##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 alpha (2026-04-08 r89818)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-04-18 00:13:26 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
corr_plot     17.138  0.104  17.291
var_imp       16.993  0.137  17.249
FSmethod      17.001  0.078  17.128
pred_ensembel  6.201  0.174   5.693
enrichfindP    0.205  0.042   7.334
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.23-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/4.6/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** 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 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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 102.205868 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.108321 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.893368 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.799656 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.501396 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 93.920041 
iter  10 value 89.512320
iter  20 value 85.554806
iter  30 value 85.177400
iter  40 value 85.119029
final  value 85.089396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.256586 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.416786 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.325295 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.143680 
iter  10 value 93.394936
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.604768 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.600492 
iter  10 value 92.117780
iter  20 value 91.818846
iter  30 value 91.782431
final  value 91.781957 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.748688 
final  value 94.428839 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.241772 
iter  10 value 92.592109
iter  20 value 92.591670
final  value 92.591667 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.717888 
iter  10 value 89.955668
iter  20 value 89.697383
iter  30 value 89.695257
final  value 89.695239 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.051393 
iter  10 value 94.466065
iter  20 value 93.726068
iter  30 value 93.703286
iter  40 value 93.609618
iter  50 value 93.355455
iter  60 value 89.974747
iter  70 value 87.136379
iter  80 value 87.053469
iter  90 value 86.103140
iter 100 value 85.898728
final  value 85.898728 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.276053 
iter  10 value 94.486179
iter  20 value 93.753013
iter  30 value 93.680938
iter  40 value 92.751913
iter  50 value 87.891046
iter  60 value 86.874986
iter  70 value 86.465850
iter  80 value 86.060818
iter  90 value 85.902871
iter 100 value 85.868082
final  value 85.868082 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 110.062273 
iter  10 value 94.405617
iter  20 value 93.153057
iter  30 value 86.506099
iter  40 value 85.909817
iter  50 value 85.867961
final  value 85.867793 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.732192 
iter  10 value 94.434243
iter  20 value 93.576692
iter  30 value 93.353458
iter  40 value 93.242230
iter  50 value 92.572803
iter  60 value 86.816378
iter  70 value 84.363124
iter  80 value 84.010144
iter  90 value 83.625707
iter 100 value 83.091047
final  value 83.091047 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.900835 
iter  10 value 94.486459
iter  20 value 93.847833
iter  30 value 93.678749
iter  40 value 93.661790
iter  50 value 93.316124
iter  60 value 90.093238
iter  70 value 86.351688
iter  80 value 85.274461
iter  90 value 84.589844
iter 100 value 83.897473
final  value 83.897473 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.551133 
iter  10 value 95.019425
iter  20 value 93.333499
iter  30 value 90.654163
iter  40 value 86.753759
iter  50 value 86.252324
iter  60 value 85.889607
iter  70 value 83.421480
iter  80 value 82.745012
iter  90 value 81.791281
iter 100 value 81.489092
final  value 81.489092 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.304424 
iter  10 value 94.495968
iter  20 value 94.486197
iter  30 value 93.694571
iter  40 value 88.611678
iter  50 value 87.775597
iter  60 value 86.172667
iter  70 value 85.429072
iter  80 value 85.205932
iter  90 value 84.626253
iter 100 value 83.475068
final  value 83.475068 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.460130 
iter  10 value 87.635441
iter  20 value 86.852849
iter  30 value 85.946247
iter  40 value 85.855216
iter  50 value 85.662176
iter  60 value 85.588459
iter  70 value 85.467745
iter  80 value 83.989903
iter  90 value 83.191071
iter 100 value 82.986489
final  value 82.986489 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.585480 
iter  10 value 92.114864
iter  20 value 88.963269
iter  30 value 86.027954
iter  40 value 84.000939
iter  50 value 83.347002
iter  60 value 83.050419
iter  70 value 83.011296
iter  80 value 82.645160
iter  90 value 82.087884
iter 100 value 81.918753
final  value 81.918753 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.008877 
iter  10 value 94.616526
iter  20 value 89.121185
iter  30 value 86.589282
iter  40 value 85.925125
iter  50 value 85.366388
iter  60 value 84.875900
iter  70 value 84.504152
iter  80 value 83.718434
iter  90 value 82.631083
iter 100 value 82.199631
final  value 82.199631 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.039873 
iter  10 value 94.007116
iter  20 value 93.352248
iter  30 value 91.672407
iter  40 value 88.255383
iter  50 value 84.602977
iter  60 value 83.733016
iter  70 value 83.254517
iter  80 value 82.742194
iter  90 value 82.432826
iter 100 value 82.230503
final  value 82.230503 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.223321 
iter  10 value 94.678758
iter  20 value 88.657020
iter  30 value 86.440276
iter  40 value 86.027929
iter  50 value 85.471484
iter  60 value 85.109058
iter  70 value 84.801260
iter  80 value 84.064119
iter  90 value 83.880943
iter 100 value 82.952147
final  value 82.952147 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.831293 
iter  10 value 94.099871
iter  20 value 90.175466
iter  30 value 87.180112
iter  40 value 86.062153
iter  50 value 85.503923
iter  60 value 85.331439
iter  70 value 84.987613
iter  80 value 84.383398
