##############################################################################
##############################################################################
###
### 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_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-03-02 r87868)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.13.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       18.030  0.757  18.854
FSmethod      18.014  0.710  18.975
corr_plot     17.550  0.742  18.566
pred_ensembel  5.550  0.096   5.055
enrichfindP    0.163  0.026   7.597
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.13.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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 102.067636 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.750781 
final  value 94.052435 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.086361 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.170934 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.192650 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.562818 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.468155 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.817259 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.009442 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.178907 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.530171 
iter  10 value 93.892780
final  value 93.890562 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.089788 
final  value 94.484208 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.083625 
iter  10 value 83.716147
iter  20 value 83.331537
final  value 83.331152 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.951734 
iter  10 value 93.640746
iter  20 value 93.530074
final  value 93.530001 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.675913 
iter  10 value 94.434933
final  value 94.428837 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.755653 
iter  10 value 94.063650
iter  20 value 80.737123
iter  30 value 79.966128
iter  40 value 79.852826
iter  50 value 79.124923
iter  60 value 79.040609
iter  70 value 78.859651
iter  80 value 78.735018
iter  90 value 78.143619
iter 100 value 78.122725
final  value 78.122725 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.772843 
iter  10 value 94.192449
iter  20 value 91.124249
iter  30 value 90.960440
iter  40 value 90.953101
iter  50 value 90.890098
iter  60 value 80.458645
iter  70 value 79.639375
iter  80 value 79.355282
iter  90 value 78.757107
iter 100 value 78.142493
final  value 78.142493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.243305 
iter  10 value 94.139969
iter  20 value 82.557890
iter  30 value 80.839617
iter  40 value 80.798481
iter  50 value 80.728066
iter  60 value 80.710528
iter  70 value 80.698475
final  value 80.698204 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.979557 
iter  10 value 94.486666
iter  20 value 94.111478
iter  30 value 94.045034
iter  40 value 88.263128
iter  50 value 83.520277
iter  60 value 83.060216
iter  70 value 82.427500
iter  80 value 82.158676
iter  90 value 81.143370
iter 100 value 80.592347
final  value 80.592347 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.489756 
iter  10 value 94.444995
iter  20 value 85.362652
iter  30 value 81.207838
iter  40 value 80.391932
iter  50 value 80.298302
iter  60 value 80.247050
iter  70 value 80.214500
iter  80 value 80.209941
iter  80 value 80.209940
iter  80 value 80.209940
final  value 80.209940 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.482675 
iter  10 value 94.486169
iter  20 value 81.921668
iter  30 value 80.617832
iter  40 value 80.397751
iter  50 value 80.095445
iter  60 value 79.465658
iter  70 value 78.227446
iter  80 value 78.167171
iter  90 value 78.148215
iter 100 value 78.114865
final  value 78.114865 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.714153 
iter  10 value 95.169384
iter  20 value 94.237684
iter  30 value 94.118407
iter  40 value 93.989496
iter  50 value 88.305416
iter  60 value 83.544239
iter  70 value 79.377984
iter  80 value 78.086790
iter  90 value 77.300903
iter 100 value 77.160418
final  value 77.160418 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.201134 
iter  10 value 92.174159
iter  20 value 81.382071
iter  30 value 80.425149
iter  40 value 80.338668
iter  50 value 80.016987
iter  60 value 79.039913
iter  70 value 77.838315
iter  80 value 77.749016
iter  90 value 77.613225
iter 100 value 77.471394
final  value 77.471394 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.767293 
iter  10 value 94.555505
iter  20 value 94.333131
iter  30 value 93.859744
iter  40 value 89.454774
iter  50 value 86.434219
iter  60 value 83.534191
iter  70 value 81.339214
iter  80 value 80.643398
iter  90 value 79.221950
iter 100 value 78.483895
final  value 78.483895 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.806905 
iter  10 value 94.891514
iter  20 value 91.258673
iter  30 value 90.679633
iter  40 value 89.921231
iter  50 value 84.950044
iter  60 value 82.368766
iter  70 value 81.190093
iter  80 value 80.639745
iter  90 value 80.361423
iter 100 value 79.459055
final  value 79.459055 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.214725 
iter  10 value 94.980944
iter  20 value 83.110374
iter  30 value 82.141821
iter  40 value 80.853779
iter  50 value 79.124522
iter  60 value 78.765945
iter  70 value 78.132093
iter  80 value 76.676357
iter  90 value 76.321258
iter 100 value 75.826511
final  value 75.826511 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.991389 
iter  10 value 95.278407
iter  20 value 89.045349
iter  30 value 81.289547
iter  40 value 78.073805
iter  50 value 77.109306
iter  60 value 77.018606
iter  70 value 76.848218
iter  80 value 76.573289
iter  90 value 76.348435
iter 100 value 75.914396
final  value 75.914396 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.499142 
iter  10 value 95.155713
iter  20 value 93.055466
iter  30 value 89.402315
iter  40 value 83.844671
iter  50 value 81.115121
iter  60 value 79.125048
