##############################################################################
##############################################################################
###
### 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 4.4.1 (2024-06-14)
* 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 ‘1.10.0’
* 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
FSmethod      51.721  1.851  61.821
corr_plot     51.584  1.853  62.289
var_imp       50.913  1.775  62.232
pred_ensembel 24.530  0.511  24.637
calculateTC    4.803  0.525   6.161
enrichfindP    0.902  0.080  14.077
* 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 4.4.1 (2024-06-14) -- "Race for Your Life"
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 99.491548 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.739882 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.336237 
iter  10 value 94.026544
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.719128 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.190539 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.350532 
iter  10 value 92.400924
final  value 92.232622 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.030929 
iter  10 value 94.484236
iter  10 value 94.484236
final  value 94.484212 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.930989 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.699942 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.700712 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.361587 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.665411 
final  value 94.484209 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.402185 
iter  10 value 88.997890
iter  20 value 86.924521
final  value 86.916972 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.193146 
iter  10 value 94.343373
iter  20 value 94.097017
iter  30 value 93.100778
iter  40 value 87.185489
iter  50 value 87.166330
final  value 87.166217 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.830036 
iter  10 value 94.165118
final  value 94.165117 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.277532 
iter  10 value 94.195454
iter  20 value 90.772038
iter  30 value 86.972678
iter  40 value 85.179093
iter  50 value 82.830329
iter  60 value 80.812492
iter  70 value 80.212879
iter  80 value 79.579144
iter  90 value 79.565907
iter 100 value 79.513539
final  value 79.513539 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.438625 
iter  10 value 94.480477
iter  20 value 85.931878
iter  30 value 83.180298
iter  40 value 82.918125
iter  50 value 82.418403
iter  60 value 82.361584
iter  70 value 82.244942
final  value 82.234992 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.879933 
iter  10 value 94.212099
iter  20 value 85.882325
iter  30 value 83.264176
iter  40 value 82.366419
iter  50 value 81.936520
iter  60 value 81.891864
iter  70 value 81.793861
iter  80 value 81.779623
final  value 81.779609 
converged
Fitting Repeat 4 

# weights:  103
initial  value 118.238660 
iter  10 value 94.275321
iter  20 value 93.642880
iter  30 value 93.640664
iter  40 value 93.515238
iter  50 value 85.920934
iter  60 value 85.658389
iter  70 value 82.534854
iter  80 value 81.900166
iter  90 value 81.817261
iter 100 value 81.786081
final  value 81.786081 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.955350 
iter  10 value 94.486600
iter  20 value 93.768742
iter  30 value 93.511076
iter  40 value 90.855098
iter  50 value 81.919682
iter  60 value 80.763125
iter  70 value 80.394852
iter  80 value 79.809451
iter  90 value 79.518893
final  value 79.514500 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.768405 
iter  10 value 94.493914
iter  20 value 90.611065
iter  30 value 84.847538
iter  40 value 82.723172
iter  50 value 82.302126
iter  60 value 79.764351
iter  70 value 79.322113
iter  80 value 79.132929
iter  90 value 79.001081
iter 100 value 78.696488
final  value 78.696488 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.979568 
iter  10 value 94.642293
iter  20 value 94.037625
iter  30 value 92.191384
iter  40 value 90.638309
iter  50 value 84.784773
iter  60 value 83.161771
iter  70 value 82.795423
iter  80 value 81.917904
iter  90 value 79.781531
iter 100 value 79.028801
final  value 79.028801 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.559991 
iter  10 value 95.249767
iter  20 value 94.255908
iter  30 value 89.534857
iter  40 value 85.455679
iter  50 value 82.562403
iter  60 value 79.705112
iter  70 value 79.081471
iter  80 value 78.793268
iter  90 value 78.726576
iter 100 value 78.498989
final  value 78.498989 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.398540 
iter  10 value 94.486768
iter  20 value 93.506524
iter  30 value 91.553928
iter  40 value 89.336946
iter  50 value 81.818415
iter  60 value 79.993562
iter  70 value 79.762208
iter  80 value 79.261455
iter  90 value 79.162137
iter 100 value 79.092579
final  value 79.092579 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.839060 
iter  10 value 94.472238
iter  20 value 84.560714
iter  30 value 83.771968
iter  40 value 83.566438
iter  50 value 81.665801
iter  60 value 79.732560
iter  70 value 79.299014
iter  80 value 78.975512
iter  90 value 78.861132
iter 100 value 78.749801
final  value 78.749801 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.366633 
iter  10 value 94.196661
iter  20 value 90.594274
iter  30 value 85.853267
iter  40 value 82.840581
iter  50 value 80.655931
iter  60 value 79.292223
iter  70 value 78.933575
iter  80 value 78.457421
iter  90 value 77.679237
iter 100 value 77.625344
final  value 77.625344 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.210093 
iter  10 value 85.641602
iter  20 value 83.898839
iter  30 value 82.468079
iter  40 value 82.166888
iter  50 value 81.937747
iter  60 value 81.338387
iter  70 value 79.808145
iter  80 value 78.824606
iter  90 value 78.521627
iter 100 value 78.162554
final  value 78.162554 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.737222 
iter  10 value 92.455643
iter  20 value 86.236551
iter  30 value 85.529787
