##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* 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 ‘1.12.0’
* 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         33.355  1.093  44.431
corr_plot        32.732  0.872  34.997
var_imp          32.914  0.660  34.381
pred_ensembel    13.597  0.449  60.256
calculateAutocor  0.474  0.068  11.555
enrichfindP       0.489  0.053  17.941
plotPPI           0.077  0.005   6.961
* 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-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 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 96.793128 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.910302 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.641282 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.492623 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.577972 
final  value 94.385583 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.895638 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.706342 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.644754 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.817578 
final  value 94.365462 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.281052 
final  value 94.400000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.221277 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.325482 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.286295 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.141284 
iter  10 value 94.260370
iter  20 value 85.693592
iter  30 value 85.631688
final  value 85.582895 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.138616 
iter  10 value 86.225958
iter  20 value 84.498016
final  value 84.481576 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.454463 
iter  10 value 94.096463
iter  20 value 87.904224
iter  30 value 86.520482
iter  40 value 85.989721
iter  50 value 85.966969
iter  60 value 85.932372
iter  70 value 85.920970
final  value 85.920968 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.084353 
iter  10 value 94.488561
iter  20 value 88.540249
iter  30 value 86.745880
iter  40 value 86.139406
iter  50 value 85.109126
iter  60 value 84.715473
iter  70 value 84.601837
final  value 84.600904 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.322633 
iter  10 value 94.487132
iter  20 value 94.090626
iter  30 value 94.015939
iter  40 value 93.859827
iter  50 value 90.845410
iter  60 value 84.307352
iter  70 value 82.459339
iter  80 value 82.302590
iter  90 value 81.877934
iter 100 value 80.710232
final  value 80.710232 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.235172 
iter  10 value 94.489971
iter  20 value 94.486764
final  value 94.486439 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.806823 
iter  10 value 94.490592
iter  20 value 94.475073
iter  30 value 86.740021
iter  40 value 86.038384
iter  50 value 85.944333
iter  60 value 85.921814
final  value 85.920969 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.735401 
iter  10 value 94.033886
iter  20 value 86.729501
iter  30 value 84.887398
iter  40 value 81.267593
iter  50 value 80.185452
iter  60 value 80.009423
iter  70 value 79.931624
iter  80 value 79.567337
iter  90 value 79.486492
iter 100 value 79.459962
final  value 79.459962 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.781650 
iter  10 value 94.428749
iter  20 value 92.826056
iter  30 value 87.633421
iter  40 value 85.738571
iter  50 value 84.454318
iter  60 value 83.111557
iter  70 value 82.425641
iter  80 value 81.917825
iter  90 value 81.789874
iter 100 value 81.725537
final  value 81.725537 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.641404 
iter  10 value 94.465817
iter  20 value 87.564728
iter  30 value 85.873088
iter  40 value 84.857097
iter  50 value 82.778574
iter  60 value 81.757793
iter  70 value 80.889876
iter  80 value 80.684430
iter  90 value 80.101284
iter 100 value 79.478077
final  value 79.478077 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.246385 
iter  10 value 94.518185
iter  20 value 93.335578
iter  30 value 88.226740
iter  40 value 87.953772
iter  50 value 86.022359
iter  60 value 85.444940
iter  70 value 83.006967
iter  80 value 82.733372
iter  90 value 82.500204
iter 100 value 82.130268
final  value 82.130268 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.996299 
iter  10 value 94.323371
iter  20 value 87.738158
iter  30 value 85.270213
iter  40 value 84.049709
iter  50 value 83.472327
iter  60 value 80.538952
iter  70 value 80.057464
iter  80 value 79.398595
iter  90 value 79.283707
iter 100 value 79.279104
final  value 79.279104 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.101045 
iter  10 value 94.927368
iter  20 value 86.507183
iter  30 value 85.824675
iter  40 value 85.726196
iter  50 value 85.668462
iter  60 value 83.959408
iter  70 value 81.882868
iter  80 value 81.467907
iter  90 value 81.157252
iter 100 value 80.084772
final  value 80.084772 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.069416 
iter  10 value 94.479743
iter  20 value 90.676867
iter  30 value 86.324979
iter  40 value 84.717104
iter  50 value 84.133192
iter  60 value 83.949027
iter  70 value 83.699036
iter  80 value 82.527303
iter  90 value 80.128119
iter 100 value 79.775017
final  value 79.775017 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.437020 
iter  10 value 94.509113
iter  20 value 94.057164
iter  30 value 93.340203
iter  40 value 93.074431
iter  50 value 92.347496
iter  60 value 89.624034
iter  70 value 84.255284
iter  80 value 82.790238
iter  90 value 82.300596
iter 100 value 82.230768
final  value 82.230768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.000932 
iter  10 value 90.703084
iter  20 value 88.066758
iter  30 value 86.600217
iter  40 value 83.776392
iter  50 value 82.260596
iter  60 value 80.731673
iter  70 value 80.429280
iter  80 value 79.850215
iter  90 value 79.807864
iter 100 value 79.781214
