##############################################################################
##############################################################################
###
### 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_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 RC (2025-06-05 r88288)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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
var_imp       52.445  1.937  56.415
corr_plot     50.389  1.874  53.687
FSmethod      49.986  1.883  52.512
pred_ensembel 24.939  0.392  22.578
enrichfindP    0.874  0.078  13.898
* 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-3.21-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/4.5-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 112.457687 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.799694 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.789580 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.441173 
final  value 94.482478 
converged
Fitting Repeat 5 

# weights:  103
initial  value 120.622382 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.119539 
iter  10 value 85.976083
final  value 85.840146 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.947825 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.783384 
iter  10 value 93.530228
iter  20 value 93.504298
iter  30 value 93.503451
final  value 93.503449 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.205564 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.339147 
iter  10 value 94.354423
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.794621 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.633229 
iter  10 value 93.599792
final  value 93.599711 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.674567 
final  value 93.599711 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.313484 
iter  10 value 94.275928
iter  20 value 86.427964
iter  30 value 83.720442
final  value 83.720430 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.717927 
iter  10 value 94.385742
final  value 94.354404 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.408130 
iter  10 value 94.506927
iter  20 value 94.395036
iter  30 value 84.771117
iter  40 value 83.547798
iter  50 value 82.695928
iter  60 value 82.393379
iter  70 value 82.232251
iter  80 value 82.109145
iter  90 value 82.027065
iter 100 value 81.804377
final  value 81.804377 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.509521 
iter  10 value 94.490827
iter  20 value 94.302412
iter  30 value 89.932825
iter  40 value 85.058883
iter  50 value 84.155752
iter  60 value 83.020814
iter  70 value 82.097409
iter  80 value 81.965154
iter  90 value 81.915372
iter 100 value 81.867235
final  value 81.867235 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.826887 
iter  10 value 94.417543
iter  20 value 93.866212
iter  30 value 88.610541
iter  40 value 86.800061
iter  50 value 83.188200
iter  60 value 82.676995
iter  70 value 82.361169
iter  80 value 82.180965
iter  90 value 82.070403
iter 100 value 81.889278
final  value 81.889278 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.399900 
iter  10 value 94.468364
iter  20 value 93.233989
iter  30 value 92.250507
iter  40 value 92.117184
iter  50 value 92.106843
final  value 92.106583 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.401828 
iter  10 value 94.484703
iter  20 value 94.075604
iter  30 value 88.659219
iter  40 value 87.213090
iter  50 value 86.889075
iter  60 value 84.848986
iter  70 value 84.068349
iter  80 value 83.974759
iter  90 value 83.786960
iter 100 value 83.631239
final  value 83.631239 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.866365 
iter  10 value 94.469494
iter  20 value 88.270788
iter  30 value 85.054380
iter  40 value 84.209077
iter  50 value 83.524676
iter  60 value 83.335416
iter  70 value 83.283341
iter  80 value 83.219600
iter  90 value 82.683978
iter 100 value 81.757066
final  value 81.757066 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.307427 
iter  10 value 95.491330
iter  20 value 92.526178
iter  30 value 91.094650
iter  40 value 88.970783
iter  50 value 86.042237
iter  60 value 83.374597
iter  70 value 82.879619
iter  80 value 82.514810
iter  90 value 81.790045
iter 100 value 81.202711
final  value 81.202711 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.108651 
iter  10 value 94.697659
iter  20 value 88.187037
iter  30 value 85.101005
iter  40 value 82.984495
iter  50 value 80.855893
iter  60 value 80.657540
iter  70 value 80.546406
iter  80 value 80.414177
iter  90 value 80.304304
iter 100 value 80.142977
final  value 80.142977 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.931690 
iter  10 value 94.709580
iter  20 value 89.529219
iter  30 value 87.675046
iter  40 value 83.343117
iter  50 value 81.665852
iter  60 value 81.145597
iter  70 value 80.713926
iter  80 value 80.622425
iter  90 value 80.479645
iter 100 value 80.453215
final  value 80.453215 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.578040 
iter  10 value 94.491547
iter  20 value 90.434654
iter  30 value 87.493523
iter  40 value 86.543729
iter  50 value 86.200076
iter  60 value 84.453778
iter  70 value 81.638590
iter  80 value 81.263437
iter  90 value 81.169927
iter 100 value 81.115764
final  value 81.115764 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.627674 
iter  10 value 94.471726
iter  20 value 94.338034
iter  30 value 85.943991
iter  40 value 85.362563
iter  50 value 84.870194
iter  60 value 83.526860
iter  70 value 81.397234
iter  80 value 80.708889
iter  90 value 80.400214
iter 100 value 80.091746
final  value 80.091746 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.729792 
iter  10 value 94.514713
iter  20 value 86.678540
iter  30 value 85.049605
iter  40 value 84.044389
iter  50 value 83.057568
iter  60 value 81.752840
iter  70 value 81.176851
iter  80 value 80.678892
iter  90 value 80.532781
iter 100 value 80.465037
final  value 80.465037 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.710280 
iter  10 value 94.782733
iter  20 value 93.640607