iter  40 value 82.529407
iter  50 value 82.095480
iter  60 value 81.515371
iter  70 value 80.747987
iter  80 value 79.833354
iter  90 value 78.258488
iter 100 value 77.627247
final  value 77.627247 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.726874 
iter  10 value 94.151830
iter  20 value 93.820973
iter  30 value 85.115733
iter  40 value 82.286360
iter  50 value 79.921090
iter  60 value 78.355795
iter  70 value 77.990344
iter  80 value 77.854905
iter  90 value 77.752755
iter 100 value 77.713797
final  value 77.713797 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.221462 
iter  10 value 94.482050
iter  20 value 93.254181
iter  30 value 85.187916
iter  40 value 81.464498
iter  50 value 80.718024
iter  60 value 79.970245
iter  70 value 79.338256
iter  80 value 78.791601
iter  90 value 78.220134
iter 100 value 77.924326
final  value 77.924326 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.312381 
final  value 94.486371 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.456546 
final  value 94.166801 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.569817 
iter  10 value 94.485735
iter  20 value 94.481038
iter  30 value 93.095915
iter  40 value 91.629363
iter  50 value 91.507155
iter  60 value 91.276415
iter  70 value 91.204572
iter  80 value 91.202589
final  value 91.202565 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.489116 
final  value 94.485941 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.167090 
final  value 94.485855 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.711919 
iter  10 value 94.488977
iter  20 value 94.484226
iter  30 value 94.001985
iter  40 value 90.325017
iter  50 value 83.136740
iter  60 value 80.047237
iter  70 value 79.164639
iter  80 value 78.424906
iter  90 value 78.406588
iter 100 value 78.380095
final  value 78.380095 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.045203 
iter  10 value 94.490338
iter  20 value 93.725126
iter  30 value 89.233000
iter  40 value 89.167874
iter  50 value 89.065356
iter  60 value 88.600361
iter  70 value 80.901574
iter  80 value 80.566675
iter  90 value 80.563198
iter 100 value 80.556785
final  value 80.556785 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.725003 
iter  10 value 93.388733
iter  20 value 84.487729
iter  30 value 84.484386
iter  40 value 84.478676
iter  50 value 84.470945
iter  60 value 83.322006
iter  70 value 83.272097
iter  80 value 83.113042
final  value 83.112575 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.450126 
iter  10 value 94.488928
iter  20 value 91.747289
iter  30 value 86.483007
iter  40 value 84.908505
iter  50 value 84.678353
iter  60 value 84.361068
iter  70 value 84.097925
iter  80 value 82.612547
iter  90 value 82.015448
final  value 82.015060 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.534785 
iter  10 value 94.489151
iter  20 value 94.484448
iter  30 value 93.779880
final  value 93.323458 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.768410 
iter  10 value 94.491695
iter  20 value 94.455827
iter  30 value 94.311933
final  value 94.026796 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.994063 
iter  10 value 94.489451
iter  20 value 94.027150
final  value 94.026917 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.595901 
iter  10 value 90.347224
iter  20 value 89.942105
iter  30 value 89.935778
iter  40 value 86.828060
iter  50 value 81.777911
iter  60 value 78.859267
iter  70 value 78.768243
iter  80 value 78.766111
iter  90 value 78.738697
iter 100 value 78.732376
final  value 78.732376 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.429450 
iter  10 value 94.493084
iter  20 value 94.439900
iter  30 value 85.442257
iter  40 value 83.102554
iter  50 value 83.100304
iter  60 value 83.100187
iter  70 value 83.029766
final  value 83.003155 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.273657 
iter  10 value 94.492108
iter  20 value 89.527562
iter  30 value 86.143245
iter  40 value 85.936106
iter  50 value 84.429632
iter  60 value 79.310716
iter  70 value 78.407782
iter  80 value 78.148326
iter  90 value 78.148135
iter 100 value 78.145242
final  value 78.145242 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.798630 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.419172 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.112937 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.029366 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.297789 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.017222 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.020126 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.020853 
iter  10 value 94.291892
iter  10 value 94.291892
iter  10 value 94.291892
final  value 94.291892 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.531100 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 136.036846 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.557849 
iter  10 value 87.541225
iter  20 value 86.621149
final  value 86.621137 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.453055 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.624536 
iter  10 value 94.294841
iter  20 value 94.291627
final  value 94.290196 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.340485 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.980930 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.591461 
iter  10 value 94.479766
iter  20 value 93.267519
iter  30 value 92.812576
iter  40 value 92.755392
iter  50 value 92.746942
iter  60 value 92.744380
iter  70 value 92.743706
final  value 92.742738 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.041736 
iter  10 value 94.481458
iter  20 value 90.425776
iter  30 value 87.719184
iter  40 value 87.016552
iter  50 value 86.322535
iter  60 value 85.876537
iter  70 value 84.848873
iter  80 value 83.743952
iter  90 value 83.686939
iter 100 value 83.671953
final  value 83.671953 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.158981 
iter  10 value 94.494356
iter  20 value 94.465634
iter  30 value 88.075478
iter  40 value 86.987316