iter  90 value 83.932096
iter 100 value 83.645023
final  value 83.645023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.004750 
iter  10 value 95.500040
iter  20 value 93.689303
iter  30 value 87.843843
iter  40 value 86.562612
iter  50 value 83.970991
iter  60 value 82.970244
iter  70 value 82.776634
iter  80 value 82.592827
iter  90 value 82.263026
iter 100 value 82.112523
final  value 82.112523 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.683530 
iter  10 value 94.313288
iter  20 value 93.652041
iter  30 value 93.003695
iter  40 value 90.892581
iter  50 value 87.807104
iter  60 value 86.568679
iter  70 value 85.344475
iter  80 value 84.608950
iter  90 value 83.216333
iter 100 value 82.921849
final  value 82.921849 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.657903 
final  value 94.486092 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.195933 
final  value 94.485852 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.527087 
final  value 94.485890 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.859621 
iter  10 value 93.563044
iter  20 value 93.560266
iter  30 value 93.364579
iter  40 value 93.078752
final  value 93.059293 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.850950 
final  value 94.485713 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.396764 
iter  10 value 94.489039
iter  20 value 94.484270
final  value 94.484238 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.347150 
iter  10 value 94.489118
iter  20 value 94.484235
iter  30 value 93.071378
iter  40 value 92.218400
final  value 92.214976 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.141740 
iter  10 value 94.488698
iter  20 value 94.481946
iter  30 value 93.268236
iter  40 value 89.939335
final  value 89.934568 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.532539 
iter  10 value 94.489421
iter  20 value 94.484302
iter  30 value 93.396321
final  value 93.396152 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.275964 
iter  10 value 94.489064
iter  20 value 94.453036
iter  30 value 90.659085
iter  40 value 87.570977
iter  50 value 85.772305
iter  60 value 85.727122
iter  70 value 85.725856
final  value 85.725854 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.112030 
iter  10 value 94.492121
iter  20 value 93.454168
iter  30 value 88.895596
iter  40 value 85.489019
iter  50 value 85.227903
iter  60 value 85.183104
iter  70 value 85.168479
iter  80 value 85.067918
iter  90 value 84.829025
iter 100 value 84.812320
final  value 84.812320 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.909717 
iter  10 value 91.867250
iter  20 value 91.696924
iter  30 value 91.692541
iter  40 value 87.816250
iter  50 value 87.473899
iter  60 value 87.465327
iter  70 value 86.359056
iter  80 value 86.356683
iter  90 value 84.165448
iter 100 value 84.102577
final  value 84.102577 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.383910 
iter  10 value 93.406141
iter  20 value 93.401520
iter  30 value 93.236534
iter  40 value 93.060952
iter  50 value 93.060637
iter  60 value 93.058890
iter  70 value 92.737080
iter  80 value 85.479113
iter  90 value 84.296185
iter 100 value 84.089037
final  value 84.089037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.981198 
iter  10 value 94.493038
iter  20 value 94.484163
iter  30 value 93.397559
iter  40 value 93.396191
final  value 93.395628 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.375249 
iter  10 value 94.131822
iter  20 value 94.120171
iter  30 value 93.496932
iter  40 value 88.317527
iter  50 value 87.961678
iter  60 value 87.654959
iter  70 value 87.648991
iter  80 value 87.646999
iter  90 value 87.646479
iter  90 value 87.646479
iter  90 value 87.646479
final  value 87.646479 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.277487 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.552404 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.836760 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.332059 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.650345 
iter  10 value 93.648462
final  value 93.647673 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.934590 
iter  10 value 93.904720
iter  10 value 93.904720
iter  10 value 93.904720
final  value 93.904720 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.587687 
final  value 93.842773 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.375166 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.592381 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.838618 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.680407 
iter  10 value 91.715089
iter  20 value 91.714401
final  value 91.714400 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.107410 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.644135 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.264998 
iter  10 value 91.718799
final  value 91.714401 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.996157 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.986043 
iter  10 value 94.067959
iter  20 value 94.047867
iter  30 value 93.871151
iter  40 value 93.644857
iter  50 value 93.565697
iter  60 value 85.677605
iter  70 value 83.767702
iter  80 value 83.707962
iter  90 value 83.676987
iter 100 value 83.514976
final  value 83.514976 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.586023 
iter  10 value 94.055323
iter  20 value 93.631444
iter  30 value 91.568193
iter  40 value 85.055934
iter  50 value 84.268914
iter  60 value 83.836988
iter  70 value 83.498690
iter  80 value 83.478764
final  value 83.478659 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.023972 
iter  10 value 94.065771
iter  20 value 93.945832
iter  30 value 85.893153
iter  40 value 84.070463
iter  50 value 83.901479
iter  60 value 83.611256
iter  70 value 83.463572
iter  80 value 83.423005
final  value 83.422481 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.970085 
iter  10 value 94.037749
iter  20 value 93.733481
iter  30 value 93.619258
iter  40 value 84.556632
iter  50 value 83.397654
iter  60 value 83.338669
iter  70 value 83.308623
iter  70 value 83.308622
iter  70 value 83.308622
final  value 83.308622 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.355169 