iter  70 value 78.525696
iter  80 value 78.138570
iter  90 value 77.899641
iter 100 value 77.584539
final  value 77.584539 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.612914 
iter  10 value 92.845517
iter  20 value 84.233981
iter  30 value 82.455352
iter  40 value 79.327810
iter  50 value 78.563113
iter  60 value 77.239924
iter  70 value 76.073778
iter  80 value 75.951914
iter  90 value 75.859928
iter 100 value 75.716036
final  value 75.716036 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.270811 
iter  10 value 94.077869
iter  20 value 84.770201
iter  30 value 81.116740
iter  40 value 80.381586
iter  50 value 80.161524
iter  60 value 79.750470
iter  70 value 78.818932
iter  80 value 77.437601
iter  90 value 76.359001
iter 100 value 76.091668
final  value 76.091668 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.626194 
iter  10 value 94.485811
iter  20 value 94.484149
iter  30 value 81.745565
iter  40 value 80.806756
iter  40 value 80.806756
iter  40 value 80.806756
final  value 80.806756 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.913700 
final  value 94.485757 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.994274 
final  value 94.485958 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.347313 
final  value 94.485703 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.067607 
iter  10 value 94.485749
final  value 94.485164 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.657000 
iter  10 value 94.489274
iter  20 value 94.484364
iter  30 value 90.207751
iter  40 value 83.195876
iter  50 value 83.188742
iter  60 value 79.241018
iter  70 value 77.511769
iter  80 value 77.469934
iter  90 value 77.467311
iter 100 value 77.465750
final  value 77.465750 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.458468 
iter  10 value 94.485564
iter  20 value 94.289091
iter  30 value 93.987335
iter  40 value 90.027278
iter  50 value 89.991715
iter  60 value 89.989507
iter  70 value 89.985209
final  value 89.984647 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.713564 
iter  10 value 94.436023
iter  20 value 94.429125
iter  30 value 83.739883
iter  40 value 77.239081
iter  50 value 76.575809
iter  60 value 76.170825
iter  70 value 76.147539
iter  80 value 76.146274
iter  90 value 76.145354
iter 100 value 76.144979
final  value 76.144979 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.233097 
iter  10 value 94.359319
iter  20 value 94.336273
iter  30 value 84.602438
iter  40 value 81.950893
iter  50 value 81.769852
iter  60 value 81.765585
iter  70 value 81.612267
final  value 81.612189 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.961781 
iter  10 value 94.358837
iter  20 value 94.085727
iter  30 value 94.039267
iter  40 value 92.343798
iter  50 value 91.235535
iter  60 value 91.101985
iter  70 value 91.061585
iter  80 value 88.805136
iter  90 value 80.647288
final  value 80.591490 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.080821 
iter  10 value 94.437202
iter  20 value 86.208098
iter  30 value 81.820367
iter  40 value 81.523419
iter  50 value 79.070026
iter  60 value 75.729358
iter  70 value 75.188269
iter  80 value 75.083879
iter  90 value 75.080796
iter 100 value 75.080540
final  value 75.080540 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.762057 
iter  10 value 94.363385
iter  20 value 94.361927
iter  30 value 94.360449
iter  40 value 89.481828
iter  50 value 83.196845
iter  60 value 83.194815
iter  70 value 83.186765
iter  80 value 83.183264
iter  90 value 81.372095
iter 100 value 80.407638
final  value 80.407638 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.184605 
iter  10 value 92.302817
iter  20 value 91.499788
iter  30 value 91.497704
iter  40 value 89.371204
iter  50 value 89.316590
iter  60 value 89.236383
final  value 89.223543 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.749442 
iter  10 value 94.492431
iter  20 value 91.516554
iter  30 value 91.226261
final  value 91.224006 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.940065 
iter  10 value 94.362683
iter  20 value 94.162667
iter  30 value 93.974335
iter  40 value 80.252980
iter  50 value 79.574151
iter  60 value 78.709953
iter  70 value 77.908472
iter  80 value 77.778069
final  value 77.777959 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.472835 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.605285 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.433017 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.638455 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.515989 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.033432 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.935040 
iter  10 value 94.387545
final  value 94.387433 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.473475 
final  value 94.385583 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.199566 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.769311 
iter  10 value 94.112904
iter  10 value 94.112903
iter  10 value 94.112903
final  value 94.112903 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.547573 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.018326 
iter  10 value 89.890027
iter  20 value 88.913683
final  value 88.913541 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.277396 
iter  10 value 94.112904
iter  10 value 94.112903
iter  10 value 94.112903
final  value 94.112903 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.487883 
iter  10 value 93.008326
iter  20 value 92.971859
final  value 92.971355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.050937 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.231127 
iter  10 value 94.449722
iter  20 value 87.579500
iter  30 value 87.028529
iter  40 value 85.781584
iter  50 value 85.025517
iter  60 value 84.714133
iter  70 value 84.591720
iter  70 value 84.591719
iter  70 value 84.591719
final  value 84.591719 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.526596 
iter  10 value 92.384233
iter  20 value 85.590595
iter  30 value 84.982834
iter  40 value 84.878008