iter  50 value 86.001250
iter  60 value 83.882539
iter  70 value 83.610922
iter  80 value 83.558848
final  value 83.557582 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.172661 
iter  10 value 94.395708
iter  20 value 94.354338
iter  30 value 92.087972
iter  40 value 87.233577
iter  50 value 86.821407
iter  60 value 86.526906
iter  70 value 86.180303
iter  80 value 86.084202
iter  90 value 86.058302
iter 100 value 85.999729
final  value 85.999729 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.144654 
iter  10 value 93.097798
iter  20 value 90.060118
iter  30 value 87.735757
iter  40 value 87.259838
iter  50 value 86.875663
iter  60 value 86.803868
iter  70 value 86.108409
iter  80 value 85.243649
iter  90 value 83.563845
final  value 83.557582 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.860731 
iter  10 value 94.716091
iter  20 value 94.081601
iter  30 value 88.000209
iter  40 value 87.121260
iter  50 value 83.665769
iter  60 value 83.429907
iter  70 value 83.025402
iter  80 value 82.490791
iter  90 value 81.747171
iter 100 value 81.575052
final  value 81.575052 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.648909 
iter  10 value 90.834185
iter  20 value 87.536521
iter  30 value 86.376997
iter  40 value 85.894471
iter  50 value 85.748784
iter  60 value 85.732414
iter  70 value 85.587955
iter  80 value 85.557110
iter  90 value 83.594596
iter 100 value 82.866446
final  value 82.866446 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.359757 
iter  10 value 94.575053
iter  20 value 86.692055
iter  30 value 86.044429
iter  40 value 85.175625
iter  50 value 81.300637
iter  60 value 81.070826
iter  70 value 80.765553
iter  80 value 80.719455
iter  90 value 80.677784
iter 100 value 80.627763
final  value 80.627763 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.504541 
iter  10 value 94.432021
iter  20 value 88.225575
iter  30 value 86.977612
iter  40 value 84.661308
iter  50 value 84.411471
iter  60 value 82.700160
iter  70 value 80.548549
iter  80 value 80.341947
iter  90 value 79.785966
iter 100 value 79.671855
final  value 79.671855 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.337702 
iter  10 value 94.610745
iter  20 value 89.379955
iter  30 value 87.425310
iter  40 value 85.977778
iter  50 value 85.310151
iter  60 value 82.602738
iter  70 value 81.919862
iter  80 value 81.240245
iter  90 value 80.499317
iter 100 value 80.350770
final  value 80.350770 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.657619 
iter  10 value 95.102772
iter  20 value 88.796699
iter  30 value 87.178809
iter  40 value 86.422541
iter  50 value 85.816613
iter  60 value 84.197263
iter  70 value 83.443394
iter  80 value 82.459679
iter  90 value 81.415945
iter 100 value 80.701307
final  value 80.701307 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.203750 
iter  10 value 96.590021
iter  20 value 93.881897
iter  30 value 91.325554
iter  40 value 85.310876
iter  50 value 84.227154
iter  60 value 83.667085
iter  70 value 83.592977
iter  80 value 82.194496
iter  90 value 81.661919
iter 100 value 81.048215
final  value 81.048215 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.889098 
iter  10 value 88.977015
iter  20 value 87.649357
iter  30 value 83.695892
iter  40 value 83.154340
iter  50 value 83.096957
iter  60 value 82.917292
iter  70 value 81.092447
iter  80 value 80.447330
iter  90 value 79.908909
iter 100 value 79.729777
final  value 79.729777 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.575362 
iter  10 value 94.455134
iter  20 value 87.560194
iter  30 value 86.167599
iter  40 value 83.060436
iter  50 value 81.533183
iter  60 value 80.494056
iter  70 value 80.354371
iter  80 value 80.325314
iter  90 value 80.259053
iter 100 value 80.244947
final  value 80.244947 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.578663 
iter  10 value 95.908712
iter  20 value 88.945219
iter  30 value 86.479290
iter  40 value 85.278611
iter  50 value 84.847735
iter  60 value 83.047178
iter  70 value 81.088469
iter  80 value 80.164779
iter  90 value 79.772880
iter 100 value 79.710578
final  value 79.710578 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.664798 
final  value 94.485497 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.035696 
final  value 94.485767 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.028333 
final  value 94.485836 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.883042 
final  value 94.485819 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.944822 
final  value 94.485926 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.363532 
iter  10 value 94.489187
iter  20 value 94.482197
iter  30 value 91.388323
iter  40 value 89.387572
final  value 89.386025 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.430164 
iter  10 value 94.487867
iter  20 value 94.483981
iter  30 value 94.478688
iter  40 value 94.477906
final  value 94.477904 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.420182 
iter  10 value 94.489082
iter  20 value 94.472608
iter  30 value 93.469540
iter  40 value 93.465931
iter  50 value 93.465539
iter  60 value 93.465438
iter  70 value 93.198079
iter  80 value 93.196677
iter  90 value 92.985139
iter 100 value 92.913261
final  value 92.913261 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.808293 
iter  10 value 94.296945
iter  20 value 92.807527
iter  30 value 84.957559
iter  40 value 84.109783
iter  50 value 83.326885
iter  60 value 82.739770
iter  70 value 81.956961
iter  80 value 81.882693
iter  90 value 81.881911
iter 100 value 81.881499
final  value 81.881499 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.495971 
iter  10 value 94.296833
iter  20 value 94.246515
iter  30 value 89.263767
iter  40 value 86.959282
iter  50 value 86.957807
iter  60 value 86.957503
iter  60 value 86.957502
iter  60 value 86.957502
final  value 86.957502 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.917910 
iter  10 value 94.492461
iter  20 value 94.484964
iter  30 value 86.882409
iter  40 value 85.324463
iter  40 value 85.324463
iter  40 value 85.324463