iter  30 value 91.558075
iter  40 value 91.049206
iter  50 value 83.807470
iter  60 value 82.538112
iter  70 value 82.418521
iter  80 value 82.118339
iter  90 value 81.332568
iter 100 value 80.842934
final  value 80.842934 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.241149 
iter  10 value 100.523238
iter  20 value 85.354876
iter  30 value 83.872227
iter  40 value 82.899828
iter  50 value 82.817183
iter  60 value 82.624666
iter  70 value 82.484001
iter  80 value 82.378505
iter  90 value 82.028363
iter 100 value 81.191438
final  value 81.191438 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.724799 
iter  10 value 94.770596
iter  20 value 93.020318
iter  30 value 91.693578
iter  40 value 86.684035
iter  50 value 84.777067
iter  60 value 84.647604
iter  70 value 84.041432
iter  80 value 82.655927
iter  90 value 81.154737
iter 100 value 80.903361
final  value 80.903361 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.488522 
final  value 94.485993 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.011987 
final  value 94.485675 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.702903 
iter  10 value 88.168327
iter  20 value 86.520500
iter  30 value 86.519589
iter  40 value 86.519486
iter  50 value 86.518415
iter  60 value 84.718549
iter  70 value 83.786537
iter  80 value 83.633494
iter  90 value 83.622063
final  value 83.619359 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.976502 
final  value 94.485607 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.579850 
final  value 94.485990 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.435146 
iter  10 value 94.355811
iter  20 value 94.351956
iter  30 value 94.345904
iter  40 value 94.258409
iter  50 value 87.637737
iter  60 value 87.372405
iter  70 value 87.372172
iter  80 value 85.676460
iter  90 value 85.405361
iter 100 value 85.404929
final  value 85.404929 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.626415 
iter  10 value 94.490393
iter  20 value 94.485280
iter  30 value 87.862829
iter  40 value 87.777081
iter  50 value 85.896445
iter  60 value 85.709342
iter  70 value 85.708807
iter  80 value 85.706343
iter  90 value 85.577619
iter 100 value 85.495015
final  value 85.495015 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.267568 
iter  10 value 94.488844
iter  20 value 94.476787
iter  30 value 94.314579
iter  40 value 94.139912
iter  50 value 91.977462
iter  50 value 91.977461
iter  50 value 91.977461
final  value 91.977461 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.589010 
iter  10 value 94.489107
iter  20 value 94.483930
iter  30 value 92.080954
iter  40 value 89.436594
iter  50 value 89.433271
iter  60 value 89.431393
iter  60 value 89.431393
iter  60 value 89.431393
final  value 89.431393 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.177589 
iter  10 value 94.414302
iter  20 value 94.409022
iter  30 value 94.350871
final  value 94.350856 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.787075 
iter  10 value 94.362765
iter  20 value 92.430744
iter  30 value 86.206132
iter  40 value 84.826958
iter  50 value 84.809240
iter  60 value 84.808331
final  value 84.808320 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.692612 
iter  10 value 94.492941
iter  20 value 94.465720
iter  30 value 92.088504
iter  40 value 90.085677
iter  50 value 88.999451
iter  60 value 87.405424
iter  70 value 87.398347
iter  80 value 87.397581
iter  90 value 82.249332
iter 100 value 81.880880
final  value 81.880880 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.762286 
iter  10 value 94.491552
iter  20 value 94.465022
final  value 94.354595 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.915255 
iter  10 value 92.554411
iter  20 value 91.946945
iter  30 value 90.710062
iter  40 value 83.085422
iter  50 value 82.920630
iter  60 value 82.890903
iter  70 value 82.880526
iter  80 value 82.818408
iter  90 value 82.160652
iter 100 value 81.850823
final  value 81.850823 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.277796 
iter  10 value 94.492430
iter  20 value 91.951457
iter  30 value 91.161802
iter  40 value 87.303542
iter  50 value 86.534301
iter  60 value 84.938492
iter  70 value 84.815788
iter  80 value 84.815214
iter  90 value 84.814334
iter 100 value 84.806260
final  value 84.806260 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.942927 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.507286 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.679933 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.105634 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.799086 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.779239 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.228313 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.005624 
iter  10 value 93.689254
iter  20 value 93.392479
iter  30 value 93.213592
iter  40 value 92.894302
final  value 92.894120 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.334933 
iter  10 value 89.604807
iter  20 value 88.158340
iter  30 value 87.979538
iter  40 value 87.330809
iter  50 value 87.179609
final  value 87.179115 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.784693 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.373808 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.539961 
iter  10 value 93.457014
final  value 93.456974 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.138354 
iter  10 value 93.728278
iter  20 value 93.725283
final  value 93.725275 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.014856 
iter  10 value 93.300231
final  value 93.300000 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.030426 
iter  10 value 93.884526
final  value 93.813953 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.415728 
iter  10 value 94.460874
iter  20 value 92.152879
iter  30 value 85.989979
iter  40 value 84.750629
iter  50 value 84.505909
iter  60 value 83.982254
iter  70 value 83.854393
iter  80 value 83.288130
iter  90 value 82.921958
final  value 82.911358 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.959156 
