##############################################################################
##############################################################################
###
### 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) (2026-01-15 r89304)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Sonoma 14.8.3
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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
FSmethod      19.057  0.982  21.157
corr_plot     19.050  0.950  20.801
var_imp       18.316  1.009  20.579
pred_ensembel  6.583  0.121   6.154
enrichfindP    0.203  0.039   9.188
* 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-arm64/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) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-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 101.563331 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.055336 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.843881 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.690245 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.535749 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.396513 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.842952 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.084891 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.043992 
final  value 94.354395 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.952319 
iter  10 value 93.995389
iter  20 value 93.300014
final  value 93.300000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.248200 
iter  10 value 93.721795
iter  20 value 91.301517
iter  30 value 84.588757
iter  30 value 84.588756
iter  30 value 84.588756
final  value 84.588756 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.314955 
iter  10 value 87.061620
iter  20 value 83.338040
final  value 83.336234 
converged
Fitting Repeat 3 

# weights:  507
initial  value 127.186481 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.002440 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.159082 
iter  10 value 94.354398
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.421713 
iter  10 value 93.956890
iter  20 value 84.455528
iter  30 value 84.240506
iter  40 value 84.139086
iter  50 value 84.089286
iter  60 value 84.082500
final  value 84.082416 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.693184 
iter  10 value 94.301184
iter  20 value 90.954859
iter  30 value 88.495335
iter  40 value 84.278519
iter  50 value 84.130983
iter  60 value 84.112468
iter  70 value 84.086483
final  value 84.086411 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.522340 
iter  10 value 94.512322
iter  20 value 94.425059
iter  30 value 87.234381
iter  40 value 84.168606
iter  50 value 83.975356
iter  60 value 83.966329
final  value 83.965916 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.559095 
iter  10 value 91.896082
iter  20 value 90.182846
iter  30 value 88.875789
iter  40 value 87.911218
iter  50 value 86.355389
iter  60 value 85.877770
iter  70 value 85.608075
final  value 85.608074 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.348169 
iter  10 value 94.499531
iter  20 value 92.422509
iter  30 value 90.392049
iter  40 value 84.319155
iter  50 value 82.789211
iter  60 value 82.241726
iter  70 value 82.040068
iter  80 value 82.033923
final  value 82.033012 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.534776 
iter  10 value 94.188718
iter  20 value 91.324097
iter  30 value 85.352050
iter  40 value 83.930160
iter  50 value 83.713170
iter  60 value 82.874474
iter  70 value 82.367939
iter  80 value 80.984393
iter  90 value 80.675859
iter 100 value 80.498741
final  value 80.498741 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.598451 
iter  10 value 94.516594
iter  20 value 88.158885
iter  30 value 84.312832
iter  40 value 84.055204
iter  50 value 83.982218
iter  60 value 83.903104
iter  70 value 83.843326
iter  80 value 82.868614
iter  90 value 82.047735
iter 100 value 81.630536
final  value 81.630536 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.096506 
iter  10 value 94.452863
iter  20 value 84.600056
iter  30 value 84.012478
iter  40 value 83.962347
iter  50 value 83.790835
iter  60 value 83.339245
iter  70 value 82.510869
iter  80 value 81.955447
iter  90 value 81.797804
iter 100 value 81.767582
final  value 81.767582 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.522119 
iter  10 value 94.171632
iter  20 value 93.642647
iter  30 value 86.478665
iter  40 value 85.658439
iter  50 value 85.544964
iter  60 value 85.437551
iter  70 value 85.262548
iter  80 value 83.814998
iter  90 value 82.489569
iter 100 value 81.887285
final  value 81.887285 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.521175 
iter  10 value 94.296738
iter  20 value 93.989756
iter  30 value 93.949550
iter  40 value 93.792905
iter  50 value 88.077765
iter  60 value 86.126957
iter  70 value 85.857091
iter  80 value 85.669615
iter  90 value 84.898123
iter 100 value 82.352844
final  value 82.352844 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.911653 
iter  10 value 94.351382
iter  20 value 92.480000
iter  30 value 88.356757
iter  40 value 83.150918
iter  50 value 82.546475
iter  60 value 81.742456
iter  70 value 81.115059
iter  80 value 80.949915
iter  90 value 80.903753
iter 100 value 80.891262
final  value 80.891262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.595809 
iter  10 value 94.508199
iter  20 value 89.759734
iter  30 value 84.500014
iter  40 value 84.312113
iter  50 value 84.256227
iter  60 value 84.183681
iter  70 value 84.004571
iter  80 value 82.690593
iter  90 value 82.030839
iter 100 value 81.304918
final  value 81.304918 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.200071 
iter  10 value 93.741721
iter  20 value 84.480444
iter  30 value 84.217599
iter  40 value 84.015949
iter  50 value 83.845918
iter  60 value 83.131284
iter  70 value 81.687034