final  value 85.324463 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.175250 
iter  10 value 94.492673
iter  20 value 94.381921
iter  30 value 91.415096
iter  40 value 85.588656
iter  50 value 85.540066
iter  60 value 85.423258
iter  70 value 79.997207
iter  80 value 78.543966
iter  90 value 78.503275
iter 100 value 78.496682
final  value 78.496682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.451564 
iter  10 value 91.748755
iter  20 value 87.329675
iter  30 value 85.896156
iter  40 value 84.809869
iter  50 value 84.796404
final  value 84.792820 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.620759 
iter  10 value 94.492176
iter  20 value 94.469456
iter  30 value 88.985124
iter  40 value 86.959216
iter  50 value 86.957838
iter  60 value 86.583662
final  value 86.583307 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.383484 
iter  10 value 94.492723
iter  20 value 94.478213
iter  30 value 88.926211
iter  40 value 88.925056
iter  50 value 88.656101
iter  60 value 87.370616
iter  70 value 86.457800
iter  80 value 84.523458
iter  90 value 82.216938
iter 100 value 82.102853
final  value 82.102853 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.195932 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.341285 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.587412 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.580434 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.875098 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.410304 
iter  10 value 94.045800
iter  20 value 93.988160
final  value 93.988114 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.503023 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.647367 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.690003 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.901801 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.843274 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.547405 
iter  10 value 93.869758
final  value 93.869755 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.633236 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.492599 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.332091 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.053800 
iter  10 value 94.075953
iter  20 value 93.607572
iter  30 value 89.430909
iter  40 value 84.219873
iter  50 value 83.848068
iter  60 value 83.767642
final  value 83.763929 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.833345 
iter  10 value 94.025814
iter  20 value 91.348100
iter  30 value 88.428370
iter  40 value 88.133967
iter  50 value 84.329558
iter  60 value 83.881542
iter  70 value 82.397472
iter  80 value 82.130104
iter  90 value 81.846929
iter 100 value 81.686294
final  value 81.686294 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.334134 
iter  10 value 94.080241
iter  20 value 93.921670
iter  30 value 93.877125
iter  40 value 93.873437
final  value 93.873406 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.974145 
iter  10 value 94.056677
iter  20 value 90.965117
iter  30 value 89.822983
iter  40 value 86.691970
iter  50 value 86.296888
iter  60 value 86.222141
iter  70 value 83.284341
iter  80 value 83.183627
iter  90 value 83.159407
final  value 83.157414 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.139534 
iter  10 value 94.055088
iter  20 value 94.007499
iter  30 value 84.904109
iter  40 value 83.887744
iter  50 value 83.830182
iter  60 value 83.797611
iter  70 value 83.674083
iter  80 value 83.578917
final  value 83.577274 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.937742 
iter  10 value 94.069416
iter  20 value 92.884902
iter  30 value 92.028316
iter  40 value 91.098698
iter  50 value 86.629465
iter  60 value 85.485983
iter  70 value 85.013538
iter  80 value 83.616972
iter  90 value 82.472374
iter 100 value 82.293881
final  value 82.293881 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.606770 
iter  10 value 94.049559
iter  20 value 93.387223
iter  30 value 93.124518
iter  40 value 88.543529
iter  50 value 85.178202
iter  60 value 84.179598
iter  70 value 83.353503
iter  80 value 82.217720
iter  90 value 81.360441
iter 100 value 80.961389
final  value 80.961389 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.343878 
iter  10 value 94.064404
iter  20 value 87.164593
iter  30 value 84.242485
iter  40 value 82.197187
iter  50 value 81.313090
iter  60 value 80.928284
iter  70 value 80.906371
iter  80 value 80.732231
iter  90 value 80.486365
iter 100 value 80.287345
final  value 80.287345 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.822704 
iter  10 value 94.966804
iter  20 value 94.378907
iter  30 value 93.217005
iter  40 value 86.338738
iter  50 value 85.839596
iter  60 value 85.567413
iter  70 value 84.089914
iter  80 value 81.399332
iter  90 value 80.819660
iter 100 value 80.757316
final  value 80.757316 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.169191 
iter  10 value 98.130567
iter  20 value 94.121420
iter  30 value 94.065835
iter  40 value 92.192896
iter  50 value 84.690976
iter  60 value 83.245068
iter  70 value 83.043597
iter  80 value 82.607295
iter  90 value 82.433027
iter 100 value 81.833724
final  value 81.833724 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.049385 
iter  10 value 93.960819
iter  20 value 90.394865
iter  30 value 84.405727
iter  40 value 83.880773
iter  50 value 83.723245
iter  60 value 83.589353
iter  70 value 83.456925
iter  80 value 83.357802
iter  90 value 83.288887
iter 100 value 82.525262
final  value 82.525262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.869948 
iter  10 value 93.934728
iter  20 value 91.890519
iter  30 value 85.450587
iter  40 value 83.816018
iter  50 value 83.390143
iter  60 value 81.920010
iter  70 value 80.840156
iter  80 value 80.256426
iter  90 value 80.043886
iter 100 value 80.007211
final  value 80.007211 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.753559 
iter  10 value 93.843829
iter  20 value 89.038938
iter  30 value 83.910794
iter  40 value 83.133514
iter  50 value 82.558980
