##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-20 r89666)
* 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: 2026-03-23 00:10:04 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       17.377  0.170  17.729
corr_plot     17.182  0.113  17.575
FSmethod      16.821  0.135  17.340
pred_ensembel  6.358  0.180   5.798
enrichfindP    0.207  0.046  14.814
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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

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

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

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

# weights:  103
initial  value 97.174876 
final  value 94.052448 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.964187 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 120.103743 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.271662 
iter  10 value 93.328403
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.692059 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.407744 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.088050 
iter  10 value 94.052026
final  value 94.051984 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.211268 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.284216 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.567702 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.255760 
final  value 93.328073 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.465068 
iter  10 value 94.044081
iter  20 value 89.126250
iter  30 value 88.873546
iter  40 value 88.869064
final  value 88.869060 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.787902 
iter  10 value 93.565780
iter  20 value 93.410989
iter  30 value 90.862264
iter  40 value 85.201081
iter  50 value 81.264162
iter  60 value 80.221576
iter  70 value 80.220790
iter  80 value 80.202863
iter  90 value 80.076243
iter 100 value 80.065037
final  value 80.065037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.321057 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.972025 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.445717 
iter  10 value 94.102617
iter  20 value 94.056741
iter  30 value 93.597174
iter  40 value 93.540827
iter  50 value 93.533360
iter  60 value 87.421751
iter  70 value 85.128094
iter  80 value 84.692250
iter  90 value 83.853051
iter 100 value 81.784020
final  value 81.784020 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.886700 
iter  10 value 93.887345
iter  20 value 86.354091
iter  30 value 83.425810
iter  40 value 83.167658
iter  50 value 83.010572
iter  60 value 82.847752
iter  70 value 82.783455
iter  80 value 82.662472
iter  90 value 82.607379
final  value 82.606594 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.065351 
iter  10 value 94.056714
iter  20 value 89.066813
iter  30 value 85.582393
iter  40 value 84.655649
iter  50 value 82.840404
iter  60 value 82.611663
iter  70 value 81.154541
iter  80 value 80.757906
iter  90 value 80.737294
iter 100 value 80.723392
final  value 80.723392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.304004 
iter  10 value 93.722563
iter  20 value 93.537970
iter  30 value 92.404577
iter  40 value 86.018917
iter  50 value 85.281519
iter  60 value 82.104909
iter  70 value 81.337552
iter  80 value 81.294136
iter  90 value 81.285890
final  value 81.285888 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.826227 
iter  10 value 94.054959
iter  20 value 93.986211
iter  30 value 93.187171
iter  40 value 91.561160
iter  50 value 87.071600
iter  60 value 85.039103
iter  70 value 84.790174
iter  80 value 83.644688
iter  90 value 83.337422
final  value 83.336160 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.365144 
iter  10 value 95.985328
iter  20 value 95.056008
iter  30 value 86.477243
iter  40 value 85.666570
iter  50 value 83.772340
iter  60 value 82.007277
iter  70 value 80.508311
iter  80 value 80.423985
iter  90 value 80.306225
iter 100 value 80.281415
final  value 80.281415 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.157183 
iter  10 value 94.074695
iter  20 value 93.925456
iter  30 value 86.223392
iter  40 value 83.306466
iter  50 value 82.895432
iter  60 value 82.831342
iter  70 value 82.664523
iter  80 value 81.997169
iter  90 value 81.021779
iter 100 value 80.794793
final  value 80.794793 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.199578 
iter  10 value 94.246802
iter  20 value 92.792146
iter  30 value 85.157593
iter  40 value 84.858887
iter  50 value 83.592081
iter  60 value 82.252956
iter  70 value 81.507060
iter  80 value 80.984551
iter  90 value 80.454857
iter 100 value 79.823056
final  value 79.823056 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 130.006219 
iter  10 value 94.063099
iter  20 value 88.033595
iter  30 value 85.728489
iter  40 value 84.408426
iter  50 value 82.755732
iter  60 value 81.348201
iter  70 value 81.285275
iter  80 value 81.233825
iter  90 value 81.107585
iter 100 value 81.012606
final  value 81.012606 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.518058 
iter  10 value 93.738354
iter  20 value 89.862962
iter  30 value 87.593213
iter  40 value 83.563425
iter  50 value 82.237251
iter  60 value 80.913784
iter  70 value 80.328840
iter  80 value 79.705048
iter  90 value 79.688416
iter 100 value 79.578261
final  value 79.578261 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.360933 
iter  10 value 94.660347
iter  20 value 93.910195
iter  30 value 93.177105
iter  40 value 92.231281
iter  50 value 92.037783
iter  60 value 86.261922
iter  70 value 83.902458
iter  80 value 83.024942
iter  90 value 82.316351
iter 100 value 81.383789
final  value 81.383789 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.807133 
iter  10 value 94.157978
iter  20 value 93.593826
iter  30 value 92.130348
iter  40 value 85.344913
iter  50 value 83.337956
iter  60 value 83.039716
iter  70 value 82.792861
iter  80 value 82.499079
iter  90 value 81.660057
iter 100 value 81.296497
final  value 81.296497 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.492780 
iter  10 value 94.240928
iter  20 value 89.990872
