##############################################################################
##############################################################################
###
### 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_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-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 Ventura 13.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       18.657  0.611  19.279
FSmethod      17.809  0.609  18.430
corr_plot     17.730  0.551  18.288
pred_ensembel  6.032  0.505   4.537
enrichfindP    0.168  0.029   9.134
* 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-3.20-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-arm64/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: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 97.170496 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.470440 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.802138 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.402912 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.996067 
iter  10 value 94.455592
final  value 94.455555 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.725676 
iter  10 value 93.969902
final  value 93.918130 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.226110 
final  value 94.276324 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.068945 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.208084 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.028278 
iter  10 value 91.890908
final  value 91.726410 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.912758 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.081498 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.621577 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.608720 
final  value 92.579683 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.197830 
iter  10 value 94.341971
final  value 94.337838 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.175422 
iter  10 value 94.490920
iter  20 value 94.127821
iter  30 value 87.809751
iter  40 value 86.028728
iter  50 value 85.766461
iter  60 value 85.459409
iter  70 value 85.173688
iter  80 value 84.988845
iter  90 value 84.949485
final  value 84.944884 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.458171 
iter  10 value 94.480680
iter  20 value 87.108705
iter  30 value 86.812905
iter  40 value 86.594753
iter  50 value 86.552920
iter  60 value 86.427802
iter  70 value 85.511310
iter  80 value 84.857108
iter  90 value 84.707677
final  value 84.693715 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.397870 
iter  10 value 94.404210
iter  20 value 88.090405
iter  30 value 87.758954
iter  40 value 87.319194
iter  50 value 86.216653
iter  60 value 84.986086
iter  70 value 84.901085
iter  80 value 84.899707
final  value 84.899702 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.061445 
iter  10 value 94.488668
iter  20 value 94.145285
iter  30 value 92.674985
iter  40 value 88.533788
iter  50 value 88.113003
iter  60 value 87.738574
iter  70 value 87.632159
iter  80 value 87.488940
iter  90 value 85.404938
iter 100 value 84.702143
final  value 84.702143 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.386103 
iter  10 value 94.495400
iter  20 value 94.440848
iter  30 value 90.698916
iter  40 value 87.215893
iter  50 value 86.754951
iter  60 value 86.624932
iter  70 value 85.435051
iter  80 value 84.780884
iter  90 value 84.701344
final  value 84.693714 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.758274 
iter  10 value 94.528463
iter  20 value 90.369169
iter  30 value 88.762625
iter  40 value 88.455078
iter  50 value 88.070959
iter  60 value 85.736377
iter  70 value 84.721776
iter  80 value 84.447338
iter  90 value 84.398664
iter 100 value 84.254300
final  value 84.254300 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.324391 
iter  10 value 94.888647
iter  20 value 94.511250
iter  30 value 90.740980
iter  40 value 89.823334
iter  50 value 87.954638
iter  60 value 87.491387
iter  70 value 87.399390
iter  80 value 86.013841
iter  90 value 83.741365
iter 100 value 83.064409
final  value 83.064409 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.736604 
iter  10 value 94.464985
iter  20 value 92.878773
iter  30 value 89.304184
iter  40 value 88.104237
iter  50 value 86.964546
iter  60 value 85.613757
iter  70 value 83.607796
iter  80 value 82.055965
iter  90 value 81.870755
iter 100 value 81.631260
final  value 81.631260 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.631489 
iter  10 value 94.497130
iter  20 value 92.313232
iter  30 value 87.655380
iter  40 value 87.160516
iter  50 value 85.096616
iter  60 value 83.329402
iter  70 value 83.070109
iter  80 value 82.930800
iter  90 value 82.584738
iter 100 value 82.408415
final  value 82.408415 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.331928 
iter  10 value 94.542917
iter  20 value 93.426722
iter  30 value 86.687545
iter  40 value 85.528471
iter  50 value 85.138842
iter  60 value 84.918701
iter  70 value 84.586374
iter  80 value 84.289558
iter  90 value 83.779393
iter 100 value 83.617354
final  value 83.617354 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.027016 
iter  10 value 91.174457
iter  20 value 86.818970
iter  30 value 84.771184
iter  40 value 84.654512
iter  50 value 84.595868
iter  60 value 84.435412
iter  70 value 84.342194
iter  80 value 84.251590
iter  90 value 83.801115
iter 100 value 83.153525
final  value 83.153525 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.412674 
iter  10 value 94.422073
iter  20 value 92.361238
iter  30 value 85.525847
iter  40 value 83.479012
iter  50 value 82.911527
iter  60 value 82.558268
iter  70 value 81.358927
iter  80 value 80.888761
iter  90 value 80.815508
iter 100 value 80.727975
final  value 80.727975 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.015999 
iter  10 value 94.393350
iter  20 value 87.592339
iter  30 value 87.252694
iter  40 value 86.294903
iter  50 value 85.350770
iter  60 value 85.045521
iter  70 value 83.417009
iter  80 value 83.176403