iter  60 value 82.263944
iter  70 value 82.222683
iter  80 value 82.033775
iter  90 value 81.532760
iter 100 value 80.698028
final  value 80.698028 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.050566 
iter  10 value 84.722837
iter  20 value 82.354992
iter  30 value 81.805409
iter  40 value 81.440792
iter  50 value 80.985433
iter  60 value 80.770033
iter  70 value 80.751213
iter  80 value 80.633823
iter  90 value 80.461304
iter 100 value 80.277915
final  value 80.277915 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.036327 
iter  10 value 91.115141
iter  20 value 86.739778
iter  30 value 84.594262
iter  40 value 84.127838
iter  50 value 83.630575
iter  60 value 82.208378
iter  70 value 80.979455
iter  80 value 80.480591
iter  90 value 80.190358
iter 100 value 80.099330
final  value 80.099330 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.874238 
final  value 94.054366 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.991585 
final  value 93.493128 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.158441 
final  value 94.054679 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.323217 
final  value 94.054607 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.665273 
iter  10 value 94.054415
iter  20 value 94.052925
final  value 94.052915 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.656552 
iter  10 value 94.037757
iter  20 value 94.033641
iter  30 value 93.873510
iter  40 value 85.935220
iter  50 value 84.901010
iter  60 value 84.893738
final  value 84.893727 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.776749 
iter  10 value 94.057953
iter  20 value 93.938800
final  value 90.711408 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.166334 
iter  10 value 93.993453
iter  20 value 93.971235
iter  30 value 93.832292
iter  40 value 93.823795
iter  50 value 93.757146
final  value 93.755274 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.214249 
iter  10 value 94.057576
iter  20 value 94.041682
iter  30 value 88.665820
iter  40 value 88.204330
iter  50 value 88.203415
iter  60 value 87.679607
iter  70 value 83.630511
iter  80 value 81.654616
iter  90 value 81.649080
iter 100 value 79.798946
final  value 79.798946 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.372159 
iter  10 value 94.016290
iter  20 value 94.011903
final  value 94.011852 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.843366 
iter  10 value 94.041587
iter  20 value 93.964469
iter  30 value 88.483797
iter  40 value 88.469642
iter  50 value 86.734201
iter  60 value 85.971861
iter  70 value 85.790011
iter  70 value 85.790010
iter  70 value 85.790010
final  value 85.790010 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.369144 
iter  10 value 92.197763
iter  20 value 86.942044
iter  30 value 86.939023
iter  40 value 86.936047
iter  50 value 86.933941
iter  60 value 86.927797
iter  70 value 86.815085
iter  80 value 86.034760
iter  90 value 85.771883
iter 100 value 85.770357
final  value 85.770357 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.422340 
iter  10 value 94.061278
iter  20 value 93.933869
iter  30 value 88.811535
iter  40 value 88.346053
iter  50 value 88.173529
iter  60 value 88.168845
final  value 88.167350 
converged
Fitting Repeat 4 

# weights:  507
initial  value 129.120048 
iter  10 value 94.041563
iter  20 value 94.034082
iter  30 value 93.666711
iter  40 value 88.274349
iter  50 value 86.031460
iter  60 value 83.006749
iter  70 value 81.898980
iter  80 value 81.727494
iter  90 value 81.718291
iter 100 value 81.674733
final  value 81.674733 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.222402 
iter  10 value 94.060246
iter  20 value 93.953290
iter  30 value 87.824067
final  value 87.824054 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.113790 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.478634 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.511359 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.425924 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.039101 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.487150 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.709290 
iter  10 value 93.900822
final  value 93.900821 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.779333 
iter  10 value 94.032971
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.686688 
iter  10 value 90.356069
iter  20 value 90.080410
iter  30 value 90.080000
iter  30 value 90.080000
iter  30 value 90.080000
final  value 90.080000 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.035056 
iter  10 value 94.051987
final  value 94.051984 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.513540 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.990940 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.741779 
iter  10 value 86.759985
iter  20 value 85.625703
final  value 85.617239 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.049500 
iter  10 value 90.243419
final  value 90.133835 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.997974 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.245442 
iter  10 value 94.046480
iter  20 value 91.777800
iter  30 value 90.115964
iter  40 value 88.849346
iter  50 value 85.584157
iter  60 value 82.215006
iter  70 value 81.950054
iter  80 value 81.169945
iter  90 value 80.361565
iter 100 value 80.324197
final  value 80.324197 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.246090 
iter  10 value 93.906084
iter  20 value 88.401597
iter  30 value 86.092229
iter  40 value 85.805188
iter  50 value 85.071825
iter  60 value 84.784369
iter  70 value 84.719854
final  value 84.718333 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.111471 
iter  10 value 93.916281
iter  20 value 90.526762
iter  30 value 85.917872
iter  40 value 85.274205
iter  50 value 84.931775
iter  60 value 84.827449
iter  70 value 84.739385
iter  80 value 84.718426
final  value 84.718333 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.460267 
iter  10 value 93.973251
iter  20 value 91.689364
iter  30 value 91.157312
iter  40 value 90.126020