iter  10 value 94.055135
iter  20 value 88.565825
iter  30 value 88.016860
iter  40 value 86.799341
iter  50 value 85.872973
iter  60 value 83.206705
iter  70 value 82.031722
iter  80 value 81.841552
iter  90 value 81.672008
iter 100 value 81.606989
final  value 81.606989 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.779288 
iter  10 value 93.899048
iter  20 value 93.493479
iter  30 value 89.229122
iter  40 value 86.005380
iter  50 value 84.808472
iter  60 value 83.669156
iter  70 value 81.458120
iter  80 value 80.926316
iter  90 value 80.715287
iter 100 value 80.589526
final  value 80.589526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.819637 
iter  10 value 91.924087
iter  20 value 86.637156
iter  30 value 86.299438
iter  40 value 85.867049
iter  50 value 84.859518
iter  60 value 83.859193
iter  70 value 83.727798
iter  80 value 82.828128
iter  90 value 82.209756
iter 100 value 81.926347
final  value 81.926347 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.717718 
iter  10 value 94.062249
iter  20 value 93.697078
iter  30 value 85.799792
iter  40 value 84.995578
iter  50 value 84.473170
iter  60 value 83.586808
iter  70 value 83.498578
iter  80 value 83.276445
iter  90 value 82.874726
iter 100 value 82.479721
final  value 82.479721 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 130.883600 
iter  10 value 93.241247
iter  20 value 84.644853
iter  30 value 84.190915
iter  40 value 83.854098
iter  50 value 82.179716
iter  60 value 81.907348
iter  70 value 81.481693
iter  80 value 81.424033
iter  90 value 80.660598
iter 100 value 80.455672
final  value 80.455672 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.742251 
iter  10 value 94.032081
iter  20 value 87.645894
iter  30 value 84.776255
iter  40 value 84.144708
iter  50 value 83.849763
iter  60 value 83.721564
iter  70 value 83.369738
iter  80 value 83.257881
iter  90 value 83.250127
iter 100 value 83.026428
final  value 83.026428 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.616331 
iter  10 value 94.452302
iter  20 value 92.466451
iter  30 value 84.768544
iter  40 value 84.319751
iter  50 value 84.086871
iter  60 value 83.062908
iter  70 value 82.549985
iter  80 value 81.404806
iter  90 value 81.150435
iter 100 value 81.038413
final  value 81.038413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.153002 
iter  10 value 94.161880
iter  20 value 87.689744
iter  30 value 86.317677
iter  40 value 83.800076
iter  50 value 83.292334
iter  60 value 83.043094
iter  70 value 82.579172
iter  80 value 81.813727
iter  90 value 81.547217
iter 100 value 81.103384
final  value 81.103384 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.471150 
iter  10 value 94.087320
iter  20 value 93.532351
iter  30 value 87.770619
iter  40 value 85.251843
iter  50 value 84.193159
iter  60 value 83.920986
iter  70 value 82.038142
iter  80 value 81.418339
iter  90 value 80.794585
iter 100 value 80.720062
final  value 80.720062 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.347380 
iter  10 value 96.272371
iter  20 value 88.740623
iter  30 value 87.829283
iter  40 value 84.648934
iter  50 value 82.542761
iter  60 value 82.040111
iter  70 value 81.919171
iter  80 value 81.722358
iter  90 value 81.447063
iter 100 value 80.763321
final  value 80.763321 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.725438 
iter  10 value 87.341931
iter  20 value 86.103720
iter  30 value 85.659734
iter  40 value 85.384028
iter  50 value 84.595143
iter  60 value 83.426042
iter  70 value 82.127429
iter  80 value 81.012216
iter  90 value 80.853969
iter 100 value 80.638283
final  value 80.638283 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.549637 
final  value 94.054496 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.181018 
iter  10 value 94.054692
iter  20 value 94.052874
iter  30 value 87.649599
iter  40 value 83.040076
iter  50 value 82.718694
iter  60 value 82.716959
final  value 82.716635 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.191942 
iter  10 value 89.399827
iter  20 value 87.004007
iter  30 value 85.509203
iter  30 value 85.509203
iter  30 value 85.509202
final  value 85.509202 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.111010 
final  value 94.054462 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.959941 
iter  10 value 94.054605
iter  20 value 94.005363
iter  30 value 93.672174
iter  40 value 93.671735
iter  50 value 93.632941
iter  60 value 93.626608
final  value 93.626574 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.492871 
iter  10 value 94.057624
iter  20 value 93.622141
iter  30 value 83.378586
iter  40 value 82.924399
iter  50 value 82.596910
final  value 82.596907 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.753244 
iter  10 value 93.967956
iter  20 value 85.459678
iter  30 value 85.374493
iter  40 value 85.370824
final  value 85.370608 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.041787 
iter  10 value 93.655778
iter  20 value 93.652179
iter  30 value 93.439971
iter  40 value 93.436907
iter  50 value 86.107049
iter  60 value 82.092439
iter  70 value 80.812325
iter  80 value 80.091670
iter  90 value 80.083021
iter 100 value 80.082239
final  value 80.082239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.540332 
iter  10 value 94.057922
iter  20 value 93.917636
iter  30 value 87.773644
iter  40 value 83.262880
iter  50 value 82.693673
iter  60 value 82.006516
iter  70 value 81.590267
iter  80 value 81.440367
final  value 81.439985 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.039361 
iter  10 value 93.864947
iter  20 value 93.854421
final  value 93.843043 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.285252 
iter  10 value 94.061270
iter  20 value 93.992753
iter  30 value 93.601524
final  value 93.596396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.361400 
iter  10 value 94.061089
iter  20 value 94.045105
iter  30 value 94.034973
iter  40 value 94.033965
iter  50 value 93.956233
iter  60 value 87.277320
iter  70 value 87.060794
iter  80 value 86.792711
iter  90 value 86.777108
iter 100 value 86.488416
final  value 86.488416 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.612396 