iter  90 value 82.302440
iter 100 value 81.847821
final  value 81.847821 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.997516 
iter  10 value 94.813122
iter  20 value 89.720531
iter  30 value 88.369713
iter  40 value 87.732076
iter  50 value 84.855300
iter  60 value 82.938503
iter  70 value 81.181860
iter  80 value 81.006956
iter  90 value 80.957641
iter 100 value 80.580480
final  value 80.580480 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.378547 
iter  10 value 94.441925
iter  20 value 90.414594
iter  30 value 88.611937
iter  40 value 87.740413
iter  50 value 84.474587
iter  60 value 84.012969
iter  70 value 83.368874
iter  80 value 83.213434
iter  90 value 82.956312
iter 100 value 82.818993
final  value 82.818993 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.720589 
final  value 94.485778 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.000064 
final  value 94.485770 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.453403 
iter  10 value 94.485970
iter  20 value 94.468708
iter  30 value 94.242964
iter  40 value 87.872482
iter  50 value 86.378967
iter  60 value 86.368643
iter  70 value 86.366891
final  value 86.366847 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.831265 
final  value 94.485781 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.019831 
final  value 94.485818 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.486073 
iter  10 value 94.489040
iter  20 value 93.825449
iter  30 value 92.151045
iter  40 value 91.825389
final  value 91.825386 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.653452 
iter  10 value 94.460487
iter  20 value 94.456659
iter  30 value 92.759022
iter  40 value 87.845400
iter  50 value 87.335773
final  value 87.230297 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.420186 
iter  10 value 94.449814
iter  20 value 94.445260
iter  30 value 94.442461
iter  40 value 94.022613
iter  50 value 87.479696
iter  60 value 87.445993
iter  70 value 87.162153
iter  80 value 85.623303
iter  90 value 84.870208
iter 100 value 84.311481
final  value 84.311481 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.582233 
iter  10 value 94.488684
iter  20 value 94.472496
iter  30 value 88.619706
iter  40 value 88.049579
final  value 88.040793 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.331720 
iter  10 value 89.862644
iter  20 value 88.411064
iter  30 value 88.044383
iter  40 value 85.533225
iter  50 value 85.515878
iter  60 value 84.581738
iter  70 value 84.581137
iter  80 value 84.552202
iter  90 value 84.548387
iter 100 value 84.374396
final  value 84.374396 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.602070 
iter  10 value 93.914455
iter  20 value 93.495770
iter  30 value 92.584488
iter  40 value 92.583403
iter  50 value 92.581436
iter  60 value 91.936257
iter  70 value 91.920810
iter  80 value 91.733869
iter  90 value 91.727878
iter 100 value 91.727566
final  value 91.727566 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.058351 
iter  10 value 94.475229
iter  20 value 94.293988
iter  30 value 89.412872
final  value 89.412779 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.506052 
iter  10 value 94.495634
iter  20 value 94.346017
iter  30 value 87.555700
iter  40 value 86.250168
iter  50 value 86.236099
iter  60 value 86.153301
iter  70 value 85.683086
iter  80 value 85.210794
iter  90 value 85.210465
final  value 85.210352 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.080241 
iter  10 value 94.491978
iter  20 value 91.093980
iter  30 value 86.333934
final  value 86.333802 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.073738 
iter  10 value 94.492143
iter  20 value 94.451793
iter  30 value 88.284835
iter  40 value 86.278616
iter  50 value 86.099345
final  value 86.098788 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.001129 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.530886 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.745388 
final  value 94.305882 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.204281 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.686597 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.160492 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.602433 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.691652 
iter  10 value 94.046738
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.323138 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.913919 
iter  10 value 94.145120
iter  20 value 94.132269
final  value 94.130499 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.922141 
iter  10 value 93.105396
final  value 90.971959 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.397637 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.824802 
iter  10 value 94.573905
iter  20 value 94.040161
iter  30 value 94.038598
iter  30 value 94.038597
iter  30 value 94.038597
final  value 94.038597 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.389742 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.265951 
final  value 94.144481 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.992226 
iter  10 value 94.457726
iter  20 value 94.137471
iter  30 value 94.105074
iter  40 value 93.719465
iter  50 value 89.036401
iter  60 value 87.068376
iter  70 value 86.545297
iter  80 value 86.472316
iter  90 value 85.861538
iter 100 value 85.657909
final  value 85.657909 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 116.016603 
iter  10 value 94.481600
iter  20 value 94.154441
iter  30 value 94.114595
iter  40 value 92.358031
iter  50 value 89.299485
iter  60 value 89.022756
iter  70 value 87.299970
iter  80 value 87.165491
iter  90 value 87.008949
iter 100 value 86.983479
final  value 86.983479 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.687416 
iter  10 value 94.489410
iter  20 value 94.404455
iter  30 value 94.233405
iter  40 value 90.115776
iter  50 value 88.392012
iter  60 value 87.429797
iter  70 value 87.222617
iter  80 value 87.057962
iter  90 value 86.987583
final  value 86.983453 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.498018 
