##############################################################################
##############################################################################
###
### 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 (2026-03-28 r89739)
* 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: 2026-04-04 00:14:00 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
var_imp       17.184  0.194  17.580
corr_plot     17.103  0.133  17.348
FSmethod      16.726  0.098  17.160
pred_ensembel  6.288  0.207   5.766
enrichfindP    0.208  0.045  12.474
* 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 (2026-03-28 r89739)
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 97.680195 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.623986 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.144052 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.982707 
final  value 94.323812 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.677795 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.142876 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.054852 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.582698 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.981398 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.117445 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.164020 
iter  10 value 94.354397
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.412240 
iter  10 value 92.968645
iter  20 value 84.488718
iter  30 value 84.451010
iter  40 value 84.011613
final  value 84.011208 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.540856 
iter  10 value 93.661518
final  value 93.659488 
converged
Fitting Repeat 4 

# weights:  507
initial  value 129.821877 
iter  10 value 94.484216
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.372370 
iter  10 value 94.234878
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.113273 
iter  10 value 94.505497
iter  20 value 94.258814
iter  30 value 91.413820
iter  40 value 84.063798
iter  50 value 83.430401
iter  60 value 82.438012
iter  70 value 82.099738
iter  80 value 81.928302
iter  90 value 81.841878
iter 100 value 81.822093
final  value 81.822093 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.676389 
iter  10 value 94.487536
iter  20 value 94.200706
iter  30 value 90.092476
iter  40 value 87.927632
iter  50 value 87.722929
iter  60 value 82.449041
iter  70 value 81.755578
iter  80 value 81.602877
iter  90 value 81.328632
iter 100 value 81.082652
final  value 81.082652 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 127.477555 
iter  10 value 91.056557
iter  20 value 87.211038
iter  30 value 85.193776
iter  40 value 84.032570
iter  50 value 83.476197
iter  60 value 83.331690
final  value 83.330406 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.778986 
iter  10 value 91.926710
iter  20 value 88.319574
iter  30 value 87.553732
iter  40 value 85.539873
iter  50 value 84.316326
iter  60 value 83.572426
iter  70 value 83.335098
iter  80 value 83.330134
final  value 83.329518 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.441293 
iter  10 value 94.510673
iter  20 value 94.486385
iter  30 value 93.756981
iter  40 value 93.688164
iter  50 value 87.406770
iter  60 value 86.642179
iter  70 value 86.033788
iter  80 value 85.893064
iter  90 value 83.921283
iter 100 value 83.770298
final  value 83.770298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.808543 
iter  10 value 94.329262
iter  20 value 89.334684
iter  30 value 85.242702
iter  40 value 84.475399
iter  50 value 83.691869
iter  60 value 81.526426
iter  70 value 81.193890
iter  80 value 80.495084
iter  90 value 80.300654
iter 100 value 80.170807
final  value 80.170807 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.588993 
iter  10 value 94.410317
iter  20 value 93.759342
iter  30 value 93.695485
iter  40 value 90.094408
iter  50 value 89.085183
iter  60 value 83.005253
iter  70 value 82.472169
iter  80 value 80.964426
iter  90 value 80.076166
iter 100 value 79.734989
final  value 79.734989 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.751301 
iter  10 value 86.657527
iter  20 value 83.518649
iter  30 value 81.948375
iter  40 value 81.003062
iter  50 value 80.033664
iter  60 value 79.907745
iter  70 value 79.886010
iter  80 value 79.789785
iter  90 value 79.656202
iter 100 value 79.541713
final  value 79.541713 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.855449 
iter  10 value 95.755290
iter  20 value 92.693456
iter  30 value 83.769865
iter  40 value 82.925064
iter  50 value 82.082685
iter  60 value 81.547638
iter  70 value 81.040937
iter  80 value 80.185823
iter  90 value 79.708746
iter 100 value 79.597268
final  value 79.597268 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.024531 
iter  10 value 94.489938
iter  20 value 94.459147
iter  30 value 92.003886
iter  40 value 85.352800
iter  50 value 84.431431
iter  60 value 82.947242
iter  70 value 81.533341
iter  80 value 81.353761
iter  90 value 80.881366
iter 100 value 80.511853
final  value 80.511853 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.848089 
iter  10 value 94.078366
iter  20 value 86.020625
iter  30 value 84.911483
iter  40 value 81.238189
iter  50 value 80.249723
iter  60 value 79.914413
iter  70 value 79.804844
iter  80 value 79.447236
iter  90 value 78.996185
iter 100 value 78.924940
final  value 78.924940 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.430135 
iter  10 value 93.425054
iter  20 value 85.912094
iter  30 value 85.477204
iter  40 value 85.159623
iter  50 value 84.071827
iter  60 value 82.506018
iter  70 value 81.623366
iter  80 value 80.930121
iter  90 value 80.000427
iter 100 value 79.530816
final  value 79.530816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.493398 
iter  10 value 97.350950
iter  20 value 94.454228
iter  30 value 85.319614
iter  40 value 81.582891
iter  50 value 81.228910
iter  60 value 80.863625
iter  70 value 80.682299
iter  80 value 80.373373
iter  90 value 79.970113
iter 100 value 79.764430
final  value 79.764430 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 133.468892 
iter  10 value 94.763358
iter  20 value 84.133384
iter  30 value 82.990321