iter  10 value 94.703978
iter  20 value 94.397546
iter  30 value 81.977272
iter  40 value 81.474344
iter  50 value 81.181436
iter  60 value 80.981863
iter  70 value 80.958990
final  value 80.958963 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.848030 
iter  10 value 89.095104
iter  20 value 82.134523
iter  30 value 81.160864
iter  40 value 81.119912
iter  50 value 81.072887
iter  60 value 80.875818
iter  70 value 80.457313
iter  80 value 80.404507
final  value 80.404178 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.607697 
iter  10 value 94.478623
iter  20 value 81.486802
iter  30 value 81.112867
iter  40 value 80.920870
iter  50 value 80.405174
iter  60 value 80.404180
final  value 80.404178 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.484701 
iter  10 value 94.456818
iter  20 value 81.991683
iter  30 value 81.314622
iter  40 value 81.278271
iter  50 value 81.031648
iter  60 value 80.961207
iter  70 value 80.958963
iter  70 value 80.958963
iter  70 value 80.958963
final  value 80.958963 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.198966 
iter  10 value 94.773892
iter  20 value 93.091421
iter  30 value 91.372180
iter  40 value 87.334020
iter  50 value 80.254055
iter  60 value 79.318753
iter  70 value 78.438532
iter  80 value 77.934609
iter  90 value 77.190202
iter 100 value 77.015721
final  value 77.015721 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.827916 
iter  10 value 93.100822
iter  20 value 82.067101
iter  30 value 80.898248
iter  40 value 80.779961
iter  50 value 80.301680
iter  60 value 78.361603
iter  70 value 77.147875
iter  80 value 76.822270
iter  90 value 76.801356
iter 100 value 76.781296
final  value 76.781296 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 129.204562 
iter  10 value 94.750437
iter  20 value 94.388436
iter  30 value 93.583098
iter  40 value 86.723942
iter  50 value 86.409531
iter  60 value 86.145743
iter  70 value 82.406536
iter  80 value 80.480621
iter  90 value 79.798048
iter 100 value 78.724256
final  value 78.724256 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.536451 
iter  10 value 93.813982
iter  20 value 92.045845
iter  30 value 87.024731
iter  40 value 82.839552
iter  50 value 80.457170
iter  60 value 79.511950
iter  70 value 77.826604
iter  80 value 76.857238
iter  90 value 76.512898
iter 100 value 76.424708
final  value 76.424708 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.296991 
iter  10 value 93.213340
iter  20 value 87.570097
iter  30 value 79.154078
iter  40 value 78.562840
iter  50 value 77.828075
iter  60 value 77.248795
iter  70 value 77.151028
iter  80 value 77.044354
iter  90 value 76.965990
iter 100 value 76.847585
final  value 76.847585 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.565070 
iter  10 value 94.413376
iter  20 value 93.339378
iter  30 value 93.155425
iter  40 value 89.890575
iter  50 value 84.002261
iter  60 value 81.392389
iter  70 value 80.134593
iter  80 value 78.822773
iter  90 value 78.392617
iter 100 value 77.859968
final  value 77.859968 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.289896 
iter  10 value 94.491079
iter  20 value 85.451284
iter  30 value 82.706504
iter  40 value 80.721440
iter  50 value 80.525444
iter  60 value 80.011661
iter  70 value 78.550761
iter  80 value 77.563159
iter  90 value 77.079644
iter 100 value 76.457700
final  value 76.457700 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.901728 
iter  10 value 98.236163
iter  20 value 93.124298
iter  30 value 85.165081
iter  40 value 83.672193
iter  50 value 79.194059
iter  60 value 77.268504
iter  70 value 76.934894
iter  80 value 76.861349
iter  90 value 76.813675
iter 100 value 76.724786
final  value 76.724786 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.552778 
iter  10 value 91.977206
iter  20 value 86.333596
iter  30 value 84.915688
iter  40 value 81.251289
iter  50 value 80.775948
iter  60 value 80.403903
iter  70 value 80.321053
iter  80 value 79.666164
iter  90 value 78.334675
iter 100 value 78.242301
final  value 78.242301 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 157.808288 
iter  10 value 94.454392
iter  20 value 89.586705
iter  30 value 84.687247
iter  40 value 83.961248
iter  50 value 82.728309
iter  60 value 81.073043
iter  70 value 78.069714
iter  80 value 76.830919
iter  90 value 76.512971
iter 100 value 76.375690
final  value 76.375690 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.416926 
final  value 94.486018 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.079456 
final  value 94.485742 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.245270 
final  value 94.277260 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.963296 
final  value 94.485914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.845729 
iter  10 value 94.485898
iter  20 value 94.484252
iter  30 value 82.467928
iter  40 value 81.022181
iter  50 value 81.021904
iter  60 value 81.021011
iter  70 value 81.019214
iter  80 value 81.018945
iter  90 value 81.004409
iter 100 value 80.983242
final  value 80.983242 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.606671 
iter  10 value 94.279876
final  value 94.275763 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.959435 
iter  10 value 94.487251
iter  20 value 94.123512
iter  30 value 83.834600
final  value 83.824545 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.547407 
iter  10 value 94.488451
iter  20 value 94.483095
iter  30 value 93.726265
final  value 93.725661 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.822419 
iter  10 value 94.281829
iter  20 value 94.277658
iter  30 value 94.276688
iter  30 value 94.276687
iter  30 value 94.276687
final  value 94.276687 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.607200 
iter  10 value 94.489601
iter  20 value 91.619271
iter  30 value 86.733787
iter  40 value 86.699315
iter  50 value 86.698611
iter  60 value 86.698439
iter  70 value 86.698286
iter  80 value 85.911102
iter  90 value 85.530300
iter 100 value 85.122560
