##############################################################################
##############################################################################
###
### 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_1.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 Patched (2026-04-24 r89963)
* 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: 2026-05-07 00:42:54 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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     17.011  0.092  17.156
var_imp       16.945  0.086  17.064
FSmethod      16.940  0.064  17.251
pred_ensembel  6.115  0.153   5.505
enrichfindP    0.203  0.042  10.977
* 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 ‘1.18.0’
** 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 Patched (2026-04-24 r89963) -- "Because it was There"
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
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 96.385354 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.647374 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.328057 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.012932 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.261750 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.601220 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.189401 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.933572 
final  value 93.811828 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.030020 
iter  10 value 93.811847
final  value 93.811828 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.370233 
iter  10 value 93.811831
final  value 93.811828 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.835413 
iter  10 value 93.811829
iter  10 value 93.811828
iter  10 value 93.811828
final  value 93.811828 
converged
Fitting Repeat 2 

# weights:  507
initial  value 128.578658 
iter  10 value 93.827811
iter  20 value 93.634312
iter  30 value 93.628065
final  value 93.628061 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.071001 
iter  10 value 93.811828
iter  10 value 93.811828
iter  10 value 93.811828
final  value 93.811828 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.794369 
iter  10 value 93.811830
final  value 93.811828 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.123395 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.480024 
iter  10 value 94.392006
iter  20 value 92.319916
iter  30 value 88.844586
iter  40 value 86.454831
iter  50 value 84.136799
iter  60 value 82.886033
iter  70 value 82.290620
iter  80 value 82.114747
iter  90 value 82.108649
final  value 82.106631 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.677019 
iter  10 value 94.412610
iter  20 value 92.448419
iter  30 value 89.884135
iter  40 value 87.020193
iter  50 value 86.138606
iter  60 value 83.410846
iter  70 value 82.806699
iter  80 value 80.701519
iter  90 value 79.849172
iter 100 value 79.495858
final  value 79.495858 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.415431 
iter  10 value 94.488484
iter  20 value 93.236530
iter  30 value 84.720453
iter  40 value 81.955749
iter  50 value 81.187507
iter  60 value 80.541396
iter  70 value 80.462983
final  value 80.457530 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.995902 
iter  10 value 94.463080
iter  20 value 94.025719
iter  30 value 93.965882
iter  40 value 91.788314
iter  50 value 86.521835
iter  60 value 85.922977
iter  70 value 85.830786
iter  80 value 85.784368
iter  90 value 82.815469
iter 100 value 82.173672
final  value 82.173672 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.612782 
iter  10 value 94.462931
iter  20 value 91.152133
iter  30 value 85.335850
iter  40 value 84.848140
iter  50 value 82.501160
iter  60 value 80.480169
iter  70 value 79.553067
iter  80 value 79.536822
iter  90 value 79.528990
final  value 79.525788 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.741622 
iter  10 value 96.478115
iter  20 value 94.460247
iter  30 value 89.574145
iter  40 value 87.135661
iter  50 value 83.791145
iter  60 value 83.569589
iter  70 value 82.766315
iter  80 value 82.083456
iter  90 value 80.305331
iter 100 value 78.784745
final  value 78.784745 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.166744 
iter  10 value 94.552191
iter  20 value 93.825324
iter  30 value 91.779299
iter  40 value 90.382273
iter  50 value 85.544239
iter  60 value 84.382002
iter  70 value 83.664104
iter  80 value 82.302893
iter  90 value 79.975968
iter 100 value 79.582934
final  value 79.582934 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.038684 
iter  10 value 94.709587
iter  20 value 94.112415
iter  30 value 85.454344
iter  40 value 83.563817
iter  50 value 82.910216
iter  60 value 82.745288
iter  70 value 82.302765
iter  80 value 81.003401
iter  90 value 80.238223
iter 100 value 79.657844
final  value 79.657844 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.537684 
iter  10 value 94.407008
iter  20 value 88.896237
iter  30 value 83.996055
iter  40 value 80.809660
iter  50 value 78.742472
iter  60 value 78.565089
iter  70 value 78.368141
iter  80 value 78.209976
iter  90 value 78.113568
iter 100 value 77.987555
final  value 77.987555 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.623129 
iter  10 value 94.579917
iter  20 value 92.642142
iter  30 value 92.498424
iter  40 value 91.717754
iter  50 value 86.528219
iter  60 value 85.869845
iter  70 value 82.263313
iter  80 value 80.304678
iter  90 value 79.803158
iter 100 value 79.755108
final  value 79.755108 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.464775 
iter  10 value 94.636884
iter  20 value 91.696782
iter  30 value 90.556434
iter  40 value 85.890780
iter  50 value 84.151793
iter  60 value 83.940802
iter  70 value 83.165019
iter  80 value 81.847994
iter  90 value 81.471601
iter 100 value 80.559943
final  value 80.559943 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.116023 
iter  10 value 94.458972
iter  20 value 90.398717
iter  30 value 84.365702
iter  40 value 82.260127
iter  50 value 81.377012
iter  60 value 81.215382
iter  70 value 80.945548
iter  80 value 80.749084