iter  80 value 80.380002
iter  90 value 80.081524
iter 100 value 79.920798
final  value 79.920798 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.172881 
iter  10 value 95.880849
iter  20 value 94.710635
iter  30 value 93.246098
iter  40 value 89.578416
iter  50 value 86.056542
iter  60 value 82.878821
iter  70 value 82.067745
iter  80 value 81.320151
iter  90 value 81.247228
iter 100 value 81.153860
final  value 81.153860 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.572499 
iter  10 value 94.545918
iter  20 value 84.243176
iter  30 value 84.066181
iter  40 value 83.855757
iter  50 value 83.354311
iter  60 value 82.194696
iter  70 value 81.966565
iter  80 value 81.727406
iter  90 value 80.841145
iter 100 value 80.541851
final  value 80.541851 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 119.012328 
final  value 94.485841 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.110444 
iter  10 value 94.485829
iter  20 value 94.484220
final  value 94.484215 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.142051 
final  value 94.485784 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.559133 
final  value 94.485755 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.378577 
final  value 94.485747 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.461504 
iter  10 value 86.389471
iter  20 value 84.585154
iter  30 value 84.582677
iter  40 value 83.297116
iter  50 value 82.678240
iter  60 value 82.558429
iter  70 value 82.365931
iter  80 value 82.342664
final  value 82.341485 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.828410 
iter  10 value 93.305012
iter  20 value 93.301079
final  value 93.301016 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.017355 
iter  10 value 94.358922
iter  20 value 89.725530
final  value 86.311937 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.166839 
iter  10 value 94.488932
iter  20 value 94.409392
final  value 93.943184 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.392994 
iter  10 value 94.488675
iter  20 value 94.178717
iter  30 value 91.090269
final  value 91.090267 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.495016 
iter  10 value 89.644891
iter  20 value 86.956935
iter  30 value 86.951409
iter  40 value 83.345869
iter  50 value 83.340100
iter  60 value 83.115305
iter  70 value 81.959455
final  value 81.463759 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.263469 
iter  10 value 94.363195
iter  20 value 92.664466
iter  30 value 92.141302
iter  40 value 92.140585
iter  50 value 92.139899
final  value 92.139894 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.134189 
iter  10 value 94.362309
iter  20 value 94.354467
iter  30 value 93.931096
iter  40 value 93.928931
final  value 93.928905 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.860974 
iter  10 value 94.174665
iter  20 value 94.114718
iter  30 value 93.531579
final  value 93.531239 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.715550 
iter  10 value 94.362960
iter  20 value 93.977568
iter  30 value 87.359983
final  value 86.310248 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.354730 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.978612 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.159978 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.952379 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.850384 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.997555 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.616259 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.254447 
final  value 93.690763 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.374805 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.866502 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.898160 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.404163 
final  value 94.313349 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.219113 
iter  10 value 92.428471
iter  20 value 91.438318
final  value 91.436400 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.142053 
iter  10 value 93.212739
iter  20 value 93.135786
iter  30 value 92.621560
iter  40 value 92.615199
final  value 92.615194 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.086486 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.036841 
iter  10 value 94.489065
iter  20 value 93.309244
iter  30 value 87.869973
iter  40 value 84.446905
iter  50 value 83.488525
iter  60 value 82.856599
iter  70 value 82.025486
iter  80 value 81.863482
iter  90 value 80.942149
iter 100 value 79.176200
final  value 79.176200 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.809584 
iter  10 value 94.486612
iter  20 value 93.006249
iter  30 value 84.363429
iter  40 value 82.175608
iter  50 value 79.531291
iter  60 value 78.527862
iter  70 value 78.474515
iter  80 value 78.474266
final  value 78.474252 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.809042 
iter  10 value 94.411503
iter  20 value 83.669208
iter  30 value 82.841246
iter  40 value 81.767538
iter  50 value 81.479209
iter  60 value 80.127245
iter  70 value 79.013739
iter  80 value 78.740023
iter  90 value 78.536111
final  value 78.474252 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.254493 
iter  10 value 94.320012
iter  20 value 83.462228
iter  30 value 80.058358
iter  40 value 79.491856
iter  50 value 79.010817
iter  60 value 78.797326
iter  70 value 78.547005
iter  80 value 78.474292
final  value 78.474252 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.985992 
iter  10 value 94.454804
iter  20 value 91.287045
iter  30 value 84.515464
iter  40 value 84.012437
iter  50 value 83.746937
iter  60 value 82.078807
iter  70 value 81.283241
iter  80 value 80.955713
iter  90 value 80.911501
final  value 80.911190 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.583061 
iter  10 value 92.338034
iter  20 value 86.103750
iter  30 value 84.267263
