##############################################################################
##############################################################################
###
### 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      51.468  1.800  61.499
corr_plot     51.405  1.709  60.029
var_imp       50.818  1.721  61.452
pred_ensembel 24.631  0.471  22.945
calculateTC    4.744  0.460   5.573
enrichfindP    0.914  0.081  15.509
getFASTA       0.122  0.017  10.414
* 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 99.663387 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.290866 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.836542 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.056817 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.286139 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.509824 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.917125 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.859597 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.976635 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.535888 
iter  10 value 94.155594
iter  20 value 94.026571
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.539777 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.522054 
iter  10 value 94.169184
final  value 94.165117 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.900787 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.640024 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.414666 
iter  10 value 93.974645
final  value 93.974641 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.361870 
iter  10 value 94.425129
iter  20 value 94.127413
iter  30 value 94.077531
iter  40 value 90.119592
iter  50 value 89.634414
iter  60 value 89.436666
iter  70 value 87.573825
iter  80 value 85.542393
iter  90 value 85.342168
iter 100 value 85.226697
final  value 85.226697 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 110.180364 
iter  10 value 94.477927
iter  20 value 94.164411
iter  30 value 94.076891
iter  40 value 93.063702
iter  50 value 90.832043
iter  60 value 85.443876
iter  70 value 83.952046
iter  80 value 83.888426
iter  90 value 83.859743
iter 100 value 83.684447
final  value 83.684447 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.450374 
iter  10 value 94.319528
iter  20 value 94.128227
iter  30 value 94.127975
iter  40 value 86.657705
iter  50 value 83.398501
iter  60 value 83.176142
iter  70 value 83.048063
iter  80 value 82.782399
iter  90 value 82.098854
iter 100 value 80.720856
final  value 80.720856 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 120.892336 
iter  10 value 94.444211
iter  20 value 86.393722
iter  30 value 86.138618
iter  40 value 85.336812
iter  50 value 83.636014
iter  60 value 83.254927
iter  70 value 83.088410
iter  80 value 83.072024
iter  90 value 83.063224
final  value 83.062847 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.622442 
iter  10 value 88.020616
iter  20 value 83.400371
iter  30 value 83.007583
iter  40 value 82.740712
iter  50 value 82.672380
final  value 82.672365 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.921585 
iter  10 value 95.678643
iter  20 value 94.267267
iter  30 value 93.852246
iter  40 value 93.364653
iter  50 value 92.674723
iter  60 value 88.704900
iter  70 value 85.179953
iter  80 value 82.917163
iter  90 value 81.402489
iter 100 value 79.914601
final  value 79.914601 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.229504 
iter  10 value 94.735329
iter  20 value 94.428402
iter  30 value 89.056287
iter  40 value 86.968796
iter  50 value 84.378092
iter  60 value 82.735313
iter  70 value 82.582128
iter  80 value 82.478883
iter  90 value 82.462248
iter 100 value 82.384913
final  value 82.384913 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.456341 
iter  10 value 94.429642
iter  20 value 94.131042
iter  30 value 94.011365
iter  40 value 92.367896
iter  50 value 91.725672
iter  60 value 85.829132
iter  70 value 84.664014
iter  80 value 82.567941
iter  90 value 82.036914
iter 100 value 81.770939
final  value 81.770939 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.435325 
iter  10 value 93.116617
iter  20 value 85.574179
iter  30 value 84.919615
iter  40 value 84.857825
iter  50 value 84.417964
iter  60 value 82.090279
iter  70 value 80.024026
iter  80 value 79.097308
iter  90 value 79.012538
iter 100 value 78.864674
final  value 78.864674 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.915376 
iter  10 value 94.489282
iter  20 value 94.086427
iter  30 value 85.108521
iter  40 value 82.991461
iter  50 value 81.937538
iter  60 value 81.548015
iter  70 value 80.975661
iter  80 value 80.568479
iter  90 value 80.325841
iter 100 value 80.178829
final  value 80.178829 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.833303 
iter  10 value 94.946866
iter  20 value 90.090587
iter  30 value 83.337959
iter  40 value 80.649592
iter  50 value 80.373968
iter  60 value 80.103065
iter  70 value 80.030860
iter  80 value 79.634356
iter  90 value 79.280914
iter 100 value 79.035430
final  value 79.035430 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.329113 
iter  10 value 94.191074
iter  20 value 92.652657
iter  30 value 85.486039
iter  40 value 84.487899
iter  50 value 83.634427
iter  60 value 80.788696
iter  70 value 80.559913
iter  80 value 80.209378
iter  90 value 79.701741
iter 100 value 79.540163
final  value 79.540163 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.183002 
iter  10 value 87.547296
iter  20 value 85.525934
iter  30 value 83.600126
iter  40 value 82.677294
iter  50 value 82.519605
iter  60 value 82.329886
iter  70 value 82.240019
iter  80 value 82.157871
iter  90 value 81.790021
iter 100 value 80.702133
final  value 80.702133 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.302327 
iter  10 value 94.727860
iter  20 value 94.161875
iter  30 value 89.570137
iter  40 value 87.692297
iter  50 value 84.323363
iter  60 value 81.133973
iter  70 value 79.996986
iter  80 value 79.555144
iter  90 value 79.419499
iter 100 value 79.126544
final  value 79.126544 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.189019 
iter  10 value 94.066949