iter  30 value 85.050783
iter  40 value 82.886211
iter  50 value 80.888684
iter  60 value 80.616221
iter  70 value 80.385996
iter  80 value 79.891564
iter  90 value 79.516846
iter 100 value 79.352765
final  value 79.352765 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.008008 
iter  10 value 95.767465
iter  20 value 92.873534
iter  30 value 92.486051
iter  40 value 85.181147
iter  50 value 83.222187
iter  60 value 80.449648
iter  70 value 79.457379
iter  80 value 79.249600
iter  90 value 79.204583
iter 100 value 79.077386
final  value 79.077386 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.248759 
iter  10 value 94.031797
iter  20 value 91.800441
iter  30 value 86.995871
iter  40 value 83.860006
iter  50 value 81.115786
iter  60 value 80.188707
iter  70 value 79.857531
iter  80 value 79.712877
iter  90 value 79.600853
iter 100 value 79.254127
final  value 79.254127 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.976725 
final  value 94.054452 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.054516 
final  value 94.054391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.280463 
final  value 94.054362 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.265998 
iter  10 value 94.054525
iter  20 value 94.052930
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.404512 
final  value 94.054552 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.676633 
iter  10 value 94.057667
iter  20 value 94.052609
iter  30 value 84.507783
iter  40 value 83.848404
iter  50 value 83.808566
iter  60 value 82.866071
iter  70 value 80.288877
iter  80 value 79.439825
iter  90 value 79.258635
iter 100 value 79.151396
final  value 79.151396 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.957882 
iter  10 value 94.057546
iter  20 value 91.809777
iter  30 value 87.837383
iter  40 value 87.026354
iter  50 value 87.024827
iter  60 value 87.021833
iter  70 value 83.804414
iter  80 value 82.548694
iter  90 value 82.476644
iter 100 value 82.476012
final  value 82.476012 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.675750 
iter  10 value 94.052239
iter  20 value 93.154724
final  value 93.154621 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.318082 
iter  10 value 94.017276
iter  20 value 92.902297
iter  30 value 85.570998
iter  40 value 85.515560
iter  50 value 83.449956
iter  60 value 82.752744
iter  70 value 82.488717
iter  80 value 82.274220
iter  90 value 82.206160
iter 100 value 81.885670
final  value 81.885670 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.483372 
iter  10 value 83.589407
iter  20 value 83.346047
iter  30 value 83.345460
iter  40 value 83.341332
iter  50 value 83.340958
iter  60 value 82.070578
iter  70 value 81.974577
final  value 81.974570 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.356530 
iter  10 value 92.502243
iter  20 value 91.425850
iter  30 value 90.825739
iter  40 value 90.810396
final  value 90.810278 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.371353 
iter  10 value 93.336905
iter  20 value 93.310624
iter  30 value 86.012416
iter  40 value 83.703469
iter  50 value 83.655332
final  value 83.654686 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.116678 
iter  10 value 89.581453
iter  20 value 83.361522
iter  30 value 81.268492
iter  40 value 81.262620
iter  50 value 81.259254
iter  60 value 81.257312
iter  70 value 81.227336
iter  80 value 80.629689
iter  90 value 79.649484
iter 100 value 78.980022
final  value 78.980022 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.812208 
iter  10 value 94.156245
iter  20 value 85.785986
iter  30 value 84.484037
iter  40 value 84.481965
iter  50 value 84.383528
iter  60 value 84.332609
iter  70 value 84.278880
iter  80 value 84.276043
final  value 84.274992 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.789219 
iter  10 value 93.336672
iter  20 value 93.329365
iter  30 value 88.096963
iter  40 value 85.334519
iter  50 value 84.709546
iter  60 value 81.648313
iter  70 value 78.250210
iter  80 value 77.975094
iter  90 value 77.973102
iter 100 value 77.908204
final  value 77.908204 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.097531 
final  value 94.428839 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.534267 
final  value 94.385584 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.077654 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.709759 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.454090 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.485465 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.221817 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.184362 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.585576 
iter  10 value 94.484229
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.476073 
iter  10 value 94.490959
final  value 94.385584 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.381999 
iter  10 value 91.325017
iter  20 value 85.481809
iter  30 value 85.479474
final  value 85.479399 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.551288 
iter  10 value 92.559385
iter  20 value 91.863914
iter  30 value 91.824782
final  value 91.824715 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.994317 
iter  10 value 94.428840
final  value 94.428839 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.846021 
iter  10 value 93.094490
final  value 92.896540 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.314232 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.316761 
iter  10 value 94.507977
iter  20 value 94.479918
iter  30 value 93.440759
iter  40 value 88.070207
iter  50 value 86.124338
iter  60 value 85.896055
iter  70 value 85.709363
iter  80 value 85.078315
iter  90 value 84.870049
iter 100 value 84.820059
final  value 84.820059 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.899713 
iter  10 value 94.602948
iter  20 value 94.493277
iter  30 value 94.412352
iter  40 value 88.903998
iter  50 value 84.872989
iter  60 value 84.520467
iter  70 value 84.267948
iter  80 value 84.081652
iter  90 value 83.850663
iter 100 value 83.660993