iter  10 value 94.061070
iter  20 value 94.053549
iter  30 value 92.531991
iter  40 value 85.363405
iter  50 value 84.545272
iter  60 value 83.520536
iter  70 value 83.494885
iter  80 value 82.503667
iter  90 value 80.848515
iter 100 value 79.115240
final  value 79.115240 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.001272 
iter  10 value 94.061284
iter  20 value 94.053450
iter  30 value 94.024409
iter  40 value 91.685774
iter  50 value 83.236854
iter  60 value 83.040091
iter  70 value 82.121197
iter  80 value 81.397491
iter  90 value 80.495323
iter 100 value 80.480515
final  value 80.480515 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.248058 
iter  10 value 93.857167
iter  20 value 93.547637
iter  30 value 93.544193
iter  40 value 84.760791
iter  50 value 83.128147
iter  60 value 83.014711
iter  70 value 82.704735
iter  80 value 81.980716
iter  90 value 80.486499
iter 100 value 79.606522
final  value 79.606522 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.654557 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.798538 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.259585 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.076071 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.876640 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.738640 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.474221 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.905331 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.664336 
iter  10 value 93.836066
iter  10 value 93.836066
iter  10 value 93.836066
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.179232 
iter  10 value 93.710458
final  value 93.704676 
converged
Fitting Repeat 1 

# weights:  507
initial  value 136.000653 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.905267 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.590274 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.913183 
iter  10 value 91.322826
iter  20 value 90.054612
iter  30 value 89.255482
iter  40 value 89.221968
iter  40 value 89.221968
final  value 89.221968 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.666290 
iter  10 value 93.836066
iter  10 value 93.836066
iter  10 value 93.836066
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.089728 
iter  10 value 93.830433
iter  20 value 92.019751
iter  30 value 89.388285
iter  40 value 89.057912
iter  50 value 87.364604
iter  60 value 85.755442
iter  70 value 84.049074
iter  80 value 84.002696
iter  90 value 83.479826
iter 100 value 82.769422
final  value 82.769422 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.768041 
iter  10 value 93.986998
iter  20 value 89.094208
iter  30 value 87.179295
iter  40 value 85.636564
iter  50 value 85.139016
iter  60 value 85.008697
iter  70 value 85.001901
iter  80 value 84.897735
iter  90 value 83.575997
iter 100 value 83.340878
final  value 83.340878 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.084543 
iter  10 value 93.936817
iter  20 value 90.057718
iter  30 value 85.379586
iter  40 value 84.537116
iter  50 value 84.082217
iter  60 value 83.883281
iter  70 value 83.763363
final  value 83.763355 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.981525 
iter  10 value 94.056907
iter  20 value 94.011296
iter  30 value 92.212520
iter  40 value 90.974349
iter  50 value 88.686869
iter  60 value 87.508025
iter  70 value 86.917920
iter  80 value 84.559532
iter  90 value 83.991759
iter 100 value 83.790220
final  value 83.790220 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.451102 
iter  10 value 93.892518
iter  20 value 87.149009
iter  30 value 84.736676
iter  40 value 84.575231
iter  50 value 83.951488
iter  60 value 83.817132
iter  70 value 83.442942
iter  80 value 83.336920
final  value 83.336843 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.227032 
iter  10 value 94.239730
iter  20 value 89.187586
iter  30 value 85.621058
iter  40 value 84.955613
iter  50 value 84.473313
iter  60 value 84.074165
iter  70 value 83.869960
iter  80 value 83.761846
iter  90 value 83.161424
iter 100 value 82.503173
final  value 82.503173 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.969629 
iter  10 value 92.497951
iter  20 value 89.109398
iter  30 value 88.687163
iter  40 value 88.392594
iter  50 value 86.854447
iter  60 value 83.989791
iter  70 value 82.979244
iter  80 value 82.689230
iter  90 value 82.174451
iter 100 value 81.723790
final  value 81.723790 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.082354 
iter  10 value 94.800333
iter  20 value 92.806990
iter  30 value 85.724604
iter  40 value 82.763711
iter  50 value 82.413661
iter  60 value 82.032692
iter  70 value 81.716498
iter  80 value 81.471404
iter  90 value 80.986066
iter 100 value 80.868336
final  value 80.868336 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.423810 
iter  10 value 93.769422
iter  20 value 90.045327
iter  30 value 87.151357
iter  40 value 83.586240
iter  50 value 82.352108
iter  60 value 82.254498
iter  70 value 82.209291
iter  80 value 81.956828
iter  90 value 81.478178
iter 100 value 81.105442
final  value 81.105442 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.343912 
iter  10 value 94.819391
iter  20 value 93.885644
iter  30 value 89.364043
iter  40 value 86.333965
iter  50 value 86.026043
iter  60 value 85.154454
iter  70 value 84.902619
iter  80 value 84.043478
iter  90 value 82.205973
iter 100 value 81.976335
final  value 81.976335 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.112435 
iter  10 value 95.708505
iter  20 value 89.648055
iter  30 value 87.915650
iter  40 value 86.029553
iter  50 value 83.404334
iter  60 value 82.646571
iter  70 value 82.109422
iter  80 value 81.756896
iter  90 value 81.483322
iter 100 value 81.372677
final  value 81.372677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.339227 
iter  10 value 94.127467
iter  20 value 91.004297
iter  30 value 86.334014
iter  40 value 84.765485
iter  50 value 83.927996
iter  60 value 83.593253
iter  70 value 82.505231
iter  80 value 81.850749
iter  90 value 81.669660
iter 100 value 81.289995
final  value 81.289995 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.384937 
iter  10 value 91.530964