iter  90 value 80.113377
iter 100 value 79.142998
final  value 79.142998 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.892913 
iter  10 value 94.207259
iter  20 value 85.832771
iter  30 value 83.609584
iter  40 value 83.165367
iter  50 value 80.496994
iter  60 value 78.328226
iter  70 value 78.116168
iter  80 value 77.955137
iter  90 value 77.780962
iter 100 value 77.729591
final  value 77.729591 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.150205 
iter  10 value 94.842281
iter  20 value 94.097609
iter  30 value 86.413321
iter  40 value 83.309761
iter  50 value 82.792167
iter  60 value 79.639979
iter  70 value 78.464786
iter  80 value 78.345879
iter  90 value 78.269020
iter 100 value 78.228929
final  value 78.228929 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.954758 
iter  10 value 95.871424
iter  20 value 88.108102
iter  30 value 83.779307
iter  40 value 80.702342
iter  50 value 79.347214
iter  60 value 79.089233
iter  70 value 78.855859
iter  80 value 78.716005
iter  90 value 78.261313
iter 100 value 78.077579
final  value 78.077579 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.403242 
final  value 94.485754 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.905710 
final  value 94.485896 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.483124 
final  value 94.485649 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.993239 
final  value 94.486068 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.090164 
iter  10 value 94.485846
iter  20 value 94.474062
iter  30 value 93.838520
iter  40 value 85.700788
iter  50 value 85.692393
iter  50 value 85.692392
iter  60 value 85.093108
iter  70 value 85.057484
final  value 85.057449 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.115349 
iter  10 value 94.488939
iter  20 value 93.973840
final  value 93.812757 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.473036 
iter  10 value 94.489752
iter  20 value 94.484483
iter  30 value 92.330618
iter  40 value 91.927151
final  value 91.927109 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.726674 
iter  10 value 93.779440
iter  20 value 93.778772
iter  30 value 93.776565
iter  40 value 93.775217
iter  50 value 93.774814
iter  60 value 93.773380
iter  60 value 93.773379
final  value 93.773379 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.850660 
iter  10 value 94.488953
iter  20 value 94.484219
iter  30 value 90.892450
iter  40 value 85.962686
iter  50 value 83.479466
iter  60 value 83.478149
iter  70 value 83.311985
final  value 83.311904 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.713759 
iter  10 value 94.486205
iter  20 value 86.903114
iter  30 value 82.515264
iter  40 value 82.508482
final  value 82.508414 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.992875 
iter  10 value 94.492616
iter  20 value 94.361996
iter  30 value 91.684792
iter  40 value 91.345382
final  value 91.276475 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.905902 
iter  10 value 94.066705
iter  20 value 91.304030
iter  30 value 91.300588
iter  40 value 91.015332
iter  50 value 90.993552
iter  60 value 90.992175
iter  70 value 90.990603
iter  80 value 90.987235
final  value 90.985568 
converged
Fitting Repeat 3 

# weights:  507
initial  value 147.923124 
iter  10 value 93.820829
iter  20 value 93.819122
iter  30 value 93.319555
iter  40 value 92.497443
iter  50 value 85.631862
iter  60 value 85.206508
iter  70 value 85.197536
iter  80 value 83.655977
iter  90 value 80.028503
iter 100 value 79.463106
final  value 79.463106 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.600588 
iter  10 value 94.495317
iter  20 value 94.453070
iter  30 value 93.882899
iter  40 value 91.700122
iter  50 value 91.691010
iter  60 value 91.689536
iter  70 value 91.686448
iter  80 value 91.673333
iter  90 value 91.669841
iter 100 value 86.443895
final  value 86.443895 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.141370 
iter  10 value 93.820205
iter  20 value 93.818121
iter  30 value 93.682929
iter  40 value 93.629140
iter  50 value 93.628939
iter  60 value 93.628887
final  value 93.628873 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.683485 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.882930 
iter  10 value 92.247458
iter  20 value 92.222391
iter  30 value 92.222324
iter  40 value 92.222271
iter  50 value 92.222224
final  value 92.222222 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.983366 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.935477 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.505543 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.550609 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.132546 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.776701 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.949981 
iter  10 value 92.230004
iter  20 value 92.222266
final  value 92.222223 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.573038 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.260768 
iter  10 value 92.297334
iter  20 value 92.281096
final  value 92.281082 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.006040 
iter  10 value 92.287033
iter  20 value 92.281087
final  value 92.281082 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.892013 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.999303 
iter  10 value 93.694474
iter  20 value 93.668596
iter  20 value 93.668596
iter  20 value 93.668596
final  value 93.668596 
converged
Fitting Repeat 5 

# weights:  507
initial  value 127.817848 
iter  10 value 92.617671
iter  20 value 92.281448
final  value 92.281082 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.265434 
iter  10 value 95.927126
iter  20 value 94.056445
iter  30 value 93.408578
iter  40 value 93.163429
iter  50 value 92.821204
iter  60 value 92.738118
iter  70 value 86.359112
iter  80 value 85.860432
iter  90 value 85.616738
iter 100 value 84.405836
final  value 84.405836 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.886440 
iter  10 value 93.779294
iter  20 value 89.832110
iter  30 value 84.125702
iter  40 value 83.442224
iter  50 value 81.805655