final  value 83.660993 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.421931 
iter  10 value 94.156326
iter  20 value 86.401198
iter  30 value 85.808825
iter  40 value 85.546847
iter  50 value 85.485138
iter  60 value 84.611017
iter  70 value 84.444175
iter  80 value 84.371422
iter  90 value 84.369125
final  value 84.368148 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.205326 
iter  10 value 94.486441
iter  20 value 87.959318
iter  30 value 87.441838
iter  40 value 86.348999
iter  50 value 85.934515
iter  60 value 85.707314
iter  70 value 85.612345
iter  80 value 85.564794
final  value 85.561832 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.022937 
iter  10 value 94.491618
iter  20 value 93.781417
iter  30 value 90.068062
iter  40 value 89.547582
iter  50 value 86.402339
iter  60 value 85.629327
iter  70 value 85.362844
iter  80 value 85.050446
iter  90 value 84.860568
final  value 84.730043 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.750640 
iter  10 value 94.483731
iter  20 value 88.583922
iter  30 value 84.455664
iter  40 value 83.760805
iter  50 value 83.681992
iter  60 value 83.452651
iter  70 value 82.805262
iter  80 value 82.712497
iter  90 value 82.563222
iter 100 value 82.490026
final  value 82.490026 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.371056 
iter  10 value 94.073784
iter  20 value 92.143907
iter  30 value 86.341856
iter  40 value 85.056632
iter  50 value 84.156777
iter  60 value 83.669939
iter  70 value 82.931082
iter  80 value 82.744615
iter  90 value 82.491734
iter 100 value 82.328155
final  value 82.328155 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.690169 
iter  10 value 94.490525
iter  20 value 93.542978
iter  30 value 86.939548
iter  40 value 85.747570
iter  50 value 85.039787
iter  60 value 84.851801
iter  70 value 84.707866
iter  80 value 84.583773
iter  90 value 84.408563
iter 100 value 83.126841
final  value 83.126841 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.096203 
iter  10 value 94.515566
iter  20 value 89.285750
iter  30 value 84.973623
iter  40 value 83.344650
iter  50 value 81.631579
iter  60 value 81.285031
iter  70 value 81.244716
iter  80 value 81.210289
iter  90 value 81.174022
iter 100 value 81.168927
final  value 81.168927 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.522232 
iter  10 value 94.327658
iter  20 value 86.106886
iter  30 value 85.871001
iter  40 value 85.722682
iter  50 value 85.412844
iter  60 value 85.159362
iter  70 value 84.409237
iter  80 value 84.304829
iter  90 value 84.017474
iter 100 value 83.605055
final  value 83.605055 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.892116 
iter  10 value 94.489774
iter  20 value 89.332529
iter  30 value 87.319282
iter  40 value 85.994276
iter  50 value 84.755122
iter  60 value 83.592917
iter  70 value 82.526172
iter  80 value 82.390349
iter  90 value 81.874427
iter 100 value 81.622720
final  value 81.622720 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.162718 
iter  10 value 94.923199
iter  20 value 87.922466
iter  30 value 86.583292
iter  40 value 84.940766
iter  50 value 83.840016
iter  60 value 82.773521
iter  70 value 82.248765
iter  80 value 81.885310
iter  90 value 81.662564
iter 100 value 81.395805
final  value 81.395805 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.829128 
iter  10 value 94.446276
iter  20 value 91.509627
iter  30 value 84.797791
iter  40 value 83.758985
iter  50 value 83.310288
iter  60 value 83.242948
iter  70 value 82.456311
iter  80 value 82.289020
iter  90 value 81.761482
iter 100 value 81.249528
final  value 81.249528 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.089484 
iter  10 value 93.196011
iter  20 value 87.894472
iter  30 value 85.935104
iter  40 value 84.255095
iter  50 value 83.584865
iter  60 value 83.176949
iter  70 value 82.993422
iter  80 value 82.908676
iter  90 value 82.563686
iter 100 value 82.341042
final  value 82.341042 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.965164 
iter  10 value 97.676683
iter  20 value 93.038056
iter  30 value 91.669657
iter  40 value 87.768263
iter  50 value 86.006917
iter  60 value 83.560961
iter  70 value 82.093573
iter  80 value 81.353000
iter  90 value 81.197669
iter 100 value 81.106301
final  value 81.106301 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.432449 
final  value 94.485908 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.532645 
final  value 94.485555 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.923967 
final  value 94.485965 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.815098 
iter  10 value 94.485797
iter  20 value 94.484296
iter  30 value 94.110406
iter  40 value 84.235351
iter  50 value 84.208149
iter  60 value 83.984168
iter  70 value 83.983942
iter  80 value 83.681385
final  value 83.661247 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.237441 
final  value 94.486051 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.642210 
iter  10 value 94.488532
iter  20 value 94.463346
iter  30 value 89.541874
iter  40 value 87.590558
iter  50 value 87.553810
iter  60 value 87.543621
iter  70 value 87.539899
final  value 87.539726 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.546725 
iter  10 value 94.492805
iter  20 value 94.330611
iter  30 value 88.799858
iter  40 value 87.557348
iter  50 value 86.040161
iter  60 value 86.005567
iter  70 value 85.990475
iter  80 value 85.621481
iter  90 value 85.620952
iter 100 value 85.612391
final  value 85.612391 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.578375 
iter  10 value 94.472180
iter  20 value 94.377117
iter  30 value 94.338926
iter  40 value 86.992280
iter  50 value 85.170590
iter  60 value 85.170539
iter  60 value 85.170538
iter  60 value 85.170538
final  value 85.170538 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.514909 
iter  10 value 94.488876
iter  20 value 94.484064
iter  30 value 87.947310
iter  40 value 87.786617
iter  50 value 86.149148
iter  60 value 85.311594
final  value 85.266806 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.739818 
iter  10 value 94.404862
iter  20 value 94.400696