iter  10 value 94.490967
iter  20 value 88.746982
iter  30 value 87.779716
iter  40 value 87.562155
iter  50 value 87.428756
iter  60 value 87.150058
iter  70 value 86.927170
iter  80 value 86.715100
final  value 86.711769 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.104929 
iter  10 value 94.492683
iter  20 value 94.423545
iter  30 value 89.985717
iter  40 value 89.284910
iter  50 value 88.924623
iter  60 value 87.710962
iter  70 value 87.072469
iter  80 value 87.000466
iter  90 value 86.823931
iter 100 value 86.722359
final  value 86.722359 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.982072 
iter  10 value 92.226610
iter  20 value 90.965211
iter  30 value 90.870349
iter  40 value 89.318440
iter  50 value 86.947258
iter  60 value 86.738664
iter  70 value 86.625780
iter  80 value 86.507976
iter  90 value 86.496638
iter 100 value 86.422765
final  value 86.422765 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.910129 
iter  10 value 94.847752
iter  20 value 92.310647
iter  30 value 88.313128
iter  40 value 87.743832
iter  50 value 87.402483
iter  60 value 87.032734
iter  70 value 85.598397
iter  80 value 84.549171
iter  90 value 84.256610
iter 100 value 83.865742
final  value 83.865742 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.686988 
iter  10 value 94.531694
iter  20 value 94.111111
iter  30 value 90.138771
iter  40 value 89.391082
iter  50 value 88.097949
iter  60 value 86.784817
iter  70 value 85.354043
iter  80 value 84.059077
iter  90 value 83.594667
iter 100 value 83.422638
final  value 83.422638 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.217085 
iter  10 value 93.780096
iter  20 value 88.955006
iter  30 value 87.971103
iter  40 value 87.537655
iter  50 value 86.933289
iter  60 value 86.842530
iter  70 value 86.553107
iter  80 value 86.490067
iter  90 value 86.314102
iter 100 value 86.120315
final  value 86.120315 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.561809 
iter  10 value 94.422795
iter  20 value 90.683638
iter  30 value 87.934836
iter  40 value 86.764071
iter  50 value 85.078524
iter  60 value 84.648175
iter  70 value 84.380520
iter  80 value 83.863539
iter  90 value 83.689034
iter 100 value 83.636972
final  value 83.636972 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.477824 
iter  10 value 94.451065
iter  20 value 89.887939
iter  30 value 88.322960
iter  40 value 87.404090
iter  50 value 86.600493
iter  60 value 86.293984
iter  70 value 84.175611
iter  80 value 83.347869
iter  90 value 82.992300
iter 100 value 82.972024
final  value 82.972024 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 135.006854 
iter  10 value 94.998500
iter  20 value 94.348082
iter  30 value 92.238968
iter  40 value 89.757298
iter  50 value 88.769282
iter  60 value 87.318771
iter  70 value 87.043600
iter  80 value 86.416625
iter  90 value 86.022053
iter 100 value 85.644775
final  value 85.644775 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.679382 
iter  10 value 94.561457
iter  20 value 93.284585
iter  30 value 90.202834
iter  40 value 88.601031
iter  50 value 87.953661
iter  60 value 86.258087
iter  70 value 84.573924
iter  80 value 83.994369
iter  90 value 83.592524
iter 100 value 83.480939
final  value 83.480939 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.437031 
iter  10 value 94.322033
iter  20 value 89.886553
iter  30 value 89.311559
iter  40 value 87.227892
iter  50 value 86.352759
iter  60 value 85.476439
iter  70 value 84.936839
iter  80 value 84.374749
iter  90 value 84.150676
iter 100 value 84.030534
final  value 84.030534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.665031 
iter  10 value 94.593489
iter  20 value 94.243450
iter  30 value 94.105276
iter  40 value 94.079778
iter  50 value 88.914439
iter  60 value 85.183660
iter  70 value 84.540801
iter  80 value 84.008400
iter  90 value 83.662087
iter 100 value 83.473339
final  value 83.473339 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 114.990543 
final  value 94.356219 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.793374 
final  value 94.355986 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.999754 
final  value 94.485765 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.351289 
iter  10 value 94.485773
final  value 94.484215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.203815 
final  value 94.485699 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.439163 
final  value 94.489294 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.798043 
iter  10 value 94.120151
iter  20 value 94.114227
iter  30 value 94.068865
iter  40 value 94.067057
final  value 94.067052 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.504956 
iter  10 value 94.099507
iter  20 value 94.071950
iter  30 value 94.069257
iter  40 value 94.067091
iter  40 value 94.067091
final  value 94.067091 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.555643 
iter  10 value 93.491348
iter  20 value 93.215877
iter  30 value 92.657011
iter  40 value 92.295310
iter  50 value 92.291871
iter  60 value 92.276848
iter  70 value 92.276712
iter  80 value 92.121591
iter  90 value 92.076557
iter 100 value 92.075045
final  value 92.075045 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.026849 
iter  10 value 94.288283
iter  20 value 94.162064
iter  30 value 94.142164
iter  40 value 94.127244
iter  50 value 90.223021
iter  60 value 88.810549
final  value 88.810333 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.587529 
iter  10 value 94.436881
iter  20 value 94.430321
final  value 94.430300 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.734843 
iter  10 value 94.362846
iter  20 value 94.354552
iter  30 value 94.048048
iter  40 value 89.460436
iter  50 value 89.458884
iter  60 value 87.975852
iter  70 value 86.772076
iter  80 value 86.696552
iter  90 value 86.696187
iter 100 value 86.690428
final  value 86.690428 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.345408 
iter  10 value 94.362915
iter  20 value 93.997969
iter  30 value 93.944542
iter  40 value 93.941800
iter  50 value 93.940758