final  value 85.122560 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.513353 
iter  10 value 94.492537
iter  20 value 93.566854
iter  30 value 89.036508
iter  40 value 89.036456
final  value 89.036443 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.412219 
iter  10 value 94.492529
iter  20 value 94.454231
iter  30 value 79.956717
iter  40 value 78.993737
iter  50 value 78.970978
iter  60 value 78.928132
iter  70 value 78.414083
iter  80 value 77.194892
iter  90 value 75.554188
iter 100 value 74.709399
final  value 74.709399 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.588224 
iter  10 value 94.283980
iter  20 value 94.232469
iter  30 value 94.231255
iter  40 value 88.193895
iter  50 value 88.083164
iter  60 value 88.081035
iter  70 value 86.036470
iter  80 value 84.955583
iter  90 value 84.955349
final  value 84.955105 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.011527 
iter  10 value 93.309586
iter  20 value 93.303316
iter  30 value 93.300383
final  value 93.300271 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.998002 
iter  10 value 94.492376
iter  20 value 94.484292
iter  30 value 91.402258
iter  40 value 88.371270
iter  50 value 88.188806
iter  60 value 87.745602
iter  70 value 84.641428
iter  80 value 83.946123
iter  90 value 83.945895
iter 100 value 83.924897
final  value 83.924897 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.431798 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.142855 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.974338 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.591828 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.202536 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.423765 
iter  10 value 94.466845
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.662158 
final  value 94.312038 
converged
Fitting Repeat 3 

# weights:  305
initial  value 136.889854 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.771782 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.032589 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.583292 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.435848 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.489207 
iter  10 value 92.062521
final  value 92.036569 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.845004 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.951475 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.508338 
iter  10 value 93.999209
iter  20 value 84.340090
iter  30 value 83.293160
iter  40 value 82.810582
iter  50 value 82.411129
iter  60 value 82.397348
iter  70 value 82.392311
final  value 82.391984 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.023354 
iter  10 value 94.477885
iter  20 value 84.834563
iter  30 value 84.158650
iter  40 value 83.101613
final  value 83.098906 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.363230 
iter  10 value 94.486418
iter  20 value 94.293424
iter  30 value 90.478514
iter  40 value 87.255449
iter  50 value 86.513221
iter  60 value 85.990158
iter  70 value 85.968103
iter  80 value 83.508372
iter  90 value 82.538997
iter 100 value 82.363084
final  value 82.363084 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.762152 
iter  10 value 92.207986
iter  20 value 83.266306
iter  30 value 82.875602
iter  40 value 82.866276
iter  50 value 82.863188
final  value 82.863186 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.477787 
iter  10 value 94.188142
iter  20 value 87.697557
iter  30 value 84.131059
iter  40 value 83.183192
iter  50 value 82.657211
iter  60 value 82.400502
iter  70 value 81.650104
iter  80 value 81.047822
iter  90 value 80.779606
iter 100 value 80.228175
final  value 80.228175 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.460570 
iter  10 value 94.081591
iter  20 value 85.565955
iter  30 value 84.752489
iter  40 value 83.184385
iter  50 value 82.812751
iter  60 value 81.834985
iter  70 value 81.450208
iter  80 value 81.106972
iter  90 value 80.275956
iter 100 value 79.803786
final  value 79.803786 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.234080 
iter  10 value 94.121297
iter  20 value 86.669044
iter  30 value 84.223294
iter  40 value 81.497844
iter  50 value 81.136263
iter  60 value 80.036498
iter  70 value 79.154472
iter  80 value 78.908018
iter  90 value 78.358380
iter 100 value 78.219157
final  value 78.219157 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.474151 
iter  10 value 94.382764
iter  20 value 87.767433
iter  30 value 86.017645
iter  40 value 83.333722
iter  50 value 82.919427
iter  60 value 82.365100
iter  70 value 81.734031
iter  80 value 80.222779
iter  90 value 79.038801
iter 100 value 78.649913
final  value 78.649913 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.461752 
iter  10 value 93.498448
iter  20 value 87.251813
iter  30 value 86.966998
iter  40 value 85.164158
iter  50 value 82.845846
iter  60 value 82.368160
iter  70 value 81.856009
iter  80 value 81.159441
iter  90 value 80.454971
iter 100 value 79.755730
final  value 79.755730 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.590623 
iter  10 value 94.443794
iter  20 value 89.011922
iter  30 value 83.741964
iter  40 value 83.146225
iter  50 value 81.590585
iter  60 value 80.994259
iter  70 value 79.918120
iter  80 value 78.630289
iter  90 value 78.183456
iter 100 value 78.128570
final  value 78.128570 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.922318 
iter  10 value 94.849703
iter  20 value 91.666964
iter  30 value 82.680992
iter  40 value 82.385784
iter  50 value 82.139613
iter  60 value 80.769496
iter  70 value 79.499834
iter  80 value 78.946693
iter  90 value 78.898866
iter 100 value 78.800663
final  value 78.800663 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 168.327878 
iter  10 value 94.678555
iter  20 value 92.274794
iter  30 value 90.521926
iter  40 value 86.588404
iter  50 value 83.029353
iter  60 value 81.190660
iter  70 value 80.121967
iter  80 value 79.111826
iter  90 value 78.537256
iter 100 value 78.448035
final  value 78.448035 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.758228 