final  value 79.781214 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.665387 
iter  10 value 94.573154
iter  20 value 94.439448
iter  30 value 94.100615
iter  40 value 93.472293
iter  50 value 90.617394
iter  60 value 86.716767
iter  70 value 84.976090
iter  80 value 84.375611
iter  90 value 83.076213
iter 100 value 82.334865
final  value 82.334865 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.515853 
final  value 94.401494 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.487059 
final  value 94.485930 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.613552 
final  value 94.485780 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.640295 
final  value 94.486005 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.623508 
final  value 94.485793 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.518002 
iter  10 value 94.488902
iter  20 value 94.484109
iter  30 value 94.431539
iter  40 value 93.990710
iter  50 value 90.427493
iter  60 value 86.587715
iter  70 value 86.264662
iter  80 value 86.075754
iter  90 value 86.068719
iter 100 value 83.776805
final  value 83.776805 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.342340 
iter  10 value 94.496812
iter  20 value 94.488130
iter  30 value 93.789301
iter  40 value 93.775712
iter  50 value 93.756065
iter  60 value 93.662804
iter  70 value 93.642804
iter  80 value 93.641820
iter  90 value 93.641178
iter 100 value 93.639686
final  value 93.639686 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.534740 
iter  10 value 94.471929
iter  20 value 94.467791
iter  30 value 93.484545
iter  40 value 84.099023
iter  50 value 84.029149
final  value 84.022853 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.672105 
iter  10 value 94.471701
iter  20 value 94.467057
iter  30 value 94.303026
iter  40 value 92.916562
iter  50 value 91.072739
final  value 91.071154 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.989372 
iter  10 value 94.487659
iter  20 value 94.469413
iter  30 value 94.468066
iter  40 value 94.466443
iter  50 value 87.352756
iter  60 value 85.395263
iter  70 value 83.336689
iter  80 value 83.294007
iter  90 value 83.269443
iter 100 value 83.115743
final  value 83.115743 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.904094 
iter  10 value 94.407461
iter  20 value 94.319844
iter  30 value 90.163465
iter  40 value 88.871328
iter  50 value 88.867188
iter  60 value 88.858026
iter  70 value 88.854708
iter  80 value 87.977491
iter  90 value 86.554341
iter 100 value 85.666728
final  value 85.666728 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.146336 
iter  10 value 88.197573
iter  20 value 85.152367
iter  30 value 82.213690
iter  40 value 79.701612
iter  50 value 79.670126
iter  60 value 79.669109
final  value 79.668473 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.566875 
iter  10 value 94.317919
iter  20 value 94.312660
iter  30 value 94.311942
iter  40 value 94.220011
iter  50 value 91.223680
iter  60 value 89.994468
iter  70 value 84.241731
iter  80 value 83.911748
iter  90 value 83.726018
iter 100 value 83.725832
final  value 83.725832 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.055864 
iter  10 value 92.954388
iter  20 value 92.807069
iter  30 value 92.699890
iter  40 value 92.648585
iter  50 value 92.639700
final  value 92.639633 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.481058 
iter  10 value 94.493115
iter  20 value 94.484708
iter  30 value 94.019528
iter  40 value 93.991909
final  value 93.991860 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.058853 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.017329 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.621944 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.771512 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.471265 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.087985 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.017957 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.868523 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.129275 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.308960 
iter  10 value 94.484218
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.726186 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.518130 
iter  10 value 94.276080
iter  20 value 94.275363
iter  20 value 94.275363
iter  20 value 94.275363
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.132430 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.635938 
iter  10 value 94.275362
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.531088 
iter  10 value 93.605787
iter  20 value 93.179143
iter  30 value 92.861026
iter  40 value 92.692136
final  value 92.689978 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.152761 
iter  10 value 94.488556
iter  20 value 94.154371
iter  30 value 94.121869
iter  40 value 94.114361
iter  50 value 93.736061
iter  60 value 87.109775
iter  70 value 86.176767
iter  80 value 86.034175
iter  90 value 85.950676
iter 100 value 85.938332
final  value 85.938332 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.440208 
iter  10 value 94.488083
iter  20 value 94.474495
iter  30 value 89.309119
iter  40 value 85.494959
iter  50 value 84.186133
iter  60 value 83.906409
iter  70 value 82.755473
final  value 82.752825 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.032357 
iter  10 value 94.488561
iter  20 value 85.085965
iter  30 value 82.906127
iter  40 value 82.669202
iter  50 value 82.308102
iter  60 value 82.158904
final  value 82.149842 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.549453 
iter  10 value 94.525263
iter  20 value 94.420178
iter  30 value 94.335806
iter  40 value 94.116513
iter  50 value 85.491413
iter  60 value 84.460018
iter  70 value 83.472813
iter  80 value 82.772232
iter  90 value 82.752828
iter  90 value 82.752827
iter  90 value 82.752827
final  value 82.752827 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.144341 
iter  10 value 94.489275