iter  60 value 93.937887
final  value 93.937875 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.933709 
iter  10 value 94.362584
iter  20 value 94.355533
final  value 94.355118 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.174650 
iter  10 value 94.362996
iter  20 value 91.881973
iter  30 value 87.039326
iter  40 value 86.837701
iter  50 value 86.803482
iter  60 value 86.767116
iter  70 value 86.330278
iter  80 value 86.244567
final  value 86.244492 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.005392 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.562371 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.399433 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.451032 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.147529 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.855011 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.578381 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.898246 
iter  10 value 92.945360
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.571720 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.193461 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.226717 
iter  10 value 92.313874
iter  20 value 91.581782
iter  30 value 86.332097
iter  40 value 83.100566
iter  50 value 83.093334
final  value 83.093238 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.852504 
iter  10 value 91.461255
final  value 91.460536 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.732041 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.107718 
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.371615 
iter  10 value 87.821578
iter  20 value 84.571279
iter  30 value 84.478827
final  value 84.478730 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.034869 
iter  10 value 93.323540
iter  20 value 89.633195
iter  30 value 88.355668
iter  40 value 84.497476
iter  50 value 83.970795
iter  60 value 83.949793
final  value 83.949000 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.539559 
iter  10 value 93.212706
iter  20 value 93.137516
iter  30 value 88.970480
iter  40 value 86.431783
iter  50 value 85.983120
iter  60 value 81.961910
iter  70 value 80.203173
iter  80 value 80.067119
iter  90 value 79.798103
iter 100 value 79.602062
final  value 79.602062 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.735157 
iter  10 value 93.288286
iter  20 value 93.024911
iter  30 value 92.945361
iter  40 value 91.971887
iter  50 value 87.267932
iter  60 value 86.348772
iter  70 value 82.453404
iter  80 value 80.990543
iter  90 value 80.637352
iter 100 value 80.311208
final  value 80.311208 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.444997 
iter  10 value 93.311058
iter  20 value 92.800587
iter  30 value 87.889101
iter  40 value 86.050761
iter  50 value 85.467030
iter  60 value 85.103381
iter  70 value 84.622031
iter  80 value 81.208018
iter  90 value 80.464089
iter 100 value 79.767364
final  value 79.767364 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.780141 
iter  10 value 93.892846
iter  20 value 89.430249
iter  30 value 88.471139
iter  40 value 84.188561
iter  50 value 81.438598
iter  60 value 80.233414
iter  70 value 80.025575
iter  80 value 79.977039
iter  90 value 79.949577
final  value 79.941797 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.008186 
iter  10 value 93.887060
iter  20 value 93.262024
iter  30 value 90.204696
iter  40 value 82.453493
iter  50 value 81.341016
iter  60 value 80.870929
iter  70 value 80.031731
iter  80 value 79.627348
iter  90 value 79.570725
iter 100 value 79.569787
final  value 79.569787 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.029248 
iter  10 value 94.110883
iter  20 value 86.211846
iter  30 value 84.961707
iter  40 value 84.429314
iter  50 value 83.547413
iter  60 value 82.078655
iter  70 value 79.579868
iter  80 value 78.712168
iter  90 value 78.582402
iter 100 value 78.545201
final  value 78.545201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.801606 
iter  10 value 94.392859
iter  20 value 91.636964
iter  30 value 85.470727
iter  40 value 82.510501
iter  50 value 80.462894
iter  60 value 80.091453
iter  70 value 79.882286
iter  80 value 79.857815
final  value 79.857154 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.919288 
iter  10 value 94.035192
iter  20 value 93.081736
iter  30 value 84.218370
iter  40 value 80.177076
iter  50 value 79.356814
iter  60 value 79.298649
iter  70 value 79.265094
iter  80 value 79.150267
iter  90 value 78.782597
iter 100 value 78.221024
final  value 78.221024 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.315587 
iter  10 value 93.478785
iter  20 value 89.078863
iter  30 value 86.067744
iter  40 value 85.506356
iter  50 value 85.406899
iter  60 value 83.989693
iter  70 value 82.601114
iter  80 value 81.584910
iter  90 value 79.809189
iter 100 value 79.147230
final  value 79.147230 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.229681 
iter  10 value 94.194547
iter  20 value 87.385680
iter  30 value 85.117840
iter  40 value 83.385881
iter  50 value 82.692093
iter  60 value 81.011662
iter  70 value 80.536400
iter  80 value 80.506370
iter  90 value 80.473905
iter 100 value 80.045513
final  value 80.045513 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.353582 
iter  10 value 93.071547
iter  20 value 87.070226
iter  30 value 85.926312
iter  40 value 84.368310
iter  50 value 83.245780
iter  60 value 82.515141
iter  70 value 80.529889
iter  80 value 80.176267
iter  90 value 79.749810
iter 100 value 79.684203
final  value 79.684203 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.182612 
iter  10 value 94.017099
iter  20 value 90.710675
iter  30 value 86.048037
iter  40 value 85.250407
iter  50 value 84.950106
iter  60 value 80.771611
iter  70 value 79.604339
iter  80 value 78.851896
iter  90 value 78.566508
iter 100 value 78.126049
final  value 78.126049 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.794095 
iter  10 value 85.635423
iter  20 value 82.760925
iter  30 value 80.580731
iter  40 value 79.196649
iter  50 value 78.773546