iter  40 value 81.814316
iter  50 value 79.884870
iter  60 value 79.456791
iter  70 value 79.022780
iter  80 value 77.599505
iter  90 value 77.195693
iter 100 value 77.131005
final  value 77.131005 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.064194 
iter  10 value 94.406934
iter  20 value 93.338041
iter  30 value 90.208107
iter  40 value 85.345292
iter  50 value 82.447903
iter  60 value 78.022210
iter  70 value 77.559788
iter  80 value 77.267802
iter  90 value 77.140523
final  value 77.133625 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.967152 
iter  10 value 94.696479
iter  20 value 86.682254
iter  30 value 83.154860
iter  40 value 81.671316
iter  50 value 81.416629
iter  60 value 80.705856
iter  70 value 80.025566
iter  80 value 79.690402
iter  90 value 79.637693
iter 100 value 79.513598
final  value 79.513598 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.359688 
iter  10 value 94.640434
iter  20 value 94.261194
iter  30 value 91.548076
iter  40 value 81.507521
iter  50 value 79.662740
iter  60 value 78.618157
iter  70 value 78.127594
iter  80 value 77.749059
iter  90 value 77.586913
iter 100 value 77.530703
final  value 77.530703 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.543212 
iter  10 value 94.502141
iter  20 value 89.821308
iter  30 value 85.799819
iter  40 value 85.412356
iter  50 value 83.845813
iter  60 value 81.890503
iter  70 value 81.079198
iter  80 value 80.972049
iter  90 value 80.682510
iter 100 value 80.348469
final  value 80.348469 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.337922 
iter  10 value 90.177967
iter  20 value 83.263592
iter  30 value 81.863955
iter  40 value 81.332961
iter  50 value 81.237180
iter  60 value 80.932137
iter  70 value 79.160091
iter  80 value 78.333722
iter  90 value 77.793894
iter 100 value 77.608185
final  value 77.608185 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.756015 
iter  10 value 92.955900
iter  20 value 86.421717
iter  30 value 82.845797
iter  40 value 80.480895
iter  50 value 79.372688
iter  60 value 78.233627
iter  70 value 77.940568
iter  80 value 77.440150
iter  90 value 77.241020
iter 100 value 76.990393
final  value 76.990393 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.591444 
iter  10 value 94.594388
iter  20 value 94.303715
iter  30 value 83.590096
iter  40 value 82.643846
iter  50 value 81.537812
iter  60 value 79.914036
iter  70 value 78.511141
iter  80 value 77.964628
iter  90 value 77.718881
iter 100 value 77.475533
final  value 77.475533 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.598448 
iter  10 value 94.470827
iter  20 value 92.140938
iter  30 value 90.799438
iter  40 value 87.452829
iter  50 value 80.542539
iter  60 value 79.863294
iter  70 value 78.018004
iter  80 value 77.755818
iter  90 value 77.517799
iter 100 value 77.370673
final  value 77.370673 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.364291 
iter  10 value 94.877676
iter  20 value 85.956590
iter  30 value 83.311626
iter  40 value 80.499516
iter  50 value 79.839552
iter  60 value 78.965858
iter  70 value 78.354897
iter  80 value 77.784415
iter  90 value 77.450037
iter 100 value 77.267467
final  value 77.267467 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.001196 
final  value 94.485844 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.300108 
final  value 94.485979 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.566239 
final  value 94.486016 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.482054 
final  value 94.485857 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.308013 
final  value 94.485804 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.938326 
iter  10 value 94.487680
iter  20 value 94.467800
iter  30 value 87.278992
iter  40 value 86.967518
iter  50 value 86.731246
iter  60 value 86.334488
iter  70 value 81.257115
iter  80 value 80.805668
iter  90 value 80.772248
final  value 80.772146 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.440473 
iter  10 value 94.322084
iter  20 value 94.317081
iter  30 value 94.137663
iter  40 value 86.933289
iter  50 value 78.620668
iter  60 value 78.434227
iter  70 value 78.402802
iter  80 value 78.341299
iter  90 value 78.338958
iter 100 value 77.740695
final  value 77.740695 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.489442 
iter  10 value 94.488770
iter  20 value 94.421079
iter  30 value 90.146063
iter  40 value 87.233224
iter  50 value 85.853616
iter  60 value 85.410412
iter  70 value 83.749835
iter  80 value 83.684100
iter  90 value 83.675065
iter 100 value 83.392915
final  value 83.392915 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.960331 
iter  10 value 94.489069
iter  20 value 94.484335
iter  30 value 86.948638
final  value 86.497684 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.259050 
iter  10 value 94.488482
iter  20 value 93.083332
iter  30 value 83.047280
iter  40 value 82.674785
iter  50 value 82.639960
final  value 82.639950 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.654394 
iter  10 value 94.492491
iter  20 value 94.429211
iter  30 value 84.707676
iter  40 value 83.406200
iter  50 value 83.335716
iter  60 value 83.333498
iter  70 value 82.897689
iter  80 value 79.932032
iter  90 value 79.902658
iter 100 value 79.902156
final  value 79.902156 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.822839 
iter  10 value 94.494492
iter  20 value 94.486304
iter  30 value 94.364440
iter  40 value 90.112380
iter  50 value 78.685387
iter  60 value 78.677001
iter  70 value 78.676030
iter  80 value 78.208316
iter  90 value 77.918266
iter 100 value 77.501083
final  value 77.501083 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.069252 
iter  10 value 91.957526
iter  20 value 91.466089
iter  30 value 91.329159
iter  40 value 91.325115
iter  50 value 91.319751
iter  60 value 90.284105
iter  70 value 85.358136
iter  80 value 85.331396
iter  90 value 85.217184