iter  20 value 94.419907
iter  30 value 92.004172
iter  40 value 83.830707
iter  50 value 83.121127
iter  60 value 82.300260
iter  70 value 82.092275
iter  80 value 82.005743
iter  90 value 81.931109
final  value 81.931057 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.092186 
iter  10 value 94.803283
iter  20 value 93.863817
iter  30 value 91.294936
iter  40 value 91.039030
iter  50 value 90.125070
iter  60 value 89.700814
iter  70 value 85.578324
iter  80 value 80.663395
iter  90 value 79.311619
iter 100 value 79.119231
final  value 79.119231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.249260 
iter  10 value 94.282527
iter  20 value 94.106581
iter  30 value 89.196066
iter  40 value 82.542557
iter  50 value 81.379956
iter  60 value 80.637573
iter  70 value 80.161481
iter  80 value 79.557791
iter  90 value 79.143210
iter 100 value 78.472901
final  value 78.472901 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.719278 
iter  10 value 92.301257
iter  20 value 90.876810
iter  30 value 89.752403
iter  40 value 89.434198
iter  50 value 89.332757
iter  60 value 89.194576
iter  70 value 89.180005
iter  80 value 88.159182
iter  90 value 81.661344
iter 100 value 81.528269
final  value 81.528269 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.921523 
iter  10 value 94.446531
iter  20 value 89.268558
iter  30 value 86.297370
iter  40 value 82.397004
iter  50 value 81.624683
iter  60 value 81.352618
iter  70 value 80.675128
iter  80 value 79.815373
iter  90 value 79.016948
iter 100 value 78.746310
final  value 78.746310 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.723741 
iter  10 value 94.533797
iter  20 value 86.928724
iter  30 value 82.820627
iter  40 value 82.472032
iter  50 value 82.154419
iter  60 value 81.679177
iter  70 value 80.356818
iter  80 value 78.683912
iter  90 value 78.562084
iter 100 value 78.379301
final  value 78.379301 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.295831 
iter  10 value 94.214373
iter  20 value 89.374672
iter  30 value 83.991074
iter  40 value 83.259029
iter  50 value 82.109962
iter  60 value 81.143866
iter  70 value 79.330555
iter  80 value 78.517145
iter  90 value 78.371774
iter 100 value 78.295719
final  value 78.295719 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.230472 
iter  10 value 94.598425
iter  20 value 82.152814
iter  30 value 79.586562
iter  40 value 78.155219
iter  50 value 77.930997
iter  60 value 77.794614
iter  70 value 77.744536
iter  80 value 77.690704
iter  90 value 77.653128
iter 100 value 77.610028
final  value 77.610028 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.012690 
iter  10 value 94.355109
iter  20 value 90.599307
iter  30 value 86.046959
iter  40 value 80.769073
iter  50 value 79.616816
iter  60 value 79.470970
iter  70 value 79.003973
iter  80 value 78.406007
iter  90 value 78.272688
iter 100 value 78.049458
final  value 78.049458 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.263532 
iter  10 value 95.031922
iter  20 value 93.137394
iter  30 value 91.370933
iter  40 value 82.392300
iter  50 value 81.131295
iter  60 value 80.039313
iter  70 value 79.277032
iter  80 value 79.062492
iter  90 value 78.870630
iter 100 value 78.736000
final  value 78.736000 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.067966 
iter  10 value 94.815829
iter  20 value 82.685586
iter  30 value 81.260810
iter  40 value 79.380652
iter  50 value 78.406267
iter  60 value 78.122944
iter  70 value 78.050834
iter  80 value 78.044770
iter  90 value 78.006589
iter 100 value 77.978268
final  value 77.978268 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.904441 
final  value 94.485603 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.461287 
final  value 94.485975 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.316898 
iter  10 value 94.485709
iter  20 value 94.484113
iter  30 value 94.053296
final  value 94.046283 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.006578 
final  value 94.486004 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.114520 
iter  10 value 94.073016
final  value 94.054004 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.099855 
iter  10 value 94.489326
iter  20 value 93.769636
iter  30 value 87.268234
iter  40 value 87.249565
iter  50 value 87.248266
iter  60 value 87.247376
iter  70 value 87.246620
iter  80 value 87.232736
final  value 87.232211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.613941 
iter  10 value 94.280635
iter  20 value 94.276123
final  value 94.275859 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.111490 
iter  10 value 94.280809
iter  20 value 94.277641
iter  30 value 94.275248
iter  30 value 94.275247
iter  30 value 94.275247
final  value 94.275247 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.609481 
iter  10 value 94.280178
iter  20 value 94.084015
iter  30 value 94.049951
iter  40 value 94.049804
final  value 94.049782 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.646753 
iter  10 value 94.488897
iter  20 value 89.352625
iter  30 value 82.590368
iter  40 value 82.051599
iter  50 value 82.049434
iter  60 value 82.018414
iter  70 value 81.934655
iter  80 value 81.934368
iter  90 value 81.934197
final  value 81.933741 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.519986 
iter  10 value 94.060799
iter  20 value 93.649986
iter  30 value 84.048141
iter  40 value 83.712901
final  value 83.103716 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.799716 
iter  10 value 94.492427
iter  20 value 94.482587
iter  30 value 92.041963
iter  40 value 83.722838
iter  50 value 83.709991
iter  60 value 83.699060
iter  70 value 78.323356
iter  80 value 77.053807
iter  90 value 76.926486
iter 100 value 76.911048
final  value 76.911048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.457567 
iter  10 value 94.283167
iter  20 value 93.940605
iter  30 value 87.875170
iter  40 value 83.482438
iter  50 value 82.520707
iter  60 value 81.566382