iter  50 value 84.759854
iter  60 value 84.395471
iter  70 value 84.207725
final  value 84.201781 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.581959 
iter  10 value 94.479567
iter  20 value 94.237933
iter  30 value 94.078593
iter  40 value 94.045454
iter  50 value 94.040873
iter  60 value 93.437819
iter  70 value 91.545328
iter  80 value 89.563532
iter  90 value 86.937469
iter 100 value 84.993119
final  value 84.993119 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.910929 
iter  10 value 94.444626
iter  20 value 91.545751
iter  30 value 88.926621
iter  40 value 88.781099
iter  50 value 85.671292
iter  60 value 84.584642
iter  70 value 84.407605
iter  80 value 84.312491
iter  90 value 83.845197
iter 100 value 83.616293
final  value 83.616293 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.982210 
iter  10 value 94.489150
iter  20 value 90.058554
iter  30 value 87.532085
iter  40 value 82.979559
iter  50 value 82.102238
iter  60 value 82.011385
iter  70 value 81.982413
iter  80 value 81.897287
iter  90 value 81.853148
final  value 81.852176 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.933355 
iter  10 value 94.500750
iter  20 value 93.049562
iter  30 value 91.871233
iter  40 value 90.673139
iter  50 value 90.584907
iter  60 value 90.373664
iter  70 value 89.983854
iter  80 value 87.318245
iter  90 value 83.226667
iter 100 value 82.380640
final  value 82.380640 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.515464 
iter  10 value 94.385217
iter  20 value 88.035920
iter  30 value 87.119576
iter  40 value 85.126940
iter  50 value 84.622356
iter  60 value 83.265896
iter  70 value 82.729869
iter  80 value 82.409396
iter  90 value 82.381125
iter 100 value 82.258178
final  value 82.258178 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.458896 
iter  10 value 94.433743
iter  20 value 87.587010
iter  30 value 87.072334
iter  40 value 86.763832
iter  50 value 84.886712
iter  60 value 84.281719
iter  70 value 84.265700
iter  80 value 84.208542
iter  90 value 83.171460
iter 100 value 82.137150
final  value 82.137150 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.396714 
iter  10 value 94.472810
iter  20 value 94.200671
iter  30 value 93.677114
iter  40 value 88.422163
iter  50 value 82.798638
iter  60 value 82.218089
iter  70 value 81.621048
iter  80 value 81.336838
iter  90 value 81.016796
iter 100 value 80.802252
final  value 80.802252 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.331851 
iter  10 value 95.146966
iter  20 value 87.988818
iter  30 value 85.377567
iter  40 value 82.650634
iter  50 value 82.022152
iter  60 value 81.612959
iter  70 value 81.402541
iter  80 value 81.392963
iter  90 value 81.364818
iter 100 value 81.096157
final  value 81.096157 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.510776 
iter  10 value 94.505058
iter  20 value 89.454369
iter  30 value 86.516649
iter  40 value 85.976829
iter  50 value 85.809960
iter  60 value 83.150209
iter  70 value 82.616641
iter  80 value 82.116337
iter  90 value 81.793571
iter 100 value 81.644654
final  value 81.644654 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.054999 
iter  10 value 94.222890
iter  20 value 87.535803
iter  30 value 85.488681
iter  40 value 85.306506
iter  50 value 84.386533
iter  60 value 82.511929
iter  70 value 81.732470
iter  80 value 81.247486
iter  90 value 80.933879
iter 100 value 80.697045
final  value 80.697045 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.789449 
iter  10 value 92.765586
iter  20 value 86.392662
iter  30 value 84.238078
iter  40 value 84.014968
iter  50 value 82.963838
iter  60 value 82.217112
iter  70 value 81.639494
iter  80 value 81.371197
iter  90 value 81.250718
iter 100 value 81.162976
final  value 81.162976 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.897895 
iter  10 value 93.456483
iter  20 value 88.132600
iter  30 value 85.118193
iter  40 value 82.449529
iter  50 value 81.599595
iter  60 value 81.278252
iter  70 value 80.792532
iter  80 value 80.599533
iter  90 value 80.337865
iter 100 value 80.065458
final  value 80.065458 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.019216 
iter  10 value 94.340887
iter  20 value 86.752705
iter  30 value 84.649689
iter  40 value 83.115837
iter  50 value 81.596887
iter  60 value 81.007828
iter  70 value 80.847396
iter  80 value 80.753912
iter  90 value 80.645756
iter 100 value 80.599977
final  value 80.599977 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.375710 
final  value 94.485837 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.426231 
final  value 94.485727 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.588789 
final  value 94.485828 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.202777 
final  value 94.485782 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.264841 
final  value 94.325346 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.697351 
iter  10 value 94.489376
iter  20 value 94.357842
iter  30 value 92.028807
iter  40 value 91.482062
iter  50 value 87.848577
iter  60 value 86.714950
iter  70 value 86.097116
iter  80 value 86.067234
iter  90 value 86.066786
iter 100 value 86.063166
final  value 86.063166 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.285742 
iter  10 value 94.489371
iter  20 value 94.484662
iter  30 value 94.406759
iter  40 value 91.404522
iter  50 value 86.124138
iter  60 value 85.783352
iter  70 value 84.811093
iter  80 value 84.772490
final  value 84.772284 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.407646 
iter  10 value 94.488929
iter  20 value 94.410561
iter  30 value 94.064226
iter  30 value 94.064226
iter  30 value 94.064226
final  value 94.064226 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.132446 
iter  10 value 94.476399
iter  20 value 91.207602
iter  30 value 91.205952
iter  40 value 88.983883
iter  50 value 88.411207
iter  60 value 88.402672
iter  70 value 88.402085
iter  80 value 88.400981
final  value 88.400887 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.376380 
iter  10 value 94.144558