iter  60 value 81.570606
iter  70 value 80.969059
iter  80 value 80.831875
iter  90 value 80.461059
iter 100 value 80.279691
final  value 80.279691 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.295697 
iter  10 value 92.038176
iter  20 value 86.036755
iter  30 value 83.848490
iter  40 value 83.123241
iter  50 value 82.497018
iter  60 value 82.399158
iter  70 value 82.365304
final  value 82.365278 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.389665 
iter  10 value 94.048442
iter  20 value 86.825604
iter  30 value 84.719036
iter  40 value 84.230408
iter  50 value 83.737072
iter  60 value 83.366250
iter  70 value 81.285671
iter  80 value 80.579766
iter  90 value 80.281925
final  value 80.279436 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.173216 
iter  10 value 93.434464
iter  20 value 87.003329
iter  30 value 86.672690
iter  40 value 85.448503
iter  50 value 83.532781
iter  60 value 83.090702
iter  70 value 81.397344
iter  80 value 80.445653
iter  90 value 80.280427
final  value 80.279435 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.250278 
iter  10 value 87.970108
iter  20 value 87.032142
iter  30 value 83.673026
iter  40 value 82.868318
iter  50 value 81.018452
iter  60 value 79.924335
iter  70 value 79.732770
iter  80 value 79.720938
iter  90 value 79.685292
iter 100 value 79.654192
final  value 79.654192 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.067515 
iter  10 value 93.280242
iter  20 value 92.856124
iter  30 value 87.228544
iter  40 value 85.705623
iter  50 value 85.190159
iter  60 value 84.707793
iter  70 value 83.786070
iter  80 value 81.454213
iter  90 value 79.850726
iter 100 value 79.228348
final  value 79.228348 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.872074 
iter  10 value 91.551650
iter  20 value 86.895317
iter  30 value 85.473989
iter  40 value 82.074671
iter  50 value 80.989112
iter  60 value 80.715300
iter  70 value 80.630443
iter  80 value 79.849297
iter  90 value 79.266744
iter 100 value 78.846310
final  value 78.846310 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.653958 
iter  10 value 93.953753
iter  20 value 92.869666
iter  30 value 88.129287
iter  40 value 86.540778
iter  50 value 83.689006
iter  60 value 80.628881
iter  70 value 80.329833
iter  80 value 80.186307
iter  90 value 79.840530
iter 100 value 79.163795
final  value 79.163795 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.001689 
iter  10 value 88.451666
iter  20 value 83.174902
iter  30 value 82.054312
iter  40 value 79.745478
iter  50 value 78.460340
iter  60 value 78.414433
iter  70 value 78.326754
iter  80 value 78.103926
iter  90 value 77.934652
iter 100 value 77.903123
final  value 77.903123 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.748483 
iter  10 value 94.057145
iter  20 value 92.962680
iter  30 value 91.379351
iter  40 value 84.721768
iter  50 value 83.589103
iter  60 value 81.138116
iter  70 value 79.547455
iter  80 value 78.689919
iter  90 value 78.509410
iter 100 value 78.368207
final  value 78.368207 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.901420 
iter  10 value 93.476742
iter  20 value 91.435836
iter  30 value 87.658221
iter  40 value 86.450253
iter  50 value 83.544189
iter  60 value 82.368850
iter  70 value 79.916150
iter  80 value 79.298943
iter  90 value 78.965234
iter 100 value 78.904024
final  value 78.904024 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.842216 
iter  10 value 93.233483
iter  20 value 86.526659
iter  30 value 82.161686
iter  40 value 81.720779
iter  50 value 81.073762
iter  60 value 80.175057
iter  70 value 78.759207
iter  80 value 78.579666
iter  90 value 78.385015
iter 100 value 78.270980
final  value 78.270980 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.851991 
iter  10 value 94.159490
iter  20 value 93.435127
iter  30 value 93.094425
iter  40 value 92.560096
iter  50 value 86.788569
iter  60 value 85.201394
iter  70 value 83.650237
iter  80 value 82.652774
iter  90 value 82.452468
iter 100 value 80.729553
final  value 80.729553 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.240676 
iter  10 value 94.040656
iter  20 value 91.084850
iter  30 value 84.618657
iter  40 value 80.967117
iter  50 value 79.916485
iter  60 value 79.195512
iter  70 value 78.605855
iter  80 value 78.331495
iter  90 value 78.002011
iter 100 value 77.861563
final  value 77.861563 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.577489 
final  value 94.054804 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.729792 
final  value 94.054538 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.020568 
final  value 94.054711 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.698901 
iter  10 value 94.054408
iter  20 value 94.052912
iter  20 value 94.052912
iter  20 value 94.052912
final  value 94.052912 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.353651 
final  value 94.054600 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.131343 
iter  10 value 93.379088
iter  20 value 87.022275
iter  30 value 85.926080
iter  40 value 85.601628
iter  50 value 85.591619
iter  60 value 85.591123
final  value 85.590854 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.021680 
iter  10 value 94.058184
iter  20 value 94.053263
final  value 94.053235 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.027516 
iter  10 value 94.057649
iter  20 value 94.052930
iter  30 value 93.353956
iter  40 value 92.287672
final  value 92.286188 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.854514 
iter  10 value 92.233987
iter  20 value 92.226773
iter  30 value 92.224256
iter  40 value 92.223832
final  value 92.223160 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.047885 
iter  10 value 94.057812
iter  20 value 89.175073
iter  30 value 86.908139
iter  40 value 86.907255
final  value 86.906781 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.846331 
iter  10 value 93.536092
iter  20 value 92.301753
iter  30 value 92.296803
iter  40 value 91.159761
iter  50 value 84.874103
iter  60 value 84.502895
final  value 84.497652 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.624648 