iter  70 value 81.084468
iter  80 value 81.059506
iter  90 value 81.059262
final  value 81.058939 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.235090 
iter  10 value 94.491680
iter  20 value 94.484228
iter  30 value 94.475008
final  value 94.275490 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.053595 
iter  10 value 94.283705
iter  20 value 94.275584
iter  30 value 92.448825
iter  40 value 89.816872
iter  50 value 89.092541
iter  60 value 88.949836
iter  70 value 88.705729
iter  80 value 88.689633
iter  90 value 87.356271
iter 100 value 82.167273
final  value 82.167273 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.421279 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.555785 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.563220 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.104578 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.676324 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.744249 
iter  10 value 94.484657
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.366207 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.492439 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.201607 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.311514 
final  value 94.322897 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.042077 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.389523 
final  value 94.206005 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.463421 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.624245 
iter  10 value 89.341014
iter  20 value 87.991730
iter  30 value 85.807384
iter  40 value 85.410909
iter  50 value 85.212418
iter  60 value 84.352064
iter  70 value 84.215494
iter  80 value 84.212118
iter  90 value 84.211159
iter 100 value 84.210652
final  value 84.210652 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.709702 
iter  10 value 94.465465
final  value 94.453335 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.594819 
iter  10 value 93.799445
iter  20 value 87.761857
iter  30 value 87.510896
iter  40 value 87.315717
iter  50 value 85.537431
iter  60 value 85.362063
iter  70 value 84.932233
iter  80 value 84.648875
iter  90 value 84.633155
final  value 84.623191 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.386985 
iter  10 value 94.509374
iter  20 value 94.440613
iter  30 value 90.726681
iter  40 value 89.204674
iter  50 value 89.141072
iter  60 value 88.886826
iter  70 value 88.167863
iter  80 value 87.664137
iter  90 value 87.557136
iter 100 value 87.481760
final  value 87.481760 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.538856 
iter  10 value 94.490971
iter  20 value 94.272440
iter  30 value 92.887430
iter  40 value 91.058280
iter  50 value 87.934726
iter  60 value 86.545559
iter  70 value 84.790105
iter  80 value 84.360501
iter  90 value 84.345891
iter 100 value 84.189671
final  value 84.189671 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.030123 
iter  10 value 93.471566
iter  20 value 89.680155
iter  30 value 88.105499
iter  40 value 86.977520
iter  50 value 86.960486
iter  60 value 86.950335
final  value 86.949795 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.444610 
iter  10 value 93.970840
iter  20 value 91.511008
iter  30 value 89.258214
iter  40 value 88.920604
iter  50 value 87.127206
iter  60 value 86.585611
iter  70 value 86.565653
final  value 86.556969 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.838825 
iter  10 value 94.370324
iter  20 value 88.944062
iter  30 value 87.734861
iter  40 value 87.015066
iter  50 value 86.706293
iter  60 value 86.625362
iter  70 value 86.442654
iter  80 value 86.044821
iter  90 value 84.770372
iter 100 value 84.410127
final  value 84.410127 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.153421 
iter  10 value 94.465137
iter  20 value 90.864431
iter  30 value 88.807592
iter  40 value 88.186419
iter  50 value 86.597905
iter  60 value 84.345862
iter  70 value 83.978524
iter  80 value 83.518372
iter  90 value 83.364331
iter 100 value 83.237937
final  value 83.237937 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.873588 
iter  10 value 94.708405
iter  20 value 94.508292
iter  30 value 94.298045
iter  40 value 90.863306
iter  50 value 89.789979
iter  60 value 88.641638
iter  70 value 87.676734
iter  80 value 87.041116
iter  90 value 86.247754
iter 100 value 85.934163
final  value 85.934163 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.715646 
iter  10 value 94.467935
iter  20 value 86.691457
iter  30 value 85.885665
iter  40 value 83.938796
iter  50 value 83.402175
iter  60 value 83.171704
iter  70 value 83.060056
iter  80 value 82.990808
iter  90 value 82.986258
iter 100 value 82.966827
final  value 82.966827 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.264965 
iter  10 value 94.456232
iter  20 value 92.277426
iter  30 value 87.480956
iter  40 value 85.441421
iter  50 value 84.189172
iter  60 value 83.643490
iter  70 value 83.134480
iter  80 value 82.930667
iter  90 value 82.784037
iter 100 value 82.676107
final  value 82.676107 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.192336 
iter  10 value 97.093043
iter  20 value 91.859821
iter  30 value 86.345053
iter  40 value 85.389958
iter  50 value 85.005552
iter  60 value 84.820382
iter  70 value 84.764858
iter  80 value 84.708225
iter  90 value 84.650021
iter 100 value 84.252995
final  value 84.252995 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.574682 
iter  10 value 94.704196
iter  20 value 91.178378
iter  30 value 88.385532
iter  40 value 86.797062
iter  50 value 84.715804
iter  60 value 82.938408
iter  70 value 82.596522
iter  80 value 82.420701
iter  90 value 82.349480
iter 100 value 82.264887
final  value 82.264887 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.515844 
iter  10 value 90.900948
iter  20 value 88.408315
iter  30 value 87.085702
iter  40 value 85.680380
iter  50 value 84.745645
iter  60 value 83.680104
iter  70 value 82.908890