iter  20 value 92.167098
iter  30 value 90.970448
iter  40 value 89.524913
iter  50 value 82.675641
iter  60 value 82.216404
iter  70 value 82.025301
iter  80 value 81.690021
iter  90 value 81.166767
iter 100 value 80.570587
final  value 80.570587 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.959062 
final  value 94.485735 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.323998 
iter  10 value 94.485966
final  value 94.484331 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.749610 
final  value 94.485923 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.594059 
iter  10 value 94.485803
iter  20 value 94.461984
iter  30 value 84.533533
iter  40 value 84.402700
iter  50 value 84.353768
iter  60 value 84.082165
iter  70 value 82.400439
final  value 82.256264 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.749874 
final  value 94.485943 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.871893 
iter  10 value 94.489315
iter  20 value 94.484423
iter  30 value 94.068815
final  value 93.974941 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.325803 
iter  10 value 93.960546
iter  20 value 93.882245
iter  30 value 93.708544
iter  40 value 93.676061
final  value 93.675985 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.696481 
iter  10 value 94.170075
iter  20 value 94.088476
final  value 93.974982 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.066523 
iter  10 value 94.488464
iter  20 value 94.484322
iter  30 value 94.186131
final  value 94.165232 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.910667 
iter  10 value 94.488588
iter  20 value 93.418566
iter  30 value 91.740551
iter  40 value 80.535572
iter  50 value 80.386433
iter  60 value 80.384191
iter  70 value 80.330075
iter  80 value 80.327466
final  value 80.326165 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.354663 
iter  10 value 94.456317
iter  20 value 94.448233
iter  20 value 94.448233
iter  20 value 94.448232
final  value 94.448232 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.284491 
iter  10 value 93.417096
iter  20 value 90.299301
iter  30 value 90.280684
iter  40 value 90.125769
iter  50 value 89.388613
iter  60 value 89.372325
iter  70 value 89.371220
final  value 89.370854 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.903053 
iter  10 value 92.742687
iter  20 value 92.723120
iter  30 value 92.715875
iter  40 value 92.694428
iter  50 value 92.291476
iter  60 value 85.382162
final  value 84.793822 
converged
Fitting Repeat 4 

# weights:  507
initial  value 142.917281 
iter  10 value 94.036231
iter  20 value 94.027961
iter  30 value 93.157986
iter  40 value 89.700503
iter  50 value 88.675878
iter  60 value 87.975649
iter  70 value 84.444167
iter  80 value 84.257006
iter  90 value 84.250549
iter 100 value 84.249995
final  value 84.249995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.696180 
iter  10 value 94.034701
iter  20 value 94.028172
iter  30 value 93.975508
final  value 93.975117 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.600718 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.093470 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.233896 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.273291 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.130840 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.762705 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.139078 
iter  10 value 94.038342
iter  20 value 93.465590
iter  30 value 92.363276
iter  40 value 92.358142
final  value 92.358089 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.661667 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.142882 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.607473 
iter  10 value 94.051407
iter  20 value 94.034652
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.167587 
iter  10 value 90.947443
iter  20 value 90.658907
final  value 90.658894 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.364889 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.005196 
iter  10 value 88.703015
iter  20 value 85.112621
iter  30 value 84.991839
final  value 84.948891 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.652123 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.694905 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.964968 
iter  10 value 93.883401
iter  20 value 86.827606
iter  30 value 83.139628
iter  40 value 81.434236
iter  50 value 81.093730
iter  60 value 80.624864
iter  70 value 79.794420
iter  80 value 79.575354
iter  90 value 79.556449
final  value 79.556436 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.897321 
iter  10 value 94.080054
iter  20 value 90.886891
iter  30 value 85.800720
iter  40 value 84.200194
iter  50 value 84.001400
iter  60 value 83.271123
iter  70 value 83.234767
iter  80 value 83.159773
iter  90 value 82.517217
iter 100 value 81.371494
final  value 81.371494 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.254861 
iter  10 value 94.071654
iter  20 value 94.054866
iter  30 value 88.309764
iter  40 value 85.101449
iter  50 value 84.692086
iter  60 value 83.627073
iter  70 value 82.716066
iter  80 value 82.540879
iter  90 value 82.458631
iter 100 value 82.402783
final  value 82.402783 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.743822 
iter  10 value 92.037686
iter  20 value 84.074021
iter  30 value 83.911893
iter  40 value 83.290833
iter  50 value 82.588918
iter  60 value 82.043326
iter  70 value 81.975982
iter  80 value 81.969818
final  value 81.969343 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.231193 
iter  10 value 94.056478
iter  20 value 88.099139
iter  30 value 83.845065
iter  40 value 82.686736
iter  50 value 82.310828
iter  60 value 81.923487
iter  70 value 81.272974
iter  80 value 80.976633
final  value 80.973965 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.235741 
iter  10 value 93.512802
iter  20 value 82.015213
iter  30 value 81.178654
iter  40 value 79.270904
iter  50 value 78.535459
iter  60 value 78.409477
iter  70 value 78.335516
iter  80 value 78.289165
iter  90 value 78.286330
iter 100 value 78.280036
final  value 78.280036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.913847 