iter  40 value 82.265811
iter  50 value 81.258412
iter  60 value 80.616634
iter  70 value 80.221246
iter  80 value 79.951035
iter  90 value 79.502766
iter 100 value 79.424335
final  value 79.424335 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.702384 
iter  10 value 95.546260
iter  20 value 93.797381
iter  30 value 87.830769
iter  40 value 83.237381
iter  50 value 82.153788
iter  60 value 81.203336
iter  70 value 79.661373
iter  80 value 79.310720
iter  90 value 79.129606
iter 100 value 78.948724
final  value 78.948724 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.253031 
final  value 94.313633 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.289431 
final  value 94.485834 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.245671 
final  value 94.355861 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.528092 
final  value 94.485724 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.162052 
final  value 94.485808 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.630020 
iter  10 value 92.842346
iter  20 value 85.324403
iter  30 value 84.746302
iter  40 value 84.295712
iter  50 value 82.368990
iter  60 value 82.344281
iter  70 value 82.341005
iter  80 value 82.339286
iter  90 value 81.386759
iter 100 value 81.193790
final  value 81.193790 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.568977 
final  value 94.489551 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.798485 
iter  10 value 94.489036
iter  20 value 92.984797
iter  30 value 87.729539
iter  40 value 84.669148
iter  50 value 83.829921
iter  60 value 83.827939
iter  60 value 83.827939
final  value 83.827939 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.484629 
iter  10 value 94.426827
iter  20 value 94.359282
iter  30 value 94.354694
iter  40 value 93.911193
iter  50 value 93.578458
iter  60 value 85.567190
iter  70 value 82.924091
iter  80 value 82.379385
iter  90 value 82.375923
final  value 82.367124 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.284053 
iter  10 value 93.781627
iter  20 value 93.289802
iter  30 value 93.287606
iter  40 value 93.170053
iter  50 value 93.165110
iter  60 value 92.336431
iter  70 value 81.893610
iter  80 value 81.402229
iter  90 value 81.390536
iter 100 value 81.389450
final  value 81.389450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.297163 
iter  10 value 94.362673
iter  20 value 93.908599
iter  30 value 93.660061
iter  40 value 93.641649
final  value 93.640663 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.600320 
iter  10 value 94.492579
iter  20 value 94.127941
iter  30 value 88.129390
iter  40 value 84.898204
iter  50 value 84.754217
iter  60 value 84.626997
iter  70 value 84.624572
iter  80 value 84.622310
iter  90 value 84.504318
iter 100 value 82.181441
final  value 82.181441 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.577908 
iter  10 value 94.320205
iter  20 value 93.393903
iter  30 value 88.686675
iter  40 value 81.791495
iter  50 value 81.510816
iter  60 value 80.663501
iter  70 value 80.139642
iter  80 value 80.106366
final  value 80.100404 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.853702 
iter  10 value 94.070461
iter  20 value 93.817889
iter  30 value 90.078549
iter  40 value 84.967186
iter  50 value 84.743362
iter  60 value 84.307435
iter  70 value 84.306703
iter  80 value 84.303047
final  value 84.302808 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.682004 
iter  10 value 94.362845
iter  20 value 93.661764
iter  30 value 82.322926
iter  40 value 81.869474
iter  50 value 81.853110
iter  60 value 81.005886
iter  70 value 80.172556
iter  80 value 80.140629
iter  90 value 80.139587
iter 100 value 80.109044
final  value 80.109044 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.770872 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.549562 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.508329 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.833855 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.023766 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.129598 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.136547 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.146468 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.387844 
iter  10 value 93.840819
iter  20 value 93.786709
iter  20 value 93.786708
iter  20 value 93.786708
final  value 93.786708 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.179190 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.060984 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.106726 
iter  10 value 92.964626
iter  20 value 92.748846
iter  30 value 92.748057
iter  30 value 92.748056
final  value 92.748052 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.551345 
iter  10 value 92.815239
iter  20 value 88.684971
iter  30 value 88.643751
final  value 88.643550 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.200237 
final  value 94.008695 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.033611 
iter  10 value 93.782313
iter  20 value 89.327444
iter  30 value 87.410229
iter  40 value 87.065059
iter  50 value 87.004292
iter  60 value 84.702063
iter  70 value 84.297678
iter  80 value 84.084340
iter  90 value 84.039228
iter 100 value 84.038316
final  value 84.038316 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.764054 
iter  10 value 94.056190
iter  20 value 94.011996
iter  30 value 93.074093
iter  40 value 87.674245
iter  50 value 86.599734
iter  60 value 85.703751
iter  70 value 85.372560
iter  80 value 85.356287
iter  80 value 85.356287
iter  80 value 85.356287
final  value 85.356287 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.728872 
iter  10 value 94.068535
iter  20 value 94.001504
iter  30 value 89.248630
iter  40 value 88.755469
iter  50 value 86.464789
iter  60 value 85.701722
iter  70 value 84.531273
iter  80 value 84.020624
iter  90 value 83.493297
iter 100 value 82.827177
final  value 82.827177 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.797944 
iter  10 value 94.028685
iter  20 value 92.290622
iter  30 value 87.742867
iter  40 value 86.027196
iter  50 value 85.908739
iter  60 value 85.597295
iter  70 value 84.735043
iter  80 value 84.541301