iter 100 value 84.088171
final  value 84.088171 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.024207 
iter  10 value 94.491164
iter  20 value 92.586172
final  value 91.790894 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.873771 
iter  10 value 94.463725
iter  20 value 88.262206
iter  30 value 86.700074
iter  40 value 85.811184
iter  50 value 85.810237
iter  60 value 83.603245
iter  70 value 83.583675
iter  80 value 83.583521
final  value 83.583492 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.558899 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.253299 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.492794 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.190952 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.097008 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.049710 
final  value 94.033150 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.019982 
iter  10 value 88.289173
iter  20 value 87.929579
iter  30 value 87.407688
iter  40 value 82.866662
iter  40 value 82.866662
iter  50 value 81.537569
iter  60 value 81.322465
final  value 81.320513 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.010084 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.833255 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.066076 
iter  10 value 93.766369
iter  20 value 91.849261
iter  30 value 88.307406
iter  40 value 82.824597
iter  50 value 82.182848
iter  60 value 81.789526
iter  70 value 81.755709
final  value 81.754943 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.051527 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.667728 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.239095 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.944223 
final  value 93.860355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.937441 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.376776 
iter  10 value 93.945874
iter  20 value 86.050463
iter  30 value 85.162984
iter  40 value 84.703021
iter  50 value 83.379355
iter  60 value 82.777595
iter  70 value 82.656452
iter  80 value 82.639146
final  value 82.625612 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.357717 
iter  10 value 93.992501
iter  20 value 87.306607
iter  30 value 84.314623
iter  40 value 83.733403
iter  50 value 83.262163
iter  60 value 83.119627
iter  70 value 82.337084
iter  80 value 81.587722
iter  90 value 81.566288
iter 100 value 81.508982
final  value 81.508982 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.637402 
iter  10 value 94.094258
iter  20 value 94.028792
iter  30 value 90.918221
iter  40 value 88.718000
iter  50 value 86.564161
iter  60 value 86.382757
iter  70 value 86.023930
iter  80 value 85.717033
iter  90 value 84.886852
final  value 84.886081 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.313301 
iter  10 value 94.044131
iter  20 value 93.563385
iter  30 value 89.143631
iter  40 value 87.447864
iter  50 value 86.713452
iter  60 value 85.276082
iter  70 value 82.206670
iter  80 value 82.075300
iter  90 value 82.066912
final  value 82.066872 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.981120 
iter  10 value 94.052675
iter  20 value 86.484749
iter  30 value 83.657450
iter  40 value 83.134327
final  value 83.114553 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.861308 
iter  10 value 93.989876
iter  20 value 91.080525
iter  30 value 86.200596
iter  40 value 84.189897
iter  50 value 82.059283
iter  60 value 80.982146
iter  70 value 80.753250
iter  80 value 80.182936
iter  90 value 79.967235
iter 100 value 79.946782
final  value 79.946782 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.277269 
iter  10 value 93.748387
iter  20 value 86.928461
iter  30 value 85.959705
iter  40 value 82.998365
iter  50 value 82.029538
iter  60 value 80.547598
iter  70 value 79.993201
iter  80 value 79.864947
iter  90 value 79.805144
iter 100 value 79.790361
final  value 79.790361 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.827254 
iter  10 value 94.187592
iter  20 value 94.047454
iter  30 value 86.664814
iter  40 value 84.853637
iter  50 value 83.257286
iter  60 value 83.220170
iter  70 value 83.109570
iter  80 value 82.962503
iter  90 value 82.720823
iter 100 value 81.134059
final  value 81.134059 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.804367 
iter  10 value 93.369101
iter  20 value 90.787343
iter  30 value 86.961628
iter  40 value 86.128325
iter  50 value 84.386553
iter  60 value 82.861167
iter  70 value 82.749792
iter  80 value 82.289581
iter  90 value 81.079256
iter 100 value 80.182505
final  value 80.182505 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.580875 
iter  10 value 93.938591
iter  20 value 88.909755
iter  30 value 87.148022
iter  40 value 84.511018
iter  50 value 83.604026
iter  60 value 82.132279
iter  70 value 81.501552
iter  80 value 81.129815
iter  90 value 80.669617
iter 100 value 80.397808
final  value 80.397808 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.092595 
iter  10 value 94.023685
iter  20 value 90.004346
iter  30 value 84.803727
iter  40 value 82.004289
iter  50 value 80.516094
iter  60 value 80.246454
iter  70 value 80.060318
iter  80 value 79.836156
iter  90 value 79.681973
iter 100 value 79.652236
final  value 79.652236 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.174115 
iter  10 value 94.041925
iter  20 value 90.272077
iter  30 value 86.316424
iter  40 value 85.024435
iter  50 value 82.328415
iter  60 value 81.220496
iter  70 value 80.644474
iter  80 value 80.197883
iter  90 value 79.895323
iter 100 value 79.675629
final  value 79.675629 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.736530 
iter  10 value 94.460712
iter  20 value 93.970457
iter  30 value 87.680257
iter  40 value 85.450504
iter  50 value 82.052824
iter  60 value 81.719938
iter  70 value 81.107173
iter  80 value 80.079116
iter  90 value 79.877474