iter  60 value 78.645013
iter  70 value 78.473950
iter  80 value 78.315146
iter  90 value 78.069148
iter 100 value 78.006632
final  value 78.006632 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.773654 
iter  10 value 94.176937
iter  20 value 93.422863
iter  30 value 86.810489
iter  40 value 85.213769
iter  50 value 84.394712
iter  60 value 84.073040
iter  70 value 81.911351
iter  80 value 80.976810
iter  90 value 80.789383
iter 100 value 80.105358
final  value 80.105358 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.879981 
iter  10 value 94.054514
iter  20 value 94.008102
iter  30 value 92.955059
iter  40 value 92.951194
iter  50 value 92.948320
final  value 92.948314 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.478741 
final  value 94.054472 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.993990 
final  value 94.054675 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.015965 
iter  10 value 94.054539
iter  20 value 94.052931
iter  30 value 93.452842
iter  40 value 84.573803
iter  40 value 84.573803
iter  40 value 84.573803
final  value 84.573803 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.511394 
iter  10 value 94.054499
iter  20 value 94.052952
iter  30 value 87.485664
iter  40 value 81.210471
iter  50 value 81.205629
iter  60 value 80.422800
iter  70 value 80.307731
iter  80 value 79.720688
iter  90 value 79.257934
iter 100 value 79.255353
final  value 79.255353 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.498827 
iter  10 value 94.057793
iter  20 value 93.517641
final  value 92.946342 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.765383 
iter  10 value 92.635507
iter  20 value 85.251853
iter  30 value 85.191175
iter  40 value 85.071287
iter  50 value 85.063985
iter  60 value 84.296043
iter  70 value 84.289377
final  value 84.288960 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.643251 
iter  10 value 94.058162
iter  20 value 94.053477
final  value 94.052957 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.371912 
iter  10 value 94.054434
iter  20 value 93.119759
iter  30 value 92.959910
iter  40 value 92.950004
iter  50 value 92.937037
iter  60 value 92.648316
iter  70 value 92.646839
final  value 92.646482 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.076665 
iter  10 value 92.950831
iter  20 value 92.946622
iter  30 value 92.707487
iter  40 value 92.645423
iter  50 value 92.645317
final  value 92.645303 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.407981 
iter  10 value 92.954595
iter  20 value 92.953614
iter  30 value 91.323925
iter  40 value 88.302397
iter  50 value 82.213788
iter  60 value 80.773593
iter  70 value 78.108217
iter  80 value 77.734368
iter  90 value 76.992332
iter 100 value 76.968632
final  value 76.968632 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.693813 
iter  10 value 92.954803
iter  20 value 92.952514
iter  30 value 89.341903
iter  40 value 84.133333
iter  50 value 84.001827
iter  60 value 83.996664
iter  70 value 83.995547
iter  80 value 83.994665
iter  90 value 83.993993
final  value 83.993977 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.088307 
iter  10 value 94.060351
iter  20 value 92.965761
final  value 92.946425 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.058441 
iter  10 value 91.774946
iter  20 value 91.757824
iter  30 value 91.709876
iter  40 value 91.580058
iter  50 value 91.578398
iter  60 value 91.547184
iter  70 value 91.341925
iter  80 value 91.337902
iter  90 value 91.333332
iter 100 value 90.090161
final  value 90.090161 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.926184 
iter  10 value 94.060772
iter  20 value 94.053662
iter  30 value 93.572354
iter  40 value 88.155636
iter  50 value 83.072893
iter  60 value 82.694629
iter  70 value 82.562034
iter  80 value 82.493249
iter  90 value 82.484631
iter 100 value 81.718419
final  value 81.718419 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.713385 
iter  10 value 88.064661
iter  20 value 85.102682
iter  30 value 85.081684
final  value 85.081621 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.761369 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.639128 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.785051 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.172697 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.656707 
iter  10 value 93.180699
iter  20 value 93.006250
final  value 92.933333 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.512717 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.964315 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.446913 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.404150 
final  value 93.830514 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.368485 
iter  10 value 92.070705
iter  20 value 91.059197
iter  30 value 91.055484
final  value 91.055424 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.137499 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.772353 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.741443 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.279454 
iter  10 value 92.935799
final  value 92.933333 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.066685 
iter  10 value 93.854413
iter  20 value 86.007248
iter  30 value 85.611391
iter  40 value 82.403617
iter  50 value 81.343322
iter  60 value 79.102731
iter  70 value 78.733350
iter  80 value 78.624152
final  value 78.573157 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.041746 
iter  10 value 93.970239
iter  20 value 93.246886
iter  30 value 87.995000
iter  40 value 84.585866
iter  50 value 80.553939
iter  60 value 79.135688
iter  70 value 78.678695
iter  80 value 78.499779
iter  90 value 78.464226
final  value 78.462419 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.957085 
iter  10 value 93.585927
iter  20 value 86.248372
iter  30 value 83.006982
iter  40 value 81.532118
iter  50 value 81.366897
iter  60 value 79.468222
iter  70 value 78.903460
iter  80 value 78.695915
iter  90 value 78.573158
final  value 78.573156 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.626908 