iter  10 value 95.253751
iter  20 value 86.008900
iter  30 value 85.514321
iter  40 value 84.991963
iter  50 value 83.455228
iter  60 value 83.018469
iter  70 value 81.580468
iter  80 value 81.305290
iter  90 value 80.621287
iter 100 value 79.948563
final  value 79.948563 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.914093 
iter  10 value 94.066784
iter  20 value 93.614738
iter  30 value 83.486348
iter  40 value 82.565806
iter  50 value 81.243518
iter  60 value 80.207500
iter  70 value 79.205594
iter  80 value 78.845355
iter  90 value 78.255095
iter 100 value 78.126475
final  value 78.126475 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.059284 
iter  10 value 94.711070
iter  20 value 94.067400
iter  30 value 93.818485
iter  40 value 93.629281
iter  50 value 88.501274
iter  60 value 86.486315
iter  70 value 82.094467
iter  80 value 79.719093
iter  90 value 79.319263
iter 100 value 78.829869
final  value 78.829869 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.231420 
iter  10 value 94.067929
iter  20 value 88.373842
iter  30 value 84.618769
iter  40 value 84.075784
iter  50 value 83.402148
iter  60 value 82.517002
iter  70 value 82.134547
iter  80 value 81.977231
iter  90 value 81.849814
iter 100 value 81.581815
final  value 81.581815 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.439006 
iter  10 value 94.071296
iter  20 value 84.138670
iter  30 value 82.955229
iter  40 value 82.564607
iter  50 value 81.089437
iter  60 value 80.326050
iter  70 value 79.169691
iter  80 value 78.658257
iter  90 value 78.405248
iter 100 value 78.346212
final  value 78.346212 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.229075 
iter  10 value 94.137150
iter  20 value 91.472034
iter  30 value 83.809927
iter  40 value 80.906107
iter  50 value 79.367160
iter  60 value 78.622778
iter  70 value 78.142805
iter  80 value 77.997675
iter  90 value 77.955851
iter 100 value 77.901130
final  value 77.901130 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.815881 
iter  10 value 96.570440
iter  20 value 91.528838
iter  30 value 86.690022
iter  40 value 84.740198
iter  50 value 81.654624
iter  60 value 79.016368
iter  70 value 78.665546
iter  80 value 78.329557
iter  90 value 78.207945
iter 100 value 78.174139
final  value 78.174139 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.629727 
iter  10 value 90.960344
iter  20 value 83.197596
iter  30 value 81.620539
iter  40 value 79.449391
iter  50 value 79.200350
iter  60 value 78.851328
iter  70 value 78.397652
iter  80 value 78.335711
iter  90 value 78.321530
iter 100 value 78.249765
final  value 78.249765 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.200341 
iter  10 value 94.227774
iter  20 value 87.163884
iter  30 value 84.817888
iter  40 value 83.907313
iter  50 value 83.152548
iter  60 value 82.385710
iter  70 value 81.000379
iter  80 value 80.231660
iter  90 value 79.179668
iter 100 value 78.506599
final  value 78.506599 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.459720 
iter  10 value 94.054566
iter  20 value 94.052908
iter  30 value 83.958601
iter  40 value 82.418628
iter  50 value 82.392071
final  value 82.392049 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.335939 
final  value 94.054676 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.545507 
iter  10 value 94.054679
iter  20 value 94.050135
iter  30 value 82.853010
iter  40 value 82.390307
iter  50 value 82.169576
iter  60 value 81.919409
final  value 81.842896 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.282588 
iter  10 value 94.054637
iter  20 value 94.052610
iter  30 value 89.666798
iter  40 value 89.018161
iter  40 value 89.018161
iter  40 value 89.018161
final  value 89.018161 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.472453 
iter  10 value 91.845466
iter  20 value 91.255321
iter  30 value 91.181281
iter  40 value 91.181106
iter  50 value 91.179732
iter  60 value 91.168487
iter  70 value 91.166787
iter  80 value 91.165754
iter  90 value 87.196486
iter 100 value 83.016182
final  value 83.016182 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 97.191364 
iter  10 value 93.609809
iter  20 value 93.604346
iter  30 value 91.384008
iter  40 value 86.439295
iter  50 value 86.211876
iter  60 value 86.198974
iter  70 value 86.197471
iter  80 value 86.120694
iter  90 value 79.424938
iter 100 value 79.140814
final  value 79.140814 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.452466 
iter  10 value 94.058281
iter  20 value 94.050291
iter  30 value 92.094731
iter  40 value 90.954088
iter  50 value 90.774685
iter  60 value 90.769378
final  value 90.769274 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.997212 
iter  10 value 94.057522
iter  20 value 94.048135
iter  30 value 83.204007
iter  40 value 82.506246
iter  50 value 82.348901
iter  60 value 77.898534
iter  70 value 77.125093
iter  80 value 77.117557
iter  90 value 77.070676
iter 100 value 76.951635
final  value 76.951635 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.210373 
iter  10 value 87.331220
iter  20 value 86.626642
iter  30 value 86.620140
iter  40 value 86.374836
iter  50 value 83.566955
iter  60 value 83.566291
iter  70 value 83.519337
iter  80 value 83.514028
final  value 83.513995 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.429111 
iter  10 value 94.058124
iter  20 value 93.972532
iter  30 value 92.008416
iter  40 value 91.139270
iter  50 value 91.138626
iter  60 value 91.137998
iter  70 value 90.904202
iter  80 value 90.798670
iter  90 value 90.653655
final  value 90.652807 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.387166 
iter  10 value 93.756351
iter  20 value 88.413713
iter  30 value 88.391447
iter  40 value 88.379986
iter  50 value 86.900440
iter  60 value 86.497315
iter  70 value 85.755858
iter  80 value 81.509512
iter  90 value 78.671791
iter 100 value 77.503910
final  value 77.503910 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.599529 
iter  10 value 94.061234
iter  20 value 94.010444
iter  30 value 91.355241
iter  40 value 87.714851
iter  50 value 82.751335
iter  60 value 82.706192
iter  70 value 82.545516