final  value 84.541036 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.203149 
iter  10 value 94.936374
iter  20 value 94.056413
iter  30 value 93.815338
iter  40 value 86.735010
iter  50 value 85.959724
iter  60 value 85.689899
iter  70 value 85.068673
iter  80 value 84.557380
iter  90 value 84.043970
final  value 84.031070 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.128246 
iter  10 value 94.057699
iter  20 value 94.039707
iter  30 value 93.934881
iter  40 value 91.756250
iter  50 value 86.042788
iter  60 value 85.808490
iter  70 value 85.472634
iter  80 value 84.570765
iter  90 value 84.039791
iter 100 value 84.031072
final  value 84.031072 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.888297 
iter  10 value 94.123098
iter  20 value 87.070112
iter  30 value 85.796316
iter  40 value 85.541012
iter  50 value 85.247608
iter  60 value 84.143767
iter  70 value 83.570559
iter  80 value 82.012675
iter  90 value 81.501065
iter 100 value 81.398921
final  value 81.398921 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.119880 
iter  10 value 94.042389
iter  20 value 93.811919
iter  30 value 91.573106
iter  40 value 88.579254
iter  50 value 87.967853
iter  60 value 87.356211
iter  70 value 86.838374
iter  80 value 86.344518
iter  90 value 84.174446
iter 100 value 82.821877
final  value 82.821877 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.588757 
iter  10 value 93.949307
iter  20 value 90.126035
iter  30 value 86.824857
iter  40 value 84.264675
iter  50 value 82.599996
iter  60 value 82.299602
iter  70 value 81.956842
iter  80 value 81.081152
iter  90 value 80.958070
iter 100 value 80.854795
final  value 80.854795 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.882039 
iter  10 value 93.967456
iter  20 value 89.019244
iter  30 value 88.620805
iter  40 value 87.274294
iter  50 value 87.106923
iter  60 value 85.430329
iter  70 value 83.892244
iter  80 value 83.693551
iter  90 value 83.624680
iter 100 value 83.205452
final  value 83.205452 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.965475 
iter  10 value 93.670590
iter  20 value 88.114232
iter  30 value 86.880815
iter  40 value 86.218831
iter  50 value 85.030258
iter  60 value 84.895039
iter  70 value 84.037307
iter  80 value 82.851325
iter  90 value 82.076782
iter 100 value 81.725617
final  value 81.725617 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.648000 
iter  10 value 93.641594
iter  20 value 89.557881
iter  30 value 86.045468
iter  40 value 85.797812
iter  50 value 85.190114
iter  60 value 84.197527
iter  70 value 83.084106
iter  80 value 82.571278
iter  90 value 82.303177
iter 100 value 82.086777
final  value 82.086777 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.192990 
iter  10 value 94.355703
iter  20 value 93.262051
iter  30 value 87.349575
iter  40 value 85.132005
iter  50 value 82.493745
iter  60 value 81.812354
iter  70 value 81.653465
iter  80 value 81.512419
iter  90 value 81.503740
iter 100 value 81.480193
final  value 81.480193 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.007429 
iter  10 value 94.043903
iter  20 value 87.787573
iter  30 value 86.646802
iter  40 value 85.403392
iter  50 value 84.250425
iter  60 value 82.336614
iter  70 value 81.301215
iter  80 value 81.077564
iter  90 value 80.880289
iter 100 value 80.836874
final  value 80.836874 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.147971 
iter  10 value 94.071221
iter  20 value 94.046969
iter  30 value 93.857790
iter  40 value 87.683425
iter  50 value 85.537367
iter  60 value 85.043250
iter  70 value 82.897026
iter  80 value 82.483938
iter  90 value 82.263461
iter 100 value 81.699266
final  value 81.699266 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.045917 
iter  10 value 94.089219
iter  20 value 93.150448
iter  30 value 86.018834
iter  40 value 83.133289
iter  50 value 82.778666
iter  60 value 82.258962
iter  70 value 81.645963
iter  80 value 81.206606
iter  90 value 80.997435
iter 100 value 80.890361
final  value 80.890361 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.101977 
final  value 94.054796 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.292925 
final  value 94.054560 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.933526 
final  value 94.054312 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.582059 
final  value 94.018830 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.100335 
final  value 94.046080 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.620714 
iter  10 value 94.054829
iter  20 value 90.014502
iter  30 value 87.456549
iter  40 value 86.885384
iter  50 value 86.745880
iter  60 value 86.707512
iter  70 value 86.706006
iter  80 value 86.704462
iter  90 value 86.704164
iter 100 value 86.704045
final  value 86.704045 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.990248 
iter  10 value 94.013227
iter  20 value 94.008916
iter  30 value 90.601885
iter  40 value 90.326459
iter  50 value 85.851331
iter  60 value 85.847196
iter  70 value 85.716567
iter  80 value 85.557113
iter  90 value 85.006699
iter 100 value 82.018001
final  value 82.018001 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.129173 
iter  10 value 94.013480
iter  20 value 94.008882
iter  30 value 93.711301
iter  40 value 86.107429
iter  50 value 85.874149
iter  60 value 85.873479
iter  70 value 85.578560
iter  80 value 85.490978
iter  90 value 85.490818
iter  90 value 85.490817
iter  90 value 85.490817
final  value 85.490817 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.606262 
iter  10 value 94.015270
iter  20 value 94.010879
iter  30 value 94.009895
final  value 94.009853 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.883152 
iter  10 value 94.056170
iter  20 value 90.503658
iter  30 value 88.967683
iter  40 value 88.941995
iter  50 value 87.540743
iter  60 value 86.253990
iter  70 value 85.968031
iter  80 value 85.810008
iter  90 value 85.789583
iter 100 value 85.789457
final  value 85.789457 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.773276 
iter  10 value 94.058766
iter  20 value 94.001755
iter  30 value 92.117403
iter  40 value 91.615880
iter  50 value 91.609322
iter  50 value 91.609321