final  value 94.400600 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.766976 
iter  10 value 94.475764
iter  20 value 94.467480
iter  30 value 92.715129
iter  40 value 90.935343
iter  50 value 90.813079
iter  60 value 90.275972
iter  70 value 90.219764
iter  80 value 90.196779
iter  90 value 90.196093
iter 100 value 90.195977
final  value 90.195977 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.819057 
iter  10 value 94.486592
iter  20 value 94.469270
iter  30 value 93.807905
iter  40 value 85.565879
iter  50 value 85.500175
iter  60 value 85.290214
iter  70 value 85.278959
iter  80 value 84.725222
iter  90 value 83.754086
iter 100 value 83.049707
final  value 83.049707 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.496111 
iter  10 value 94.492482
iter  20 value 94.467180
iter  30 value 94.460872
iter  40 value 94.184455
iter  50 value 85.512311
final  value 85.512306 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.363642 
iter  10 value 94.475320
iter  20 value 94.467828
iter  30 value 94.223249
iter  40 value 90.439903
iter  50 value 85.192884
iter  60 value 83.904463
iter  70 value 83.872573
iter  80 value 83.872417
final  value 83.872088 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.738795 
iter  10 value 94.490868
iter  20 value 94.450379
iter  30 value 87.566570
iter  40 value 85.188645
iter  50 value 85.181345
iter  60 value 84.981734
iter  70 value 84.942929
iter  80 value 84.912965
iter  90 value 84.909459
iter 100 value 84.804475
final  value 84.804475 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.649119 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.556634 
final  value 92.892738 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.323998 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.330453 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.682126 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.020087 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.473167 
final  value 94.052909 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.641976 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.002324 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.516904 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.058850 
iter  10 value 83.336966
iter  20 value 81.236861
iter  30 value 80.840761
iter  40 value 80.677443
final  value 80.677352 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.184230 
final  value 93.491108 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.271564 
final  value 92.892736 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.378330 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.057181 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.709104 
iter  10 value 93.984635
iter  20 value 90.126806
iter  30 value 83.499143
iter  40 value 82.841412
iter  50 value 82.719856
iter  60 value 82.665596
iter  70 value 82.614844
final  value 82.614271 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.884912 
iter  10 value 93.916552
iter  20 value 83.339482
iter  30 value 82.980728
iter  40 value 82.782428
iter  50 value 82.532133
iter  60 value 82.505819
iter  70 value 82.493440
iter  80 value 82.276215
iter  90 value 82.186402
final  value 82.186284 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.661467 
iter  10 value 94.044100
iter  20 value 84.459613
iter  30 value 83.146764
iter  40 value 82.719606
iter  50 value 82.647780
iter  60 value 82.614315
final  value 82.614271 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.432905 
iter  10 value 94.065625
iter  20 value 93.960677
iter  30 value 93.843027
iter  40 value 93.825064
iter  50 value 85.813582
iter  60 value 84.440874
iter  70 value 82.404661
iter  80 value 81.032932
iter  90 value 80.666964
final  value 80.655893 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.316669 
iter  10 value 93.937885
iter  20 value 93.230177
iter  30 value 91.599246
iter  40 value 84.672459
iter  50 value 84.077507
iter  60 value 82.900642
iter  70 value 82.833328
iter  80 value 82.799297
final  value 82.798916 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.059793 
iter  10 value 94.067219
iter  20 value 89.724907
iter  30 value 86.451042
iter  40 value 84.101019
iter  50 value 82.105773
iter  60 value 80.866390
iter  70 value 80.550990
iter  80 value 80.252717
iter  90 value 80.224118
iter 100 value 80.212198
final  value 80.212198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.860934 
iter  10 value 96.938801
iter  20 value 94.038719
iter  30 value 85.888515
iter  40 value 85.023402
iter  50 value 83.454193
iter  60 value 83.007408
iter  70 value 80.209437
iter  80 value 80.080230
iter  90 value 80.034919
iter 100 value 79.769663
final  value 79.769663 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.912324 
iter  10 value 94.243575
iter  20 value 85.727548
iter  30 value 83.359669
iter  40 value 82.791418
iter  50 value 82.621409
iter  60 value 82.532049
iter  70 value 82.233362
iter  80 value 80.904096
iter  90 value 79.842187
iter 100 value 79.646931
final  value 79.646931 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.084058 
iter  10 value 94.054909
iter  20 value 93.755399
iter  30 value 90.725450
iter  40 value 89.473421
iter  50 value 85.672736
iter  60 value 81.691779
iter  70 value 80.484940
iter  80 value 79.832221
iter  90 value 79.500756
iter 100 value 79.249958
final  value 79.249958 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.749620 
iter  10 value 93.941700
iter  20 value 87.453491
iter  30 value 83.122064
iter  40 value 81.995754
iter  50 value 81.229258
iter  60 value 80.781979
iter  70 value 80.649264
iter  80 value 80.467133
iter  90 value 80.427486
iter 100 value 80.166228
final  value 80.166228 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.326284 
iter  10 value 94.138742
iter  20 value 94.057696
iter  30 value 90.353861
iter  40 value 86.307439
iter  50 value 83.138375
iter  60 value 82.086881
iter  70 value 79.736617
iter  80 value 79.611430
iter  90 value 79.556242
iter 100 value 79.468647
final  value 79.468647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.898521 