iter  10 value 95.138519
iter  20 value 94.056511
iter  30 value 94.054972
iter  40 value 87.621441
iter  50 value 86.057692
iter  60 value 83.434764
iter  70 value 83.258560
iter  80 value 83.155424
iter  90 value 83.039599
iter 100 value 83.022548
final  value 83.022548 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.785036 
iter  10 value 94.181473
iter  20 value 94.005202
iter  30 value 93.155151
iter  40 value 93.134720
iter  50 value 93.122351
final  value 93.121065 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.167545 
iter  10 value 94.079533
iter  20 value 88.358690
iter  30 value 85.049115
iter  40 value 83.709311
iter  50 value 81.326910
iter  60 value 80.678657
iter  70 value 80.461943
iter  80 value 79.099117
iter  90 value 78.765550
iter 100 value 78.492624
final  value 78.492624 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.298357 
iter  10 value 97.741561
iter  20 value 93.943061
iter  30 value 84.154400
iter  40 value 83.075456
iter  50 value 82.483089
iter  60 value 80.323498
iter  70 value 78.767789
iter  80 value 78.231814
iter  90 value 77.129281
iter 100 value 76.903538
final  value 76.903538 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.575798 
iter  10 value 93.453524
iter  20 value 88.961926
iter  30 value 85.239539
iter  40 value 83.808880
iter  50 value 83.206910
iter  60 value 83.142082
iter  70 value 79.101196
iter  80 value 78.062980
iter  90 value 77.377179
iter 100 value 77.192409
final  value 77.192409 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.534652 
iter  10 value 92.505345
iter  20 value 85.653001
iter  30 value 85.338679
iter  40 value 85.101759
iter  50 value 81.376026
iter  60 value 78.577517
iter  70 value 78.239484
iter  80 value 77.888240
iter  90 value 77.846811
iter 100 value 77.805972
final  value 77.805972 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.789777 
iter  10 value 93.890779
iter  20 value 87.176024
iter  30 value 84.317150
iter  40 value 82.584777
iter  50 value 80.781312
iter  60 value 78.637031
iter  70 value 77.799693
iter  80 value 77.472954
iter  90 value 77.444745
iter 100 value 77.443851
final  value 77.443851 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.762591 
iter  10 value 93.825517
iter  20 value 82.944790
iter  30 value 80.419752
iter  40 value 78.881486
iter  50 value 77.795401
iter  60 value 77.551040
iter  70 value 77.444739
iter  80 value 77.404611
iter  90 value 77.226288
iter 100 value 76.970231
final  value 76.970231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.823519 
iter  10 value 94.019008
iter  20 value 90.076909
iter  30 value 86.526146
iter  40 value 82.208914
iter  50 value 79.411482
iter  60 value 78.082765
iter  70 value 77.762796
iter  80 value 77.556333
iter  90 value 77.422955
iter 100 value 77.229255
final  value 77.229255 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 142.099873 
iter  10 value 97.053698
iter  20 value 95.221134
iter  30 value 92.262355
iter  40 value 88.101429
iter  50 value 87.397485
iter  60 value 84.606265
iter  70 value 82.293503
iter  80 value 80.514737
iter  90 value 79.477686
iter 100 value 77.963344
final  value 77.963344 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.051916 
iter  10 value 94.165260
iter  20 value 93.786983
iter  30 value 87.666434
iter  40 value 81.493807
iter  50 value 79.717747
iter  60 value 79.292799
iter  70 value 78.392389
iter  80 value 77.876900
iter  90 value 77.404321
iter 100 value 77.192429
final  value 77.192429 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.893950 
iter  10 value 94.062477
iter  20 value 93.468782
iter  30 value 83.872873
iter  40 value 83.159803
iter  50 value 79.914909
iter  60 value 77.694918
iter  70 value 77.442938
iter  80 value 77.204136
iter  90 value 76.944354
iter 100 value 76.920908
final  value 76.920908 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.053372 
final  value 94.054681 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.636298 
iter  10 value 94.054529
final  value 94.053097 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.832523 
final  value 94.054616 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.254587 
final  value 94.054357 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.669731 
final  value 94.054567 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.345047 
iter  10 value 93.841297
iter  20 value 93.837767
iter  30 value 93.226408
iter  40 value 89.771453
iter  50 value 88.450479
iter  60 value 88.118510
iter  70 value 88.066138
iter  80 value 88.033538
iter  90 value 88.027111
iter  90 value 88.027111
iter  90 value 88.027111
final  value 88.027111 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.079400 
iter  10 value 92.744860
iter  20 value 92.740150
iter  30 value 92.499839
iter  40 value 92.496047
iter  50 value 92.494329
iter  60 value 92.494187
iter  70 value 92.481887
iter  80 value 92.481281
final  value 92.481277 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.347727 
iter  10 value 94.058163
iter  20 value 94.053080
iter  30 value 93.993152
iter  40 value 93.458467
iter  50 value 93.456422
iter  60 value 93.455872
iter  70 value 84.290647
iter  80 value 83.523386
iter  90 value 82.822413
iter 100 value 82.800704
final  value 82.800704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.714077 
iter  10 value 94.056122
iter  20 value 93.081720
iter  30 value 92.422466
iter  40 value 88.095347
iter  50 value 83.198213
iter  60 value 83.168626
iter  70 value 80.823968
iter  80 value 80.810120
iter  90 value 80.807652
iter 100 value 80.740461
final  value 80.740461 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.781770 
iter  10 value 94.058311
iter  20 value 94.053239
iter  30 value 93.134490
final  value 87.248352 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.995747 
iter  10 value 93.844596
iter  20 value 93.307071
iter  30 value 84.497717
iter  40 value 83.528400
iter  50 value 81.230669
iter  60 value 81.156283
iter  70 value 80.860794
iter  80 value 79.496726
iter  90 value 79.451363