iter  10 value 94.860178
iter  20 value 94.665573
iter  30 value 93.734614
iter  40 value 87.493793
iter  50 value 83.373592
iter  60 value 81.058236
iter  70 value 79.604559
iter  80 value 78.941070
iter  90 value 78.807418
iter 100 value 78.626250
final  value 78.626250 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.681727 
iter  10 value 90.972780
iter  20 value 85.676542
iter  30 value 84.380635
iter  40 value 82.884812
iter  50 value 82.289375
iter  60 value 81.046656
iter  70 value 80.402713
iter  80 value 79.683968
iter  90 value 78.921902
iter 100 value 78.270413
final  value 78.270413 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.475002 
iter  10 value 94.483865
iter  20 value 92.618383
iter  30 value 85.112536
iter  40 value 84.163813
iter  50 value 83.193662
iter  60 value 82.968024
iter  70 value 82.831126
iter  80 value 82.046616
iter  90 value 80.923837
iter 100 value 79.044039
final  value 79.044039 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.164660 
final  value 94.486016 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.849953 
final  value 94.485687 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.129378 
iter  10 value 94.485860
iter  20 value 94.482207
iter  30 value 86.240474
iter  40 value 82.599648
iter  50 value 81.570724
iter  60 value 81.565466
final  value 81.565412 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.108593 
final  value 94.485957 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.912140 
final  value 94.468461 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.600626 
iter  10 value 94.428966
iter  20 value 88.176898
iter  30 value 87.786679
iter  40 value 87.293552
iter  50 value 86.502650
iter  60 value 86.499625
iter  70 value 86.080647
iter  80 value 85.550454
iter  90 value 85.545426
iter 100 value 85.543797
final  value 85.543797 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.369729 
iter  10 value 94.094009
iter  20 value 88.337790
iter  30 value 86.333688
iter  40 value 85.678514
iter  50 value 84.977744
final  value 84.976703 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.933949 
iter  10 value 94.269894
iter  20 value 94.263897
iter  30 value 83.504441
iter  40 value 82.846511
iter  50 value 81.906573
iter  60 value 81.864194
iter  70 value 81.864048
iter  80 value 80.913659
iter  90 value 80.478253
final  value 80.477431 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.894068 
iter  10 value 94.494748
iter  20 value 94.491042
iter  30 value 94.397911
iter  40 value 93.614860
iter  50 value 93.452837
iter  60 value 93.450694
iter  70 value 93.448575
iter  80 value 93.447938
iter  90 value 93.447639
iter 100 value 93.447102
final  value 93.447102 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.722088 
iter  10 value 94.488980
iter  20 value 94.296006
iter  30 value 93.943400
final  value 93.942435 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.751553 
iter  10 value 94.096368
iter  20 value 94.091375
iter  30 value 94.090692
iter  40 value 85.395303
iter  50 value 83.316490
iter  60 value 83.289496
iter  70 value 83.289011
iter  80 value 82.235218
iter  90 value 81.991903
final  value 81.991885 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.917976 
iter  10 value 94.395420
iter  20 value 94.086595
iter  30 value 94.079676
iter  40 value 86.783595
iter  50 value 83.332901
iter  60 value 83.272943
iter  70 value 83.249761
final  value 83.249578 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.330438 
iter  10 value 94.120784
iter  20 value 92.723578
iter  30 value 92.703545
iter  40 value 92.414356
iter  50 value 92.399766
iter  60 value 92.392440
iter  70 value 92.062860
final  value 92.060948 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.065462 
iter  10 value 94.474903
iter  20 value 94.468081
iter  30 value 84.917360
iter  40 value 83.382087
iter  50 value 83.373045
iter  60 value 83.372690
iter  70 value 83.372069
iter  80 value 82.263983
iter  90 value 82.234260
iter 100 value 82.200246
final  value 82.200246 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 134.683028 
iter  10 value 94.461156
iter  20 value 94.446080
iter  30 value 94.430337
iter  40 value 87.007225
iter  50 value 84.148228
iter  60 value 84.147799
iter  70 value 84.120576
iter  80 value 84.119634
iter  80 value 84.119633
final  value 84.119633 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.741183 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.668777 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.739259 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.657410 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.204606 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.871690 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.034858 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.499002 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.053290 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.969983 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.608474 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.345210 
iter  10 value 93.725752
iter  20 value 93.068147
final  value 93.067600 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.919843 
iter  10 value 93.943843
iter  10 value 93.943842
iter  10 value 93.943842
final  value 93.943842 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.992662 
final  value 94.042012 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.318534 
iter  10 value 92.195055
iter  20 value 87.076818
iter  30 value 86.734035
final  value 86.734033 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.891294 
iter  10 value 94.061106
iter  20 value 94.050377
iter  30 value 89.353324
iter  40 value 88.327616
iter  50 value 87.792970
iter  60 value 87.242962
iter  70 value 87.097558
iter  80 value 87.084253
final  value 87.084249 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.826749 
iter  10 value 94.053400
iter  20 value 88.616199
iter  30 value 88.362149
iter  40 value 87.720391
iter  50 value 86.773013