iter  20 value 94.116904
iter  30 value 94.111778
iter  40 value 88.879233
iter  50 value 86.864976
iter  60 value 86.467597
iter  70 value 86.152874
final  value 86.151892 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.123727 
iter  10 value 94.491655
iter  20 value 93.312043
iter  30 value 83.803907
iter  40 value 83.219295
final  value 83.219061 
converged
Fitting Repeat 2 

# weights:  507
initial  value 140.477627 
iter  10 value 94.492911
iter  20 value 94.483024
iter  30 value 94.432183
iter  40 value 94.428327
iter  50 value 94.354643
final  value 94.354626 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.531476 
iter  10 value 94.217799
iter  20 value 94.137530
iter  30 value 94.133197
final  value 94.133125 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.315054 
iter  10 value 94.121265
iter  20 value 94.114324
iter  30 value 87.519263
iter  40 value 86.764110
iter  50 value 86.240948
final  value 86.225899 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.246347 
iter  10 value 94.478427
final  value 94.478347 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.703276 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.600626 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.501325 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.191922 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.336828 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.660223 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.553200 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.452309 
iter  10 value 94.008285
iter  20 value 88.629650
iter  30 value 87.121567
iter  40 value 86.876117
final  value 86.874733 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.733292 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.523706 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.095571 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.473940 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.058805 
iter  10 value 93.579161
iter  20 value 93.376233
iter  30 value 93.224404
iter  40 value 93.222089
final  value 93.222083 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.858718 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.946944 
iter  10 value 94.052832
iter  20 value 94.033425
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.701157 
iter  10 value 94.045399
iter  20 value 89.356155
iter  30 value 86.010446
iter  40 value 85.692072
iter  50 value 85.367468
iter  60 value 83.514949
iter  70 value 82.747845
iter  80 value 82.629809
iter  90 value 82.593751
final  value 82.592899 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.036827 
iter  10 value 94.067299
iter  20 value 92.070278
iter  30 value 91.434861
iter  40 value 91.419827
iter  50 value 91.415927
iter  60 value 91.414426
final  value 91.414343 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.701642 
iter  10 value 93.966311
iter  20 value 92.369679
iter  30 value 89.979172
iter  40 value 85.857945
iter  50 value 85.338800
iter  60 value 85.260261
iter  70 value 85.246844
final  value 85.246806 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.857789 
iter  10 value 91.742462
iter  20 value 87.888062
iter  30 value 84.055816
iter  40 value 83.713466
iter  50 value 83.052130
iter  60 value 82.811118
iter  70 value 82.639482
iter  80 value 82.393587
iter  90 value 82.373602
final  value 82.364284 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.146259 
iter  10 value 93.885810
iter  20 value 85.689409
iter  30 value 84.153018
iter  40 value 83.350513
iter  50 value 82.922470
iter  60 value 82.673576
iter  70 value 82.635408
iter  80 value 82.599461
final  value 82.592899 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.320479 
iter  10 value 94.057899
iter  20 value 92.873606
iter  30 value 85.128499
iter  40 value 84.224917
iter  50 value 83.625219
iter  60 value 82.285388
iter  70 value 82.100454
iter  80 value 81.612798
iter  90 value 81.569206
iter 100 value 81.522030
final  value 81.522030 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.632899 
iter  10 value 93.899106
iter  20 value 92.461719
iter  30 value 91.817304
iter  40 value 91.609209
iter  50 value 90.280950
iter  60 value 88.360025
iter  70 value 86.273738
iter  80 value 85.663978
iter  90 value 85.236364
iter 100 value 84.734250
final  value 84.734250 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.284238 
iter  10 value 93.443941
iter  20 value 86.405586
iter  30 value 85.007960
iter  40 value 84.627852
iter  50 value 84.495029
iter  60 value 84.451260
iter  70 value 84.374024
iter  80 value 83.527161
iter  90 value 82.371820
iter 100 value 82.185482
final  value 82.185482 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.225722 
iter  10 value 94.061493
iter  20 value 90.069908
iter  30 value 88.334071
iter  40 value 86.483131
iter  50 value 84.603471
iter  60 value 83.575905
iter  70 value 83.033927
iter  80 value 82.531663
iter  90 value 82.358287
iter 100 value 82.332965
final  value 82.332965 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.344346 
iter  10 value 94.057977
iter  20 value 94.036558
iter  30 value 88.807984
iter  40 value 87.322678
iter  50 value 85.183778
iter  60 value 85.092843
iter  70 value 84.923637
iter  80 value 84.897587
iter  90 value 84.829808
iter 100 value 83.974173
final  value 83.974173 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.019790 
iter  10 value 94.899007
iter  20 value 88.549390
iter  30 value 86.240303
iter  40 value 85.278774
iter  50 value 83.471546
iter  60 value 82.843139
iter  70 value 81.769273
iter  80 value 81.591182
iter  90 value 81.399022
iter 100 value 81.309144
final  value 81.309144 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.196727 
iter  10 value 91.096056
iter  20 value 86.313875
iter  30 value 85.338392
iter  40 value 84.623255
iter  50 value 83.269324
iter  60 value 81.992075
iter  70 value 81.556706
iter  80 value 81.448904
iter  90 value 81.184002
iter 100 value 81.069133