iter 100 value 79.370308
final  value 79.370308 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.326332 
iter  10 value 94.059251
iter  20 value 93.614139
iter  30 value 89.936236
iter  40 value 85.455499
iter  50 value 85.273321
iter  60 value 85.272986
iter  70 value 85.272900
final  value 85.272895 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.166665 
iter  10 value 93.844733
iter  20 value 93.838031
final  value 93.837460 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.551625 
iter  10 value 84.314371
iter  20 value 83.272358
iter  30 value 80.153318
iter  40 value 79.909932
iter  50 value 79.843620
iter  60 value 79.023944
iter  70 value 78.971084
iter  80 value 78.965287
iter  90 value 78.960214
iter  90 value 78.960213
final  value 78.960213 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.662527 
iter  10 value 93.464859
iter  20 value 93.432795
iter  30 value 92.948722
iter  40 value 92.921155
final  value 92.921126 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.212076 
iter  10 value 84.974681
final  value 84.974324 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.722357 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.612067 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.637317 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.794143 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.014978 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.811361 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.936263 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 123.269662 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.679825 
iter  10 value 91.252086
iter  20 value 90.320553
final  value 90.320332 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.762993 
iter  10 value 88.906174
iter  20 value 84.484151
final  value 84.480002 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.675418 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.417926 
final  value 94.443182 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.814355 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 127.494501 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.886374 
iter  10 value 94.316416
iter  20 value 85.628823
iter  30 value 84.602479
iter  40 value 81.446912
iter  50 value 81.399966
iter  60 value 81.396342
iter  70 value 81.379605
iter  80 value 81.272293
final  value 81.260365 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.142060 
iter  10 value 94.437588
iter  20 value 91.253866
iter  30 value 87.184126
iter  40 value 84.290645
iter  50 value 83.021137
iter  60 value 81.704097
iter  70 value 81.004810
iter  80 value 80.975514
final  value 80.975443 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.505741 
iter  10 value 93.110542
iter  20 value 91.359936
iter  30 value 82.746912
iter  40 value 81.894577
iter  50 value 81.658202
iter  60 value 81.549813
iter  70 value 81.426715
iter  80 value 80.732188
iter  90 value 80.442197
final  value 80.422886 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.826695 
iter  10 value 94.452979
iter  20 value 83.307942
iter  30 value 82.223564
iter  40 value 82.118525
iter  50 value 81.391784
iter  60 value 81.368329
final  value 81.368327 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.576861 
iter  10 value 92.302063
iter  20 value 82.854981
iter  30 value 82.027475
iter  40 value 81.934814
iter  50 value 81.414814
iter  60 value 81.368327
iter  60 value 81.368327
iter  60 value 81.368327
final  value 81.368327 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.720830 
iter  10 value 87.531419
iter  20 value 83.275610
iter  30 value 81.853174
iter  40 value 80.120525
iter  50 value 79.614041
iter  60 value 79.090002
iter  70 value 79.015779
iter  80 value 78.964129
iter  90 value 78.947201
iter 100 value 78.932507
final  value 78.932507 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.327263 
iter  10 value 94.928570
iter  20 value 86.880757
iter  30 value 85.883436
iter  40 value 83.258651
iter  50 value 82.755237
iter  60 value 82.214237
iter  70 value 80.918120
iter  80 value 80.394000
final  value 80.389215 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.294648 
iter  10 value 94.426378
iter  20 value 90.326762
iter  30 value 89.897593
iter  40 value 83.602490
iter  50 value 82.232701
iter  60 value 81.390025
iter  70 value 81.145150
iter  80 value 81.017227
iter  90 value 80.337545
iter 100 value 79.017476
final  value 79.017476 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.276894 
iter  10 value 94.130035
iter  20 value 88.832462
iter  30 value 85.772969
iter  40 value 84.962443
iter  50 value 83.606397
iter  60 value 82.287236
iter  70 value 81.979888
iter  80 value 81.284801
iter  90 value 81.086359
iter 100 value 81.008027
final  value 81.008027 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.500783 
iter  10 value 95.305894
iter  20 value 91.984038
iter  30 value 83.686423
iter  40 value 80.846114
iter  50 value 80.081356
iter  60 value 79.701015
iter  70 value 79.304135
iter  80 value 79.266217
iter  90 value 79.204971
iter 100 value 79.173839
final  value 79.173839 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.780791 
iter  10 value 97.640305
iter  20 value 94.594809
iter  30 value 88.225651
iter  40 value 83.012165
iter  50 value 82.393258
iter  60 value 81.867989
iter  70 value 81.287780
iter  80 value 81.267438
iter  90 value 81.095953
iter 100 value 80.856176
final  value 80.856176 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.684402 
iter  10 value 93.794213
iter  20 value 88.489210
iter  30 value 87.630782
iter  40 value 82.138964
iter  50 value 81.320168
iter  60 value 80.593213
iter  70 value 80.188998
iter  80 value 80.147665
iter  90 value 79.824687
iter 100 value 79.524733
final  value 79.524733 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.534439 
iter  10 value 94.948527
iter  20 value 94.391419
iter  30 value 90.749991
iter  40 value 87.500645
iter  50 value 84.257948
iter  60 value 82.252441
iter  70 value 81.438338
iter  80 value 80.843075