iter  80 value 82.691369
iter  90 value 82.597762
iter 100 value 82.510149
final  value 82.510149 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.121283 
iter  10 value 94.291014
iter  20 value 93.166050
iter  30 value 92.681937
iter  40 value 91.916941
iter  50 value 86.149198
iter  60 value 83.954529
iter  70 value 83.586100
iter  80 value 83.042012
iter  90 value 82.542465
iter 100 value 82.398286
final  value 82.398286 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.492587 
iter  10 value 94.471272
iter  20 value 92.228618
iter  30 value 87.178015
iter  40 value 85.654159
iter  50 value 84.954277
iter  60 value 84.839404
iter  70 value 84.566797
iter  80 value 84.356458
iter  90 value 84.120839
iter 100 value 83.975491
final  value 83.975491 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.284651 
final  value 94.485757 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.335110 
final  value 94.485821 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.274614 
final  value 94.486069 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.873665 
final  value 94.486204 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.629225 
final  value 94.485843 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.035677 
iter  10 value 94.335281
iter  20 value 94.314082
iter  30 value 89.334934
iter  40 value 88.537590
iter  50 value 88.537260
iter  60 value 88.534644
iter  70 value 88.247600
iter  80 value 88.244776
iter  90 value 88.244666
iter 100 value 88.243035
final  value 88.243035 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.108901 
iter  10 value 93.304731
iter  20 value 92.240234
iter  30 value 92.233543
iter  40 value 92.210847
iter  50 value 92.129087
iter  60 value 92.126190
iter  70 value 92.125541
iter  80 value 92.124804
iter  90 value 91.925764
final  value 91.925614 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.214779 
iter  10 value 94.487847
iter  20 value 94.354492
final  value 94.354455 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.265560 
iter  10 value 94.488775
iter  20 value 94.419819
final  value 94.354478 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.522909 
iter  10 value 94.489508
iter  20 value 94.205448
iter  30 value 88.262294
iter  40 value 87.709068
final  value 87.674329 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.855692 
iter  10 value 94.362607
iter  20 value 94.030396
iter  30 value 89.417525
iter  40 value 88.649001
iter  50 value 87.019659
iter  60 value 87.003643
iter  70 value 86.991572
iter  80 value 86.991419
iter  90 value 86.991076
final  value 86.990966 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.132143 
iter  10 value 94.492644
iter  20 value 94.412470
iter  30 value 94.351395
iter  40 value 93.600529
iter  50 value 87.687067
iter  60 value 87.377040
iter  70 value 87.373616
iter  80 value 86.615549
iter  90 value 86.375124
iter 100 value 86.115414
final  value 86.115414 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.959317 
iter  10 value 94.331004
iter  20 value 94.325857
iter  30 value 94.324461
iter  40 value 92.789652
iter  50 value 85.925513
iter  60 value 85.916252
iter  70 value 85.523247
iter  80 value 85.523162
final  value 85.523126 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.132861 
iter  10 value 94.492336
iter  20 value 93.792842
iter  30 value 90.719749
iter  40 value 88.253207
iter  50 value 88.238824
iter  60 value 88.226525
final  value 88.225718 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.258574 
iter  10 value 94.362806
iter  20 value 94.354654
iter  30 value 90.543063
iter  40 value 89.034638
iter  50 value 88.639503
iter  60 value 88.628048
final  value 88.627970 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.465322 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.437516 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.697162 
final  value 91.824176 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.261932 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.255329 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.184246 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.865558 
final  value 94.052902 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.930934 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.632099 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.139644 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.200825 
iter  10 value 91.675405
final  value 91.653679 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.447007 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.497876 
iter  10 value 91.781468
iter  20 value 86.121916
iter  30 value 84.204580
iter  40 value 84.141680
iter  40 value 84.141680
iter  40 value 84.141680
final  value 84.141680 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.388556 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.407731 
iter  10 value 93.141412
iter  20 value 93.122067
final  value 93.122019 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.758576 
iter  10 value 94.056766
iter  20 value 93.714938
iter  30 value 84.996981
iter  40 value 84.684889
iter  50 value 82.794377
iter  60 value 82.712049
iter  70 value 82.051514
iter  80 value 81.842617
iter  90 value 81.584151
iter 100 value 81.265128
final  value 81.265128 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.176595 
iter  10 value 94.056658
iter  20 value 93.195727
iter  30 value 85.373037
iter  40 value 84.796649
iter  50 value 83.352517
iter  60 value 83.216084
iter  70 value 83.099324
iter  80 value 82.722312
iter  90 value 82.490696
iter 100 value 82.030880
final  value 82.030880 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.118972 
iter  10 value 94.085811
iter  20 value 94.054995
iter  30 value 93.997362
iter  40 value 93.246047
iter  50 value 91.990038
iter  60 value 91.813312
iter  70 value 91.774563
iter  80 value 90.959060
iter  90 value 86.589499
iter 100 value 84.371397