iter  20 value 87.356696
iter  30 value 86.669509
iter  40 value 83.425564
iter  50 value 82.098111
iter  60 value 81.328003
iter  70 value 80.760542
iter  80 value 80.561968
iter  90 value 80.496562
iter 100 value 80.453186
final  value 80.453186 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.234763 
iter  10 value 94.214472
iter  20 value 89.098481
iter  30 value 87.396514
iter  40 value 85.613827
iter  50 value 84.561112
iter  60 value 83.397417
iter  70 value 82.403598
iter  80 value 81.793382
iter  90 value 81.510256
iter 100 value 81.113519
final  value 81.113519 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.822774 
iter  10 value 94.541785
iter  20 value 93.337795
iter  30 value 85.840811
iter  40 value 84.929268
iter  50 value 84.536997
iter  60 value 84.346657
iter  70 value 83.964472
iter  80 value 82.712283
iter  90 value 82.006066
iter 100 value 81.790545
final  value 81.790545 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.631105 
final  value 94.054679 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.576257 
iter  10 value 93.066993
iter  20 value 93.047682
final  value 93.047548 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.910137 
final  value 94.054426 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.005578 
iter  10 value 94.054520
iter  20 value 94.052967
final  value 94.052916 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.812918 
final  value 94.054671 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.739911 
iter  10 value 94.060853
iter  20 value 94.024361
iter  30 value 89.702516
iter  40 value 89.119391
iter  50 value 89.111975
iter  60 value 89.108416
iter  70 value 89.107731
iter  80 value 89.088088
iter  90 value 89.086308
iter 100 value 89.086280
final  value 89.086280 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.634388 
iter  10 value 94.058125
iter  20 value 94.053094
iter  30 value 91.376599
iter  40 value 88.689180
iter  50 value 88.547240
iter  60 value 88.518932
iter  70 value 88.518648
iter  80 value 88.516626
iter  90 value 88.516524
final  value 88.516522 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.396348 
iter  10 value 94.057505
iter  20 value 93.993079
iter  30 value 87.101234
iter  40 value 85.677131
iter  50 value 83.076740
iter  60 value 81.973401
iter  70 value 81.835558
final  value 81.835225 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.921729 
iter  10 value 94.057914
iter  20 value 94.052968
iter  30 value 93.937367
iter  40 value 89.503994
iter  50 value 88.752868
iter  60 value 85.680132
iter  70 value 83.723211
iter  80 value 83.042324
iter  90 value 82.753414
iter 100 value 82.085082
final  value 82.085082 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.125088 
iter  10 value 94.058774
iter  20 value 94.054125
final  value 94.053628 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.174781 
iter  10 value 86.210310
iter  20 value 85.688630
iter  30 value 84.519261
iter  40 value 84.499284
iter  50 value 84.486383
iter  60 value 84.436120
iter  70 value 84.436027
iter  80 value 84.434298
iter  90 value 83.293156
iter 100 value 83.005062
final  value 83.005062 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.146051 
iter  10 value 94.063086
iter  20 value 94.054521
iter  30 value 93.844407
iter  40 value 93.184552
iter  50 value 92.687590
iter  60 value 92.685912
iter  70 value 92.685518
iter  80 value 87.048305
iter  90 value 87.044586
final  value 87.044579 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.539252 
iter  10 value 93.844394
iter  20 value 93.836883
iter  30 value 93.836197
final  value 93.836188 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.060889 
iter  10 value 87.287594
iter  20 value 85.547362
iter  30 value 83.126346
iter  40 value 82.955007
iter  50 value 82.952566
iter  60 value 82.950669
iter  70 value 82.950195
iter  80 value 82.943754
iter  90 value 82.522205
iter 100 value 82.028170
final  value 82.028170 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.003588 
iter  10 value 93.850724
iter  20 value 93.843406
iter  30 value 93.796489
iter  40 value 87.241790
iter  50 value 84.469432
iter  60 value 81.292229
iter  70 value 80.804640
iter  80 value 80.652074
iter  90 value 80.612883
iter 100 value 80.430007
final  value 80.430007 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.540898 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.834383 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.995278 
final  value 94.443244 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.396616 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.821812 
iter  10 value 94.298933
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.704105 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.784667 
final  value 94.144480 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.062279 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.625779 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.561066 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.765944 
final  value 94.287626 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.636907 
iter  10 value 92.201217
iter  20 value 90.867090
iter  30 value 86.113096
iter  40 value 85.978212
iter  50 value 84.951731
iter  60 value 84.244502
final  value 84.240925 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.642233 
iter  10 value 94.443403
final  value 94.443246 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.468486 
iter  10 value 93.655692
iter  20 value 93.603739
final  value 93.603727 
converged
Fitting Repeat 5 

# weights:  507
initial  value 124.831308 
final  value 94.088889 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.373747 
iter  10 value 94.188963
iter  20 value 88.995702
iter  30 value 86.577193
iter  40 value 84.695446
iter  50 value 82.380182
iter  60 value 80.924410
iter  70 value 80.863158
final  value 80.862120 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.184508 
iter  10 value 90.175041
iter  20 value 85.869395
iter  30 value 85.287862
iter  40 value 84.303808
iter  50 value 84.297337
iter  60 value 84.297096
final  value 84.296978 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.035116 