final  value 81.069133 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.546393 
iter  10 value 94.356638
iter  20 value 88.803527
iter  30 value 87.455314
iter  40 value 85.677432
iter  50 value 83.634781
iter  60 value 83.250015
iter  70 value 82.721920
iter  80 value 82.111741
iter  90 value 81.839243
iter 100 value 81.513111
final  value 81.513111 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.889308 
iter  10 value 94.295478
iter  20 value 93.654476
iter  30 value 89.505832
iter  40 value 86.226732
iter  50 value 85.571771
iter  60 value 84.308601
iter  70 value 83.705023
iter  80 value 81.749375
iter  90 value 81.299698
iter 100 value 81.076280
final  value 81.076280 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.761653 
iter  10 value 94.628642
iter  20 value 93.641234
iter  30 value 92.481363
iter  40 value 90.732626
iter  50 value 90.036798
iter  60 value 89.633956
iter  70 value 87.197451
iter  80 value 85.661090
iter  90 value 82.673248
iter 100 value 82.297700
final  value 82.297700 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.597595 
final  value 94.054749 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.271880 
final  value 94.054663 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.333865 
iter  10 value 93.837888
iter  20 value 93.836623
iter  30 value 91.432716
iter  40 value 91.212766
iter  50 value 88.467855
iter  60 value 88.467551
iter  70 value 88.466365
iter  80 value 88.465679
iter  90 value 88.456991
iter 100 value 88.367391
final  value 88.367391 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.521161 
iter  10 value 93.837662
iter  20 value 93.837394
final  value 93.837385 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.767281 
final  value 94.054736 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.247567 
iter  10 value 93.840390
iter  20 value 93.831013
final  value 93.830796 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.429483 
iter  10 value 94.058269
iter  20 value 94.052973
iter  30 value 92.318859
iter  40 value 90.724441
iter  50 value 87.992902
iter  60 value 83.237848
iter  70 value 81.699314
iter  80 value 81.314285
iter  90 value 81.146831
iter 100 value 81.140314
final  value 81.140314 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.618686 
iter  10 value 93.840976
iter  20 value 93.837813
final  value 93.836921 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.084983 
iter  10 value 94.057257
iter  20 value 94.037081
iter  30 value 93.664413
iter  40 value 85.898413
iter  50 value 85.442232
iter  60 value 85.441203
final  value 85.355821 
converged
Fitting Repeat 5 

# weights:  305
initial  value 125.590685 
iter  10 value 94.057536
iter  20 value 94.024814
iter  30 value 86.495777
iter  40 value 86.319166
iter  50 value 86.216950
iter  60 value 83.163200
iter  70 value 83.020516
iter  80 value 82.992326
iter  90 value 82.946045
iter 100 value 82.655361
final  value 82.655361 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.654608 
iter  10 value 93.877380
iter  20 value 88.426290
iter  30 value 88.078454
iter  40 value 86.651162
iter  50 value 86.214225
iter  60 value 84.276901
iter  70 value 84.254559
iter  80 value 84.217854
iter  90 value 84.173169
final  value 84.160339 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.507812 
iter  10 value 94.040935
iter  20 value 94.035499
iter  30 value 93.837036
final  value 93.758557 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.014210 
iter  10 value 94.059149
iter  20 value 94.054576
iter  30 value 94.044384
iter  40 value 94.029982
iter  40 value 94.029982
iter  40 value 94.029982
final  value 94.029982 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.904888 
iter  10 value 93.325369
iter  20 value 90.722280
iter  30 value 85.663313
iter  40 value 85.278947
iter  50 value 85.268907
iter  60 value 85.266081
iter  60 value 85.266081
final  value 85.266081 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.887909 
iter  10 value 94.061201
iter  20 value 94.004949
iter  30 value 93.769967
iter  40 value 88.432753
iter  50 value 88.038840
iter  60 value 84.810412
iter  70 value 81.965400
iter  80 value 81.798308
iter  90 value 81.752979
iter 100 value 81.708778
final  value 81.708778 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.573411 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.886014 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.632400 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.724005 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.445095 
final  value 93.912644 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.681922 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.207165 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.026053 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.056634 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.178758 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.627528 
final  value 93.604520 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.913639 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.898216 
iter  10 value 87.814205
final  value 86.618182 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.150901 
iter  10 value 94.032968
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.966933 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.099831 
iter  10 value 95.055863
iter  20 value 94.126913
iter  30 value 94.056837
iter  40 value 93.629764
iter  50 value 93.418423
iter  60 value 89.423603
iter  70 value 86.640415
iter  80 value 85.477666
iter  90 value 84.556806
iter 100 value 82.751603
final  value 82.751603 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 112.353090 
iter  10 value 93.167960
iter  20 value 86.168054
iter  30 value 84.764919
iter  40 value 83.886002
iter  50 value 83.700115
iter  60 value 83.468013
iter  70 value 83.388415
final  value 83.388294 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.250908 
iter  10 value 93.604656
iter  20 value 86.355173
iter  30 value 84.471332
iter  40 value 83.271628
iter  50 value 82.718919
iter  60 value 81.815399