iter 100 value 79.660924
final  value 79.660924 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.431079 
iter  10 value 93.999018
iter  20 value 91.455808
iter  30 value 85.825056
iter  40 value 84.965602
iter  50 value 83.766880
iter  60 value 82.073608
iter  70 value 81.332178
iter  80 value 80.695786
iter  90 value 80.348800
iter 100 value 79.769189
final  value 79.769189 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.153534 
iter  10 value 93.662802
iter  20 value 89.396421
iter  30 value 85.851446
iter  40 value 84.413617
iter  50 value 82.925216
iter  60 value 82.354690
iter  70 value 81.744792
iter  80 value 81.334865
iter  90 value 81.248121
iter 100 value 81.148651
final  value 81.148651 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.443385 
final  value 94.054723 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.842737 
final  value 94.054527 
converged
Fitting Repeat 3 

# weights:  103
initial  value 132.039632 
final  value 94.054384 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.159852 
iter  10 value 94.010256
iter  20 value 94.008750
final  value 94.008726 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.282563 
final  value 94.054659 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.263417 
iter  10 value 94.056497
iter  20 value 93.974479
iter  30 value 93.917306
final  value 93.913452 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.769519 
iter  10 value 94.020496
iter  20 value 88.890074
iter  30 value 88.888439
iter  40 value 88.886067
iter  50 value 88.875970
iter  60 value 87.795751
iter  70 value 87.002407
iter  80 value 86.975986
iter  90 value 86.962516
iter 100 value 86.961771
final  value 86.961771 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.617814 
iter  10 value 94.057425
final  value 94.052920 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.833662 
iter  10 value 94.057446
iter  20 value 94.050923
final  value 94.008788 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.525437 
iter  10 value 94.057897
iter  20 value 93.937240
iter  30 value 88.496884
iter  40 value 85.372716
iter  50 value 85.339054
final  value 85.338125 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.787481 
iter  10 value 94.060579
iter  20 value 94.052941
iter  30 value 88.239777
iter  40 value 83.017061
iter  50 value 80.150506
iter  60 value 79.365597
iter  70 value 78.963529
iter  80 value 78.794927
iter  90 value 78.073131
iter 100 value 78.032789
final  value 78.032789 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.816380 
iter  10 value 94.018416
iter  20 value 94.012093
iter  30 value 94.011857
iter  40 value 93.634624
iter  50 value 86.088511
iter  60 value 85.978273
iter  70 value 84.897092
iter  80 value 82.251733
iter  90 value 81.897120
iter 100 value 81.824971
final  value 81.824971 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.328763 
iter  10 value 93.921021
iter  20 value 91.939657
iter  30 value 87.417665
iter  40 value 87.252597
final  value 87.252572 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.553017 
iter  10 value 94.057040
iter  20 value 94.052976
iter  30 value 93.942964
iter  40 value 93.750729
iter  50 value 88.147622
iter  60 value 85.916568
iter  70 value 85.551577
iter  80 value 85.534050
iter  90 value 85.121396
iter 100 value 83.793786
final  value 83.793786 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.037814 
iter  10 value 94.006120
iter  20 value 93.610199
iter  30 value 86.041746
iter  40 value 85.871136
iter  50 value 85.798981
iter  60 value 82.036758
iter  70 value 82.018129
iter  80 value 81.905977
iter  90 value 80.704781
iter 100 value 80.159405
final  value 80.159405 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.397582 
final  value 94.025289 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.157454 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.170268 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.702428 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.536220 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.433228 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.956508 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.166243 
final  value 93.899999 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.233397 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.283685 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.054472 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.700879 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.858974 
iter  10 value 94.053225
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.759265 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.820255 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.244386 
iter  10 value 94.056672
iter  20 value 92.668965
iter  30 value 85.928777
iter  40 value 84.999739
iter  50 value 84.353126
iter  60 value 83.853598
iter  70 value 82.405077
iter  80 value 81.793255
iter  90 value 81.695582
final  value 81.695348 
converged
Fitting Repeat 2 

# weights:  103
initial  value 117.000381 
iter  10 value 93.965312
iter  20 value 92.794113
iter  30 value 91.657145
iter  40 value 91.582245
iter  50 value 91.543862
iter  60 value 91.540991
final  value 91.540985 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.883667 
iter  10 value 94.063789
iter  20 value 93.742156
iter  30 value 87.327445
iter  40 value 84.685218
iter  50 value 84.155561
iter  60 value 83.998681
iter  70 value 83.742730
iter  80 value 83.700349
iter  90 value 83.468310
iter 100 value 83.212542
final  value 83.212542 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.391375 
iter  10 value 92.130009
iter  20 value 85.934822
iter  30 value 85.671259
iter  40 value 84.159533
iter  50 value 84.087727
iter  60 value 84.077633
final  value 84.077626 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.805458 
iter  10 value 93.995125
iter  20 value 91.730463