iter  10 value 94.488612
iter  20 value 94.351413
iter  30 value 92.126723
iter  40 value 88.128027
iter  50 value 87.132022
iter  60 value 86.641485
iter  70 value 86.608545
iter  80 value 84.367214
iter  90 value 84.298596
iter 100 value 84.296982
final  value 84.296982 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.894387 
iter  10 value 94.462957
iter  20 value 94.057517
iter  30 value 83.476713
iter  40 value 82.670678
iter  50 value 82.101808
iter  60 value 81.494512
iter  70 value 80.980696
iter  80 value 80.806990
iter  90 value 80.709894
final  value 80.709889 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.120112 
iter  10 value 94.446470
iter  20 value 93.331098
iter  30 value 88.604440
iter  40 value 87.491588
iter  50 value 86.871011
iter  60 value 85.512110
iter  70 value 84.486042
iter  80 value 84.435346
final  value 84.435273 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.284314 
iter  10 value 94.444310
iter  20 value 92.800128
iter  30 value 87.851854
iter  40 value 86.489512
iter  50 value 85.358359
iter  60 value 82.990112
iter  70 value 81.444421
iter  80 value 81.043800
iter  90 value 80.742483
iter 100 value 80.576378
final  value 80.576378 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.707925 
iter  10 value 94.496356
iter  20 value 87.722831
iter  30 value 85.982423
iter  40 value 85.565083
iter  50 value 84.166811
iter  60 value 83.376421
iter  70 value 82.543946
iter  80 value 82.144165
iter  90 value 82.000441
iter 100 value 81.899523
final  value 81.899523 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.536803 
iter  10 value 94.487513
iter  20 value 88.184999
iter  30 value 83.638758
iter  40 value 82.487659
iter  50 value 81.993772
iter  60 value 81.754306
iter  70 value 81.332748
iter  80 value 81.132445
iter  90 value 80.521876
iter 100 value 80.012433
final  value 80.012433 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.273750 
iter  10 value 94.619227
iter  20 value 94.473344
iter  30 value 94.399225
iter  40 value 94.198707
iter  50 value 93.201861
iter  60 value 90.990345
iter  70 value 86.303678
iter  80 value 80.917888
iter  90 value 80.093516
iter 100 value 79.543804
final  value 79.543804 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.886921 
iter  10 value 94.481032
iter  20 value 93.967543
iter  30 value 89.050470
iter  40 value 87.889952
iter  50 value 87.747149
iter  60 value 87.426538
iter  70 value 86.639253
iter  80 value 86.606652
iter  90 value 83.754036
iter 100 value 81.554077
final  value 81.554077 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 134.054759 
iter  10 value 99.184375
iter  20 value 97.049662
iter  30 value 94.676058
iter  40 value 92.653089
iter  50 value 86.857253
iter  60 value 85.766481
iter  70 value 83.068576
iter  80 value 82.012566
iter  90 value 81.797556
iter 100 value 81.520868
final  value 81.520868 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.747932 
iter  10 value 98.851871
iter  20 value 87.961766
iter  30 value 82.999450
iter  40 value 81.154641
iter  50 value 80.105134
iter  60 value 80.004555
iter  70 value 79.828732
iter  80 value 79.414258
iter  90 value 78.967537
iter 100 value 78.859313
final  value 78.859313 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.805035 
iter  10 value 94.750527
iter  20 value 91.868515
iter  30 value 85.924095
iter  40 value 83.186577
iter  50 value 82.573728
iter  60 value 81.982098
iter  70 value 80.912437
iter  80 value 80.575968
iter  90 value 80.327942
iter 100 value 80.089941
final  value 80.089941 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.523392 
iter  10 value 94.525796
iter  20 value 94.384464
iter  30 value 88.705078
iter  40 value 86.428443
iter  50 value 83.532848
iter  60 value 81.745676
iter  70 value 80.486561
iter  80 value 80.218845
iter  90 value 80.061151
iter 100 value 79.917928
final  value 79.917928 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.204298 
iter  10 value 94.651554
iter  20 value 92.247420
iter  30 value 88.712569
iter  40 value 86.160780
iter  50 value 82.260074
iter  60 value 81.744679
iter  70 value 81.339692
iter  80 value 80.225427
iter  90 value 79.940214
iter 100 value 79.902024
final  value 79.902024 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.611589 
final  value 94.485623 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.803823 
final  value 94.485711 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.697851 
iter  10 value 92.432627
iter  20 value 91.866405
iter  30 value 91.866190
iter  40 value 91.666644
iter  50 value 91.666255
final  value 91.666244 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.846388 
final  value 94.485944 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.260799 
final  value 94.485699 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.944533 
iter  10 value 94.489014
iter  20 value 94.132440
iter  30 value 85.933499
iter  40 value 85.044209
iter  50 value 84.709030
iter  60 value 84.651459
iter  70 value 84.586516
iter  80 value 84.584166
iter  90 value 84.575852
iter 100 value 84.410470
final  value 84.410470 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.779120 
iter  10 value 94.222052
iter  20 value 94.219981
iter  30 value 94.177547
iter  40 value 94.175972
iter  50 value 94.175782
iter  60 value 94.175088
iter  70 value 94.080829
final  value 94.080827 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.544218 
iter  10 value 94.305544
iter  20 value 94.300980
iter  30 value 93.019600
iter  40 value 89.964712
iter  50 value 87.065379
iter  60 value 87.046439
iter  70 value 87.045153
iter  80 value 86.928512
iter  90 value 83.580868
iter 100 value 82.956751
final  value 82.956751 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.313928 
iter  10 value 94.113278
iter  20 value 94.108183
iter  30 value 94.093191
final  value 94.093015 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.742650 
iter  10 value 94.489071
iter  20 value 94.211468
iter  30 value 87.346638
iter  40 value 86.153471
iter  50 value 81.048085
iter  60 value 79.665655
iter  70 value 79.581713
iter  80 value 79.576769
final  value 79.576748 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.689037 