final  value 84.371397 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.329553 
iter  10 value 94.040207
iter  20 value 92.352252
iter  30 value 84.937483
iter  40 value 82.792268
iter  50 value 81.794452
iter  60 value 81.509353
iter  70 value 81.269525
final  value 81.267554 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.344625 
iter  10 value 94.058641
iter  20 value 92.266138
iter  30 value 90.597228
iter  40 value 83.331073
iter  50 value 82.750806
iter  60 value 82.315868
iter  70 value 81.990518
iter  80 value 81.604708
iter  90 value 81.552183
iter 100 value 81.526302
final  value 81.526302 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.618883 
iter  10 value 93.581710
iter  20 value 86.566675
iter  30 value 84.755402
iter  40 value 84.675441
iter  50 value 82.575604
iter  60 value 81.528278
iter  70 value 81.219524
iter  80 value 81.186693
iter  90 value 81.143803
iter 100 value 81.057060
final  value 81.057060 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.349217 
iter  10 value 92.804988
iter  20 value 85.102179
iter  30 value 83.925385
iter  40 value 82.717650
iter  50 value 81.539988
iter  60 value 81.281518
iter  70 value 81.195928
iter  80 value 80.911077
iter  90 value 80.480075
iter 100 value 80.361645
final  value 80.361645 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.805910 
iter  10 value 89.994545
iter  20 value 83.332370
iter  30 value 82.965919
iter  40 value 82.452393
iter  50 value 82.325383
iter  60 value 81.566469
iter  70 value 81.340854
iter  80 value 81.311731
iter  90 value 81.308379
iter 100 value 81.209610
final  value 81.209610 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.861427 
iter  10 value 93.690210
iter  20 value 84.423353
iter  30 value 83.223968
iter  40 value 82.591000
iter  50 value 82.147107
iter  60 value 81.343319
iter  70 value 80.563797
iter  80 value 80.049103
iter  90 value 80.024565
iter 100 value 79.999490
final  value 79.999490 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.472369 
iter  10 value 94.099705
iter  20 value 93.996445
iter  30 value 83.771279
iter  40 value 83.172823
iter  50 value 82.147007
iter  60 value 81.042150
iter  70 value 80.654469
iter  80 value 80.527396
iter  90 value 80.438968
iter 100 value 80.402130
final  value 80.402130 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.020863 
iter  10 value 94.008563
iter  20 value 90.492318
iter  30 value 84.716075
iter  40 value 83.385880
iter  50 value 82.178699
iter  60 value 81.225446
iter  70 value 80.560086
iter  80 value 80.322699
iter  90 value 80.107587
iter 100 value 79.908894
final  value 79.908894 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.767740 
iter  10 value 93.840314
iter  20 value 84.311517
iter  30 value 82.660829
iter  40 value 81.436542
iter  50 value 80.336924
iter  60 value 80.174559
iter  70 value 79.872511
iter  80 value 79.690010
iter  90 value 79.598393
iter 100 value 79.527682
final  value 79.527682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.253523 
iter  10 value 93.529270
iter  20 value 92.388103
iter  30 value 84.048195
iter  40 value 82.330449
iter  50 value 82.121741
iter  60 value 81.770288
iter  70 value 81.239456
iter  80 value 80.788529
iter  90 value 80.412895
iter 100 value 80.344917
final  value 80.344917 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.147452 
iter  10 value 93.623887
iter  20 value 82.623693
iter  30 value 81.101604
iter  40 value 80.398214
iter  50 value 80.194220
iter  60 value 80.054720
iter  70 value 79.773614
iter  80 value 79.671074
iter  90 value 79.658503
iter 100 value 79.640969
final  value 79.640969 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.634800 
iter  10 value 91.396049
iter  20 value 86.091135
iter  30 value 84.590218
iter  40 value 82.033884
iter  50 value 80.917301
iter  60 value 80.542711
iter  70 value 80.397772
iter  80 value 80.275914
iter  90 value 80.136135
iter 100 value 80.020945
final  value 80.020945 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.746383 
final  value 94.054396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.573817 
final  value 94.054906 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.911714 
final  value 94.054625 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.027706 
iter  10 value 94.007517
iter  20 value 93.980434
iter  30 value 93.964684
final  value 93.964659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.087891 
iter  10 value 82.190119
iter  20 value 81.846792
iter  30 value 81.842847
iter  40 value 81.683676
final  value 81.551853 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.224111 
iter  10 value 93.596940
iter  20 value 88.614845
iter  30 value 88.609037
iter  40 value 88.525313
iter  50 value 87.391083
iter  60 value 87.051980
iter  70 value 87.048044
iter  80 value 86.881979
iter  90 value 86.754812
iter 100 value 86.754624
final  value 86.754624 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.786255 
iter  10 value 93.548258
iter  20 value 93.465761
iter  30 value 93.365519
iter  40 value 91.099132
iter  50 value 83.572490
final  value 83.572453 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.690006 
iter  10 value 94.057502
iter  20 value 93.954930
iter  30 value 83.518096
iter  40 value 83.512545
iter  50 value 82.218153
iter  60 value 81.749239
iter  70 value 81.546492
iter  80 value 81.337631
iter  90 value 80.954552
iter 100 value 79.574883
final  value 79.574883 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.151762 
iter  10 value 93.270755
iter  20 value 91.596113
iter  30 value 91.581881
iter  40 value 91.580671
final  value 91.580612 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.980957 
iter  10 value 93.814011
iter  20 value 93.810391
iter  30 value 93.808960
iter  40 value 90.554087
final  value 90.410595 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.177905 
iter  10 value 93.844144
iter  20 value 93.836963
final  value 93.836292 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.448268 