iter  70 value 81.675058
final  value 81.675014 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.419816 
iter  10 value 93.989509
iter  20 value 90.660138
iter  30 value 88.017570
iter  40 value 84.587719
iter  50 value 83.861453
iter  60 value 83.571242
iter  70 value 83.399114
iter  80 value 83.388428
final  value 83.388294 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.447111 
iter  10 value 94.045989
iter  20 value 91.127611
iter  30 value 87.352847
iter  40 value 86.618335
iter  50 value 83.485718
iter  60 value 83.436040
iter  70 value 83.394351
iter  80 value 83.388848
final  value 83.388294 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.209944 
iter  10 value 94.062162
iter  20 value 90.954188
iter  30 value 89.112269
iter  40 value 88.116028
iter  50 value 86.040847
iter  60 value 81.716754
iter  70 value 81.235595
iter  80 value 80.765642
iter  90 value 80.550666
iter 100 value 80.440110
final  value 80.440110 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.208997 
iter  10 value 94.139705
iter  20 value 89.289844
iter  30 value 87.294936
iter  40 value 86.703694
iter  50 value 84.159255
iter  60 value 83.244798
iter  70 value 82.643119
iter  80 value 81.701905
iter  90 value 81.386506
iter 100 value 80.990589
final  value 80.990589 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.749816 
iter  10 value 94.049415
iter  20 value 86.356853
iter  30 value 84.845365
iter  40 value 84.656855
iter  50 value 83.729939
iter  60 value 83.276348
iter  70 value 83.197120
iter  80 value 82.682446
iter  90 value 81.487543
iter 100 value 80.970744
final  value 80.970744 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.937755 
iter  10 value 94.027765
iter  20 value 93.574749
iter  30 value 92.837219
iter  40 value 88.674000
iter  50 value 85.020772
iter  60 value 84.180879
iter  70 value 82.536796
iter  80 value 81.698496
iter  90 value 80.941612
iter 100 value 80.591264
final  value 80.591264 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.914397 
iter  10 value 90.832698
iter  20 value 85.856859
iter  30 value 83.266031
iter  40 value 81.928890
iter  50 value 81.111668
iter  60 value 81.008547
iter  70 value 80.912629
iter  80 value 80.908538
iter  90 value 80.906738
iter 100 value 80.896301
final  value 80.896301 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.569223 
iter  10 value 94.670907
iter  20 value 88.641941
iter  30 value 85.122627
iter  40 value 83.941107
iter  50 value 81.851194
iter  60 value 81.516457
iter  70 value 81.115558
iter  80 value 80.874713
iter  90 value 80.727235
iter 100 value 80.701022
final  value 80.701022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.287903 
iter  10 value 92.706633
iter  20 value 86.290965
iter  30 value 85.288021
iter  40 value 84.855721
iter  50 value 84.124371
iter  60 value 83.582012
iter  70 value 83.382629
iter  80 value 83.338474
iter  90 value 83.215524
iter 100 value 83.077432
final  value 83.077432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.636209 
iter  10 value 89.631594
iter  20 value 84.213449
iter  30 value 83.005578
iter  40 value 82.486503
iter  50 value 81.232522
iter  60 value 80.711835
iter  70 value 80.562125
iter  80 value 80.318357
iter  90 value 80.242118
iter 100 value 80.154651
final  value 80.154651 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.414173 
iter  10 value 95.179002
iter  20 value 90.499262
iter  30 value 86.478233
iter  40 value 86.232108
iter  50 value 84.877735
iter  60 value 82.963966
iter  70 value 82.583521
iter  80 value 81.994255
iter  90 value 81.912882
iter 100 value 81.443984
final  value 81.443984 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.664958 
iter  10 value 94.047409
iter  20 value 89.554865
iter  30 value 86.181490
iter  40 value 84.183976
iter  50 value 82.916461
iter  60 value 82.291183
iter  70 value 82.172186
iter  80 value 81.906264
iter  90 value 81.491130
iter 100 value 80.729624
final  value 80.729624 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.355881 
final  value 94.054567 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.737264 
iter  10 value 93.322445
iter  20 value 92.231853
iter  30 value 91.719135
iter  40 value 91.698934
iter  50 value 91.698552
iter  60 value 90.387179
iter  70 value 90.368116
iter  80 value 90.367932
final  value 90.367900 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.387672 
iter  10 value 91.016424
iter  20 value 85.883532
final  value 85.312601 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.674608 
final  value 94.054795 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.059885 
final  value 94.054444 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.556355 
iter  10 value 93.514087
iter  20 value 93.507137
iter  30 value 92.791363
iter  40 value 91.512997
iter  50 value 91.507555
iter  60 value 90.968951
iter  70 value 90.964140
iter  80 value 90.963420
iter  90 value 90.700478
final  value 90.677042 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.090045 
iter  10 value 94.057862
iter  20 value 94.052923
iter  30 value 90.221334
iter  40 value 85.914352
iter  50 value 85.905945
iter  60 value 85.802502
iter  70 value 84.481553
iter  80 value 84.068591
iter  90 value 83.976456
iter 100 value 83.140148
final  value 83.140148 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.242785 
iter  10 value 94.057757
iter  20 value 87.433577
iter  30 value 84.575149
iter  40 value 84.541744
iter  50 value 84.539547
iter  60 value 84.444236
iter  70 value 83.582104
iter  80 value 81.534667
iter  90 value 81.147875
iter 100 value 80.724505
final  value 80.724505 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.128259 
iter  10 value 94.057468
iter  20 value 94.004776
iter  30 value 93.482186
iter  40 value 93.481681
final  value 93.481677 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.731625 
iter  10 value 94.085041
iter  20 value 93.554106
iter  30 value 93.510089
iter  40 value 93.496391
iter  50 value 93.418078
iter  60 value 93.417614