iter  30 value 89.284506
iter  40 value 86.419947
iter  50 value 84.419716
iter  60 value 83.886955
iter  70 value 83.614485
iter  80 value 83.477407
final  value 83.475610 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.508036 
iter  10 value 94.048964
iter  20 value 92.192646
iter  30 value 87.625548
iter  40 value 83.632275
iter  50 value 83.087467
iter  60 value 82.459233
iter  70 value 81.963230
iter  80 value 81.722193
iter  90 value 81.660289
iter 100 value 81.113340
final  value 81.113340 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.156881 
iter  10 value 90.931890
iter  20 value 87.190028
iter  30 value 84.153827
iter  40 value 83.416897
iter  50 value 82.017458
iter  60 value 81.513942
iter  70 value 81.173922
iter  80 value 81.092519
iter  90 value 80.790177
iter 100 value 80.659248
final  value 80.659248 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.071022 
iter  10 value 93.166007
iter  20 value 88.202265
iter  30 value 86.375080
iter  40 value 86.203976
iter  50 value 84.418487
iter  60 value 82.354993
iter  70 value 81.801303
iter  80 value 81.116387
iter  90 value 80.878400
iter 100 value 80.846705
final  value 80.846705 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.335696 
iter  10 value 94.011173
iter  20 value 93.491547
iter  30 value 90.092691
iter  40 value 84.920574
iter  50 value 83.240604
iter  60 value 81.194274
iter  70 value 80.856227
iter  80 value 80.581655
iter  90 value 80.499942
iter 100 value 80.396673
final  value 80.396673 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.697274 
iter  10 value 94.021489
iter  20 value 93.535927
iter  30 value 93.438208
iter  40 value 92.775485
iter  50 value 91.852937
iter  60 value 85.387289
iter  70 value 83.695513
iter  80 value 82.865454
iter  90 value 82.570307
iter 100 value 82.397677
final  value 82.397677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.656309 
iter  10 value 94.013679
iter  20 value 87.353789
iter  30 value 84.505018
iter  40 value 82.508468
iter  50 value 81.573950
iter  60 value 81.223607
iter  70 value 80.550018
iter  80 value 80.023459
iter  90 value 79.976773
iter 100 value 79.960096
final  value 79.960096 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.053713 
iter  10 value 95.744316
iter  20 value 88.518570
iter  30 value 85.319869
iter  40 value 84.908389
iter  50 value 84.131372
iter  60 value 83.644975
iter  70 value 81.568691
iter  80 value 80.716573
iter  90 value 80.285904
iter 100 value 80.081445
final  value 80.081445 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.938245 
iter  10 value 93.668248
iter  20 value 89.522001
iter  30 value 86.370018
iter  40 value 83.309159
iter  50 value 81.610591
iter  60 value 81.296202
iter  70 value 80.997768
iter  80 value 80.870001
iter  90 value 80.783134
iter 100 value 80.567889
final  value 80.567889 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 140.704171 
iter  10 value 94.139597
iter  20 value 92.663887
iter  30 value 85.486025
iter  40 value 83.857647
iter  50 value 82.391194
iter  60 value 81.883736
iter  70 value 81.494077
iter  80 value 80.972877
iter  90 value 80.782701
iter 100 value 80.710076
final  value 80.710076 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.045020 
iter  10 value 93.649828
iter  20 value 88.557348
iter  30 value 86.350099
iter  40 value 85.522997
iter  50 value 85.304547
iter  60 value 84.529483
iter  70 value 82.766501
iter  80 value 81.741682
iter  90 value 81.706105
iter 100 value 81.629148
final  value 81.629148 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.094012 
iter  10 value 94.054645
iter  20 value 94.052926
final  value 94.052917 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.614588 
final  value 94.054560 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.977719 
iter  10 value 94.054403
iter  20 value 93.741502
iter  30 value 85.991829
iter  40 value 85.991060
iter  50 value 85.990834
final  value 85.990042 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.818832 
final  value 94.054466 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.840073 
final  value 94.054423 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.050097 
iter  10 value 94.052084
iter  20 value 94.048341
iter  30 value 94.047692
iter  40 value 94.045129
iter  50 value 94.044883
iter  60 value 94.044460
iter  70 value 93.890717
iter  80 value 84.661247
iter  90 value 84.576205
iter 100 value 83.720631
final  value 83.720631 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.966444 
iter  10 value 93.587554
iter  20 value 93.584578
iter  30 value 84.753924
iter  40 value 84.003758
iter  50 value 83.965597
final  value 83.965543 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.517440 
iter  10 value 94.054999
iter  20 value 88.740144
iter  30 value 85.761962
iter  40 value 85.115667
iter  50 value 84.798904
iter  60 value 84.298859
iter  70 value 83.505683
iter  80 value 83.498660
iter  90 value 83.497275
iter 100 value 83.495346
final  value 83.495346 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.992335 
iter  10 value 94.057921
iter  20 value 94.053004
iter  30 value 92.552078
iter  40 value 86.264539
iter  50 value 86.262601
iter  60 value 85.004853
iter  70 value 85.002057
iter  80 value 84.717166
iter  90 value 84.714697
iter 100 value 84.711565
final  value 84.711565 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.932716 
iter  10 value 93.609398
iter  20 value 93.587228
iter  30 value 93.582708
iter  40 value 93.423083
iter  50 value 88.355656
iter  60 value 87.625189
iter  70 value 87.624862
final  value 87.624857 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.097108 
iter  10 value 87.213654
iter  20 value 85.282378
iter  30 value 85.279180
iter  40 value 84.593275
iter  50 value 84.463191
iter  60 value 83.905328
iter  70 value 83.847712
iter  80 value 83.582103
iter  90 value 82.576327
iter 100 value 80.991731