iter  50 value 91.609321
final  value 91.609321 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.366171 
iter  10 value 93.870023
iter  20 value 93.681044
iter  30 value 87.055477
final  value 87.042906 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.534859 
iter  10 value 94.016973
iter  20 value 93.980833
iter  30 value 87.436927
final  value 87.042530 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.451586 
iter  10 value 93.958386
iter  20 value 93.827962
iter  30 value 91.309872
iter  40 value 86.188359
iter  50 value 85.542015
iter  60 value 85.540976
iter  70 value 85.320881
iter  80 value 85.313709
iter  90 value 85.312809
iter 100 value 85.312587
final  value 85.312587 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.393351 
iter  10 value 93.984276
iter  20 value 93.981565
iter  30 value 90.912578
iter  40 value 88.321794
iter  50 value 88.240299
iter  60 value 88.238495
iter  70 value 88.237837
final  value 88.237792 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.560452 
iter  10 value 86.990823
iter  20 value 86.956011
final  value 86.955824 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.582029 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.840563 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.902937 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.409253 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.177347 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.897898 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.297654 
iter  10 value 94.427939
final  value 94.427933 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.285017 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.528192 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.832414 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.204115 
iter  10 value 93.769109
iter  20 value 93.730406
final  value 93.729005 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.746437 
final  value 94.300045 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.642215 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.830516 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.252993 
iter  10 value 94.490134
iter  20 value 88.112959
iter  30 value 84.933366
iter  40 value 84.501496
iter  50 value 84.076976
iter  60 value 83.930780
iter  70 value 83.903617
iter  80 value 83.899083
final  value 83.898240 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.559660 
iter  10 value 94.397657
iter  20 value 94.054140
iter  30 value 93.893322
iter  40 value 93.232714
iter  50 value 92.086762
iter  60 value 88.127041
iter  70 value 84.531239
iter  80 value 83.737262
iter  90 value 83.689579
iter 100 value 83.469658
final  value 83.469658 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.448190 
iter  10 value 94.486002
iter  20 value 91.171346
iter  30 value 85.445538
iter  40 value 84.800230
iter  50 value 84.492123
iter  60 value 84.052108
iter  70 value 83.929025
iter  80 value 83.898254
final  value 83.898240 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.907318 
iter  10 value 94.466272
iter  20 value 89.246033
iter  30 value 88.437906
iter  40 value 87.811039
iter  50 value 87.513283
iter  60 value 84.595530
iter  70 value 82.691543
iter  80 value 82.674593
final  value 82.674528 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.251297 
iter  10 value 94.542811
iter  20 value 94.381336
iter  30 value 87.541401
iter  40 value 85.324224
iter  50 value 84.486372
iter  60 value 84.441582
iter  70 value 83.927138
iter  80 value 83.898701
iter  90 value 83.898498
iter 100 value 83.898315
final  value 83.898315 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.904520 
iter  10 value 94.384483
iter  20 value 88.676950
iter  30 value 86.557908
iter  40 value 83.661765
iter  50 value 82.618090
iter  60 value 82.321279
iter  70 value 82.168271
iter  80 value 81.909615
iter  90 value 81.708829
iter 100 value 81.650773
final  value 81.650773 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.304514 
iter  10 value 99.970472
iter  20 value 94.522718
iter  30 value 91.578256
iter  40 value 89.282473
iter  50 value 86.499663
iter  60 value 86.321727
iter  70 value 83.810559
iter  80 value 83.221699
iter  90 value 82.928303
iter 100 value 82.317942
final  value 82.317942 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.201893 
iter  10 value 94.695568
iter  20 value 93.959110
iter  30 value 90.536057
iter  40 value 85.884682
iter  50 value 83.848115
iter  60 value 83.658343
iter  70 value 83.470978
iter  80 value 82.448566
iter  90 value 82.094960
iter 100 value 81.577418
final  value 81.577418 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.885614 
iter  10 value 94.495891
iter  20 value 86.346122
iter  30 value 85.030809
iter  40 value 84.354937
iter  50 value 83.208193
iter  60 value 81.916490
iter  70 value 81.641707
iter  80 value 81.347583
iter  90 value 81.320345
iter 100 value 81.260617
final  value 81.260617 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.073333 
iter  10 value 94.508346
iter  20 value 92.849408
iter  30 value 87.332895
iter  40 value 87.088719
iter  50 value 86.246268
iter  60 value 84.605085
iter  70 value 84.522919
iter  80 value 84.477450
iter  90 value 84.402849
iter 100 value 84.312304
final  value 84.312304 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.791680 
iter  10 value 94.674456
iter  20 value 94.462868
iter  30 value 92.051334
iter  40 value 89.573250
iter  50 value 84.331370
iter  60 value 83.327367
iter  70 value 82.557344
iter  80 value 81.643180
iter  90 value 81.225168
iter 100 value 81.107040
final  value 81.107040 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.850960 
iter  10 value 95.092148
iter  20 value 94.022805
iter  30 value 90.468704
iter  40 value 87.285908
iter  50 value 84.100627
iter  60 value 82.394344
iter  70 value 81.255361
iter  80 value 81.055833
iter  90 value 80.971515
iter 100 value 80.934239
final  value 80.934239 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.332612 
iter  10 value 94.435164
iter  20 value 91.815718
iter  30 value 91.517311
iter  40 value 91.303533
iter  50 value 90.237276
iter  60 value 86.229883