iter  10 value 94.059409
iter  20 value 94.002185
iter  30 value 83.058857
iter  40 value 81.477271
iter  50 value 81.312626
iter  60 value 81.107862
iter  70 value 80.904831
iter  80 value 80.392790
iter  90 value 80.382023
iter 100 value 80.111414
final  value 80.111414 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.704672 
iter  10 value 88.546546
iter  20 value 84.356604
iter  30 value 84.113909
iter  40 value 83.904761
iter  50 value 83.871413
iter  60 value 83.869002
iter  70 value 83.866171
iter  80 value 83.688334
iter  90 value 83.685582
iter 100 value 83.573151
final  value 83.573151 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.058110 
iter  10 value 94.060882
iter  20 value 94.052946
iter  30 value 94.008066
iter  40 value 86.729545
iter  50 value 84.854895
iter  60 value 83.533406
iter  70 value 83.523541
iter  80 value 83.134151
iter  90 value 83.121051
iter 100 value 82.124334
final  value 82.124334 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.559486 
iter  10 value 94.061255
iter  20 value 94.046880
iter  30 value 92.752840
iter  40 value 92.706531
iter  50 value 92.584057
iter  60 value 92.526089
iter  70 value 90.590463
iter  80 value 89.851995
iter  90 value 83.884652
iter 100 value 83.313012
final  value 83.313012 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.585993 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.381778 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.332791 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.411731 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.460014 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.632991 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.705348 
final  value 94.052912 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.555089 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.141233 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.995142 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.878787 
iter  10 value 85.335187
iter  20 value 83.458766
final  value 83.422018 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.320929 
iter  10 value 85.573373
final  value 85.321378 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.279884 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.686367 
final  value 93.714286 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.588784 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.850535 
iter  10 value 94.054841
iter  20 value 93.807474
iter  30 value 91.574647
iter  40 value 86.635398
iter  50 value 81.781944
iter  60 value 80.615823
iter  70 value 80.311764
iter  80 value 80.277989
iter  90 value 80.169322
iter 100 value 80.145815
final  value 80.145815 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.130407 
iter  10 value 93.981598
iter  20 value 86.087032
iter  30 value 84.474563
iter  40 value 84.134853
iter  50 value 83.856031
iter  60 value 83.430302
iter  70 value 83.341804
iter  80 value 82.975621
iter  90 value 82.868333
final  value 82.867551 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.930341 
iter  10 value 89.984793
iter  20 value 84.715754
iter  30 value 83.073650
iter  40 value 82.755994
iter  50 value 82.573037
iter  60 value 82.559455
final  value 82.559278 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.772071 
iter  10 value 93.914163
iter  20 value 87.270935
iter  30 value 84.765951
iter  40 value 84.696777
iter  50 value 84.119931
iter  60 value 83.938365
iter  70 value 83.354169
iter  80 value 82.948724
iter  90 value 82.873761
iter 100 value 82.867551
final  value 82.867551 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.772549 
iter  10 value 94.005476
iter  20 value 92.133934
iter  30 value 86.129490
iter  40 value 84.817594
iter  50 value 82.382387
iter  60 value 80.465860
iter  70 value 80.291582
iter  80 value 80.202249
iter  90 value 80.130296
iter 100 value 79.978780
final  value 79.978780 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.747928 
iter  10 value 92.801701
iter  20 value 84.269010
iter  30 value 81.721224
iter  40 value 80.343635
iter  50 value 79.459979
iter  60 value 78.921474
iter  70 value 78.733500
iter  80 value 78.645109
iter  90 value 78.514478
iter 100 value 78.431527
final  value 78.431527 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.944508 
iter  10 value 94.048478
iter  20 value 89.877910
iter  30 value 84.326551
iter  40 value 80.387614
iter  50 value 78.788073
iter  60 value 78.509557
iter  70 value 78.075400
iter  80 value 77.969981
iter  90 value 77.959910
iter 100 value 77.957822
final  value 77.957822 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.118414 
iter  10 value 93.918046
iter  20 value 85.444309
iter  30 value 83.888712
iter  40 value 83.475915
iter  50 value 83.146482
iter  60 value 82.838783
iter  70 value 82.383530
iter  80 value 82.336843
iter  90 value 82.306513
iter 100 value 81.566451
final  value 81.566451 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.911372 
iter  10 value 94.075590
iter  20 value 88.558802
iter  30 value 86.691263
iter  40 value 85.989256
iter  50 value 85.393353
iter  60 value 85.070639
iter  70 value 82.489066
iter  80 value 81.063161
iter  90 value 80.168948
iter 100 value 80.067416
final  value 80.067416 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.964343 
iter  10 value 94.090625
iter  20 value 93.016083
iter  30 value 83.367418
iter  40 value 82.100492
iter  50 value 81.423806
iter  60 value 81.293943
iter  70 value 81.066877
iter  80 value 80.747119
iter  90 value 80.478453
iter 100 value 80.348142
final  value 80.348142 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.391866 
iter  10 value 94.455971
iter  20 value 93.979767
iter  30 value 92.641457
iter  40 value 92.000093
iter  50 value 91.235384
iter  60 value 84.000297
iter  70 value 81.039682
iter  80 value 79.617604
iter  90 value 79.032769
iter 100 value 78.639745