iter  80 value 82.545005
iter  90 value 82.543794
iter 100 value 81.688908
final  value 81.688908 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.417776 
iter  10 value 94.024451
iter  20 value 91.515621
iter  30 value 87.060977
iter  40 value 86.997217
iter  50 value 85.298190
iter  60 value 84.182324
iter  70 value 84.157762
iter  80 value 84.155883
iter  90 value 83.984408
iter 100 value 81.297353
final  value 81.297353 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.410619 
iter  10 value 94.041329
iter  20 value 94.038065
iter  30 value 94.036133
iter  40 value 90.436604
iter  50 value 83.405429
iter  60 value 82.560415
iter  70 value 80.761517
iter  80 value 79.038217
iter  90 value 78.796647
iter 100 value 78.748274
final  value 78.748274 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.397165 
iter  10 value 89.434773
iter  20 value 88.529270
iter  30 value 83.848695
iter  40 value 82.931704
iter  50 value 82.371902
iter  60 value 82.322251
final  value 82.321859 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.227449 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.980053 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.464654 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.174045 
iter  10 value 94.119478
iter  20 value 93.976697
iter  30 value 93.923304
final  value 93.922611 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.289376 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.031052 
iter  10 value 86.467760
iter  20 value 86.440703
final  value 86.440679 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.973197 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.828687 
iter  10 value 94.305883
iter  10 value 94.305882
iter  10 value 94.305882
final  value 94.305882 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.101367 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.201650 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.926456 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.847473 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.361906 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.977407 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.040731 
final  value 94.289216 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.827332 
iter  10 value 94.494809
iter  20 value 87.582413
iter  30 value 86.475885
iter  40 value 85.707199
iter  50 value 85.550353
iter  60 value 85.134287
iter  70 value 84.665397
iter  80 value 84.471175
iter  90 value 83.395597
iter 100 value 82.051926
final  value 82.051926 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.273291 
iter  10 value 94.486513
iter  20 value 94.097892
iter  30 value 94.041667
iter  40 value 85.224751
iter  50 value 84.050867
iter  60 value 83.139136
iter  70 value 82.985279
iter  80 value 82.962878
iter  90 value 82.932546
final  value 82.932143 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.326581 
iter  10 value 94.495364
iter  20 value 94.129601
iter  30 value 92.964388
iter  40 value 89.244216
iter  50 value 88.803073
iter  60 value 87.845280
iter  70 value 83.896909
iter  80 value 83.090443
iter  90 value 82.935230
iter 100 value 82.933918
final  value 82.933918 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.634268 
iter  10 value 94.458885
iter  20 value 92.343622
iter  30 value 85.958169
iter  40 value 83.122912
iter  50 value 82.037979
iter  60 value 81.779621
iter  70 value 81.428411
iter  80 value 81.247646
final  value 81.247569 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.509450 
iter  10 value 94.488782
iter  20 value 94.062112
iter  30 value 86.672928
iter  40 value 84.977195
iter  50 value 84.900957
iter  60 value 84.588642
iter  70 value 83.587250
iter  80 value 82.958732
iter  90 value 81.950492
iter 100 value 81.498888
final  value 81.498888 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.684715 
iter  10 value 94.408767
iter  20 value 85.680862
iter  30 value 83.816565
iter  40 value 83.673292
iter  50 value 82.960828
iter  60 value 81.030409
iter  70 value 80.471252
iter  80 value 80.264459
iter  90 value 80.124332
iter 100 value 79.736162
final  value 79.736162 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.331885 
iter  10 value 93.882514
iter  20 value 92.031854
iter  30 value 85.340835
iter  40 value 84.139608
iter  50 value 83.447322
iter  60 value 81.751884
iter  70 value 80.578890
iter  80 value 80.308104
iter  90 value 79.939186
iter 100 value 79.620754
final  value 79.620754 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.239567 
iter  10 value 94.388097
iter  20 value 85.152704
iter  30 value 83.628439
iter  40 value 82.659179
iter  50 value 82.186285
iter  60 value 81.891004
iter  70 value 81.859252
iter  80 value 81.247805
iter  90 value 80.619809
iter 100 value 80.127546
final  value 80.127546 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.074750 
iter  10 value 91.049139
iter  20 value 84.365141
iter  30 value 83.354758
iter  40 value 82.863524
iter  50 value 81.588733
iter  60 value 80.450335
iter  70 value 80.005422
iter  80 value 79.970814
iter  90 value 79.927997
iter 100 value 79.828946
final  value 79.828946 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.710579 
iter  10 value 95.135448
iter  20 value 94.487380
iter  30 value 94.212996
iter  40 value 89.994140
iter  50 value 85.730298
iter  60 value 83.830852
iter  70 value 83.697055
iter  80 value 82.950942
iter  90 value 82.659747
iter 100 value 82.655655
final  value 82.655655 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.489999 
iter  10 value 100.063777
iter  20 value 90.601020
iter  30 value 87.717134
iter  40 value 84.808045
iter  50 value 84.288414
iter  60 value 82.939261
iter  70 value 80.672212
iter  80 value 80.363032
iter  90 value 80.152868
iter 100 value 79.594965
final  value 79.594965 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.752867 
iter  10 value 94.552586
iter  20 value 88.471176
iter  30 value 87.851068
iter  40 value 84.718991
iter  50 value 83.719205
iter  60 value 82.823675
iter  70 value 81.148359
iter  80 value 80.091745
iter  90 value 80.023100
iter 100 value 79.971668