iter  70 value 84.352764
iter  80 value 83.453147
iter  90 value 83.297850
iter 100 value 83.044888
final  value 83.044888 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.184389 
iter  10 value 94.366658
iter  20 value 94.287670
iter  30 value 88.881545
iter  40 value 85.936228
iter  50 value 85.505247
iter  60 value 84.150730
iter  70 value 83.117895
iter  80 value 82.301392
iter  90 value 81.520081
iter 100 value 81.272265
final  value 81.272265 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.088877 
iter  10 value 93.852518
iter  20 value 90.767885
iter  30 value 85.592561
iter  40 value 84.065961
iter  50 value 83.615832
iter  60 value 83.502499
iter  70 value 83.441867
iter  80 value 83.271907
iter  90 value 83.187988
iter 100 value 83.153624
final  value 83.153624 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.414044 
final  value 94.485785 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.666438 
iter  10 value 94.485954
final  value 94.484375 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.311533 
final  value 94.485969 
converged
Fitting Repeat 4 

# weights:  103
initial  value 116.197988 
final  value 94.485806 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.308042 
final  value 94.485944 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.828231 
iter  10 value 94.370443
iter  20 value 94.368608
iter  30 value 85.710115
final  value 85.707314 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.993419 
iter  10 value 94.472099
iter  20 value 92.592632
iter  30 value 83.705305
final  value 83.564177 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.088397 
iter  10 value 94.489298
iter  20 value 94.485611
iter  30 value 94.485197
iter  40 value 94.484779
final  value 94.484703 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.869772 
iter  10 value 94.370335
iter  20 value 94.365728
iter  30 value 94.289062
iter  40 value 87.709598
iter  50 value 84.683463
iter  60 value 81.351625
iter  70 value 79.766291
iter  80 value 79.520452
iter  90 value 79.511230
iter 100 value 79.329713
final  value 79.329713 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.380951 
iter  10 value 94.317028
iter  20 value 94.312297
iter  30 value 92.531566
final  value 92.529527 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.558461 
iter  10 value 94.492319
iter  20 value 94.484409
iter  30 value 91.959629
iter  40 value 86.374353
iter  50 value 86.347480
iter  60 value 86.344025
iter  70 value 86.321543
iter  80 value 85.812764
iter  90 value 85.592877
iter 100 value 85.591721
final  value 85.591721 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.827605 
iter  10 value 94.492821
iter  20 value 94.173598
iter  30 value 86.060600
iter  40 value 83.667679
iter  50 value 83.299177
iter  60 value 83.294966
iter  70 value 83.287556
iter  80 value 83.140414
iter  90 value 82.168165
iter 100 value 81.743156
final  value 81.743156 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.164639 
iter  10 value 94.492492
iter  20 value 94.422476
iter  30 value 93.967524
iter  40 value 87.172317
iter  50 value 85.711517
iter  60 value 85.706984
iter  70 value 85.703490
iter  80 value 85.533021
iter  90 value 85.526906
iter 100 value 85.524146
final  value 85.524146 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.712148 
iter  10 value 94.492460
iter  20 value 94.420321
iter  30 value 85.752287
iter  40 value 85.709028
iter  50 value 85.708720
iter  60 value 85.708194
iter  70 value 85.705515
iter  80 value 85.701891
final  value 85.701314 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.201050 
iter  10 value 93.749873
iter  20 value 90.014995
iter  30 value 82.300909
iter  40 value 82.170180
iter  50 value 82.168378
iter  60 value 82.162462
iter  70 value 82.039825
iter  80 value 80.469107
iter  90 value 79.517195
iter 100 value 79.268760
final  value 79.268760 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.059857 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.771405 
iter  10 value 93.394928
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.273389 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.050941 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.856122 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.417437 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.471623 
iter  10 value 85.001364
iter  20 value 83.813939
iter  30 value 83.560845
final  value 83.496405 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.799027 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.090911 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.851519 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.568508 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.505517 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.388572 
iter  10 value 93.932501
final  value 93.930685 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.504801 
iter  10 value 93.096126
iter  20 value 92.246081
iter  30 value 92.114235
iter  40 value 92.109854
final  value 92.109849 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.439407 
iter  10 value 93.436422
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.519604 
iter  10 value 94.488520
iter  20 value 93.702700
iter  30 value 93.689443
iter  40 value 92.950233
iter  50 value 92.824758
iter  60 value 91.673153
iter  70 value 87.869180
iter  80 value 86.192520
iter  90 value 81.983187
iter 100 value 81.512933
final  value 81.512933 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.456049 
iter  10 value 93.763131
iter  20 value 92.937347
iter  30 value 86.506351
iter  40 value 85.237264
iter  50 value 83.820825
iter  60 value 81.905082
iter  70 value 81.511281
iter  80 value 81.484782
iter  90 value 81.464612
final  value 81.464588 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.240193 
iter  10 value 94.488614
iter  20 value 93.678245
iter  30 value 92.615912
iter  40 value 87.762557
iter  50 value 86.879357
iter  60 value 86.240405
iter  70 value 84.493875
iter  80 value 83.013624
iter  90 value 82.904452
iter 100 value 81.673413
final  value 81.673413 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.321215 
iter  10 value 94.399728
