 93.561313
iter  30 value 93.555999
iter  40 value 89.133322
iter  50 value 89.076594
iter  60 value 88.897365
iter  70 value 88.879529
iter  80 value 84.395853
iter  90 value 84.392017
final  value 84.391853 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.630091 
final  value 93.814430 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.418133 
iter  10 value 94.488452
iter  20 value 93.746566
iter  30 value 92.581313
iter  40 value 88.774732
iter  50 value 86.181501
iter  60 value 80.618303
iter  70 value 79.915022
iter  80 value 79.530167
iter  90 value 79.161806
iter 100 value 79.146304
final  value 79.146304 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.471379 
iter  10 value 91.107924
iter  20 value 91.036103
iter  30 value 91.025872
final  value 91.025685 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.310791 
iter  10 value 94.488681
iter  20 value 94.484311
iter  30 value 91.701627
iter  40 value 81.973651
iter  50 value 81.313211
iter  60 value 81.309625
iter  70 value 81.242833
iter  80 value 81.238262
iter  90 value 81.230030
iter 100 value 81.229835
final  value 81.229835 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.801297 
iter  10 value 94.035061
iter  20 value 94.029587
iter  30 value 85.762555
iter  40 value 82.263929
final  value 82.263927 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.224661 
iter  10 value 93.710740
iter  20 value 93.610465
iter  30 value 93.126136
iter  40 value 91.286383
iter  50 value 90.933165
iter  60 value 90.623318
iter  70 value 81.808677
iter  80 value 81.502386
iter  90 value 81.501947
iter 100 value 81.497997
final  value 81.497997 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.653682 
iter  10 value 93.590355
iter  20 value 93.531526
iter  30 value 93.525243
iter  40 value 93.515419
final  value 93.507430 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.143682 
iter  10 value 94.376199
iter  20 value 94.375204
iter  30 value 93.573236
iter  40 value 87.016011
iter  50 value 85.779402
final  value 85.776909 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.916968 
iter  10 value 94.068044
iter  20 value 94.032282
iter  30 value 94.027651
iter  40 value 93.587340
iter  50 value 88.516096
iter  60 value 85.428650
iter  70 value 85.175972
final  value 85.175929 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.775866 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.163574 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.910607 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.390421 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.739627 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.860057 
final  value 93.809648 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.587114 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.860872 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.016953 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.400026 
iter  10 value 94.434757
iter  20 value 94.434200
iter  20 value 94.434199
iter  20 value 94.434199
final  value 94.434199 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.508027 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.325101 
iter  10 value 93.695378
final  value 93.681320 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.398490 
final  value 94.086550 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.396606 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.458796 
iter  10 value 94.467437
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.166324 
iter  10 value 94.495844
iter  20 value 94.476386
iter  30 value 90.888397
iter  40 value 84.449557
iter  50 value 84.046398
iter  60 value 83.618133
iter  70 value 83.574782
iter  80 value 81.242415
iter  90 value 80.513363
iter 100 value 80.413959
final  value 80.413959 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.574701 
iter  10 value 91.763264
iter  20 value 83.379129
iter  30 value 83.221385
iter  40 value 83.199156
iter  50 value 82.248693
final  value 82.156794 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.639775 
iter  10 value 93.902717
iter  20 value 84.930245
iter  30 value 83.659150
iter  40 value 83.601955
iter  50 value 83.571358
iter  60 value 83.563733
iter  70 value 82.850771
iter  80 value 82.732245
iter  80 value 82.732245
iter  80 value 82.732245
final  value 82.732245 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.659155 
iter  10 value 90.413237
iter  20 value 84.501112
iter  30 value 83.493290
iter  40 value 82.818851
iter  50 value 82.741769
iter  60 value 82.732959
final  value 82.732245 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.457132 
iter  10 value 94.488094
iter  20 value 93.938731
iter  30 value 93.781759
iter  40 value 92.055251
iter  50 value 84.561940
iter  60 value 83.690996
iter  70 value 82.968525
iter  80 value 82.733222
final  value 82.732245 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.507953 
iter  10 value 94.487749
iter  20 value 93.936894
iter  30 value 84.416622
iter  40 value 82.335399
iter  50 value 81.987883
iter  60 value 81.732517
iter  70 value 81.602513
iter  80 value 81.545329
iter  90 value 80.875159
iter 100 value 79.523461
final  value 79.523461 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.527519 
iter  10 value 94.470156
iter  20 value 85.584583
iter  30 value 83.241233
iter  40 value 83.207231
iter  50 value 82.169951
iter  60 value 82.107748
iter  70 value 81.057175
iter  80 value 80.469904
iter  90 value 80.152711
iter 100 value 79.611456
final  value 79.611456 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.238834 
iter  10 value 94.471270
iter  20 value 93.896717
iter  30 value 86.719022
iter  40 value 84.222618
iter  50 value 83.901927
iter  60 value 83.682195
iter  70 value 82.295464
iter  80 value 81.959343
iter  90 value 81.016176
iter 100 value 80.140073
final  value 80.140073 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.439990 
iter  10 value 94.391517
iter  20 value 86.056470
iter  30 value 83.542023
iter  40 value 83.383173
iter  50 value 82.478665
iter  60 value 82.006741
iter  70 value 81.907721
iter  80 value 81.671079
iter  90 value 81.005166
iter 100 value 79.683135
final  value 79.683135 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.036956 
iter  10 value 94.502416
iter  20 value 88.545081
iter  30 value 86.652167
iter  40 value 86.047452
iter  50 value 85.198267
iter  60 value 84.887096
iter  70 value 81.632056
iter  80 value 80.600738
iter  90 value 80.344179
iter 100 value 80.111677
final  value 80.111677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.879644 
iter  10 value 95.664902
iter  20 value 94.651833
iter  30 value 94.381597
iter  40 value 87.418657
iter  50 value 84.156624
iter  60 value 82.394841
iter  70 value 79.891341
iter  80 value 78.855254
iter  90 value 78.472116
iter 100 value 78.197313
final  value 78.197313 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.292459 
iter  10 value 96.198071
iter  20 value 92.792317
iter  30 value 87.752463
iter  40 value 84.362353
iter  50 value 80.333752
iter  60 value 79.014276
iter  70 value 78.275218
iter  80 value 78.228213
iter  90 value 78.197926
iter 100 value 78.183967
final  value 78.183967 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.245798 
iter  10 value 94.464806
iter  20 value 93.960715
iter  30 value 92.067637
iter  40 value 82.911131
iter  50 value 82.481689
iter  60 value 81.800161
iter  70 value 81.417007
iter  80 value 80.701775
iter  90 value 79.679487
iter 100 value 79.083241
final  value 79.083241 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.145618 
iter  10 value 94.533402
iter  20 value 94.159165
iter  30 value 84.758339
iter  40 value 83.722220
iter  50 value 82.381692
iter  60 value 80.489579
iter  70 value 80.128313
iter  80 value 80.040492
iter  90 value 80.034224
iter 100 value 79.701233
final  value 79.701233 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.985682 
iter  10 value 93.839421
iter  20 value 84.996333
iter  30 value 81.586123
iter  40 value 81.278598
iter  50 value 80.490106
iter  60 value 79.961874
iter  70 value 79.610652
iter  80 value 78.923049
iter  90 value 78.792993
iter 100 value 78.699569
final  value 78.699569 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.103827 
final  value 94.485721 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.443658 
final  value 94.468681 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.574848 
final  value 94.485877 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.251029 
final  value 94.485797 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.616156 
final  value 94.487384 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.451625 
iter  10 value 94.488836
iter  20 value 94.025496
final  value 93.811237 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.098590 
iter  10 value 94.207391
iter  20 value 93.216552
iter  30 value 93.215843
iter  40 value 93.213053
iter  50 value 93.148301
iter  60 value 93.148145
final  value 93.148139 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.595607 
iter  10 value 94.489392
iter  20 value 94.484250
final  value 94.484237 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.688215 
iter  10 value 94.488285
iter  20 value 92.933654
iter  30 value 91.041795
iter  40 value 90.678718
iter  50 value 89.490385
iter  60 value 88.885637
iter  70 value 88.884140
final  value 88.884007 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.824388 
iter  10 value 94.488839
iter  20 value 94.316980
iter  30 value 90.964863
iter  40 value 84.671830
iter  50 value 83.827956
iter  60 value 82.309504
iter  70 value 82.308118
final  value 82.307540 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.404882 
iter  10 value 93.928538
iter  20 value 93.809009
iter  30 value 93.695926
iter  40 value 90.563400
iter  50 value 85.052373
iter  60 value 83.360199
iter  70 value 83.353618
iter  80 value 83.241732
iter  90 value 83.237481
final  value 83.237249 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.075028 
iter  10 value 94.234220
iter  20 value 84.282427
iter  30 value 83.010251
iter  40 value 82.997600
iter  50 value 82.058227
iter  60 value 81.972705
iter  70 value 81.968971
iter  80 value 81.968041
final  value 81.967396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.008238 
iter  10 value 94.492143
iter  20 value 94.071408
iter  30 value 82.810428
iter  40 value 77.109664
iter  50 value 76.488942
iter  60 value 75.988722
iter  70 value 75.771063
iter  80 value 75.656282
iter  90 value 75.632075
iter 100 value 75.626310
final  value 75.626310 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.887111 
iter  10 value 93.810155
iter  20 value 93.802532
iter  30 value 83.680815
iter  40 value 83.248034
iter  50 value 83.237942
iter  60 value 83.237627
iter  70 value 83.236265
final  value 83.236132 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.045168 
iter  10 value 94.303313
iter  20 value 94.295083
final  value 94.293891 
converged
Fitting Repeat 1 