final  value 79.971668 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.343305 
iter  10 value 94.490459
iter  20 value 94.174658
iter  30 value 89.195065
iter  40 value 85.400040
iter  50 value 83.403999
iter  60 value 83.191673
iter  70 value 82.042828
iter  80 value 81.540416
iter  90 value 80.502080
iter 100 value 79.955967
final  value 79.955967 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.615288 
iter  10 value 95.781976
iter  20 value 94.625802
iter  30 value 93.803065
iter  40 value 87.248085
iter  50 value 84.311325
iter  60 value 82.131486
iter  70 value 81.492063
iter  80 value 80.629509
iter  90 value 80.449288
iter 100 value 80.355050
final  value 80.355050 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.221564 
iter  10 value 94.483505
iter  20 value 85.156026
iter  30 value 84.875005
iter  40 value 83.970352
iter  50 value 83.579732
iter  60 value 81.894607
iter  70 value 81.463663
iter  80 value 80.645067
iter  90 value 80.267797
iter 100 value 79.937641
final  value 79.937641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.097446 
iter  10 value 94.298166
iter  20 value 94.090255
iter  30 value 86.817691
iter  40 value 84.016457
iter  50 value 83.983578
iter  60 value 82.579162
iter  70 value 82.520780
final  value 82.520735 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.045664 
final  value 94.485783 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.116542 
final  value 94.485749 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.309565 
final  value 94.485659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.576818 
iter  10 value 94.485885
iter  20 value 94.482615
final  value 94.354437 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.568180 
iter  10 value 94.057467
iter  20 value 93.978164
iter  30 value 93.974436
iter  40 value 88.732796
iter  50 value 85.992984
iter  60 value 85.992167
iter  70 value 84.734091
iter  80 value 84.323460
iter  90 value 84.320982
final  value 84.320327 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.012784 
iter  10 value 93.556346
iter  20 value 85.101110
iter  30 value 85.089778
iter  40 value 84.964734
iter  50 value 83.530514
iter  60 value 82.184952
iter  70 value 80.907596
iter  80 value 80.906444
iter  80 value 80.906443
final  value 80.906443 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.859490 
iter  10 value 94.489076
iter  20 value 94.484233
iter  30 value 94.060906
final  value 93.974019 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.510435 
iter  10 value 94.488743
iter  20 value 94.447197
iter  30 value 89.876963
iter  40 value 86.968269
iter  50 value 86.960418
iter  60 value 86.945995
iter  70 value 86.940533
iter  80 value 86.799394
iter  90 value 86.351256
iter 100 value 80.866800
final  value 80.866800 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.604624 
iter  10 value 94.359499
iter  20 value 91.713991
iter  30 value 82.475080
iter  40 value 82.474799
iter  50 value 82.465601
iter  60 value 82.464863
iter  70 value 82.382421
iter  80 value 82.339781
iter  90 value 82.339714
iter 100 value 82.069403
final  value 82.069403 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 138.645790 
iter  10 value 89.005078
iter  20 value 87.601197
iter  30 value 87.594675
iter  40 value 87.592652
final  value 87.592598 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.591278 
iter  10 value 94.492517
iter  20 value 94.397668
iter  30 value 91.249423
iter  40 value 87.448874
iter  50 value 86.326025
iter  60 value 83.789000
iter  70 value 83.717826
iter  80 value 83.715414
iter  90 value 83.708840
iter 100 value 83.707620
final  value 83.707620 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.967313 
iter  10 value 94.489410
iter  20 value 94.064015
final  value 94.057429 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.336690 
iter  10 value 94.363471
iter  20 value 94.355638
iter  30 value 93.104263
iter  40 value 90.689458
final  value 90.687761 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.303521 
iter  10 value 93.993352
iter  20 value 93.981442
iter  30 value 93.975104
iter  40 value 92.978190
iter  50 value 83.548987
iter  60 value 80.498813
iter  70 value 79.618173
iter  80 value 79.615895
iter  90 value 79.607638
iter 100 value 79.605862
final  value 79.605862 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.722435 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.535480 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.919873 
final  value 93.671508 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.794017 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.110586 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.547269 
final  value 94.050051 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.452454 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.606911 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.297839 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.549895 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.343383 
iter  10 value 87.848180
iter  20 value 87.098425
final  value 87.097089 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.079871 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.070341 
iter  10 value 92.458327
iter  20 value 91.702995
iter  30 value 89.373269
iter  40 value 89.160206
iter  50 value 89.104082
iter  60 value 88.974788
iter  70 value 88.963174
iter  80 value 88.963087
final  value 88.963083 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.918559 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.761959 
iter  10 value 93.137669
iter  20 value 93.134753
final  value 93.134731 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.191142 
iter  10 value 94.056655
iter  10 value 94.056654
iter  20 value 88.139583
iter  30 value 86.397184
iter  40 value 86.004028
iter  50 value 85.859275
iter  60 value 85.010604
iter  70 value 84.697855
iter  80 value 84.693316
iter  80 value 84.693316
iter  80 value 84.693316
final  value 84.693316 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.762727 
iter  10 value 94.064582
iter  20 value 94.049421
iter  30 value 93.802960
iter  40 value 93.007450
iter  50 value 92.937362