final  value 80.991731 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.851463 
iter  10 value 93.590515
iter  20 value 93.583267
final  value 93.582709 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.960612 
iter  10 value 93.590942
iter  20 value 93.475841
iter  30 value 88.653447
iter  40 value 84.754290
iter  50 value 83.427528
iter  60 value 83.195516
iter  70 value 83.191018
iter  70 value 83.191018
final  value 83.191018 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.305144 
iter  10 value 91.781830
iter  20 value 81.774987
iter  30 value 81.305359
iter  40 value 80.898035
iter  50 value 80.894812
iter  60 value 80.892599
iter  70 value 80.890226
iter  80 value 80.781013
iter  90 value 80.679686
iter 100 value 80.675513
final  value 80.675513 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.674608 
iter  10 value 94.060844
iter  20 value 94.027035
final  value 93.582616 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.952997 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.633317 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.655360 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.019649 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.949083 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.435016 
iter  10 value 93.783741
final  value 93.783647 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.925015 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.348485 
iter  10 value 87.820237
iter  20 value 87.228600
final  value 87.227861 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.053248 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.196955 
final  value 93.783647 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.631802 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.834867 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.415960 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.545431 
iter  10 value 93.568908
iter  20 value 92.750115
iter  30 value 92.731270
final  value 92.731183 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.788715 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.441288 
iter  10 value 93.789125
iter  20 value 86.620378
iter  30 value 84.657851
iter  40 value 83.251513
iter  50 value 82.169432
iter  60 value 81.934210
final  value 81.923007 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.946440 
iter  10 value 93.991476
iter  20 value 86.765205
iter  30 value 86.226693
iter  40 value 85.904786
iter  50 value 85.858928
final  value 85.854557 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.246719 
iter  10 value 94.463206
iter  20 value 93.846753
iter  30 value 93.558537
iter  40 value 91.617220
iter  50 value 88.810062
iter  60 value 88.409551
iter  70 value 85.538481
iter  80 value 83.465941
iter  90 value 82.659202
iter 100 value 82.244848
final  value 82.244848 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.207627 
iter  10 value 94.486983
iter  20 value 91.366089
iter  30 value 86.463708
iter  40 value 85.795000
iter  50 value 85.517098
iter  60 value 85.242335
iter  70 value 85.217676
iter  80 value 85.198879
iter  90 value 83.491141
iter 100 value 82.562464
final  value 82.562464 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 113.501591 
iter  10 value 94.446835
iter  20 value 93.685521
iter  30 value 93.494287
iter  40 value 93.264692
iter  50 value 93.219481
iter  60 value 91.507671
iter  70 value 88.038127
iter  80 value 84.109226
iter  90 value 83.921345
iter 100 value 81.944483
final  value 81.944483 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.479213 
iter  10 value 94.528157
iter  20 value 94.438719
iter  30 value 93.702735
iter  40 value 90.234195
iter  50 value 86.624022
iter  60 value 85.366115
iter  70 value 84.931351
iter  80 value 84.397376
iter  90 value 81.793341
iter 100 value 81.067521
final  value 81.067521 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.365569 
iter  10 value 94.497099
iter  20 value 93.938000
iter  30 value 90.844110
iter  40 value 87.309426
iter  50 value 84.821781
iter  60 value 84.135599
iter  70 value 83.518176
iter  80 value 82.767323
iter  90 value 82.377777
iter 100 value 82.292266
final  value 82.292266 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.096950 
iter  10 value 87.684430
iter  20 value 86.294444
iter  30 value 85.465666
iter  40 value 83.118100
iter  50 value 82.090434
iter  60 value 81.826669
iter  70 value 81.299638
iter  80 value 80.805300
iter  90 value 80.471686
iter 100 value 80.301258
final  value 80.301258 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.220152 
iter  10 value 94.243617
iter  20 value 87.099195
iter  30 value 84.203979
iter  40 value 83.638442
iter  50 value 82.205876
iter  60 value 81.697493
iter  70 value 81.462514
iter  80 value 80.884811
iter  90 value 80.450303
iter 100 value 80.193279
final  value 80.193279 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.807379 
iter  10 value 94.419586
iter  20 value 92.299092
iter  30 value 85.770670
iter  40 value 84.081702
iter  50 value 83.765786
iter  60 value 83.674568
iter  70 value 83.507674
iter  80 value 82.093402
iter  90 value 81.777398
iter 100 value 81.557904
final  value 81.557904 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.580113 
iter  10 value 94.448815
iter  20 value 93.732137
iter  30 value 93.398242
iter  40 value 93.324398
iter  50 value 91.978948
iter  60 value 86.895927
iter  70 value 85.207978
iter  80 value 84.981335
iter  90 value 84.892585
iter 100 value 83.934151
final  value 83.934151 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.578684 
iter  10 value 94.833040
iter  20 value 94.233146
iter  30 value 86.706226
iter  40 value 84.054978
iter  50 value 83.386469
iter  60 value 81.833244
iter  70 value 80.988427
iter  80 value 80.759507
iter  90 value 80.677793
iter 100 value 80.655334