iter  10 value 94.792082
iter  20 value 93.443947
iter  30 value 84.481023
iter  40 value 84.359140
iter  50 value 83.378972
iter  60 value 82.116739
iter  70 value 80.453101
iter  80 value 79.959306
iter  90 value 79.060069
iter 100 value 78.845708
final  value 78.845708 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.848281 
iter  10 value 94.380926
iter  20 value 93.022077
iter  30 value 85.921836
iter  40 value 85.623560
iter  50 value 84.401357
iter  60 value 81.161767
iter  70 value 80.262697
iter  80 value 79.992643
iter  90 value 79.775120
iter 100 value 79.396635
final  value 79.396635 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 134.783706 
iter  10 value 93.702188
iter  20 value 87.106480
iter  30 value 83.791814
iter  40 value 82.982589
iter  50 value 82.310907
iter  60 value 81.987457
iter  70 value 81.639992
iter  80 value 81.078154
iter  90 value 80.038258
iter 100 value 79.610637
final  value 79.610637 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.317655 
iter  10 value 93.525982
iter  20 value 91.578234
iter  30 value 83.894409
iter  40 value 81.219423
iter  50 value 80.523073
iter  60 value 80.205233
iter  70 value 79.831947
iter  80 value 79.534834
iter  90 value 79.435736
iter 100 value 79.360015
final  value 79.360015 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.432200 
iter  10 value 94.054725
final  value 94.052930 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.887339 
final  value 94.054673 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.441146 
final  value 94.054600 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.053015 
final  value 94.054467 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.685638 
final  value 94.054735 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.636771 
iter  10 value 93.875198
iter  20 value 92.492679
iter  30 value 90.946999
iter  40 value 90.945903
iter  50 value 84.701895
iter  60 value 84.657556
final  value 84.656539 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.777530 
iter  10 value 94.063172
iter  20 value 93.522759
iter  30 value 85.035839
iter  40 value 81.758601
iter  50 value 81.719204
iter  60 value 81.717619
final  value 81.714839 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.811146 
iter  10 value 85.503887
iter  20 value 81.712243
iter  30 value 81.541264
iter  40 value 81.354489
iter  50 value 81.225349
iter  60 value 81.183001
iter  70 value 80.916529
iter  80 value 80.909938
iter  90 value 80.909312
iter 100 value 80.909195
final  value 80.909195 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.455869 
iter  10 value 94.058641
iter  20 value 94.047681
iter  30 value 93.747449
final  value 93.747376 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.355764 
iter  10 value 94.037827
iter  20 value 93.994833
iter  20 value 93.994832
iter  30 value 84.786207
iter  40 value 84.674312
iter  50 value 84.660467
iter  60 value 84.653005
iter  70 value 84.648096
iter  80 value 84.646871
iter  90 value 84.646308
iter 100 value 84.642966
final  value 84.642966 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.946079 
iter  10 value 94.060481
iter  20 value 88.982065
iter  30 value 82.001400
iter  40 value 81.787061
iter  50 value 81.717271
iter  60 value 81.659275
iter  70 value 81.641761
final  value 81.641572 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.624161 
iter  10 value 90.877497
iter  20 value 88.358838
iter  30 value 88.312527
iter  40 value 88.238433
iter  50 value 88.076099
iter  60 value 88.064203
final  value 88.063474 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.171111 
iter  10 value 92.776745
iter  20 value 92.245672
iter  30 value 92.244683
iter  40 value 92.225495
iter  50 value 86.978326
iter  60 value 80.101084
iter  70 value 80.073840
iter  80 value 80.073073
iter  90 value 80.050853
iter 100 value 79.865225
final  value 79.865225 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.852588 
iter  10 value 94.403803
iter  20 value 94.055766
iter  30 value 93.935189
iter  40 value 92.077773
iter  50 value 87.001438
iter  60 value 86.004676
iter  70 value 85.742645
iter  80 value 85.465282
iter  90 value 85.464100
iter 100 value 85.458127
final  value 85.458127 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.124166 
iter  10 value 94.041270
iter  20 value 93.983752
iter  30 value 93.886078
iter  40 value 93.709969
iter  50 value 85.658918
final  value 85.653633 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.156514 
iter  10 value 90.333221
iter  20 value 87.508858
iter  30 value 87.464103
iter  40 value 87.414613
final  value 87.414592 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.506446 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.863193 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.012812 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.858835 
iter  10 value 94.401649
iter  20 value 94.400016
final  value 94.400001 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.871737 
iter  10 value 94.484218
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.466914 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.602300 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.982893 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.996380 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.619188 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.349592 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.358156 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.039716 
final  value 93.775294 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.976254 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.839340 
iter  10 value 93.759882
iter  20 value 85.115211
iter  30 value 83.329732
iter  40 value 82.889646
iter  50 value 82.076204
iter  60 value 81.103153
iter  70 value 80.550233
iter  80 value 80.524899
final  value 80.524897 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.379226 
iter  10 value 94.486168
iter  20 value 93.973635
iter  30 value 93.723868
iter  40 value 93.708187
iter  50 value 93.598087
iter  60 value 91.904865
iter  70 value 90.162073