iter  10 value 93.882382
iter  20 value 93.876654
iter  30 value 93.744584
iter  40 value 93.610523
iter  50 value 92.637212
iter  60 value 85.236660
iter  70 value 84.929909
iter  80 value 84.889068
iter  90 value 84.879992
iter 100 value 83.656265
final  value 83.656265 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.848650 
iter  10 value 94.485140
iter  20 value 94.269150
iter  30 value 94.144895
iter  30 value 94.144895
iter  30 value 94.144895
final  value 94.144895 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.118142 
iter  10 value 94.375052
iter  20 value 94.368326
iter  30 value 92.087789
iter  40 value 87.344067
iter  50 value 87.341138
iter  60 value 86.006714
iter  70 value 85.935459
iter  80 value 85.934158
iter  90 value 85.772927
iter 100 value 83.378006
final  value 83.378006 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.970575 
iter  10 value 94.492048
iter  20 value 93.775771
iter  30 value 88.608133
iter  40 value 87.428351
iter  50 value 86.617780
iter  60 value 86.617408
final  value 86.617329 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.586993 
iter  10 value 94.493209
iter  20 value 94.212644
iter  30 value 86.998663
iter  40 value 85.564812
iter  50 value 81.862729
iter  60 value 79.820866
iter  70 value 78.693885
iter  80 value 78.631208
iter  90 value 78.619224
iter 100 value 78.619059
final  value 78.619059 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.587573 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.081090 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.251522 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.580824 
final  value 93.939078 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.896066 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.503864 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.738909 
iter  10 value 94.336273
iter  20 value 90.372161
iter  30 value 85.923669
iter  40 value 85.645514
final  value 85.645241 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.043038 
iter  10 value 94.313260
final  value 94.266137 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.747700 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.597566 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.367038 
iter  10 value 92.705519
iter  20 value 90.774005
iter  30 value 90.721094
final  value 90.720836 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.936491 
iter  10 value 93.414835
iter  20 value 93.256512
iter  30 value 93.210778
iter  40 value 93.209666
final  value 93.209614 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.717945 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.620225 
iter  10 value 94.354806
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.227250 
iter  10 value 93.683019
final  value 93.683015 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.641625 
iter  10 value 94.676670
iter  20 value 94.462879
iter  30 value 85.945410
iter  40 value 84.121918
iter  50 value 82.820132
iter  60 value 82.000249
iter  70 value 81.413390
iter  80 value 80.565469
iter  90 value 80.533336
iter 100 value 80.529932
final  value 80.529932 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.549485 
iter  10 value 94.487733
iter  20 value 92.911732
iter  30 value 92.382687
iter  40 value 91.973541
iter  50 value 91.706536
final  value 91.706147 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.627127 
iter  10 value 93.592432
iter  20 value 86.086791
iter  30 value 84.830387
iter  40 value 84.580001
iter  50 value 82.193804
iter  60 value 80.966574
iter  70 value 80.553738
iter  80 value 80.530271
final  value 80.529932 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.559961 
iter  10 value 92.508359
iter  20 value 84.640091
iter  30 value 84.386202
iter  40 value 83.781713
iter  50 value 82.061397
iter  60 value 80.585159
iter  70 value 80.064302
iter  80 value 79.994833
final  value 79.994758 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.283134 
iter  10 value 94.452068
iter  20 value 86.163702
iter  30 value 81.919180
iter  40 value 81.682474
iter  50 value 80.755016
iter  60 value 80.104513
iter  70 value 79.681918
final  value 79.675526 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.715277 
iter  10 value 90.268412
iter  20 value 86.003629
iter  30 value 82.504111
iter  40 value 81.937265
iter  50 value 81.643838
iter  60 value 81.472904
iter  70 value 80.177240
iter  80 value 78.919266
iter  90 value 77.421400
iter 100 value 76.662336
final  value 76.662336 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.459123 
iter  10 value 95.839670
iter  20 value 85.152114
iter  30 value 83.108533
iter  40 value 81.890157
iter  50 value 80.670195
iter  60 value 80.266360
iter  70 value 80.145284
iter  80 value 79.861921
iter  90 value 77.646521
iter 100 value 76.759017
final  value 76.759017 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.060433 
iter  10 value 93.851653
iter  20 value 87.925815
iter  30 value 80.612235
iter  40 value 79.232330
iter  50 value 78.805724
iter  60 value 78.247354
iter  70 value 77.027931
iter  80 value 76.470084
iter  90 value 76.275965
iter 100 value 76.270984
final  value 76.270984 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.978544 
iter  10 value 94.100878
iter  20 value 85.474880
iter  30 value 80.762804
iter  40 value 78.961428
iter  50 value 77.521958
iter  60 value 76.796867
iter  70 value 76.628797
iter  80 value 76.585967
iter  90 value 76.539934
iter 100 value 76.487580
final  value 76.487580 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.337336 
iter  10 value 91.296798
iter  20 value 82.785095
iter  30 value 80.297570
iter  40 value 78.384763
iter  50 value 77.092937
iter  60 value 76.961765
iter  70 value 76.909340
iter  80 value 76.900746
iter  90 value 76.873505
iter 100 value 76.660101
final  value 76.660101 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.814714 
iter  10 value 91.418111
iter  20 value 85.569525
iter  30 value 83.639681
iter  40 value 81.051409
iter  50 value 78.563179
iter  60 value 78.248237
iter  70 value 77.334602
iter  80 value 76.654737
iter  90 value 76.512798
iter 100 value 76.375796