final  value 80.655334 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.290180 
iter  10 value 94.425106
iter  20 value 93.256044
iter  30 value 86.442460
iter  40 value 84.331193
iter  50 value 84.089061
iter  60 value 83.805900
iter  70 value 82.552154
iter  80 value 81.339248
iter  90 value 81.071985
iter 100 value 80.915306
final  value 80.915306 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.870034 
iter  10 value 94.479468
iter  20 value 93.842468
iter  30 value 87.718269
iter  40 value 85.202670
iter  50 value 84.089145
iter  60 value 83.785620
iter  70 value 83.691894
iter  80 value 82.817772
iter  90 value 82.025908
iter 100 value 81.153272
final  value 81.153272 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.102723 
iter  10 value 93.506587
iter  20 value 85.275116
iter  30 value 84.163338
iter  40 value 82.337923
iter  50 value 80.982840
iter  60 value 80.143302
iter  70 value 80.046551
iter  80 value 79.918539
iter  90 value 79.843216
iter 100 value 79.799184
final  value 79.799184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.803101 
final  value 94.485812 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.174454 
final  value 94.312152 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.390198 
final  value 94.485948 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.503442 
final  value 94.485995 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.395810 
iter  10 value 94.485677
iter  20 value 94.484220
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.765950 
iter  10 value 94.489291
iter  20 value 94.484245
iter  30 value 93.742081
final  value 93.567626 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.624347 
iter  10 value 94.489730
iter  20 value 93.959801
iter  30 value 86.145361
iter  40 value 86.133677
iter  50 value 85.816269
final  value 85.811809 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.818834 
iter  10 value 94.489174
final  value 94.484232 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.469615 
iter  10 value 94.488566
iter  20 value 94.478574
iter  30 value 92.507828
iter  40 value 84.974757
iter  50 value 84.503007
iter  60 value 84.501832
iter  70 value 84.194779
iter  80 value 83.348836
iter  90 value 83.346168
iter 100 value 83.344344
final  value 83.344344 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.903446 
iter  10 value 94.488262
iter  20 value 94.406648
iter  30 value 88.949212
iter  40 value 86.774918
iter  50 value 86.127098
iter  60 value 85.647957
iter  70 value 85.618374
iter  80 value 85.618101
final  value 85.618099 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.455859 
iter  10 value 94.492541
iter  20 value 94.484197
final  value 94.445287 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.697049 
iter  10 value 94.491597
iter  20 value 94.484217
iter  30 value 94.022883
iter  40 value 93.179299
iter  50 value 88.241817
iter  60 value 82.995978
iter  70 value 82.746738
iter  80 value 81.521735
iter  90 value 80.582271
iter 100 value 80.552408
final  value 80.552408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.281248 
iter  10 value 94.492365
iter  20 value 94.484318
iter  30 value 93.090637
iter  40 value 86.957330
iter  50 value 84.543206
iter  60 value 84.537290
iter  70 value 84.528973
iter  80 value 84.477686
iter  90 value 84.406343
iter 100 value 84.401183
final  value 84.401183 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.638251 
iter  10 value 93.763767
iter  20 value 84.413054
iter  30 value 83.911211
iter  40 value 83.908549
iter  50 value 83.900979
iter  60 value 83.448270
iter  70 value 80.210705
iter  80 value 78.846260
iter  90 value 78.674039
iter 100 value 78.635000
final  value 78.635000 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.002089 
iter  10 value 87.978704
iter  20 value 86.698449
iter  30 value 86.693433
iter  40 value 86.688943
iter  50 value 85.588126
iter  60 value 85.573549
iter  70 value 84.575944
iter  80 value 84.163809
iter  90 value 82.801715
iter 100 value 80.683862
final  value 80.683862 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.235751 
iter  10 value 117.886875
iter  20 value 114.253438
iter  30 value 108.287666
iter  40 value 106.970679
iter  50 value 104.844603
iter  60 value 102.597553
iter  70 value 100.580141
iter  80 value 100.524567
iter  90 value 100.446186
iter 100 value 100.397597
final  value 100.397597 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 160.434358 
iter  10 value 118.428388
iter  20 value 113.583070
iter  30 value 105.556390
iter  40 value 104.296473
iter  50 value 103.925434
iter  60 value 102.993336
iter  70 value 102.076948
iter  80 value 101.630357
iter  90 value 101.367516
iter 100 value 100.911604
final  value 100.911604 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 141.645915 
iter  10 value 118.160257
iter  20 value 117.907373
iter  30 value 117.642360
iter  40 value 111.611994
iter  50 value 108.282995
iter  60 value 107.389608
iter  70 value 105.862125
iter  80 value 105.525634
iter  90 value 104.127903
iter 100 value 103.384591
final  value 103.384591 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.977746 
iter  10 value 111.853392
iter  20 value 106.809808
iter  30 value 105.914627
iter  40 value 105.188170
iter  50 value 104.971914
iter  60 value 104.847925
iter  70 value 104.830471
iter  80 value 104.769155
iter  90 value 103.829087
iter 100 value 102.356882
final  value 102.356882 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 134.603159 
iter  10 value 117.950108
iter  20 value 113.236773
iter  30 value 110.353534
iter  40 value 107.082115
iter  50 value 106.757357
iter  60 value 106.418208
iter  70 value 105.536144
iter  80 value 105.103659
iter  90 value 104.352943
iter 100 value 102.900431
final  value 102.900431 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Feb 27 20:38:18 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 
 20.555   0.484  69.481