iter  80 value 90.067825
iter  90 value 89.827965
iter 100 value 86.918412
final  value 86.918412 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.634268 
iter  10 value 94.481014
iter  20 value 93.110106
iter  30 value 89.458421
iter  40 value 85.770233
iter  50 value 83.551692
iter  60 value 82.438576
iter  70 value 80.862093
iter  80 value 80.573077
final  value 80.524896 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.037523 
iter  10 value 94.083992
iter  20 value 93.540559
iter  30 value 86.519275
iter  40 value 85.826445
iter  50 value 85.788616
iter  60 value 85.619846
iter  70 value 85.067926
iter  80 value 84.721476
iter  90 value 84.685599
iter 100 value 84.660917
final  value 84.660917 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.255070 
iter  10 value 89.440940
iter  20 value 85.669790
iter  30 value 85.247502
iter  40 value 84.253754
iter  50 value 84.110361
final  value 84.110344 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.155308 
iter  10 value 89.098226
iter  20 value 88.696104
iter  30 value 86.610327
iter  40 value 85.323678
iter  50 value 82.687806
iter  60 value 81.827371
iter  70 value 80.685710
iter  80 value 79.992845
iter  90 value 79.659096
iter 100 value 79.377237
final  value 79.377237 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.418418 
iter  10 value 94.264790
iter  20 value 89.312538
iter  30 value 86.816055
iter  40 value 84.559663
iter  50 value 84.453047
iter  60 value 84.331140
iter  70 value 82.992830
iter  80 value 81.863563
iter  90 value 81.713927
iter 100 value 80.715241
final  value 80.715241 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.702044 
iter  10 value 94.687393
iter  20 value 94.468260
iter  30 value 93.062021
iter  40 value 86.027895
iter  50 value 84.855757
iter  60 value 82.487969
iter  70 value 81.834336
iter  80 value 81.118863
iter  90 value 80.403852
iter 100 value 80.129779
final  value 80.129779 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.191949 
iter  10 value 94.405218
iter  20 value 93.531567
iter  30 value 91.494992
iter  40 value 88.826662
iter  50 value 87.437913
iter  60 value 84.257522
iter  70 value 80.875091
iter  80 value 80.229803
iter  90 value 79.850361
iter 100 value 79.541355
final  value 79.541355 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.020845 
iter  10 value 94.426819
iter  20 value 86.535175
iter  30 value 85.804934
iter  40 value 85.511267
iter  50 value 84.503476
iter  60 value 82.718566
iter  70 value 81.020836
iter  80 value 80.175782
iter  90 value 79.951006
iter 100 value 79.350392
final  value 79.350392 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.313248 
iter  10 value 94.545732
iter  20 value 94.444023
iter  30 value 89.219037
iter  40 value 85.988588
iter  50 value 81.958136
iter  60 value 80.644507
iter  70 value 79.950502
iter  80 value 79.518153
iter  90 value 79.339961
iter 100 value 79.218375
final  value 79.218375 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.953532 
iter  10 value 89.615886
iter  20 value 85.015463
iter  30 value 84.115468
iter  40 value 83.943485
iter  50 value 83.770742
iter  60 value 83.734133
iter  70 value 83.688933
iter  80 value 83.270182
iter  90 value 81.457776
iter 100 value 80.481634
final  value 80.481634 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.448623 
iter  10 value 94.324563
iter  20 value 89.865823
iter  30 value 85.329265
iter  40 value 83.867470
iter  50 value 82.911434
iter  60 value 81.201818
iter  70 value 80.381475
iter  80 value 79.846264
iter  90 value 79.559554
iter 100 value 79.430865
final  value 79.430865 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.573670 
iter  10 value 94.593902
iter  20 value 93.783147
iter  30 value 86.410815
iter  40 value 83.397021
iter  50 value 81.838287
iter  60 value 79.960947
iter  70 value 79.309171
iter  80 value 79.084662
iter  90 value 79.051339
iter 100 value 79.043555
final  value 79.043555 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.570800 
iter  10 value 92.288905
iter  20 value 85.115304
iter  30 value 83.456290
iter  40 value 81.787751
iter  50 value 80.247186
iter  60 value 80.129014
iter  70 value 79.642926
iter  80 value 79.062317
iter  90 value 78.958879
iter 100 value 78.607027
final  value 78.607027 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.153775 
final  value 94.486096 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.698199 
final  value 94.485813 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.855985 
final  value 94.485978 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.003016 
final  value 94.485893 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.134956 
final  value 94.485710 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.142389 
iter  10 value 94.488882
iter  20 value 94.484276
iter  30 value 94.135085
final  value 93.919261 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.764179 
iter  10 value 94.488832
iter  20 value 94.375216
iter  30 value 93.144501
iter  40 value 86.061388
iter  50 value 83.925219
iter  60 value 83.020578
iter  70 value 82.045289
iter  80 value 78.888471
iter  90 value 78.247752
iter 100 value 78.222045
final  value 78.222045 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.318347 
iter  10 value 94.472028
iter  20 value 94.467477
iter  30 value 93.112178
iter  40 value 92.518971
final  value 92.518686 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.307937 
iter  10 value 92.183302
iter  20 value 84.035370
iter  30 value 83.987156
iter  40 value 82.635617
iter  50 value 82.623218
final  value 82.622318 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.083795 
iter  10 value 94.489131
iter  20 value 93.979300
iter  30 value 91.951107
iter  40 value 91.619955
iter  50 value 85.364401
iter  60 value 84.017981
iter  70 value 84.016949
final  value 84.015667 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.726934 
iter  10 value 94.192465
iter  20 value 93.791447
iter  30 value 93.784131
iter  40 value 93.713602
iter  50 value 93.222910
iter  60 value 89.953899
iter  70 value 86.214742
iter  80 value 85.250015