iter  10 value 94.061099
iter  20 value 94.006456
iter  30 value 92.310178
iter  40 value 92.305030
iter  50 value 92.292256
iter  60 value 84.557986
iter  70 value 84.118675
iter  80 value 84.116698
iter  90 value 84.076844
iter 100 value 84.025000
final  value 84.025000 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.335353 
iter  10 value 85.851470
iter  20 value 81.736229
iter  30 value 81.706393
iter  40 value 81.704834
iter  50 value 81.698300
iter  60 value 81.113797
iter  70 value 81.018965
iter  80 value 79.963215
iter  90 value 79.824618
iter 100 value 79.803934
final  value 79.803934 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.611989 
iter  10 value 94.061538
iter  20 value 91.354517
iter  30 value 88.072554
iter  40 value 88.066933
iter  50 value 85.456030
iter  60 value 85.432538
iter  70 value 85.092604
iter  80 value 84.359185
iter  90 value 84.356856
iter 100 value 84.355824
final  value 84.355824 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.902958 
iter  10 value 94.060052
iter  20 value 93.623482
iter  30 value 86.050410
iter  40 value 84.631227
iter  50 value 84.609282
iter  60 value 83.650099
iter  70 value 83.362207
iter  80 value 83.356678
iter  90 value 83.320558
iter 100 value 83.215119
final  value 83.215119 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.462224 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.896464 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 124.936212 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.805631 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.836441 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.211813 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.531904 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.671564 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.372326 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.455814 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.416512 
iter  10 value 94.334011
iter  10 value 94.334011
iter  10 value 94.334011
final  value 94.334011 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.860393 
iter  10 value 94.334038
final  value 94.334011 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.216316 
iter  10 value 89.628492
iter  20 value 88.943841
iter  30 value 88.915591
iter  40 value 88.915431
iter  40 value 88.915431
iter  40 value 88.915431
final  value 88.915431 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.211718 
iter  10 value 94.338754
final  value 94.338745 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.226155 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.674446 
iter  10 value 94.482477
iter  20 value 86.487441
iter  30 value 84.165978
iter  40 value 83.694046
iter  50 value 83.468756
iter  60 value 83.335018
iter  70 value 83.248994
iter  80 value 83.191444
final  value 83.190030 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.531849 
iter  10 value 93.678619
iter  20 value 91.256292
iter  30 value 87.791366
iter  40 value 84.573767
iter  50 value 83.210140
iter  60 value 82.356639
iter  70 value 81.987020
iter  80 value 81.954428
final  value 81.954423 
converged
Fitting Repeat 3 

# weights:  103
initial  value 122.585859 
iter  10 value 94.288469
iter  20 value 89.720453
iter  30 value 88.543513
iter  40 value 86.775482
iter  50 value 85.690296
iter  60 value 85.420543
iter  70 value 84.947001
iter  80 value 82.722435
iter  90 value 82.328038
iter 100 value 81.546791
final  value 81.546791 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.009548 
iter  10 value 94.488793
iter  20 value 94.369057
iter  30 value 88.917599
iter  40 value 87.288196
iter  50 value 85.608805
iter  60 value 84.333263
iter  70 value 84.132546
iter  80 value 83.953567
iter  90 value 83.810317
iter 100 value 83.754200
final  value 83.754200 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 113.779962 
iter  10 value 94.494773
iter  20 value 94.301143
iter  30 value 93.547423
iter  40 value 87.404814
iter  50 value 83.550122
iter  60 value 82.964773
iter  70 value 82.434481
iter  80 value 82.093786
iter  90 value 82.025025
iter 100 value 81.981178
final  value 81.981178 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.952424 
iter  10 value 94.754747
iter  20 value 94.497996
iter  30 value 88.645155
iter  40 value 86.572603
iter  50 value 83.960485
iter  60 value 82.358590
iter  70 value 81.972424
iter  80 value 81.495157
iter  90 value 81.217730
iter 100 value 81.151483
final  value 81.151483 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.910589 
iter  10 value 94.237537
iter  20 value 88.333506
iter  30 value 85.791234
iter  40 value 83.846698
iter  50 value 82.719280
iter  60 value 82.395003
iter  70 value 82.165830
iter  80 value 81.987267
iter  90 value 81.828874
iter 100 value 81.803057
final  value 81.803057 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.719961 
iter  10 value 96.606363
iter  20 value 94.724064
iter  30 value 94.092894
iter  40 value 86.477142
iter  50 value 84.405804
iter  60 value 83.954275
iter  70 value 83.760372
iter  80 value 83.672476
iter  90 value 83.611632
iter 100 value 82.803861
final  value 82.803861 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.708928 
iter  10 value 94.391132
iter  20 value 88.201625
iter  30 value 84.527853
iter  40 value 83.889095
iter  50 value 83.443545
iter  60 value 83.343848
iter  70 value 83.251984
iter  80 value 81.988515
iter  90 value 81.186533
iter 100 value 80.928202
final  value 80.928202 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.737937 
iter  10 value 94.488199
iter  20 value 87.104145
iter  30 value 85.983750
iter  40 value 84.000994
iter  50 value 83.585925
iter  60 value 83.297945
iter  70 value 81.787882
iter  80 value 81.046161
iter  90 value 80.495682
iter 100 value 80.321291
final  value 80.321291 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.523587 
iter  10 value 91.575819
iter  20 value 86.283278
iter  30 value 85.346728
iter  40 value 84.294517
iter  50 value 83.149400
iter  60 value 82.436954
iter  70 value 81.813540
iter  80 value 81.500310
iter  90 value 81.145028