iter  50 value 84.591214
iter  60 value 83.469581
iter  70 value 83.167478
final  value 83.136875 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.258918 
iter  10 value 94.048569
iter  20 value 93.670136
iter  30 value 90.510217
iter  40 value 82.929896
iter  50 value 82.651311
iter  60 value 82.491868
iter  70 value 82.356621
iter  80 value 80.906539
iter  90 value 80.326346
final  value 80.324196 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.674332 
iter  10 value 94.320411
iter  20 value 93.942581
iter  30 value 87.192172
iter  40 value 83.319989
iter  50 value 82.424754
iter  60 value 82.038807
iter  70 value 81.569966
iter  80 value 81.119938
iter  90 value 79.829491
iter 100 value 79.451994
final  value 79.451994 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.141274 
iter  10 value 93.694479
iter  20 value 92.473478
iter  30 value 92.080720
iter  40 value 86.728234
iter  50 value 85.969551
iter  60 value 85.058245
iter  70 value 84.674844
iter  80 value 84.549820
iter  90 value 84.510957
iter 100 value 84.473081
final  value 84.473081 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.938645 
iter  10 value 94.069553
iter  20 value 93.457419
iter  30 value 87.842376
iter  40 value 84.005476
iter  50 value 82.417848
iter  60 value 81.292279
iter  70 value 80.937097
iter  80 value 80.663719
iter  90 value 79.973390
iter 100 value 79.726085
final  value 79.726085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.112333 
iter  10 value 93.290751
iter  20 value 89.873198
iter  30 value 87.624833
iter  40 value 86.231430
iter  50 value 84.701595
iter  60 value 84.432476
iter  70 value 83.547195
iter  80 value 83.009276
iter  90 value 81.941281
iter 100 value 80.968779
final  value 80.968779 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.551262 
iter  10 value 93.822507
iter  20 value 87.992099
iter  30 value 83.297411
iter  40 value 82.508861
iter  50 value 81.922210
iter  60 value 81.445999
iter  70 value 81.263103
iter  80 value 81.123226
iter  90 value 80.898505
iter 100 value 80.650306
final  value 80.650306 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.792685 
iter  10 value 94.247108
iter  20 value 88.962428
iter  30 value 83.382248
iter  40 value 81.804147
iter  50 value 81.058281
iter  60 value 80.519691
iter  70 value 79.572807
iter  80 value 79.261187
iter  90 value 78.996665
iter 100 value 78.885616
final  value 78.885616 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.664553 
iter  10 value 94.462928
iter  20 value 86.193199
iter  30 value 85.877485
iter  40 value 84.399379
iter  50 value 83.580957
iter  60 value 82.277901
iter  70 value 81.618010
iter  80 value 81.466613
iter  90 value 81.321103
iter 100 value 81.200457
final  value 81.200457 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.785083 
iter  10 value 93.982642
iter  20 value 93.152461
iter  30 value 87.063407
iter  40 value 85.536527
iter  50 value 82.696688
iter  60 value 81.945342
iter  70 value 80.288810
iter  80 value 79.551858
iter  90 value 79.440902
iter 100 value 79.381652
final  value 79.381652 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.022978 
iter  10 value 94.073121
iter  20 value 90.826230
iter  30 value 84.416118
iter  40 value 82.097162
iter  50 value 81.244121
iter  60 value 81.125838
iter  70 value 80.987151
iter  80 value 80.780545
iter  90 value 80.478053
iter 100 value 80.130214
final  value 80.130214 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.096351 
iter  10 value 93.040027
iter  20 value 84.841150
iter  30 value 82.896564
iter  40 value 80.512620
iter  50 value 79.650101
iter  60 value 79.243469
iter  70 value 79.142370
iter  80 value 79.112283
iter  90 value 79.058193
iter 100 value 78.958805
final  value 78.958805 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.090238 
final  value 94.054747 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.667101 
final  value 94.054317 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.810185 
final  value 94.054478 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.327483 
iter  10 value 94.054696
iter  20 value 93.694632
final  value 93.604740 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.909730 
final  value 94.054570 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.774711 
iter  10 value 94.056614
iter  20 value 93.995513
iter  30 value 93.682486
iter  40 value 93.657466
final  value 93.633742 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.106544 
iter  10 value 94.038262
iter  20 value 93.413402
iter  30 value 85.950814
iter  40 value 85.131982
iter  50 value 85.106065
iter  60 value 85.105783
iter  70 value 84.919403
iter  80 value 84.914535
final  value 84.914463 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.284559 
iter  10 value 94.054315
iter  20 value 93.604770
final  value 93.604689 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.615357 
iter  10 value 94.057508
iter  20 value 94.052781
iter  30 value 93.536368
iter  40 value 83.743790
iter  50 value 81.686103
iter  60 value 80.479059
iter  70 value 78.646754
iter  80 value 78.537284
iter  90 value 78.484441
iter 100 value 78.484138
final  value 78.484138 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.040762 
iter  10 value 94.058023
iter  20 value 94.051561
iter  30 value 92.081741
iter  40 value 84.656892
iter  50 value 83.811375
iter  60 value 83.810710
iter  70 value 83.719070
final  value 83.717140 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.958922 
iter  10 value 94.046982
iter  20 value 93.658944
iter  30 value 85.540736
iter  40 value 85.116720
iter  50 value 84.169717
iter  60 value 84.017140
iter  70 value 83.399190
iter  80 value 83.362278
iter  90 value 83.320617
iter 100 value 83.314456
final  value 83.314456 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.273734 
iter  10 value 94.061095
iter  20 value 94.053316
iter  30 value 93.613944
final  value 93.605135 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.275129 
iter  10 value 94.041762
iter  20 value 94.034587