iter  90 value 83.912170
iter 100 value 81.616491
final  value 81.616491 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.955113 
iter  10 value 94.149911
iter  20 value 94.143986
iter  30 value 91.629293
iter  40 value 90.119945
iter  50 value 89.486383
iter  60 value 89.319760
final  value 89.319669 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.724043 
iter  10 value 93.931885
iter  20 value 93.191557
iter  30 value 93.188869
iter  40 value 90.790161
iter  50 value 83.021490
iter  60 value 82.092711
iter  70 value 81.648622
iter  80 value 81.628379
final  value 81.628154 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.153151 
iter  10 value 94.484680
iter  20 value 94.474561
final  value 94.474484 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.641963 
iter  10 value 87.522344
iter  20 value 85.418932
iter  30 value 85.410271
iter  40 value 85.014840
iter  50 value 84.988116
iter  60 value 84.982105
iter  70 value 84.276273
iter  80 value 82.251972
iter  90 value 82.134814
iter 100 value 82.134402
final  value 82.134402 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.709174 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.407355 
iter  10 value 92.877443
final  value 92.877419 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.741006 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.219350 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.847671 
iter  10 value 93.852668
iter  20 value 93.686308
iter  30 value 93.683572
final  value 90.842082 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.126068 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.864105 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.711284 
iter  10 value 89.307270
iter  20 value 86.025943
iter  30 value 86.007724
iter  40 value 84.881661
final  value 84.840427 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.583804 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.892432 
final  value 94.275363 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.347449 
iter  10 value 92.578758
final  value 92.577922 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.151294 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.141351 
iter  10 value 94.187009
iter  20 value 94.012193
iter  30 value 94.010805
final  value 94.010803 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.198647 
iter  10 value 93.959704
iter  20 value 89.134649
iter  30 value 87.668871
iter  40 value 87.581978
iter  50 value 87.495367
final  value 87.494184 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.004082 
iter  10 value 94.275363
iter  10 value 94.275363
iter  10 value 94.275363
final  value 94.275363 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.746288 
iter  10 value 94.486982
iter  20 value 94.343873
iter  30 value 93.626658
iter  40 value 90.212231
iter  50 value 87.509819
iter  60 value 85.362448
iter  70 value 84.525098
iter  80 value 84.239783
iter  90 value 83.401188
iter 100 value 83.023643
final  value 83.023643 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.263007 
iter  10 value 94.480429
iter  20 value 93.811734
iter  30 value 89.452404
iter  40 value 89.189704
iter  50 value 86.753758
iter  60 value 86.322736
iter  70 value 85.743449
iter  80 value 85.460109
final  value 85.450694 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.710775 
iter  10 value 94.458268
iter  20 value 89.101943
iter  30 value 87.437196
iter  40 value 86.931386
iter  50 value 86.887027
iter  60 value 86.841985
iter  70 value 86.750907
final  value 86.749829 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.780932 
iter  10 value 94.468696
iter  20 value 89.770387
iter  30 value 88.671058
iter  40 value 86.683543
iter  50 value 84.748359
iter  60 value 83.891927
iter  70 value 83.112381
iter  80 value 83.095043
iter  90 value 83.064599
iter 100 value 83.017602
final  value 83.017602 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.349645 
iter  10 value 94.486673
iter  20 value 94.390737
iter  30 value 94.103241
iter  40 value 94.071258
iter  50 value 90.393517
iter  60 value 89.362583
iter  70 value 88.264894
iter  80 value 86.775701
iter  90 value 86.590654
iter 100 value 85.964444
final  value 85.964444 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.281601 
iter  10 value 94.478974
iter  20 value 88.549218
iter  30 value 87.450128
iter  40 value 86.010375
iter  50 value 85.231818
iter  60 value 84.183957
iter  70 value 83.219582
iter  80 value 82.916483
iter  90 value 82.674268
iter 100 value 82.493386
final  value 82.493386 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.307189 
iter  10 value 94.209918
iter  20 value 88.697718
iter  30 value 87.217025
iter  40 value 86.476108
iter  50 value 86.208637
iter  60 value 86.117729
iter  70 value 85.932362
iter  80 value 85.779511
iter  90 value 85.625198
iter 100 value 83.936581
final  value 83.936581 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.975788 
iter  10 value 94.327450
iter  20 value 92.214852
iter  30 value 89.405780
iter  40 value 86.252591
iter  50 value 84.920914
iter  60 value 84.684182
iter  70 value 84.452317
iter  80 value 84.318073
iter  90 value 84.245122
iter 100 value 83.770919
final  value 83.770919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.834331 
iter  10 value 94.486658
iter  20 value 94.087275
iter  30 value 92.096640
iter  40 value 88.495938
iter  50 value 86.938791
iter  60 value 86.468414
iter  70 value 85.089977
iter  80 value 83.496455
iter  90 value 83.101857
iter 100 value 82.770245
final  value 82.770245 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.675034 
iter  10 value 94.561574
iter  20 value 94.437699
iter  30 value 93.908559
iter  40 value 89.046845
iter  50 value 87.226313
iter  60 value 85.847879
iter  70 value 83.195990
iter  80 value 82.365902
iter  90 value 82.201813
iter 100 value 82.121834
final  value 82.121834 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.741803 
iter  10 value 93.660664
iter  20 value 88.765108
iter  30 value 87.128554
iter  40 value 83.700582
iter  50 value 82.029083
iter  60 value 81.647480