iter  60 value 86.416018
final  value 86.408593 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.487285 
iter  10 value 94.058186
iter  20 value 93.770498
iter  30 value 93.669676
iter  40 value 93.669039
iter  50 value 93.668805
iter  60 value 93.439543
iter  70 value 89.643487
iter  80 value 89.483216
iter  90 value 89.454481
iter 100 value 87.928913
final  value 87.928913 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.519177 
iter  10 value 94.050475
iter  20 value 93.210517
iter  30 value 92.697682
iter  40 value 92.507189
iter  50 value 88.512892
iter  60 value 88.323822
iter  70 value 87.912468
iter  80 value 87.159499
iter  90 value 85.730236
iter 100 value 85.334589
final  value 85.334589 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 109.240788 
iter  10 value 94.059985
iter  20 value 93.755254
iter  30 value 93.670762
iter  40 value 93.669364
iter  50 value 93.668756
iter  60 value 89.963905
iter  70 value 88.644648
iter  80 value 87.898385
iter  90 value 87.483674
iter 100 value 87.148271
final  value 87.148271 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.597380 
iter  10 value 94.064802
iter  20 value 94.045210
iter  30 value 88.900703
iter  40 value 88.371906
iter  50 value 87.625834
iter  60 value 87.084682
iter  70 value 86.228732
iter  80 value 85.640600
iter  90 value 85.289570
iter 100 value 85.257288
final  value 85.257288 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.682940 
iter  10 value 94.097303
iter  20 value 89.814837
iter  30 value 87.905974
iter  40 value 87.431860
iter  50 value 86.727116
iter  60 value 86.412600
iter  70 value 86.067014
iter  80 value 85.026729
iter  90 value 84.252792
iter 100 value 84.116315
final  value 84.116315 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.236629 
iter  10 value 93.739235
iter  20 value 92.815983
iter  30 value 92.641584
iter  40 value 92.358256
iter  50 value 88.762692
iter  60 value 87.564337
iter  70 value 86.472888
iter  80 value 86.049440
iter  90 value 85.881324
iter 100 value 85.600457
final  value 85.600457 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.865422 
iter  10 value 96.110722
iter  20 value 94.131482
iter  30 value 93.944158
iter  40 value 89.217874
iter  50 value 87.754096
iter  60 value 87.570182
iter  70 value 87.259003
iter  80 value 87.112755
iter  90 value 86.663828
iter 100 value 84.963919
final  value 84.963919 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.635696 
iter  10 value 93.613675
iter  20 value 88.737716
iter  30 value 88.076574
iter  40 value 87.638843
iter  50 value 86.951973
iter  60 value 86.648582
iter  70 value 86.282072
iter  80 value 85.409879
iter  90 value 85.275262
iter 100 value 84.924270
final  value 84.924270 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.735474 
iter  10 value 94.132070
iter  20 value 89.110295
iter  30 value 87.713766
iter  40 value 87.057803
iter  50 value 86.847504
iter  60 value 85.317335
iter  70 value 84.832265
iter  80 value 84.195112
iter  90 value 83.839594
iter 100 value 83.778766
final  value 83.778766 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.095612 
iter  10 value 94.158319
iter  20 value 90.603901
iter  30 value 88.738546
iter  40 value 87.695741
iter  50 value 85.689918
iter  60 value 85.481228
iter  70 value 85.178968
iter  80 value 84.445169
iter  90 value 83.999329
iter 100 value 83.835241
final  value 83.835241 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.026558 
iter  10 value 94.097492
iter  20 value 93.819085
iter  30 value 92.887889
iter  40 value 92.432230
iter  50 value 89.751302
iter  60 value 87.751961
iter  70 value 86.268785
iter  80 value 84.907752
iter  90 value 83.973848
iter 100 value 83.481255
final  value 83.481255 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.337896 
iter  10 value 94.187705
iter  20 value 92.627572
iter  30 value 90.518549
iter  40 value 87.706052
iter  50 value 87.520434
iter  60 value 87.213783
iter  70 value 86.377772
iter  80 value 84.767973
iter  90 value 84.403358
iter 100 value 84.242714
final  value 84.242714 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.237437 
iter  10 value 94.273529
iter  20 value 92.367715
iter  30 value 90.456369
iter  40 value 88.065843
iter  50 value 87.820197
iter  60 value 87.023290
iter  70 value 85.615652
iter  80 value 84.616057
iter  90 value 84.263769
iter 100 value 84.124625
final  value 84.124625 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.881622 
final  value 94.054542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.278634 
final  value 94.054293 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.146643 
iter  10 value 94.054347
iter  20 value 93.878527
iter  30 value 93.097014
iter  40 value 92.592701
iter  50 value 92.572090
iter  60 value 92.572037
iter  70 value 92.571644
iter  80 value 92.516214
iter  90 value 92.485187
final  value 92.485032 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.876098 
iter  10 value 93.839809
final  value 93.837602 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.125665 
final  value 94.054602 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.714724 
iter  10 value 94.059110
iter  20 value 92.362389
iter  30 value 92.050778
iter  40 value 88.422307
iter  50 value 87.991638
iter  60 value 87.958484
iter  70 value 87.433666
iter  80 value 86.602606
iter  90 value 86.583734
final  value 86.583584 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.492619 
iter  10 value 94.051343
iter  20 value 87.774735
iter  30 value 87.616192
iter  40 value 85.563778
iter  50 value 85.076997
iter  60 value 84.980174
iter  70 value 84.767615
iter  80 value 84.497717
iter  90 value 83.547870
iter 100 value 83.535850
final  value 83.535850 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.078146 
iter  10 value 94.057938
iter  20 value 94.052952
iter  30 value 88.592405
iter  40 value 88.206399
final  value 88.206395 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.738450 
iter  10 value 94.057585
iter  20 value 94.052872
iter  30 value 93.615662