final  value 94.033589 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.041983 
iter  10 value 94.033562
iter  20 value 93.969326
iter  30 value 93.549908
iter  40 value 93.286262
iter  50 value 90.072200
iter  60 value 88.813224
iter  70 value 88.812723
iter  80 value 88.812335
iter  90 value 88.780960
iter 100 value 88.731463
final  value 88.731463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.994367 
iter  10 value 94.060760
iter  20 value 94.040241
iter  30 value 90.462831
iter  40 value 85.329171
iter  50 value 80.902844
iter  60 value 79.682909
iter  70 value 79.620433
final  value 79.608937 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.231073 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.637795 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.247617 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.006167 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.654891 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.947294 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.866982 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.047089 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.104300 
iter  10 value 93.394928
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.776033 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.783347 
iter  10 value 93.813954
iter  10 value 93.813953
iter  10 value 93.813953
final  value 93.813953 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.763306 
iter  10 value 93.352332
iter  20 value 93.135351
final  value 93.135239 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.318658 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.318309 
iter  10 value 93.394945
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.192630 
iter  10 value 93.637371
iter  10 value 93.637370
final  value 93.637370 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.687066 
iter  10 value 94.488631
iter  20 value 94.468734
iter  30 value 93.790676
iter  40 value 93.702571
iter  50 value 93.547487
iter  60 value 93.002727
iter  70 value 87.861384
iter  80 value 87.363855
iter  90 value 85.241733
iter 100 value 85.202425
final  value 85.202425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.329122 
iter  10 value 94.826942
iter  20 value 94.489163
iter  30 value 88.724920
iter  40 value 87.751420
iter  50 value 86.363896
iter  60 value 85.693904
iter  70 value 84.052890
iter  80 value 83.645084
iter  90 value 83.239129
iter 100 value 83.200323
final  value 83.200323 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.554761 
iter  10 value 94.488540
iter  20 value 93.680334
iter  30 value 92.225489
iter  40 value 86.688847
iter  50 value 85.220367
iter  60 value 84.583540
iter  70 value 84.401395
iter  80 value 84.369105
iter  90 value 82.966116
final  value 82.966113 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.304304 
iter  10 value 94.387357
iter  20 value 93.632291
iter  30 value 93.527758
iter  40 value 89.010555
iter  50 value 85.177928
iter  60 value 84.924735
iter  70 value 84.828971
iter  80 value 84.253699
iter  90 value 83.700271
iter 100 value 83.202837
final  value 83.202837 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.775749 
iter  10 value 94.511968
iter  20 value 94.464232
iter  30 value 90.612660
iter  40 value 87.571404
iter  50 value 87.481244
iter  60 value 86.011425
iter  70 value 85.678431
iter  80 value 85.323357
iter  90 value 84.575472
iter 100 value 83.931146
final  value 83.931146 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.400503 
iter  10 value 94.453095
iter  20 value 93.731305
iter  30 value 93.545263
iter  40 value 93.421281
iter  50 value 91.685761
iter  60 value 86.354835
iter  70 value 85.110717
iter  80 value 82.760762
iter  90 value 82.380195
iter 100 value 82.058973
final  value 82.058973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.187399 
iter  10 value 94.585297
iter  20 value 94.454445
iter  30 value 86.633202
iter  40 value 86.307310
iter  50 value 85.847645
iter  60 value 85.185172
iter  70 value 82.987230
iter  80 value 82.540607
iter  90 value 82.159088
iter 100 value 82.025108
final  value 82.025108 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.099989 
iter  10 value 94.493871
iter  20 value 93.560422
iter  30 value 87.099472
iter  40 value 86.276371
iter  50 value 85.689822
iter  60 value 82.967502
iter  70 value 82.243329
iter  80 value 82.077567
iter  90 value 81.890122
iter 100 value 81.830909
final  value 81.830909 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.876811 
iter  10 value 93.944179
iter  20 value 93.542847
iter  30 value 93.453055
iter  40 value 92.371988
iter  50 value 90.323116
iter  60 value 89.181659
iter  70 value 87.367917
iter  80 value 85.292969
iter  90 value 84.934807
iter 100 value 84.769695
final  value 84.769695 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.691779 
iter  10 value 94.499711
iter  20 value 90.490871
iter  30 value 88.752766
iter  40 value 87.374273
iter  50 value 85.376034
iter  60 value 84.273056
iter  70 value 83.859814
iter  80 value 83.593839
iter  90 value 83.428849
iter 100 value 83.068039
final  value 83.068039 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.143066 
iter  10 value 94.297475
iter  20 value 86.746536
iter  30 value 85.338846
iter  40 value 84.692355
iter  50 value 83.649458
iter  60 value 82.733221
iter  70 value 82.424325
iter  80 value 82.143442
iter  90 value 82.059469
iter 100 value 82.040434
final  value 82.040434 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.460781 
iter  10 value 87.256808
iter  20 value 85.751529
iter  30 value 85.435369
iter  40 value 84.699639
iter  50 value 83.763596
iter  60 value 82.836814
iter  70 value 82.417404
iter  80 value 82.161829
iter  90 value 82.065018
iter 100 value 82.018302
final  value 82.018302 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.964178 
iter  10 value 94.637473
iter  20 value 90.953043
iter  30 value 87.732682
iter  40 value 85.152062
iter  50 value 83.737056
iter  60 value 83.248727
iter  70 value 82.370239
iter  80 value 81.904388