iter 100 value 80.610881
final  value 80.610881 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.160146 
iter  10 value 94.270648
iter  20 value 91.314246
iter  30 value 90.275150
iter  40 value 89.907922
iter  50 value 89.843665
iter  60 value 89.787850
iter  70 value 88.617833
iter  80 value 83.018094
iter  90 value 81.786772
iter 100 value 81.321048
final  value 81.321048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.717355 
iter  10 value 94.469336
iter  20 value 93.927715
iter  30 value 88.628379
iter  40 value 86.365439
iter  50 value 84.513260
iter  60 value 83.963076
iter  70 value 83.085519
iter  80 value 81.413595
iter  90 value 80.871956
iter 100 value 80.800314
final  value 80.800314 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.364041 
iter  10 value 94.494858
iter  20 value 92.976574
iter  30 value 89.452754
iter  40 value 83.175753
iter  50 value 82.422225
iter  60 value 81.945600
iter  70 value 81.797058
iter  80 value 81.625593
iter  90 value 81.112346
iter 100 value 80.956805
final  value 80.956805 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.650037 
iter  10 value 94.518477
iter  20 value 94.214153
iter  30 value 89.159554
iter  40 value 88.686109
iter  50 value 86.212538
iter  60 value 82.981385
iter  70 value 82.188227
iter  80 value 80.895853
iter  90 value 80.335978
iter 100 value 79.985949
final  value 79.985949 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.107192 
final  value 94.485769 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.041637 
final  value 94.485835 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.862277 
final  value 94.486053 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.224009 
final  value 94.485744 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.327657 
final  value 94.485934 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.982451 
iter  10 value 94.359301
iter  20 value 94.354725
iter  30 value 94.313050
iter  40 value 88.874570
iter  50 value 88.837155
iter  60 value 87.843584
iter  70 value 87.823485
iter  80 value 87.823361
final  value 87.823315 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.691250 
iter  10 value 94.392025
iter  20 value 94.390688
iter  30 value 94.365210
iter  40 value 93.981701
iter  50 value 83.335519
final  value 83.335503 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.373945 
iter  10 value 94.453251
iter  20 value 94.449753
iter  30 value 86.543360
final  value 85.512642 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.568351 
iter  10 value 94.488321
iter  20 value 86.673995
iter  30 value 85.280390
iter  40 value 85.193268
iter  50 value 85.193157
iter  50 value 85.193156
iter  50 value 85.193156
final  value 85.193156 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.827004 
iter  10 value 94.488419
iter  20 value 85.710830
final  value 85.513005 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.042964 
iter  10 value 94.362915
iter  20 value 94.355592
iter  30 value 93.848852
iter  40 value 87.135183
iter  50 value 86.817431
iter  60 value 86.413590
iter  70 value 86.403746
iter  80 value 86.397339
iter  90 value 86.350233
iter 100 value 86.025723
final  value 86.025723 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.006407 
iter  10 value 91.736374
iter  20 value 87.694017
iter  30 value 87.433362
iter  40 value 83.940887
iter  50 value 83.572900
iter  60 value 83.541061
iter  70 value 83.486183
iter  80 value 82.175168
iter  90 value 81.696722
iter 100 value 81.243651
final  value 81.243651 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.568266 
iter  10 value 94.490390
iter  20 value 94.301869
iter  30 value 85.522216
iter  40 value 85.314527
iter  50 value 84.155553
iter  60 value 83.825028
iter  70 value 83.610470
iter  80 value 83.608757
iter  90 value 83.607066
iter 100 value 83.599553
final  value 83.599553 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.729762 
iter  10 value 94.491997
iter  20 value 94.479272
iter  30 value 90.280137
iter  40 value 90.247311
iter  50 value 90.116113
iter  60 value 90.109538
iter  70 value 90.093136
iter  80 value 89.843683
iter  90 value 89.839076
iter  90 value 89.839076
iter  90 value 89.839076
final  value 89.839076 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.969191 
iter  10 value 94.355574
iter  20 value 94.352323
iter  30 value 94.321300
iter  40 value 94.317592
iter  50 value 94.317454
iter  60 value 88.828920
iter  70 value 86.773749
iter  80 value 86.760376
final  value 86.760346 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.392285 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.402729 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.455099 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.923330 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.658853 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.049390 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.762997 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.280488 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.684642 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.420052 
final  value 94.385583 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.071692 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.688071 
iter  10 value 91.958177
iter  20 value 87.531629
iter  30 value 83.296644
iter  40 value 83.227672
iter  50 value 83.192943
iter  60 value 83.192550
iter  60 value 83.192549
iter  60 value 83.192549
final  value 83.192549 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.592878 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.844875 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.184257 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.990058 
iter  10 value 94.492235
iter  20 value 90.363748
iter  30 value 89.255330
iter  40 value 84.657815
iter  50 value 83.555994
iter  60 value 83.212646
iter  70 value 82.945683
iter  80 value 82.788405
iter  90 value 82.697620
final  value 82.696472 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.307679 
iter  10 value 94.441110
iter  20 value 89.038477