iter  40 value 92.819904
iter  50 value 92.717605
iter  60 value 92.717528
final  value 92.717512 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.601078 
iter  10 value 94.058118
iter  20 value 93.811354
iter  30 value 93.097104
final  value 93.096916 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.366567 
iter  10 value 92.841855
iter  20 value 87.664761
iter  30 value 87.266096
iter  40 value 86.579949
iter  50 value 86.579048
iter  60 value 86.576891
iter  70 value 85.744532
iter  80 value 85.639911
iter  90 value 85.638494
iter 100 value 85.635421
final  value 85.635421 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.687897 
iter  10 value 94.060584
iter  20 value 93.886112
iter  30 value 90.767191
iter  40 value 89.352033
iter  50 value 89.271042
iter  60 value 89.265244
final  value 89.264971 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.240452 
iter  10 value 94.060600
iter  20 value 94.028233
final  value 93.604689 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.499327 
iter  10 value 93.844027
iter  20 value 93.566683
iter  30 value 88.078369
iter  40 value 85.778290
iter  50 value 85.681485
iter  60 value 85.673856
iter  70 value 85.673429
iter  80 value 85.641841
iter  90 value 85.592221
iter 100 value 85.570427
final  value 85.570427 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.418266 
iter  10 value 94.057556
iter  20 value 94.053021
iter  30 value 89.581490
iter  40 value 88.040630
iter  50 value 87.241645
iter  60 value 87.228602
final  value 87.228569 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.574739 
final  value 94.035089 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.897763 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.984530 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.020782 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.103767 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.786094 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.421723 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.933181 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 123.297498 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.174050 
iter  10 value 85.878966
final  value 85.874988 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.737104 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.452598 
iter  10 value 92.926566
iter  20 value 84.971831
iter  30 value 84.109254
final  value 84.107621 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.149871 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.610218 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.906376 
final  value 93.785768 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.225326 
iter  10 value 94.139099
iter  20 value 94.051851
iter  30 value 93.976944
iter  40 value 93.804488
iter  50 value 92.415787
iter  60 value 85.464389
iter  70 value 84.678941
iter  80 value 83.814783
iter  90 value 83.411359
iter 100 value 83.353922
final  value 83.353922 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.729302 
iter  10 value 94.053175
iter  20 value 86.376326
iter  30 value 85.388983
iter  40 value 84.610313
iter  50 value 84.535022
iter  60 value 84.033241
iter  70 value 83.484094
iter  80 value 83.385783
final  value 83.382950 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.257468 
iter  10 value 94.057087
iter  20 value 93.786816
iter  30 value 89.031938
iter  40 value 85.814277
iter  50 value 85.735356
iter  60 value 85.355110
iter  70 value 85.079482
iter  80 value 85.063063
final  value 85.061385 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.285340 
iter  10 value 94.130784
iter  20 value 92.798635
iter  30 value 85.665385
iter  40 value 84.462398
iter  50 value 83.894714
iter  60 value 83.523069
iter  70 value 83.383016
iter  80 value 83.346990
iter  90 value 83.334015
final  value 83.332905 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.454414 
iter  10 value 89.477935
iter  20 value 84.961280
iter  30 value 84.620360
iter  40 value 84.554583
iter  50 value 83.813512
iter  60 value 83.398933
iter  70 value 83.382950
final  value 83.382944 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.016551 
iter  10 value 93.100708
iter  20 value 92.010791
iter  30 value 91.673474
iter  40 value 90.670701
iter  50 value 90.615612
iter  60 value 90.555181
iter  70 value 90.196859
iter  80 value 89.399712
iter  90 value 86.581222
iter 100 value 85.366714
final  value 85.366714 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.619804 
iter  10 value 93.504110
iter  20 value 87.143455
iter  30 value 85.447304
iter  40 value 85.061398
iter  50 value 84.690073
iter  60 value 82.768995
iter  70 value 81.448655
iter  80 value 80.671574
iter  90 value 80.395629
iter 100 value 80.297184
final  value 80.297184 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.776422 
iter  10 value 93.902388
iter  20 value 87.746439
iter  30 value 84.899082
iter  40 value 83.346976
iter  50 value 82.658706
iter  60 value 81.695162
iter  70 value 80.723257
iter  80 value 80.550565
iter  90 value 80.493054
iter 100 value 80.457779
final  value 80.457779 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.788570 
iter  10 value 94.067989
iter  20 value 91.928956
iter  30 value 89.693049
iter  40 value 87.896576
iter  50 value 85.262015
iter  60 value 84.262486
iter  70 value 84.019290
iter  80 value 83.439455
iter  90 value 82.060410
iter 100 value 81.746135
final  value 81.746135 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.277696 
iter  10 value 93.941876
iter  20 value 86.359599
iter  30 value 84.923051
iter  40 value 83.769715
iter  50 value 83.425775
iter  60 value 83.285115
iter  70 value 82.992957
iter  80 value 81.734294
iter  90 value 81.238536
iter 100 value 80.883525
final  value 80.883525 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.624416 
iter  10 value 93.797544
iter  20 value 87.175560
iter  30 value 83.139118
iter  40 value 81.575318
iter  50 value 80.804049
iter  60 value 80.642933
iter  70 value 80.629317
iter  80 value 80.591317