iter  60 value 92.897630
iter  70 value 92.837726
final  value 92.836375 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.696247 
iter  10 value 94.058156
iter  20 value 94.056723
iter  30 value 94.029462
iter  40 value 87.936518
iter  50 value 87.765953
iter  60 value 87.294425
iter  70 value 86.978377
iter  80 value 86.208977
iter  90 value 86.148920
final  value 86.147159 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.156606 
iter  10 value 94.056710
iter  20 value 90.212490
iter  30 value 87.762220
iter  40 value 86.636580
iter  50 value 85.734064
iter  60 value 85.320505
iter  70 value 85.151686
iter  80 value 85.113528
final  value 85.113488 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.885233 
iter  10 value 94.058174
iter  20 value 91.194910
iter  30 value 88.978771
iter  40 value 88.646913
iter  50 value 88.068981
iter  60 value 88.020986
iter  70 value 88.010844
iter  80 value 88.002532
iter  90 value 84.937001
iter 100 value 84.282423
final  value 84.282423 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.865802 
iter  10 value 94.010861
iter  20 value 90.980165
iter  30 value 86.614928
iter  40 value 84.746919
iter  50 value 84.216948
iter  60 value 82.653626
iter  70 value 81.613204
iter  80 value 81.396586
iter  90 value 81.313793
iter 100 value 81.222076
final  value 81.222076 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.144270 
iter  10 value 93.595063
iter  20 value 88.363231
iter  30 value 87.848744
iter  40 value 85.687296
iter  50 value 83.380360
iter  60 value 81.502974
iter  70 value 81.432202
iter  80 value 81.350673
iter  90 value 81.083845
iter 100 value 80.668641
final  value 80.668641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.615036 
iter  10 value 94.033921
iter  20 value 92.631059
iter  30 value 87.165163
iter  40 value 85.973445
iter  50 value 84.825072
iter  60 value 82.150951
iter  70 value 81.884131
iter  80 value 81.547290
iter  90 value 80.893776
iter 100 value 80.413556
final  value 80.413556 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.090574 
iter  10 value 93.375427
iter  20 value 87.266301
iter  30 value 85.850828
iter  40 value 85.023369
iter  50 value 84.378156
iter  60 value 84.211922
iter  70 value 84.183391
iter  80 value 83.555352
iter  90 value 82.417823
iter 100 value 81.834830
final  value 81.834830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.924272 
iter  10 value 93.734552
iter  20 value 87.887979
iter  30 value 86.785415
iter  40 value 86.101852
iter  50 value 84.834080
iter  60 value 83.098634
iter  70 value 81.927218
iter  80 value 81.315582
iter  90 value 81.156010
iter 100 value 81.114180
final  value 81.114180 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.118748 
iter  10 value 92.718181
iter  20 value 89.991285
iter  30 value 85.510711
iter  40 value 83.561444
iter  50 value 81.361798
iter  60 value 81.090728
iter  70 value 80.876188
iter  80 value 80.844245
iter  90 value 80.781750
iter 100 value 80.669205
final  value 80.669205 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.794073 
iter  10 value 94.864835
iter  20 value 93.956096
iter  30 value 87.751696
iter  40 value 87.474904
iter  50 value 85.539815
iter  60 value 84.392159
iter  70 value 83.045545
iter  80 value 82.284945
iter  90 value 81.884091
iter 100 value 81.237156
final  value 81.237156 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.232928 
iter  10 value 94.359865
iter  20 value 91.484230
iter  30 value 87.758745
iter  40 value 86.101960
iter  50 value 83.047110
iter  60 value 82.204311
iter  70 value 81.758838
iter  80 value 81.548154
iter  90 value 80.887715
iter 100 value 80.638657
final  value 80.638657 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.636370 
iter  10 value 94.424298
iter  20 value 94.061858
iter  30 value 91.229694
iter  40 value 90.636402
iter  50 value 88.023576
iter  60 value 85.423573
iter  70 value 84.710682
iter  80 value 84.288143
iter  90 value 83.780805
iter 100 value 83.116924
final  value 83.116924 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.383588 
iter  10 value 93.301648
iter  20 value 92.645390
iter  30 value 92.150153
iter  40 value 90.992527
iter  50 value 90.773036
iter  60 value 90.615940
iter  70 value 87.902920
iter  80 value 83.800234
iter  90 value 82.851174
iter 100 value 82.493780
final  value 82.493780 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.532283 
final  value 94.054628 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.217538 
final  value 94.054552 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.866659 
iter  10 value 94.054492
iter  20 value 94.053003
final  value 94.052916 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.169258 
final  value 94.054572 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.539865 
final  value 94.054642 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.135867 
iter  10 value 94.057238
iter  20 value 94.052097
iter  30 value 92.580849
iter  40 value 92.541682
iter  50 value 92.540864
iter  60 value 92.521135
iter  70 value 92.477313
iter  80 value 92.476976
final  value 92.476911 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.188017 
iter  10 value 94.057791
iter  20 value 94.055328
iter  30 value 94.043045
iter  40 value 94.040610
final  value 94.039068 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.551463 
iter  10 value 94.043587
iter  20 value 94.039551
final  value 94.039476 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.702216 
iter  10 value 94.043141
iter  20 value 94.038461
iter  30 value 92.688294
iter  40 value 85.267189
iter  50 value 82.401484
iter  60 value 81.979734
iter  70 value 81.894213
final  value 81.893954 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.174204 
iter  10 value 94.058084
iter  20 value 93.597437
iter  30 value 86.177915
final  value 86.176903 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.795458 
iter  10 value 94.059126
iter  20 value 93.889512
iter  30 value 90.477839
iter  40 value 89.492746
iter  50 value 89.156185
iter  60 value 89.123567
iter  70 value 88.453246
iter  80 value 86.915234
iter  90 value 86.900534