# weights:  305
initial  value 140.235240 
iter  10 value 117.895628
iter  20 value 117.890563
iter  30 value 116.568986
iter  40 value 115.299117
final  value 115.298979 
converged
Fitting Repeat 2 

# weights:  305
initial  value 128.698809 
iter  10 value 117.763625
iter  20 value 117.759365
final  value 117.759354 
converged
Fitting Repeat 3 

# weights:  305
initial  value 139.961621 
iter  10 value 117.763899
iter  20 value 117.748944
iter  30 value 109.466166
iter  40 value 105.604953
iter  50 value 105.540890
iter  60 value 105.429878
iter  70 value 105.184857
iter  80 value 103.258970
iter  90 value 100.984232
iter 100 value 100.971878
final  value 100.971878 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.430994 
iter  10 value 114.239202
iter  20 value 112.884455
iter  30 value 112.882700
iter  40 value 112.878331
iter  50 value 111.656296
iter  60 value 111.496863
final  value 111.496364 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.900482 
iter  10 value 117.735800
iter  20 value 113.683398
iter  30 value 105.605235
iter  40 value 104.842666
iter  50 value 104.811025
iter  60 value 104.807885
iter  70 value 104.807751
iter  80 value 104.426475
iter  90 value 103.556884
iter 100 value 103.460237
final  value 103.460237 
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 -- Fri Jan 10 21:07:44 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 
 39.504   1.577  61.872