iter  90 value 81.710600
iter 100 value 81.655358
final  value 81.655358 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.197733 
iter  10 value 98.130232
iter  20 value 93.061095
iter  30 value 90.734764
iter  40 value 87.465769
iter  50 value 85.755443
iter  60 value 83.169107
iter  70 value 82.568536
iter  80 value 82.006988
iter  90 value 81.846457
iter 100 value 81.566858
final  value 81.566858 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.960584 
iter  10 value 94.832212
iter  20 value 88.686725
iter  30 value 87.171352
iter  40 value 86.601242
iter  50 value 86.300921
iter  60 value 84.070205
iter  70 value 83.673257
iter  80 value 83.024919
iter  90 value 82.558491
iter 100 value 82.174146
final  value 82.174146 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.056785 
iter  10 value 93.650267
iter  20 value 93.316526
iter  30 value 93.299241
iter  40 value 93.254429
final  value 93.254364 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.452307 
final  value 94.486009 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.972914 
final  value 94.485874 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.898741 
final  value 94.485802 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.240578 
iter  10 value 93.458034
iter  20 value 88.881343
iter  30 value 88.783834
iter  40 value 88.782079
iter  50 value 88.735254
iter  60 value 88.734106
iter  70 value 88.710191
iter  80 value 87.169360
iter  90 value 86.623132
final  value 86.579184 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.439208 
iter  10 value 94.489283
iter  20 value 93.995631
iter  30 value 89.568208
iter  40 value 88.096371
iter  50 value 86.877341
iter  60 value 86.274927
iter  70 value 86.274735
final  value 86.273643 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.743526 
iter  10 value 93.642485
iter  20 value 93.455949
iter  30 value 86.178266
iter  40 value 86.117035
iter  50 value 86.116805
iter  60 value 86.116108
iter  70 value 85.926501
iter  80 value 83.986619
iter  90 value 83.018786
iter 100 value 82.853905
final  value 82.853905 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.290229 
iter  10 value 94.488765
iter  20 value 94.484219
iter  30 value 93.408161
final  value 93.395424 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.035936 
iter  10 value 94.489268
iter  20 value 94.329477
iter  30 value 86.631262
iter  40 value 86.630667
iter  50 value 86.280594
iter  60 value 86.244556
iter  70 value 85.695108
iter  80 value 85.485502
iter  90 value 85.367267
iter 100 value 85.007776
final  value 85.007776 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.987409 
iter  10 value 93.422343
iter  20 value 93.400633
iter  30 value 93.395818
iter  40 value 87.419277
iter  50 value 86.870043
iter  60 value 86.625188
iter  60 value 86.625188
iter  60 value 86.625188
final  value 86.625188 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.626363 
iter  10 value 93.404211
iter  20 value 92.890390
iter  30 value 88.991049
iter  40 value 88.838353
iter  50 value 88.835482
iter  60 value 88.267859
iter  70 value 85.544609
iter  80 value 82.691527
iter  90 value 81.248000
iter 100 value 80.983342
final  value 80.983342 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.679282 
iter  10 value 93.646970
iter  20 value 93.524139
iter  30 value 93.519686
iter  40 value 93.299573
iter  50 value 88.972990
iter  60 value 88.711744
iter  70 value 88.700762
iter  80 value 88.274788
iter  90 value 88.245632
iter 100 value 88.116971
final  value 88.116971 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.910731 
iter  10 value 89.704839
iter  20 value 85.763529
iter  30 value 85.761748
iter  40 value 85.758924
iter  50 value 85.756836
iter  60 value 85.756739
iter  70 value 85.756063
iter  80 value 84.120097
iter  90 value 84.091901
iter 100 value 83.811814
final  value 83.811814 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.148891 
iter  10 value 94.492037
iter  20 value 93.500556
final  value 92.897997 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.586673 
iter  10 value 93.363330
iter  20 value 93.349345
iter  30 value 93.342999
final  value 93.341756 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.747684 
iter  10 value 118.103117
iter  20 value 114.164317
iter  30 value 109.732972
iter  40 value 105.753000
iter  50 value 104.059008
iter  60 value 101.661853
iter  70 value 101.467175
iter  80 value 100.985531
iter  90 value 100.925084
iter 100 value 100.733897
final  value 100.733897 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.191992 
iter  10 value 115.639133
iter  20 value 106.766839
iter  30 value 105.145627
iter  40 value 103.307790
iter  50 value 103.227054
iter  60 value 102.772157
iter  70 value 102.403021
iter  80 value 102.089986
iter  90 value 101.564958
iter 100 value 101.391784
final  value 101.391784 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 138.202327 
iter  10 value 115.845192
iter  20 value 106.359185
iter  30 value 103.273327
iter  40 value 102.146009
iter  50 value 101.159016
iter  60 value 101.120958
iter  70 value 100.993608
iter  80 value 100.734035
iter  90 value 100.613112
iter 100 value 100.500974
final  value 100.500974 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 141.488406 
iter  10 value 118.774444
iter  20 value 110.170290
iter  30 value 107.626752
iter  40 value 107.192039
iter  50 value 105.334023
iter  60 value 103.977939
iter  70 value 102.375482
iter  80 value 101.683082
iter  90 value 101.474061
iter 100 value 101.364945
final  value 101.364945 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 146.920872 
iter  10 value 118.911128
iter  20 value 117.894606
iter  30 value 107.783114
iter  40 value 106.172825
iter  50 value 105.507225
iter  60 value 104.842846
iter  70 value 103.059057
iter  80 value 102.446979
iter  90 value 102.228598
iter 100 value 101.251747
final  value 101.251747 
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 -- Thu Oct 10 06:51:01 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 
 72.226   2.266  92.558