iter  30 value 87.315507
iter  40 value 86.122892
iter  50 value 84.471745
iter  60 value 84.326036
final  value 84.279778 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.160694 
iter  10 value 94.489523
iter  20 value 85.407362
iter  30 value 84.358501
iter  40 value 84.138145
iter  50 value 84.065002
iter  60 value 83.994764
iter  70 value 83.436128
iter  80 value 83.356892
iter  90 value 83.316321
iter 100 value 83.307899
final  value 83.307899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.249800 
iter  10 value 93.710446
iter  20 value 90.062831
iter  30 value 86.714362
iter  40 value 84.528096
iter  50 value 84.027305
iter  60 value 83.592991
final  value 83.587515 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.576125 
iter  10 value 94.491778
iter  20 value 94.316044
iter  30 value 91.398099
iter  40 value 89.638719
iter  50 value 88.724117
iter  60 value 85.673122
iter  70 value 84.569713
iter  80 value 84.519925
iter  90 value 84.139550
iter 100 value 83.618925
final  value 83.618925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.119063 
iter  10 value 94.866941
iter  20 value 94.469747
iter  30 value 92.863765
iter  40 value 85.136647
iter  50 value 82.865885
iter  60 value 81.264088
iter  70 value 80.770978
iter  80 value 80.406189
iter  90 value 80.324459
iter 100 value 80.269312
final  value 80.269312 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.753202 
iter  10 value 94.465314
iter  20 value 90.938637
iter  30 value 86.826591
iter  40 value 83.166665
iter  50 value 81.673853
iter  60 value 81.064019
iter  70 value 80.778487
iter  80 value 80.694986
iter  90 value 80.467349
iter 100 value 80.205506
final  value 80.205506 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.444056 
iter  10 value 93.055847
iter  20 value 91.673432
iter  30 value 89.008911
iter  40 value 86.251224
iter  50 value 85.801137
iter  60 value 85.372512
iter  70 value 83.183511
iter  80 value 80.632569
iter  90 value 80.177320
iter 100 value 80.011061
final  value 80.011061 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.705682 
iter  10 value 94.663206
iter  20 value 94.251781
iter  30 value 93.150492
iter  40 value 88.158968
iter  50 value 82.842689
iter  60 value 80.745553
iter  70 value 80.192221
iter  80 value 80.109089
iter  90 value 79.934909
iter 100 value 79.604763
final  value 79.604763 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.171249 
iter  10 value 95.564298
iter  20 value 84.269889
iter  30 value 83.495583
iter  40 value 83.378758
iter  50 value 82.744457
iter  60 value 81.431525
iter  70 value 80.600107
iter  80 value 79.674296
iter  90 value 79.596747
iter 100 value 79.558829
final  value 79.558829 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.683129 
iter  10 value 94.605234
iter  20 value 93.776013
iter  30 value 84.884795
iter  40 value 83.640138
iter  50 value 83.280404
iter  60 value 83.226052
iter  70 value 83.179701
iter  80 value 83.014885
iter  90 value 82.947038
iter 100 value 82.856217
final  value 82.856217 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.081307 
iter  10 value 95.762356
iter  20 value 95.293670
iter  30 value 94.393571
iter  40 value 86.404907
iter  50 value 83.730808
iter  60 value 83.479048
iter  70 value 83.346300
iter  80 value 83.254601
iter  90 value 82.325015
iter 100 value 81.963290
final  value 81.963290 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.253626 
iter  10 value 94.471014
iter  20 value 91.879783
iter  30 value 88.600069
iter  40 value 84.787311
iter  50 value 82.226767
iter  60 value 80.726444
iter  70 value 80.125862
iter  80 value 80.041414
iter  90 value 79.926326
iter 100 value 79.881794
final  value 79.881794 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.038226 
iter  10 value 94.462381
iter  20 value 93.212091
iter  30 value 87.792774
iter  40 value 85.220390
iter  50 value 84.700476
iter  60 value 82.931400
iter  70 value 82.058417
iter  80 value 81.268403
iter  90 value 81.066058
iter 100 value 80.219210
final  value 80.219210 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.917387 
iter  10 value 92.626226
iter  20 value 86.443001
iter  30 value 84.065978
iter  40 value 83.817519
iter  50 value 83.623945
iter  60 value 83.243217
iter  70 value 82.436536
iter  80 value 81.676547
iter  90 value 81.061960
iter 100 value 80.420875
final  value 80.420875 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.912005 
final  value 94.485836 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.728399 
final  value 94.485744 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.269305 
iter  10 value 94.355948
iter  20 value 94.131697
iter  30 value 83.353541
iter  40 value 83.265543
iter  50 value 83.232528
iter  60 value 83.230483
iter  70 value 83.228864
iter  80 value 83.228748
iter  80 value 83.228748
iter  80 value 83.228748
final  value 83.228748 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.539005 
iter  10 value 94.054213
final  value 94.054193 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.328974 
final  value 94.485943 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.303841 
iter  10 value 94.489155
iter  20 value 94.484228
final  value 94.484212 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.289639 
iter  10 value 94.359118
iter  20 value 94.354753
iter  30 value 94.043096
final  value 94.038295 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.707966 
iter  10 value 94.358923
iter  20 value 94.347060
iter  30 value 93.255727
iter  40 value 90.897322
iter  50 value 89.565186
iter  60 value 89.564926
final  value 89.564882 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.549927 
iter  10 value 92.618913
iter  20 value 92.614987
iter  30 value 85.930670
iter  40 value 85.691819
final  value 85.593372 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.894694 
iter  10 value 92.292179
iter  20 value 92.282857
iter  30 value 85.054213
iter  40 value 82.694436
final  value 82.694377 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.087944 
iter  10 value 94.150003
iter  20 value 89.819157
iter  30 value 86.829515
iter  40 value 86.688140