final  value 86.900501 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.006373 
iter  10 value 94.047166
iter  20 value 94.039008
iter  30 value 93.703892
iter  40 value 88.455231
iter  50 value 87.899995
iter  60 value 87.829168
iter  70 value 87.744035
iter  80 value 87.741586
iter  90 value 87.741498
iter 100 value 87.740451
final  value 87.740451 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.484272 
iter  10 value 94.054565
iter  20 value 90.667404
iter  30 value 89.345029
final  value 89.344927 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.683143 
iter  10 value 94.045958
iter  20 value 94.038902
iter  30 value 94.010810
iter  40 value 93.197211
iter  50 value 92.912001
iter  60 value 91.674820
iter  70 value 83.761093
iter  80 value 83.470229
final  value 83.470196 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.977758 
iter  10 value 94.046690
iter  20 value 94.040625
iter  30 value 90.970126
iter  40 value 86.447492
iter  50 value 86.445889
iter  60 value 86.444621
final  value 86.444608 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.161288 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.798800 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.015178 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.605913 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.241634 
iter  10 value 94.112903
iter  10 value 94.112903
iter  10 value 94.112903
final  value 94.112903 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.362808 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.844707 
final  value 94.354286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.888864 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.584760 
iter  10 value 94.359327
final  value 94.354293 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.728728 
iter  10 value 93.921936
iter  20 value 93.889246
final  value 93.888889 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.084060 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.175148 
iter  10 value 93.950049
final  value 93.950035 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.179188 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.570222 
iter  10 value 93.761394
final  value 93.756277 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.873948 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.473134 
iter  10 value 94.489122
iter  20 value 94.032605
iter  30 value 92.656062
iter  40 value 90.673004
iter  50 value 87.171304
iter  60 value 85.642354
iter  70 value 85.603938
iter  80 value 85.596625
iter  90 value 85.592781
iter 100 value 85.373900
final  value 85.373900 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.026912 
iter  10 value 94.494285
iter  20 value 94.151632
iter  30 value 90.000890
iter  40 value 88.735162
iter  50 value 86.666796
iter  60 value 86.369056
iter  70 value 83.695912
iter  80 value 82.894067
iter  90 value 82.778156
iter 100 value 82.058816
final  value 82.058816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.044751 
iter  10 value 94.349824
iter  20 value 93.985580
iter  30 value 93.973228
iter  40 value 93.936777
iter  50 value 91.957631
iter  60 value 89.402435
iter  70 value 85.770848
iter  80 value 85.387199
iter  90 value 85.234527
iter 100 value 84.936338
final  value 84.936338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.917222 
iter  10 value 94.483231
iter  20 value 94.239259
iter  30 value 94.038233
iter  40 value 93.755182
iter  50 value 92.147096
iter  60 value 87.910161
iter  70 value 87.312797
iter  80 value 85.221736
iter  90 value 83.578119
iter 100 value 82.743438
final  value 82.743438 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.708438 
iter  10 value 94.486489
iter  20 value 94.239888
iter  30 value 91.493045
iter  40 value 87.886969
iter  50 value 87.172376
iter  60 value 84.740484
iter  70 value 82.986693
iter  80 value 82.551255
iter  90 value 82.190187
iter 100 value 82.164732
final  value 82.164732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.458275 
iter  10 value 94.292703
iter  20 value 91.093445
iter  30 value 90.553039
iter  40 value 88.425098
iter  50 value 84.639494
iter  60 value 81.728353
iter  70 value 80.811646
iter  80 value 80.686288
iter  90 value 80.607492
iter 100 value 80.556629
final  value 80.556629 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.582164 
iter  10 value 96.806749
iter  20 value 94.169805
iter  30 value 92.077575
iter  40 value 91.453887
iter  50 value 91.397629
iter  60 value 90.752244
iter  70 value 90.306498
iter  80 value 89.938840
iter  90 value 84.704872
iter 100 value 84.079131
final  value 84.079131 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.733614 
iter  10 value 96.908318
iter  20 value 88.499732
iter  30 value 85.997870
iter  40 value 85.301533
iter  50 value 84.512482
iter  60 value 83.365988
iter  70 value 82.745111
iter  80 value 82.454971
iter  90 value 82.424949
iter 100 value 82.371508
final  value 82.371508 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.041949 
iter  10 value 94.573821
iter  20 value 86.496713
iter  30 value 86.166099
iter  40 value 85.906360
iter  50 value 85.167898
iter  60 value 85.008578
iter  70 value 84.796167
iter  80 value 83.232208
iter  90 value 82.656814
iter 100 value 82.607393
final  value 82.607393 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.654557 
iter  10 value 90.896267
iter  20 value 86.533327
iter  30 value 85.697796
iter  40 value 83.953075
iter  50 value 82.147652
iter  60 value 81.690399
iter  70 value 81.120418
iter  80 value 80.988224
iter  90 value 80.980977
iter 100 value 80.975424
final  value 80.975424 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.769562 
iter  10 value 94.566347
iter  20 value 92.505346
iter  30 value 86.179668
iter  40 value 85.001778
iter  50 value 84.668912
iter  60 value 84.374783
iter  70 value 83.859781
iter  80 value 83.429769
iter  90 value 83.036349
iter 100 value 82.767677
final  value 82.767677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.085830 
iter  10 value 94.994255
iter  20 value 86.442021
iter  30 value 83.946263
iter  40 value 82.536093
iter  50 value 81.760739
iter  60 value 81.459506