iter  20 value 93.724617
iter  30 value 93.679957
iter  40 value 92.751665
iter  50 value 90.456031
iter  60 value 87.224856
iter  70 value 84.195070
iter  80 value 83.817285
iter  90 value 83.438339
iter 100 value 83.413978
final  value 83.413978 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.373606 
iter  10 value 94.486558
iter  20 value 92.990817
iter  30 value 92.947583
iter  40 value 85.565792
iter  50 value 82.372744
iter  60 value 81.593947
iter  70 value 81.481896
final  value 81.481824 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.394414 
iter  10 value 93.580667
iter  20 value 92.631561
iter  30 value 90.784941
iter  40 value 88.852681
iter  50 value 85.301166
iter  60 value 84.960046
iter  70 value 84.635814
iter  80 value 82.467429
iter  90 value 81.414468
iter 100 value 81.200096
final  value 81.200096 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.306976 
iter  10 value 97.050944
iter  20 value 91.715062
iter  30 value 86.037172
iter  40 value 85.008225
iter  50 value 84.570715
iter  60 value 83.986946
iter  70 value 83.155745
iter  80 value 81.570997
iter  90 value 81.506088
iter 100 value 81.346092
final  value 81.346092 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.035733 
iter  10 value 94.451842
iter  20 value 87.474816
iter  30 value 85.766194
iter  40 value 82.309414
iter  50 value 81.041649
iter  60 value 80.809975
iter  70 value 80.668544
iter  80 value 80.535660
iter  90 value 80.482974
iter 100 value 80.477536
final  value 80.477536 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.727853 
iter  10 value 95.188498
iter  20 value 86.151327
iter  30 value 84.181032
iter  40 value 83.942352
iter  50 value 83.418276
iter  60 value 82.512917
iter  70 value 82.217382
iter  80 value 81.557645
iter  90 value 80.916554
iter 100 value 80.701713
final  value 80.701713 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.961013 
iter  10 value 94.585088
iter  20 value 89.873883
iter  30 value 87.839447
iter  40 value 85.613030
iter  50 value 84.081298
iter  60 value 83.867972
iter  70 value 83.696145
iter  80 value 83.476605
iter  90 value 83.040928
iter 100 value 81.953553
final  value 81.953553 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.735754 
iter  10 value 95.033808
iter  20 value 92.937915
iter  30 value 92.840426
iter  40 value 91.041110
iter  50 value 83.525180
iter  60 value 82.535949
iter  70 value 82.276737
iter  80 value 82.116971
iter  90 value 82.091724
iter 100 value 82.023274
final  value 82.023274 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.203061 
iter  10 value 93.599028
iter  20 value 92.734460
iter  30 value 87.812146
iter  40 value 82.436253
iter  50 value 81.834117
iter  60 value 81.632143
iter  70 value 81.510612
iter  80 value 81.005552
iter  90 value 80.515055
iter 100 value 80.016941
final  value 80.016941 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.111306 
iter  10 value 92.161645
iter  20 value 85.668232
iter  30 value 83.832993
iter  40 value 81.474895
iter  50 value 80.447187
iter  60 value 80.085891
iter  70 value 79.816260
iter  80 value 79.790185
iter  90 value 79.722281
iter 100 value 79.677903
final  value 79.677903 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.903777 
iter  10 value 94.684683
iter  20 value 94.147110
iter  30 value 91.569249
iter  40 value 88.142383
iter  50 value 86.838731
iter  60 value 85.194012
iter  70 value 83.127559
iter  80 value 81.011431
iter  90 value 80.568145
iter 100 value 80.537521
final  value 80.537521 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.119958 
iter  10 value 94.965146
iter  20 value 85.666869
iter  30 value 85.088211
iter  40 value 84.473863
iter  50 value 83.989164
iter  60 value 83.841947
iter  70 value 83.795472
iter  80 value 83.773754
iter  90 value 83.693804
iter 100 value 83.328713
final  value 83.328713 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.757379 
final  value 94.485675 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.937121 
iter  10 value 94.485793
iter  20 value 94.484274
final  value 94.484217 
converged
Fitting Repeat 3 

# weights:  103
initial  value 118.740791 
iter  10 value 93.569523
iter  20 value 92.896532
iter  30 value 92.836365
iter  40 value 92.825653
final  value 92.824395 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.971539 
final  value 94.485867 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.050067 
final  value 94.485907 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.986789 
iter  10 value 94.489517
iter  20 value 94.483720
iter  30 value 90.312172
iter  40 value 90.296542
iter  50 value 88.711688
iter  60 value 83.699160
iter  70 value 83.683975
iter  80 value 83.580284
iter  90 value 83.304546
iter 100 value 83.302749
final  value 83.302749 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.447472 
iter  10 value 94.490858
iter  20 value 93.209211
iter  30 value 92.638798
iter  40 value 92.634961
iter  50 value 92.631600
iter  60 value 92.622608
iter  70 value 92.620284
iter  70 value 92.620283
iter  70 value 92.620283
final  value 92.620283 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.929528 
iter  10 value 94.489057
iter  20 value 94.162444
iter  30 value 92.628408
iter  40 value 92.555225
iter  50 value 84.586065
iter  60 value 82.283772
iter  70 value 81.950025
iter  80 value 81.946660
final  value 81.946647 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.300528 
iter  10 value 94.489115
iter  20 value 94.484403
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.903333 
iter  10 value 94.476607
iter  20 value 93.639855
iter  30 value 93.559479
iter  40 value 84.239527
iter  50 value 83.657659
final  value 83.657582 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.430186 
iter  10 value 94.495834
iter  20 value 94.319352
iter  30 value 88.746536
iter  40 value 86.965194
iter  50 value 86.942883
iter  60 value 86.939740
iter  70 value 85.044307
iter  80 value 81.174413
iter  90 value 80.349403
iter 100 value 79.139971
final  value 79.139971 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.643645 
iter  10 value 94.518150
iter  20 value 94.500117
iter  30 value 93.501171
iter  40 value 93.418415