final  value 78.639745 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.540428 
iter  10 value 94.707765
iter  20 value 93.730246
iter  30 value 90.347200
iter  40 value 85.629398
iter  50 value 85.222389
iter  60 value 84.891911
iter  70 value 84.760954
iter  80 value 84.704025
iter  90 value 82.616636
iter 100 value 81.285472
final  value 81.285472 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.287816 
iter  10 value 91.215431
iter  20 value 86.986251
iter  30 value 85.681812
iter  40 value 85.114651
iter  50 value 83.745786
iter  60 value 82.341443
iter  70 value 81.622011
iter  80 value 80.617998
iter  90 value 80.114312
iter 100 value 79.735166
final  value 79.735166 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.076754 
iter  10 value 95.033313
iter  20 value 93.187601
iter  30 value 85.848531
iter  40 value 84.370127
iter  50 value 82.570587
iter  60 value 80.926808
iter  70 value 80.458271
iter  80 value 79.400756
iter  90 value 78.837436
iter 100 value 78.622249
final  value 78.622249 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.615527 
iter  10 value 93.874698
iter  20 value 88.207152
iter  30 value 86.336146
iter  40 value 85.786315
iter  50 value 85.166952
iter  60 value 85.061668
iter  70 value 84.896032
iter  80 value 83.929196
iter  90 value 81.135668
iter 100 value 80.828350
final  value 80.828350 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.408149 
final  value 94.054376 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.513277 
final  value 94.054707 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.255633 
final  value 94.010446 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.418737 
iter  10 value 94.054264
iter  20 value 94.052915
iter  30 value 93.762895
final  value 93.762887 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.535823 
final  value 94.054502 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.653094 
iter  10 value 94.013624
iter  20 value 93.603121
iter  30 value 87.613179
final  value 87.613044 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.481737 
iter  10 value 94.057113
iter  20 value 92.505348
iter  30 value 86.640055
iter  40 value 85.215425
iter  50 value 85.172249
iter  60 value 85.170359
iter  60 value 85.170358
iter  60 value 85.170358
final  value 85.170358 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.607723 
iter  10 value 94.014128
iter  20 value 94.005806
iter  30 value 93.764085
iter  40 value 84.191065
iter  50 value 83.398095
final  value 83.396807 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.214786 
iter  10 value 94.058126
iter  20 value 93.807689
iter  30 value 87.016281
iter  40 value 85.689779
iter  50 value 85.495103
iter  60 value 84.703142
iter  70 value 84.278610
final  value 84.278539 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.235684 
iter  10 value 85.271210
iter  20 value 85.189666
iter  30 value 85.187449
iter  40 value 84.567697
iter  50 value 84.289610
iter  60 value 84.287938
iter  70 value 84.254688
iter  80 value 81.621356
iter  90 value 81.183731
iter 100 value 80.320963
final  value 80.320963 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.614744 
iter  10 value 94.061129
iter  20 value 94.044936
iter  30 value 93.948301
iter  40 value 86.353554
iter  50 value 86.348147
iter  60 value 86.347412
iter  70 value 86.347044
iter  80 value 86.338534
iter  90 value 85.820348
iter 100 value 83.565337
final  value 83.565337 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.629854 
iter  10 value 94.061728
iter  20 value 94.054770
iter  30 value 92.879574
iter  40 value 84.576740
iter  50 value 82.846532
iter  60 value 78.682906
iter  70 value 78.249792
iter  80 value 77.496124
iter  90 value 76.915181
iter 100 value 76.592201
final  value 76.592201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.515378 
iter  10 value 94.059784
iter  20 value 92.759588
iter  30 value 83.940555
iter  40 value 83.926279
iter  50 value 83.915261
iter  60 value 83.890539
iter  70 value 82.512504
iter  80 value 82.510961
iter  90 value 82.508847
iter 100 value 82.508585
final  value 82.508585 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.124881 
iter  10 value 94.016118
iter  20 value 93.792278
iter  30 value 86.645271
iter  40 value 84.801059
iter  50 value 83.913845
iter  60 value 83.912530
iter  70 value 83.516915
iter  80 value 82.719368
iter  90 value 80.123481
iter 100 value 78.689498
final  value 78.689498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.634736 
iter  10 value 94.060357
iter  20 value 93.785352
iter  30 value 93.762861
iter  40 value 93.761247
final  value 93.761237 
converged
Fitting Repeat 1 

# weights:  305
initial  value 132.543269 
iter  10 value 117.902255
iter  20 value 117.896401
iter  30 value 117.517938
iter  40 value 117.514346
iter  50 value 117.463619
iter  60 value 117.457505
iter  60 value 117.457505
final  value 117.457505 
converged
Fitting Repeat 2 

# weights:  305
initial  value 132.999979 
iter  10 value 117.554326
iter  20 value 117.550010
iter  30 value 117.500576
iter  40 value 113.841703
iter  50 value 113.770036
iter  60 value 113.768630
final  value 113.768584 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.128903 
iter  10 value 117.891447
iter  20 value 107.050116
final  value 106.777560 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.758114 
iter  10 value 117.763512
iter  20 value 117.616447
iter  30 value 116.192404
iter  40 value 107.044734
iter  50 value 107.005293
iter  60 value 106.446100
iter  70 value 105.360110
iter  80 value 105.359311
final  value 105.358313 
converged
Fitting Repeat 5 

# weights:  305
initial  value 135.126205 
iter  10 value 117.575628
iter  20 value 117.572536
iter  30 value 117.571584
iter  40 value 117.570892
iter  50 value 117.570622
final  value 117.570564 
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 -- Fri Jan 24 05:57:01 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 42.883   1.596 122.946