final  value 76.375796 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 146.818024 
iter  10 value 91.724384
iter  20 value 84.979979
iter  30 value 81.852594
iter  40 value 80.792423
iter  50 value 79.664877
iter  60 value 79.182859
iter  70 value 77.272233
iter  80 value 76.696895
iter  90 value 76.454877
iter 100 value 76.158445
final  value 76.158445 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.855570 
iter  10 value 94.342729
iter  20 value 88.159709
iter  30 value 85.714612
iter  40 value 83.375040
iter  50 value 81.218833
iter  60 value 80.538323
iter  70 value 80.274334
iter  80 value 80.250732
iter  90 value 80.246141
iter 100 value 80.218994
final  value 80.218994 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.199949 
iter  10 value 94.241240
iter  20 value 90.102968
iter  30 value 84.715475
iter  40 value 83.327407
iter  50 value 81.970761
iter  60 value 81.222884
iter  70 value 80.713836
iter  80 value 80.193021
iter  90 value 79.846450
iter 100 value 79.290558
final  value 79.290558 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.720379 
iter  10 value 94.706546
iter  20 value 94.393001
iter  30 value 85.266999
iter  40 value 82.852429
iter  50 value 81.689905
iter  60 value 79.936724
iter  70 value 78.046910
iter  80 value 77.459251
iter  90 value 77.156578
iter 100 value 76.659092
final  value 76.659092 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.577685 
final  value 94.486033 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.352060 
final  value 94.355966 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.967209 
final  value 94.485761 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.771468 
final  value 94.485846 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.135920 
iter  10 value 92.396793
iter  20 value 91.978625
iter  30 value 91.950161
iter  40 value 91.780353
final  value 91.780142 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.862403 
iter  10 value 94.487688
iter  20 value 94.263448
iter  30 value 87.509810
iter  40 value 83.539983
iter  50 value 79.347654
iter  60 value 76.003024
iter  70 value 74.969223
iter  80 value 74.928367
iter  90 value 74.759284
iter 100 value 74.673812
final  value 74.673812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.434939 
iter  10 value 94.358970
iter  20 value 94.355501
iter  30 value 93.995568
iter  40 value 87.214945
iter  50 value 81.770593
iter  60 value 80.599821
iter  70 value 77.722558
iter  80 value 77.151256
iter  90 value 77.113341
iter 100 value 76.996244
final  value 76.996244 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.147774 
iter  10 value 93.851878
iter  20 value 91.496627
iter  30 value 80.876313
iter  40 value 79.118642
iter  50 value 78.984283
final  value 78.980415 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.867710 
iter  10 value 94.489044
iter  20 value 93.576637
iter  30 value 81.705404
iter  40 value 81.691789
iter  50 value 81.576349
iter  60 value 81.185768
iter  70 value 81.097833
iter  80 value 80.804423
iter  90 value 80.782032
iter 100 value 80.130860
final  value 80.130860 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.581629 
iter  10 value 94.488921
iter  20 value 94.358768
iter  30 value 87.901361
iter  40 value 81.028274
iter  50 value 80.442053
iter  60 value 78.846159
iter  70 value 78.815452
final  value 78.814637 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.600999 
iter  10 value 94.362665
iter  20 value 94.143997
iter  30 value 81.776514
final  value 81.744832 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.983334 
iter  10 value 94.362661
iter  20 value 92.366533
iter  30 value 80.927028
iter  40 value 80.363001
iter  50 value 80.312101
iter  60 value 80.311729
final  value 80.310782 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.788827 
iter  10 value 94.343419
iter  20 value 94.333397
iter  30 value 92.756129
iter  40 value 92.094278
iter  50 value 91.163199
iter  60 value 91.118835
final  value 91.118759 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.186537 
iter  10 value 94.362817
iter  20 value 93.630298
iter  30 value 93.628781
iter  40 value 93.622337
iter  50 value 92.748666
iter  60 value 90.683011
iter  70 value 90.678880
final  value 90.678872 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.848800 
iter  10 value 93.946743
iter  20 value 93.505604
iter  30 value 93.499071
iter  40 value 83.880215
iter  50 value 80.922121
iter  60 value 80.920491
iter  70 value 80.433465
iter  80 value 80.421958
iter  90 value 80.419400
final  value 80.419370 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.006831 
iter  10 value 117.308965
iter  20 value 116.883644
iter  30 value 116.880107
iter  40 value 116.878181
iter  50 value 116.725872
iter  60 value 106.589658
iter  70 value 103.636841
iter  80 value 102.700160
iter  90 value 102.684940
final  value 102.683757 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.880582 
iter  10 value 117.898293
iter  20 value 117.778749
iter  30 value 115.396632
iter  40 value 106.336704
iter  50 value 105.754694
iter  60 value 105.156788
iter  70 value 104.613624
iter  80 value 102.322825
iter  90 value 101.258503
iter 100 value 101.237031
final  value 101.237031 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 145.536238 
iter  10 value 117.767532
iter  20 value 115.959885
iter  30 value 108.129583
iter  40 value 104.150205
final  value 104.057080 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.172431 
iter  10 value 117.736519
iter  20 value 117.730534
iter  30 value 116.768455
iter  40 value 115.211553
iter  50 value 111.632325
iter  60 value 111.627160
iter  70 value 110.815238
iter  80 value 110.807930
final  value 110.807630 
converged
Fitting Repeat 5 

# weights:  507
initial  value 144.655828 
iter  10 value 111.362653
iter  20 value 104.556995
iter  30 value 103.810126
iter  40 value 103.599881
iter  50 value 103.597458
iter  60 value 103.594946
iter  70 value 103.594628
iter  80 value 103.594083
final  value 103.593846 
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 Apr 17 20:16:33 2026 
*********************************************** 
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 
 20.913   0.773  76.432