final  value 93.417605 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.743950 
iter  10 value 91.178092
iter  20 value 90.432596
iter  30 value 90.428202
iter  40 value 90.391941
iter  50 value 89.683088
iter  60 value 89.551512
iter  70 value 89.427154
iter  80 value 89.403062
iter  90 value 89.283263
iter 100 value 89.155529
final  value 89.155529 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.021150 
iter  10 value 94.053464
iter  20 value 93.987171
iter  30 value 92.475695
iter  40 value 90.584903
iter  50 value 90.578683
final  value 90.578674 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.099598 
iter  10 value 94.041101
iter  20 value 94.033287
iter  30 value 91.947936
iter  40 value 89.054082
iter  40 value 89.054081
iter  40 value 89.054081
final  value 89.054081 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.825273 
iter  10 value 93.894355
iter  20 value 93.832223
iter  30 value 93.149912
iter  40 value 91.470797
iter  50 value 91.160198
iter  60 value 91.154973
final  value 91.154771 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.284588 
iter  10 value 94.059812
iter  20 value 93.934094
iter  30 value 84.309512
iter  40 value 83.922687
iter  50 value 82.066774
iter  60 value 80.648145
iter  70 value 79.584611
iter  80 value 79.366651
iter  90 value 79.346671
iter 100 value 79.341949
final  value 79.341949 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.551341 
iter  10 value 87.356972
iter  20 value 85.758906
iter  30 value 85.603212
iter  40 value 85.603123
final  value 85.603101 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.621615 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.377268 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.030387 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.933136 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.979781 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.818324 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.691974 
final  value 94.484137 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.977668 
iter  10 value 94.466581
iter  10 value 94.466580
iter  10 value 94.466580
final  value 94.466580 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.302440 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.169616 
iter  10 value 94.378861
iter  20 value 93.128499
final  value 93.099987 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.099591 
final  value 94.484138 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.444815 
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.713407 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.294551 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.279513 
iter  10 value 94.489565
iter  20 value 94.487163
iter  30 value 93.853393
iter  40 value 86.888717
iter  50 value 85.908978
iter  60 value 85.716134
iter  70 value 85.636776
iter  80 value 85.510546
iter  90 value 85.475530
iter 100 value 85.462893
final  value 85.462893 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.523408 
iter  10 value 94.488597
iter  20 value 94.485030
iter  30 value 94.141642
iter  40 value 93.096429
iter  50 value 91.529677
iter  60 value 88.725488
iter  70 value 88.001694
iter  80 value 87.704152
iter  90 value 87.499582
iter 100 value 87.164904
final  value 87.164904 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.663980 
iter  10 value 94.488516
iter  20 value 94.473363
iter  30 value 93.388109
iter  40 value 90.338405
iter  50 value 88.902833
iter  60 value 88.341788
iter  70 value 87.263519
iter  80 value 86.796176
iter  90 value 85.933571
iter 100 value 85.523975
final  value 85.523975 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.265938 
iter  10 value 94.699558
iter  20 value 94.484875
iter  30 value 89.944039
iter  40 value 87.447412
iter  50 value 87.300716
iter  60 value 86.966329
iter  70 value 85.965270
iter  80 value 85.845325
iter  90 value 84.937426
iter 100 value 84.337167
final  value 84.337167 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 119.465510 
iter  10 value 94.414228
iter  20 value 89.336569
iter  30 value 87.893216
iter  40 value 86.652206
iter  50 value 85.092511
iter  60 value 84.634049
iter  70 value 84.504345
iter  80 value 84.420397
iter  90 value 84.279317
iter 100 value 84.097416
final  value 84.097416 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.953548 
iter  10 value 94.459170
iter  20 value 91.987966
iter  30 value 88.503170
iter  40 value 87.668891
iter  50 value 87.197840
iter  60 value 84.760803
iter  70 value 84.382583
iter  80 value 84.247857
iter  90 value 84.052466
iter 100 value 83.516081
final  value 83.516081 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.433948 
iter  10 value 93.482235
iter  20 value 87.524058
iter  30 value 86.918203
iter  40 value 86.737223
iter  50 value 85.977031
iter  60 value 85.827962
iter  70 value 85.683592
iter  80 value 85.590386
iter  90 value 85.578974
iter 100 value 85.559711
final  value 85.559711 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.820885 
iter  10 value 93.662732
iter  20 value 93.305024
iter  30 value 88.719257
iter  40 value 87.388033
iter  50 value 86.466365
iter  60 value 84.247385
iter  70 value 83.362339
iter  80 value 83.143923
iter  90 value 83.105121
iter 100 value 83.048252
final  value 83.048252 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.060452 
iter  10 value 94.421849
iter  20 value 90.684617
iter  30 value 88.486983
iter  40 value 87.734767
iter  50 value 85.786708
iter  60 value 84.865028
iter  70 value 84.395384
iter  80 value 84.334675
iter  90 value 83.917211
iter 100 value 83.287229
final  value 83.287229 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 137.036623 
iter  10 value 94.531730
iter  20 value 89.847822
iter  30 value 85.773920
iter  40 value 84.237576
iter  50 value 83.415058
iter  60 value 83.097459
iter  70 value 83.074169
iter  80 value 83.001933
iter  90 value 82.744348
iter 100 value 82.575932
final  value 82.575932 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.997698 
iter  10 value 93.643695