iter  90 value 79.970023
iter 100 value 79.260078
final  value 79.260078 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.901379 
iter  10 value 94.614137
iter  20 value 94.393833
iter  30 value 87.354152
iter  40 value 86.464121
iter  50 value 83.780827
iter  60 value 81.188506
iter  70 value 80.687046
iter  80 value 80.201834
iter  90 value 80.017548
iter 100 value 79.368688
final  value 79.368688 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.882493 
iter  10 value 94.485401
iter  20 value 87.877143
iter  30 value 82.465521
iter  40 value 82.087371
iter  50 value 81.129735
iter  60 value 81.070975
iter  70 value 80.767816
iter  80 value 80.303756
iter  90 value 80.154831
iter 100 value 80.110388
final  value 80.110388 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.042716 
final  value 94.485685 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.404970 
final  value 94.485996 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.857224 
iter  10 value 94.485861
iter  20 value 94.464679
iter  30 value 93.696312
iter  40 value 88.382613
iter  50 value 88.347134
iter  60 value 88.282914
iter  70 value 88.156196
iter  80 value 87.926379
iter  90 value 87.261357
iter 100 value 87.258154
final  value 87.258154 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 122.663444 
iter  10 value 94.485964
iter  20 value 94.484255
iter  30 value 91.435519
iter  40 value 91.394572
iter  50 value 91.381687
iter  60 value 91.375097
iter  70 value 91.373325
iter  80 value 91.372982
final  value 91.372886 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.267415 
iter  10 value 94.468905
iter  10 value 94.468904
iter  10 value 94.468904
final  value 94.468904 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.561418 
iter  10 value 94.488670
iter  20 value 87.583980
iter  30 value 86.333761
iter  40 value 85.934233
iter  50 value 85.433527
iter  60 value 84.977481
iter  70 value 84.975727
iter  80 value 84.292906
final  value 84.244796 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.914986 
iter  10 value 94.489251
iter  20 value 94.483861
iter  30 value 87.070734
iter  40 value 85.861683
iter  50 value 85.841682
iter  60 value 84.897914
iter  70 value 84.405063
iter  80 value 84.402503
iter  90 value 84.395691
iter 100 value 84.336608
final  value 84.336608 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.064268 
iter  10 value 90.979578
iter  20 value 84.743498
iter  30 value 84.509077
iter  40 value 84.498423
iter  50 value 83.462556
iter  60 value 83.364538
iter  70 value 81.856913
iter  80 value 81.784118
iter  90 value 81.779219
iter 100 value 81.776836
final  value 81.776836 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.053751 
iter  10 value 94.488899
iter  20 value 94.484120
iter  30 value 84.390970
iter  40 value 80.767039
iter  50 value 80.690623
iter  60 value 79.364697
iter  70 value 78.623566
iter  80 value 78.146641
iter  90 value 78.098446
final  value 78.094628 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.358779 
iter  10 value 94.433932
iter  20 value 94.429651
iter  30 value 94.275918
iter  30 value 94.275918
iter  30 value 94.275918
final  value 94.275918 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.073148 
iter  10 value 93.313369
iter  20 value 93.306311
iter  30 value 84.343096
iter  40 value 84.116072
iter  50 value 84.110125
iter  60 value 84.072761
iter  70 value 84.069220
iter  80 value 83.221401
iter  90 value 81.953707
iter 100 value 81.265707
final  value 81.265707 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.891614 
iter  10 value 94.492297
iter  20 value 94.428738
iter  30 value 92.634946
iter  40 value 81.005735
iter  50 value 80.762653
iter  60 value 80.617452
iter  70 value 80.617366
iter  80 value 80.616879
final  value 80.616831 
converged
Fitting Repeat 3 

# weights:  507
initial  value 130.032316 
iter  10 value 94.492804
iter  20 value 94.222503
iter  30 value 92.921468
iter  40 value 91.133105
iter  50 value 91.132025
iter  60 value 91.131647
iter  70 value 90.879048
iter  80 value 90.712883
final  value 90.712869 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.323581 
iter  10 value 88.387920
iter  20 value 83.476322
iter  30 value 83.321971
iter  40 value 83.320259
final  value 83.320052 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.040132 
iter  10 value 94.492818
iter  20 value 94.485237
iter  30 value 86.370403
iter  40 value 80.946012
iter  50 value 79.415026
iter  60 value 78.146457
iter  70 value 78.037427
iter  80 value 77.895310
iter  90 value 77.842207
iter 100 value 77.840677
final  value 77.840677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 168.953184 
iter  10 value 117.895410
iter  20 value 117.890835
iter  30 value 116.173616
iter  40 value 107.165742
iter  50 value 107.015008
iter  60 value 105.373166
iter  70 value 105.066832
iter  80 value 105.060535
iter  90 value 105.050246
iter 100 value 105.039405
final  value 105.039405 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.203039 
iter  10 value 117.895247
iter  20 value 117.882424
iter  30 value 113.840094
iter  40 value 107.041582
iter  50 value 107.028187
iter  60 value 105.393086
iter  70 value 105.054450
iter  80 value 105.052254
iter  90 value 104.772361
iter 100 value 104.567746
final  value 104.567746 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.341314 
iter  10 value 117.763449
iter  20 value 117.760470
iter  20 value 117.760469
iter  20 value 117.760469
final  value 117.760469 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.066381 
iter  10 value 117.895032
iter  20 value 117.154190
iter  30 value 115.923840
iter  40 value 112.776375
iter  50 value 106.837076
iter  60 value 105.129962
iter  70 value 105.129887
final  value 105.129465 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.939734 
iter  10 value 117.892293
iter  20 value 112.589370
final  value 112.464600 
converged
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 -- Sun Jul 21 22:26:50 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 
 17.356   1.203  25.112