iter  70 value 81.483643
iter  80 value 81.411574
iter  90 value 81.342782
iter 100 value 81.296971
final  value 81.296971 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.962906 
iter  10 value 94.361111
iter  20 value 89.425658
iter  30 value 85.621713
iter  40 value 85.339337
iter  50 value 83.975964
iter  60 value 83.410516
iter  70 value 82.809484
iter  80 value 82.777666
iter  90 value 82.702149
iter 100 value 82.693480
final  value 82.693480 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.221817 
iter  10 value 95.957738
iter  20 value 91.767833
iter  30 value 89.231605
iter  40 value 87.342432
iter  50 value 83.445965
iter  60 value 82.977390
iter  70 value 82.694470
iter  80 value 82.011878
iter  90 value 81.740039
iter 100 value 81.188980
final  value 81.188980 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.514735 
iter  10 value 94.436716
iter  20 value 91.130966
iter  30 value 86.921903
iter  40 value 84.047191
iter  50 value 82.784438
iter  60 value 82.405975
iter  70 value 82.377565
iter  80 value 82.343343
iter  90 value 82.321626
iter 100 value 82.157422
final  value 82.157422 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.139093 
iter  10 value 94.616971
iter  20 value 90.143854
iter  30 value 87.351479
iter  40 value 86.660869
iter  50 value 86.361668
iter  60 value 86.051661
iter  70 value 84.846843
iter  80 value 83.539559
iter  90 value 82.611169
iter 100 value 82.511452
final  value 82.511452 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.461700 
iter  10 value 94.485837
iter  20 value 94.484172
iter  30 value 94.156475
iter  40 value 88.857050
iter  50 value 88.714071
iter  60 value 88.713358
iter  70 value 88.712318
iter  80 value 88.617143
iter  90 value 88.613601
iter 100 value 88.613494
final  value 88.613494 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.522629 
final  value 94.485792 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.045111 
final  value 94.485844 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.378448 
final  value 94.485862 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.652642 
final  value 94.485851 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.663567 
iter  10 value 94.489500
iter  20 value 94.485360
iter  30 value 94.424037
iter  40 value 90.065790
iter  50 value 87.100172
iter  60 value 87.090784
final  value 87.089859 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.909696 
iter  10 value 94.489054
iter  20 value 93.813871
iter  30 value 89.016892
iter  40 value 88.990276
iter  50 value 88.759562
iter  60 value 88.755317
iter  70 value 87.317294
iter  80 value 87.096336
iter  80 value 87.096336
final  value 87.096336 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.341778 
iter  10 value 94.255239
iter  20 value 94.247288
final  value 94.244988 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.248961 
iter  10 value 90.896946
iter  20 value 90.553562
iter  30 value 90.388601
final  value 90.387559 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.640396 
iter  10 value 94.488405
iter  20 value 89.990173
final  value 87.182904 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.693467 
iter  10 value 94.284236
iter  20 value 94.282638
iter  30 value 94.279507
iter  40 value 93.990383
iter  50 value 93.887839
iter  60 value 92.216368
iter  70 value 91.700954
final  value 91.697181 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.652220 
iter  10 value 94.492961
iter  20 value 94.378732
iter  30 value 86.048443
iter  40 value 83.554543
final  value 83.553239 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.962300 
iter  10 value 94.082641
iter  20 value 94.018905
iter  30 value 94.011693
iter  40 value 91.053688
iter  50 value 87.314284
final  value 87.311615 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.337710 
iter  10 value 94.126116
iter  20 value 92.120751
iter  30 value 89.961002
iter  40 value 89.621619
iter  50 value 89.408177
iter  60 value 89.405625
iter  60 value 89.405625
final  value 89.405625 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.807162 
iter  10 value 94.060937
iter  20 value 94.043043
iter  30 value 94.016819
iter  40 value 94.014883
final  value 94.011303 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.245274 
iter  10 value 118.147466
iter  20 value 117.836717
iter  30 value 106.923147
iter  40 value 105.598141
iter  50 value 103.846059
iter  60 value 103.003007
iter  70 value 102.636763
iter  80 value 101.112632
iter  90 value 100.656004
iter 100 value 100.561487
final  value 100.561487 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.199724 
iter  10 value 116.819939
iter  20 value 109.035891
iter  30 value 104.776267
iter  40 value 103.990914
iter  50 value 103.571427
iter  60 value 103.023420
iter  70 value 102.700704
iter  80 value 102.687808
iter  90 value 102.654779
iter 100 value 102.288135
final  value 102.288135 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 135.218396 
iter  10 value 117.892621
iter  20 value 114.457175
iter  30 value 109.933831
iter  40 value 106.664626
iter  50 value 104.162501
iter  60 value 103.745103
iter  70 value 103.649060
iter  80 value 103.455404
iter  90 value 103.165490
iter 100 value 102.975338
final  value 102.975338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 130.155442 
iter  10 value 117.888577
iter  20 value 108.061120
iter  30 value 106.988685
iter  40 value 105.180622
iter  50 value 103.855525
iter  60 value 103.017224
iter  70 value 102.479383
iter  80 value 101.718164
iter  90 value 101.439305
iter 100 value 101.386734
final  value 101.386734 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 140.755116 
iter  10 value 118.713126
iter  20 value 117.896440
iter  30 value 111.283602
iter  40 value 110.781482
iter  50 value 106.319525
iter  60 value 104.065427
iter  70 value 103.040970
iter  80 value 102.244911
iter  90 value 101.766770
iter 100 value 101.454862
final  value 101.454862 
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 -- Sun Mar 22 20:13:28 2026 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 20.561   0.773  84.741