iter  50 value 86.592988
iter  60 value 86.343710
final  value 86.342802 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.016716 
iter  10 value 94.362486
iter  20 value 94.357154
final  value 94.356209 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.344355 
iter  10 value 87.411933
iter  20 value 86.142882
iter  30 value 83.258072
iter  40 value 83.058842
iter  50 value 83.057021
iter  60 value 83.052090
iter  70 value 83.045736
iter  80 value 83.045209
iter  90 value 82.873439
iter 100 value 82.569710
final  value 82.569710 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.472992 
iter  10 value 94.491947
iter  20 value 94.403239
iter  30 value 93.969897
final  value 93.969560 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.438538 
iter  10 value 94.339787
iter  20 value 94.060467
iter  30 value 94.052017
final  value 94.038489 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.935804 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.217854 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.348222 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.686034 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.339591 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.171309 
iter  10 value 85.361220
iter  20 value 84.751310
iter  30 value 84.654770
final  value 84.654717 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.578774 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.764855 
final  value 94.011429 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.291935 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.812045 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.002883 
iter  10 value 89.272487
iter  20 value 88.593946
iter  30 value 88.580083
iter  40 value 87.944442
iter  50 value 87.784772
iter  60 value 87.784310
final  value 87.784309 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.461216 
iter  10 value 93.836066
iter  10 value 93.836066
iter  10 value 93.836066
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.433900 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.322986 
iter  10 value 93.836072
final  value 93.836070 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.558648 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.633255 
iter  10 value 93.806018
iter  20 value 89.213718
iter  30 value 89.115865
iter  40 value 88.242984
iter  50 value 87.790593
iter  60 value 86.192764
iter  70 value 86.053900
iter  80 value 86.029154
final  value 86.029132 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.704498 
iter  10 value 93.934041
iter  20 value 88.148386
iter  30 value 87.337855
iter  40 value 86.258244
iter  50 value 84.237122
iter  60 value 83.808060
iter  70 value 83.766206
iter  80 value 83.678416
final  value 83.674642 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.722538 
iter  10 value 95.019101
iter  20 value 94.061543
iter  30 value 93.995163
iter  40 value 93.695357
iter  50 value 93.680204
iter  60 value 92.333081
iter  70 value 88.999915
iter  80 value 87.448396
iter  90 value 87.363690
iter 100 value 86.713744
final  value 86.713744 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.428690 
iter  10 value 94.047495
iter  20 value 88.626277
iter  30 value 87.771921
iter  40 value 85.268501
iter  50 value 84.694939
iter  60 value 84.260817
iter  70 value 84.047436
iter  80 value 83.801548
iter  90 value 83.761166
iter 100 value 83.712253
final  value 83.712253 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.413378 
iter  10 value 93.896961
iter  20 value 90.927954
iter  30 value 88.862150
iter  40 value 85.079056
iter  50 value 84.512216
iter  60 value 84.024127
iter  70 value 83.805160
iter  80 value 83.674827
final  value 83.674642 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.072459 
iter  10 value 94.109781
iter  20 value 90.454416
iter  30 value 88.572899
iter  40 value 88.085900
iter  50 value 87.841669
iter  60 value 87.696865
iter  70 value 87.468910
iter  80 value 85.065544
iter  90 value 84.336812
iter 100 value 84.137799
final  value 84.137799 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.134176 
iter  10 value 95.547494
iter  20 value 92.940072
iter  30 value 89.903236
iter  40 value 86.303746
iter  50 value 85.065776
iter  60 value 84.030482
iter  70 value 83.942944
iter  80 value 83.807053
iter  90 value 83.791334
iter 100 value 83.782367
final  value 83.782367 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.134143 
iter  10 value 94.096939
iter  20 value 93.970794
iter  30 value 93.649101
iter  40 value 89.076770
iter  50 value 87.714806
iter  60 value 86.823912
iter  70 value 85.501090
iter  80 value 84.788475
iter  90 value 84.392359
iter 100 value 83.103835
final  value 83.103835 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.861244 
iter  10 value 94.005084
iter  20 value 88.416473
iter  30 value 87.804993
iter  40 value 87.609314
iter  50 value 84.832465
iter  60 value 83.894242
iter  70 value 83.525204
iter  80 value 83.486893
iter  90 value 83.343229
iter 100 value 83.033316
final  value 83.033316 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.209190 
iter  10 value 93.958910
iter  20 value 89.195709
iter  30 value 85.736637
iter  40 value 85.481082
iter  50 value 85.395187
iter  60 value 84.130682
iter  70 value 83.468237
iter  80 value 83.341642
iter  90 value 83.324043
iter 100 value 83.318330
final  value 83.318330 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.182619 
iter  10 value 94.230076
iter  20 value 88.464654
iter  30 value 87.739637
iter  40 value 86.237930
iter  50 value 83.750655
iter  60 value 83.424544
iter  70 value 83.230266
iter  80 value 82.833467
iter  90 value 82.681688
iter 100 value 82.661114
final  value 82.661114 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.582612 
iter  10 value 94.073875
iter  20 value 91.875039
iter  30 value 89.828005
iter  40 value 87.989159
iter  50 value 86.936199
iter  60 value 83.950935
iter  70 value 83.202809
iter  80 value 82.814711
iter  90 value 82.661283
iter 100 value 82.518809
final  value 82.518809 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.989717 