iter  90 value 80.567951
iter 100 value 80.545817
final  value 80.545817 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.573605 
iter  10 value 94.564725
iter  20 value 89.168027
iter  30 value 85.776865
iter  40 value 85.191111
iter  50 value 82.580194
iter  60 value 81.895638
iter  70 value 81.550544
iter  80 value 81.276537
iter  90 value 81.171158
iter 100 value 81.113532
final  value 81.113532 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.367252 
iter  10 value 94.459422
iter  20 value 93.897486
iter  30 value 92.603171
iter  40 value 92.021138
iter  50 value 87.914248
iter  60 value 85.271554
iter  70 value 84.460744
iter  80 value 83.719261
iter  90 value 83.547942
iter 100 value 83.422645
final  value 83.422645 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.989757 
iter  10 value 94.411510
iter  20 value 93.715510
iter  30 value 85.875016
iter  40 value 84.653068
iter  50 value 82.352264
iter  60 value 82.074732
iter  70 value 81.821399
iter  80 value 80.801071
iter  90 value 80.460920
iter 100 value 80.297319
final  value 80.297319 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.769354 
iter  10 value 94.074449
iter  20 value 94.051209
iter  30 value 90.786774
iter  40 value 89.754226
iter  50 value 88.465913
iter  60 value 83.413720
iter  70 value 82.673784
iter  80 value 81.441699
iter  90 value 81.058343
iter 100 value 80.561464
final  value 80.561464 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.284148 
iter  10 value 93.891882
iter  20 value 89.493765
iter  30 value 85.219951
final  value 85.219929 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.971441 
final  value 94.054640 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.026258 
iter  10 value 94.054565
iter  20 value 93.909015
iter  30 value 86.719395
iter  40 value 84.246537
iter  50 value 84.211934
final  value 84.211899 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.642669 
final  value 94.054546 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.113730 
iter  10 value 94.010457
iter  20 value 94.009293
iter  30 value 93.367004
iter  40 value 86.641227
final  value 86.640240 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.213102 
iter  10 value 94.057443
iter  20 value 93.979250
iter  30 value 89.618062
iter  40 value 89.551049
iter  50 value 88.376202
iter  60 value 88.253605
final  value 88.253578 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.861903 
iter  10 value 94.057695
iter  20 value 93.977019
iter  30 value 86.769465
iter  40 value 86.589931
iter  50 value 86.546334
iter  60 value 86.520369
iter  70 value 86.516187
iter  80 value 86.242074
iter  90 value 85.694158
iter 100 value 84.773589
final  value 84.773589 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.722077 
iter  10 value 94.013829
iter  20 value 94.009105
final  value 94.008756 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.174921 
iter  10 value 94.058058
iter  20 value 94.038679
iter  30 value 93.811313
iter  40 value 93.799931
final  value 93.785925 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.707821 
iter  10 value 94.091196
iter  20 value 94.084035
iter  30 value 94.064633
iter  40 value 88.442637
iter  50 value 88.047182
iter  50 value 88.047182
final  value 88.047182 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.879190 
iter  10 value 94.017356
iter  20 value 94.011471
iter  30 value 87.321559
iter  40 value 84.352255
iter  50 value 83.937861
iter  60 value 83.936740
iter  70 value 83.936562
iter  80 value 83.936520
iter  90 value 83.935852
final  value 83.935733 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.670274 
iter  10 value 94.062665
iter  20 value 91.854189
iter  30 value 89.374788
iter  40 value 89.261417
iter  50 value 89.261055
final  value 89.261048 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.878437 
iter  10 value 94.016625
iter  20 value 94.013437
iter  30 value 94.008681
iter  40 value 85.941743
iter  50 value 84.058757
iter  60 value 84.039041
iter  70 value 84.037359
iter  80 value 84.036907
final  value 84.036865 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.598334 
iter  10 value 94.060867
iter  20 value 93.986348
iter  30 value 90.748728
iter  40 value 88.479084
iter  50 value 86.923257
iter  60 value 83.324549
iter  70 value 81.855956
iter  80 value 81.658808
iter  90 value 81.505136
iter 100 value 81.504309
final  value 81.504309 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.173243 
iter  10 value 94.055895
iter  20 value 89.939523
iter  30 value 83.919359
iter  40 value 83.723571
iter  50 value 83.208025
iter  60 value 83.207925
iter  70 value 83.207166
iter  80 value 82.534715
iter  90 value 81.550096
iter 100 value 81.311904
final  value 81.311904 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 119.616909 
iter  10 value 117.894232
iter  20 value 117.890316
final  value 117.890308 
converged
Fitting Repeat 2 

# weights:  305
initial  value 139.221146 
iter  10 value 117.894979
iter  20 value 117.806463
iter  30 value 114.509165
iter  40 value 109.727438
iter  50 value 108.960844
iter  60 value 108.085133
final  value 108.083597 
converged
Fitting Repeat 3 

# weights:  305
initial  value 135.326267 
iter  10 value 117.763932
iter  20 value 114.271614
iter  30 value 108.574762
iter  40 value 108.101616
iter  50 value 108.087142
iter  60 value 106.873011
iter  70 value 106.801847
iter  80 value 106.790412
final  value 106.790268 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.661847 
iter  10 value 117.763645
iter  20 value 117.731313
iter  30 value 113.620720
iter  40 value 111.535588
final  value 111.532149 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.397707 
iter  10 value 117.976397
iter  20 value 117.963870
iter  30 value 116.489594
iter  40 value 111.988579
iter  50 value 109.060474
iter  60 value 109.029219
iter  70 value 109.008472
iter  70 value 109.008471
final  value 109.008471 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Sep  9 05:03:42 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 75.121   2.301 141.554