iter  50 value 93.400130
iter  60 value 93.399465
iter  70 value 93.395511
final  value 93.395461 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.132992 
iter  10 value 93.118458
iter  20 value 86.370469
iter  30 value 84.429295
iter  40 value 83.280186
iter  50 value 83.275953
iter  60 value 83.167584
iter  70 value 82.865524
iter  80 value 82.864096
iter  90 value 82.863298
final  value 82.862880 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.936367 
iter  10 value 92.648380
iter  20 value 92.644024
iter  30 value 92.635873
iter  40 value 92.633179
iter  50 value 90.051444
iter  60 value 84.837261
iter  70 value 84.789889
iter  80 value 84.608327
iter  90 value 84.416841
iter 100 value 84.394980
final  value 84.394980 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.791834 
iter  10 value 94.492293
iter  20 value 93.539196
iter  30 value 92.636635
iter  30 value 92.636634
iter  30 value 92.636634
final  value 92.636634 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.313335 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.175669 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.402940 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.876500 
iter  10 value 93.994371
iter  20 value 93.988105
final  value 93.988096 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.568322 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.844847 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.160602 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.588574 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.527840 
final  value 93.991526 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.080486 
final  value 94.050051 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.826844 
iter  10 value 94.029316
iter  10 value 94.029316
iter  10 value 94.029316
final  value 94.029316 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.531193 
iter  10 value 93.116621
iter  20 value 93.081000
final  value 93.080991 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.065397 
final  value 94.029316 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.113894 
iter  10 value 93.464501
final  value 93.464368 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.175131 
iter  10 value 93.992325
iter  20 value 93.991527
iter  20 value 93.991526
iter  20 value 93.991526
final  value 93.991526 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.749130 
iter  10 value 93.757344
iter  20 value 87.681238
iter  30 value 86.955219
iter  40 value 85.892569
iter  50 value 82.622447
iter  60 value 80.760354
iter  70 value 79.854465
iter  80 value 79.480646
iter  90 value 78.878676
iter 100 value 78.839745
final  value 78.839745 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.897254 
iter  10 value 94.049348
iter  20 value 93.324920
iter  30 value 93.153355
iter  40 value 86.358141
iter  50 value 85.671186
iter  60 value 85.642105
iter  70 value 85.579137
iter  80 value 85.565022
iter  90 value 82.617942
iter 100 value 82.569917
final  value 82.569917 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.631678 
iter  10 value 93.597212
iter  20 value 84.178031
iter  30 value 83.627773
iter  40 value 83.480355
iter  50 value 83.153053
iter  60 value 81.940984
iter  70 value 80.953027
final  value 80.917350 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.591687 
iter  10 value 94.030573
iter  20 value 93.852726
iter  30 value 86.143043
iter  40 value 85.282127
iter  50 value 85.109993
iter  60 value 85.002259
iter  70 value 81.520200
iter  80 value 81.375470
iter  90 value 79.656432
iter 100 value 79.418470
final  value 79.418470 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.740705 
iter  10 value 94.037166
iter  20 value 91.174390
iter  30 value 86.143775
iter  40 value 82.452291
iter  50 value 82.065533
iter  60 value 81.736381
iter  70 value 81.403445
iter  80 value 81.286473
final  value 81.284409 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.768193 
iter  10 value 86.803396
iter  20 value 82.137954
iter  30 value 81.682453
iter  40 value 81.422845
iter  50 value 81.322066
iter  60 value 81.288852
iter  70 value 81.260160
iter  80 value 79.993773
iter  90 value 79.413628
iter 100 value 79.211418
final  value 79.211418 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.386846 
iter  10 value 93.705443
iter  20 value 91.192652
iter  30 value 82.514162
iter  40 value 81.659137
iter  50 value 79.588446
iter  60 value 78.339864
iter  70 value 78.052445
iter  80 value 77.805147
iter  90 value 77.734615
iter 100 value 77.677684
final  value 77.677684 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.153067 
iter  10 value 94.062787
iter  20 value 91.405608
iter  30 value 84.005075
iter  40 value 82.582606
iter  50 value 82.470207
iter  60 value 81.659772
iter  70 value 80.415047
iter  80 value 79.220076
iter  90 value 78.350665
iter 100 value 78.211767
final  value 78.211767 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.067450 
iter  10 value 91.976725
iter  20 value 87.964413
iter  30 value 82.639305
iter  40 value 82.163184
iter  50 value 81.794392
iter  60 value 80.514422
iter  70 value 79.671420
iter  80 value 78.850065
iter  90 value 78.473543
iter 100 value 77.545323
final  value 77.545323 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.755458 
iter  10 value 94.194364
iter  20 value 93.815028
iter  30 value 90.556219
iter  40 value 88.312456
iter  50 value 84.915279
iter  60 value 82.448948
iter  70 value 79.193398
iter  80 value 78.269065
iter  90 value 77.836260
iter 100 value 77.701320
final  value 77.701320 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.539762 
iter  10 value 94.574895
iter  20 value 86.549187
iter  30 value 85.549933
iter  40 value 82.839753
iter  50 value 79.942632
iter  60 value 79.434555
iter  70 value 78.693458
iter  80 value 77.927325
iter  90 value 77.530764
iter 100 value 77.276889
final  value 77.276889 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.788265 
iter  10 value 94.365453
iter  20 value 87.691932
iter  30 value 84.361264
iter  40 value 80.663676
iter  50 value 80.103372
iter  60 value 79.863592
iter  70 value 79.756500
iter  80 value 79.703426