iter  10 value 94.153612
iter  20 value 86.189073
iter  30 value 84.753308
iter  40 value 83.282334
iter  50 value 82.770347
iter  60 value 82.531704
iter  70 value 82.270771
iter  80 value 82.165565
iter  90 value 82.153065
iter 100 value 82.085848
final  value 82.085848 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.071379 
iter  10 value 94.026949
iter  20 value 87.339541
iter  30 value 86.148944
iter  40 value 85.551525
iter  50 value 84.200578
iter  60 value 83.917800
iter  70 value 83.877224
iter  80 value 83.852889
iter  90 value 83.812492
iter 100 value 83.178453
final  value 83.178453 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.224554 
iter  10 value 94.113496
iter  20 value 90.389511
iter  30 value 88.432778
iter  40 value 85.873961
iter  50 value 85.167212
iter  60 value 83.933383
iter  70 value 83.519947
iter  80 value 83.071291
iter  90 value 82.774932
iter 100 value 82.694025
final  value 82.694025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.100176 
final  value 94.054510 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.294019 
final  value 94.054309 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.179000 
iter  10 value 94.054412
iter  20 value 94.052966
final  value 94.052918 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.873289 
final  value 94.054582 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.353651 
final  value 94.054600 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.139570 
iter  10 value 94.057538
iter  20 value 93.953828
iter  30 value 90.366960
iter  40 value 89.832988
iter  50 value 89.776372
iter  60 value 85.866678
iter  70 value 85.241889
iter  80 value 85.227396
iter  90 value 85.208455
iter 100 value 84.581551
final  value 84.581551 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.917510 
iter  10 value 93.921127
iter  20 value 93.333591
iter  30 value 87.155530
iter  40 value 87.069645
final  value 87.069476 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.101470 
iter  10 value 93.920479
iter  20 value 93.223371
iter  30 value 91.372110
iter  40 value 86.820946
iter  50 value 83.441220
iter  60 value 83.076983
iter  70 value 82.784519
iter  80 value 82.340927
iter  90 value 82.336199
iter 100 value 82.336125
final  value 82.336125 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.515723 
iter  10 value 94.057435
iter  20 value 94.052951
final  value 94.052932 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.481864 
iter  10 value 94.057303
iter  20 value 94.052940
iter  30 value 94.039654
iter  40 value 93.697958
iter  50 value 93.153767
iter  60 value 86.620083
iter  70 value 84.168391
iter  80 value 83.851195
iter  90 value 83.824785
iter 100 value 83.822123
final  value 83.822123 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.412331 
iter  10 value 94.001549
iter  20 value 93.963053
iter  30 value 92.045959
iter  40 value 90.849024
iter  50 value 84.995909
iter  60 value 84.978710
iter  70 value 84.801878
iter  80 value 84.606356
iter  90 value 84.590605
iter 100 value 84.590518
final  value 84.590518 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.414802 
iter  10 value 94.049934
iter  20 value 93.682062
iter  30 value 93.634123
iter  40 value 93.634036
final  value 93.634033 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.790838 
iter  10 value 93.923451
iter  20 value 93.910542
iter  30 value 92.529343
iter  40 value 86.000687
iter  50 value 84.832266
iter  60 value 84.813201
iter  70 value 84.757784
iter  80 value 84.670053
iter  90 value 83.996604
iter 100 value 82.810755
final  value 82.810755 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.356161 
iter  10 value 93.924882
iter  20 value 93.917361
iter  30 value 93.739927
iter  40 value 90.839362
iter  50 value 90.838811
iter  60 value 90.794346
iter  70 value 85.771219
iter  80 value 85.760634
iter  90 value 85.595773
iter 100 value 85.539828
final  value 85.539828 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.121657 
iter  10 value 93.923829
iter  20 value 93.231852
iter  30 value 86.708749
iter  40 value 86.706648
iter  50 value 86.706514
iter  60 value 86.683644
iter  70 value 86.665437
final  value 86.665357 
converged
Fitting Repeat 1 

# weights:  305
initial  value 124.331413 
iter  10 value 117.939041
iter  20 value 117.624019
iter  30 value 107.012576
iter  40 value 105.779957
iter  50 value 104.801519
iter  60 value 104.145849
iter  70 value 103.642431
iter  80 value 103.166905
iter  90 value 102.838478
iter 100 value 102.630513
final  value 102.630513 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 145.147697 
iter  10 value 118.092386
iter  20 value 117.885246
iter  30 value 111.511415
iter  40 value 108.775443
iter  50 value 107.650649
iter  60 value 106.865087
iter  70 value 106.295210
iter  80 value 104.944879
iter  90 value 104.132206
iter 100 value 103.160878
final  value 103.160878 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.810111 
iter  10 value 117.819786
iter  20 value 108.931729
iter  30 value 106.826109
iter  40 value 106.034934
iter  50 value 105.815977
iter  60 value 105.667904
iter  70 value 105.031738
iter  80 value 104.786283
iter  90 value 104.554735
iter 100 value 103.150191
final  value 103.150191 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.696570 
iter  10 value 117.547497
iter  20 value 108.790096
iter  30 value 107.916823
iter  40 value 104.065932
iter  50 value 103.005604
iter  60 value 102.629833
iter  70 value 101.947278
iter  80 value 101.712392
iter  90 value 101.088655
iter 100 value 100.799912
final  value 100.799912 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 139.164430 
iter  10 value 117.788140
iter  20 value 113.923897
iter  30 value 106.427988
iter  40 value 105.944161
iter  50 value 103.951694
iter  60 value 103.541821
iter  70 value 103.328367
iter  80 value 103.042353
iter  90 value 102.290997
iter 100 value 101.718081
final  value 101.718081 
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 -- Wed May  6 20:45:56 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 
 19.213   0.569  68.769