iter  70 value 81.398404
iter  80 value 81.364115
iter  90 value 81.159285
iter 100 value 80.722461
final  value 80.722461 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.663513 
iter  10 value 94.754433
iter  20 value 90.177867
iter  30 value 85.685788
iter  40 value 84.405796
iter  50 value 84.181156
iter  60 value 83.797928
iter  70 value 83.379026
iter  80 value 83.274552
iter  90 value 82.973376
iter 100 value 82.752586
final  value 82.752586 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.163509 
iter  10 value 94.170617
iter  20 value 89.137637
iter  30 value 87.694856
iter  40 value 86.800254
iter  50 value 86.178515
iter  60 value 85.217768
iter  70 value 84.622250
iter  80 value 83.353220
iter  90 value 81.966984
iter 100 value 81.473574
final  value 81.473574 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.770625 
iter  10 value 94.683978
iter  20 value 93.636718
iter  30 value 88.186032
iter  40 value 83.450786
iter  50 value 83.232012
iter  60 value 82.775320
iter  70 value 82.402123
iter  80 value 81.841164
iter  90 value 81.563939
iter 100 value 81.463629
final  value 81.463629 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.614374 
iter  10 value 94.486012
iter  20 value 94.484225
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.439845 
final  value 94.485872 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.699919 
final  value 94.485868 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.887494 
final  value 94.486249 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.406472 
final  value 94.485877 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.474990 
iter  10 value 94.489023
iter  20 value 88.416370
iter  30 value 85.489897
iter  40 value 85.038594
iter  50 value 84.211026
iter  60 value 81.970006
iter  70 value 81.593610
iter  80 value 81.409823
iter  90 value 80.845748
iter 100 value 80.743489
final  value 80.743489 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.793675 
iter  10 value 94.489549
iter  20 value 93.855755
iter  30 value 85.174062
iter  40 value 84.559922
final  value 84.555521 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.669804 
iter  10 value 94.488457
iter  20 value 94.444148
iter  30 value 93.871865
final  value 93.871763 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.061804 
iter  10 value 94.121919
iter  20 value 94.117913
iter  30 value 83.307420
iter  40 value 83.133728
iter  50 value 83.128678
iter  50 value 83.128678
final  value 83.128678 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.230190 
iter  10 value 93.927277
iter  20 value 93.857748
iter  30 value 88.608555
iter  40 value 88.258023
iter  50 value 87.840127
iter  60 value 85.773910
iter  70 value 85.555960
iter  80 value 85.551796
iter  90 value 85.551612
iter 100 value 85.549811
final  value 85.549811 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.623698 
iter  10 value 94.491827
iter  20 value 94.039219
iter  30 value 91.828081
iter  40 value 91.824858
final  value 91.824741 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.753279 
iter  10 value 94.417713
iter  20 value 94.195268
iter  30 value 88.208127
iter  40 value 85.182222
iter  50 value 85.103545
iter  60 value 84.959095
iter  70 value 84.102350
iter  80 value 82.496604
iter  90 value 82.432110
iter 100 value 81.085189
final  value 81.085189 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.586889 
iter  10 value 94.121157
iter  20 value 93.895419
iter  30 value 93.751773
iter  40 value 93.726155
iter  50 value 93.713931
iter  60 value 92.593555
iter  70 value 90.087639
iter  80 value 89.233131
iter  90 value 86.844362
iter 100 value 82.769033
final  value 82.769033 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.260140 
iter  10 value 93.265816
iter  20 value 87.290464
iter  30 value 86.961712
iter  40 value 86.943157
iter  50 value 86.939439
iter  60 value 86.938638
iter  70 value 86.934136
final  value 86.932558 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.678148 
iter  10 value 94.492133
iter  20 value 94.437296
iter  30 value 86.543056
iter  40 value 85.528307
iter  50 value 83.840138
iter  60 value 81.412122
iter  70 value 79.715827
iter  80 value 79.678092
iter  90 value 79.661629
iter 100 value 79.638293
final  value 79.638293 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 140.138840 
iter  10 value 117.936583
iter  20 value 116.855233
iter  30 value 113.839691
iter  40 value 113.329002
iter  50 value 110.643478
iter  60 value 108.839764
iter  70 value 105.787116
iter  80 value 102.990953
iter  90 value 102.805848
iter 100 value 102.198433
final  value 102.198433 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.713408 
iter  10 value 112.812917
iter  20 value 106.666165
iter  30 value 106.257348
iter  40 value 105.710870
iter  50 value 105.129045
iter  60 value 104.071832
iter  70 value 103.284008
iter  80 value 102.085724
iter  90 value 101.388102
iter 100 value 101.199147
final  value 101.199147 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 137.106889 
iter  10 value 119.376587
iter  20 value 110.515131
iter  30 value 107.792521
iter  40 value 107.333084
iter  50 value 105.866068
iter  60 value 105.240463
iter  70 value 105.018931
iter  80 value 105.004465
iter  90 value 104.980408
iter 100 value 104.555198
final  value 104.555198 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 138.209095 
iter  10 value 113.536498
iter  20 value 109.824801
iter  30 value 105.227176
iter  40 value 103.871329
iter  50 value 102.107412
iter  60 value 101.567386
iter  70 value 101.115146
iter  80 value 101.103185
iter  90 value 101.092119
iter 100 value 100.986559
final  value 100.986559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 165.931756 
iter  10 value 119.063435
iter  20 value 118.094737
iter  30 value 110.030410
iter  40 value 104.323678
iter  50 value 101.152745
iter  60 value 100.756452
iter  70 value 100.467611
iter  80 value 100.406281
iter  90 value 100.324047
iter 100 value 100.295525
final  value 100.295525 
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 17 06:56:21 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 
 73.349   2.223  85.173