iter  90 value 79.618083
iter 100 value 79.006732
final  value 79.006732 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.017710 
iter  10 value 94.337245
iter  20 value 93.816978
iter  30 value 86.766802
iter  40 value 85.259397
iter  50 value 82.546612
iter  60 value 81.525131
iter  70 value 81.461322
iter  80 value 81.012743
iter  90 value 79.669026
iter 100 value 78.761409
final  value 78.761409 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.423597 
iter  10 value 94.095984
iter  20 value 90.956467
iter  30 value 85.678957
iter  40 value 84.639878
iter  50 value 81.855297
iter  60 value 80.461066
iter  70 value 79.600090
iter  80 value 77.858561
iter  90 value 77.744902
iter 100 value 77.608239
final  value 77.608239 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.138844 
iter  10 value 94.230584
iter  20 value 88.917361
iter  30 value 86.433565
iter  40 value 81.965830
iter  50 value 80.528011
iter  60 value 79.226573
iter  70 value 78.085174
iter  80 value 77.538581
iter  90 value 77.152219
iter 100 value 76.888224
final  value 76.888224 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.759972 
final  value 94.054654 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.154843 
iter  10 value 91.541010
iter  20 value 91.507952
final  value 91.507771 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.387293 
final  value 94.054522 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.459459 
iter  10 value 94.054511
iter  20 value 86.228137
iter  30 value 84.483588
final  value 84.470244 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.653427 
final  value 94.054376 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.377114 
iter  10 value 94.037769
iter  20 value 94.003641
iter  30 value 93.806637
iter  40 value 90.781682
iter  50 value 85.853432
iter  60 value 85.102369
iter  70 value 85.089792
iter  80 value 85.069844
iter  90 value 85.064510
iter 100 value 85.062977
final  value 85.062977 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.227950 
iter  10 value 94.038125
iter  20 value 93.989969
iter  30 value 93.917184
final  value 93.916227 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.379113 
iter  10 value 94.035428
iter  20 value 94.034013
iter  30 value 94.028641
iter  40 value 93.964898
iter  50 value 93.936524
iter  60 value 93.933305
iter  70 value 93.893058
iter  80 value 93.879681
iter  90 value 93.879259
iter 100 value 93.643750
final  value 93.643750 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.846561 
iter  10 value 93.996428
iter  20 value 93.994168
iter  30 value 93.991183
iter  40 value 93.989906
iter  50 value 93.987187
iter  60 value 88.888617
iter  70 value 82.589219
iter  80 value 82.449892
iter  90 value 82.449117
iter 100 value 82.448218
final  value 82.448218 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.766125 
iter  10 value 94.058001
iter  20 value 94.052959
iter  30 value 93.683171
iter  40 value 89.257547
iter  50 value 86.648928
iter  60 value 83.170367
iter  70 value 83.040798
iter  80 value 83.037799
iter  90 value 82.381603
iter 100 value 81.505299
final  value 81.505299 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.562958 
iter  10 value 94.041613
iter  20 value 91.949230
iter  30 value 87.955390
iter  40 value 82.155909
iter  50 value 81.594902
iter  60 value 81.523890
iter  70 value 78.057765
iter  80 value 77.378803
iter  90 value 77.362177
iter 100 value 77.225100
final  value 77.225100 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.691460 
iter  10 value 87.069060
iter  20 value 85.322027
iter  30 value 84.448940
iter  40 value 84.050163
iter  50 value 83.992937
iter  60 value 83.990049
iter  70 value 83.987152
iter  80 value 83.986505
iter  90 value 83.985317
iter 100 value 83.984614
final  value 83.984614 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.591547 
iter  10 value 94.057481
iter  20 value 94.044800
iter  30 value 92.708335
final  value 92.702108 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.617523 
iter  10 value 94.040740
iter  20 value 93.677231
iter  30 value 84.149432
iter  40 value 84.079890
iter  50 value 83.918259
final  value 83.918116 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.283790 
iter  10 value 91.042058
iter  20 value 83.416355
iter  30 value 81.954693
iter  40 value 81.551792
iter  50 value 81.548696
iter  60 value 81.544706
iter  70 value 81.540856
iter  80 value 80.809898
iter  90 value 80.805482
iter 100 value 80.793336
final  value 80.793336 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.453448 
iter  10 value 117.767194
iter  20 value 117.169951
iter  30 value 106.919516
iter  40 value 103.638610
iter  50 value 103.181471
iter  60 value 103.174215
iter  70 value 103.173450
iter  80 value 103.171895
iter  90 value 103.047048
iter 100 value 101.169904
final  value 101.169904 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.074906 
iter  10 value 117.269202
iter  20 value 114.977539
iter  30 value 114.940060
iter  40 value 114.830927
iter  50 value 114.826866
iter  60 value 114.811954
iter  70 value 114.572933
iter  80 value 114.516145
iter  90 value 114.496817
iter 100 value 114.454851
final  value 114.454851 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.282175 
iter  10 value 117.902979
iter  20 value 117.894808
iter  30 value 114.074332
iter  40 value 106.900965
iter  50 value 102.688254
iter  60 value 102.371329
iter  70 value 102.117590
iter  80 value 102.019118
final  value 102.018131 
converged
Fitting Repeat 4 

# weights:  507
initial  value 137.491986 
iter  10 value 117.898590
iter  20 value 117.890181
iter  30 value 117.584785
iter  40 value 117.552775
final  value 117.552768 
converged
Fitting Repeat 5 

# weights:  507
initial  value 153.046088 
iter  10 value 112.170252
iter  20 value 106.967396
iter  30 value 103.420953
iter  40 value 103.040798
iter  50 value 103.039118
iter  60 value 102.999613
iter  70 value 102.853354
iter  80 value 101.702490
iter  90 value 100.526457
iter 100 value 100.252963
final  value 100.252963 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Apr  3 20:17:11 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 
 20.138   0.736  74.468