iter  20 value 88.347766
iter  30 value 87.993622
iter  40 value 87.659633
iter  50 value 87.279483
iter  60 value 87.229665
iter  70 value 87.185988
iter  80 value 86.927263
iter  90 value 85.078023
iter 100 value 83.700772
final  value 83.700772 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.930949 
iter  10 value 93.924208
iter  20 value 91.677035
iter  30 value 87.834957
iter  40 value 86.459044
iter  50 value 85.199581
iter  60 value 84.548236
iter  70 value 83.940989
iter  80 value 83.789435
iter  90 value 83.374603
iter 100 value 83.025906
final  value 83.025906 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.775723 
iter  10 value 98.795835
iter  20 value 90.237950
iter  30 value 87.443805
iter  40 value 84.927055
iter  50 value 84.683667
iter  60 value 84.605316
iter  70 value 84.311217
iter  80 value 83.717760
iter  90 value 83.370713
iter 100 value 83.160137
final  value 83.160137 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 145.825453 
iter  10 value 94.742673
iter  20 value 88.736450
iter  30 value 88.357196
iter  40 value 87.916483
iter  50 value 86.447598
iter  60 value 86.073210
iter  70 value 85.872488
iter  80 value 84.484281
iter  90 value 84.196442
iter 100 value 83.483927
final  value 83.483927 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.529466 
iter  10 value 94.412555
iter  20 value 92.327886
iter  30 value 87.939916
iter  40 value 85.399632
iter  50 value 84.181051
iter  60 value 83.180491
iter  70 value 82.989377
iter  80 value 82.737657
iter  90 value 82.567274
iter 100 value 82.505769
final  value 82.505769 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.996455 
iter  10 value 94.450792
iter  20 value 94.427270
iter  20 value 94.427270
iter  20 value 94.427270
final  value 94.427270 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.121728 
final  value 94.485926 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.963065 
final  value 94.486062 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.063825 
final  value 94.485864 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.287919 
final  value 94.485799 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.370264 
iter  10 value 94.488867
iter  20 value 94.419744
iter  30 value 94.051396
iter  40 value 94.046806
iter  50 value 90.035328
iter  60 value 87.296685
iter  70 value 87.289103
iter  80 value 87.288969
iter  90 value 87.187873
iter 100 value 87.187502
final  value 87.187502 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.081061 
iter  10 value 94.490524
iter  20 value 94.485388
iter  30 value 93.772621
iter  40 value 93.152882
iter  50 value 93.152152
iter  60 value 92.567837
iter  70 value 92.567208
iter  80 value 92.549256
iter  90 value 92.220892
iter 100 value 90.226961
final  value 90.226961 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.815105 
iter  10 value 94.488544
iter  20 value 94.479560
iter  30 value 90.080302
iter  40 value 87.685327
iter  50 value 86.276944
iter  60 value 85.422130
iter  70 value 84.695448
final  value 84.695442 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.979342 
iter  10 value 94.473135
iter  20 value 94.471491
iter  30 value 94.466810
iter  40 value 90.626361
iter  50 value 88.941891
iter  60 value 87.187880
final  value 87.187095 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.521882 
iter  10 value 94.457776
iter  20 value 94.440685
final  value 94.429327 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.428465 
iter  10 value 94.491096
iter  20 value 92.682042
iter  30 value 89.889656
iter  40 value 87.425823
iter  50 value 87.416543
iter  60 value 87.416284
iter  70 value 87.137710
iter  80 value 84.454035
iter  90 value 83.908427
final  value 83.907498 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.411247 
final  value 94.475019 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.973913 
iter  10 value 94.389501
iter  20 value 93.253381
iter  30 value 93.218967
iter  40 value 91.294304
iter  50 value 87.106156
iter  60 value 86.911916
iter  70 value 86.895469
iter  80 value 86.571244
iter  90 value 86.469682
iter 100 value 86.220835
final  value 86.220835 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.226831 
iter  10 value 94.492123
iter  20 value 94.437453
iter  30 value 94.424819
final  value 94.424817 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.029169 
iter  10 value 94.121618
iter  20 value 94.054902
iter  30 value 86.373794
iter  40 value 85.625370
iter  50 value 85.577072
iter  60 value 85.519181
iter  70 value 85.514618
iter  80 value 85.506020
iter  90 value 85.505571
iter 100 value 85.478057
final  value 85.478057 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 131.696426 
iter  10 value 117.894693
iter  20 value 117.825507
iter  30 value 116.787691
iter  40 value 111.657989
iter  50 value 111.639412
iter  60 value 111.410704
iter  70 value 111.405813
iter  80 value 111.400575
iter  90 value 108.095549
final  value 108.094269 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.973810 
iter  10 value 106.296862
iter  20 value 105.058428
final  value 105.058098 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.137241 
iter  10 value 117.554222
iter  20 value 117.514699
iter  30 value 115.037597
iter  40 value 106.940712
iter  50 value 106.806919
iter  60 value 106.802866
iter  60 value 106.802866
iter  60 value 106.802866
final  value 106.802866 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.118248 
iter  10 value 117.887743
iter  20 value 117.262212
iter  30 value 115.287766
iter  40 value 115.101801
iter  50 value 115.061237
final  value 115.061138 
converged
Fitting Repeat 5 

# weights:  305
initial  value 125.850261 
iter  10 value 117.893879
iter  20 value 116.523375
iter  30 value 107.259115
iter  40 value 107.043315
iter  50 value 106.806595
iter  50 value 106.806595
iter  50 value 106.806595
final  value 106.806595 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Sun Mar 23 19:45:15 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 16.744   0.414  74.858