##############################################################################
##############################################################################
###
### 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 version 4.6.0 alpha (2026-04-08 r89818)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-04-23 00:15:29 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      17.106  0.175  18.127
var_imp       17.104  0.157  17.413
corr_plot     17.069  0.125  17.242
pred_ensembel  6.261  0.149   5.715
enrichfindP    0.198  0.033  10.650
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


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

R version 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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

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

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

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

# weights:  103
initial  value 97.161039 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.943596 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.113584 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.682325 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.906808 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.230318 
iter  10 value 94.043640
final  value 94.043244 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.855038 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.902465 
final  value 93.991525 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.549632 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.937189 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.574349 
iter  10 value 93.886935
iter  20 value 93.784838
final  value 93.782052 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.036714 
iter  10 value 93.543987
iter  20 value 93.413904
iter  20 value 93.413903
final  value 93.413859 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.742389 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.320647 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.853997 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.521313 
iter  10 value 94.218826
iter  20 value 94.045172
iter  30 value 90.021044
iter  40 value 85.905301
iter  50 value 84.715951
iter  60 value 84.250491
iter  70 value 84.052388
iter  80 value 83.836061
iter  90 value 83.739296
final  value 83.738515 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.406357 
iter  10 value 94.054952
iter  20 value 86.691822
iter  30 value 85.568089
iter  40 value 85.316114
iter  50 value 84.310297
iter  60 value 83.996683
iter  70 value 83.925238
iter  80 value 83.867501
final  value 83.867496 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.441338 
iter  10 value 94.055261
iter  20 value 93.840808
iter  30 value 93.826708
iter  40 value 93.820761
iter  50 value 93.816567
iter  60 value 90.253547
iter  70 value 89.029862
iter  80 value 85.944324
iter  90 value 85.777036
iter 100 value 85.753002
final  value 85.753002 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.393771 
iter  10 value 94.056694
iter  20 value 93.891490
iter  30 value 86.922890
iter  40 value 86.030652
iter  50 value 84.092301
iter  60 value 83.557988
iter  70 value 83.514926
iter  80 value 83.389188
iter  90 value 83.350245
final  value 83.350214 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.604739 
iter  10 value 93.732294
iter  20 value 86.526447
iter  30 value 85.487624
iter  40 value 85.339723
iter  50 value 85.189913
iter  60 value 85.024146
iter  70 value 84.979203
final  value 84.976179 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.309872 
iter  10 value 94.173501
iter  20 value 91.775512
iter  30 value 90.178700
iter  40 value 89.395237
iter  50 value 87.621630
iter  60 value 86.360122
iter  70 value 85.784393
iter  80 value 84.948946
iter  90 value 83.118707
iter 100 value 82.750684
final  value 82.750684 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.541140 
iter  10 value 94.050753
iter  20 value 93.608483
iter  30 value 86.550516
iter  40 value 83.770575
iter  50 value 83.274286
iter  60 value 82.789512
iter  70 value 81.921953
iter  80 value 81.207619
iter  90 value 80.885529
iter 100 value 80.874503
final  value 80.874503 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.177565 
iter  10 value 94.118044
iter  20 value 94.026295
iter  30 value 90.728680
iter  40 value 86.289607
iter  50 value 84.878018
iter  60 value 84.122904
iter  70 value 83.191560
iter  80 value 82.313752
iter  90 value 81.821627
iter 100 value 81.128832
final  value 81.128832 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.698083 
iter  10 value 93.878459
iter  20 value 90.197743
iter  30 value 86.699773
iter  40 value 84.705600
iter  50 value 83.331198
iter  60 value 82.663645
iter  70 value 82.591455
iter  80 value 82.495746
iter  90 value 82.001174
iter 100 value 81.263468
final  value 81.263468 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.226092 
iter  10 value 94.070675
iter  20 value 94.011788
iter  30 value 86.984303
iter  40 value 86.155783
iter  50 value 85.280534
iter  60 value 85.018443
iter  70 value 83.932809
iter  80 value 83.439042
iter  90 value 83.402889
iter 100 value 83.354327
final  value 83.354327 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.307706 
iter  10 value 94.094297
iter  20 value 92.506150
iter  30 value 86.664247
iter  40 value 86.030286
iter  50 value 83.276878
iter  60 value 82.672775
iter  70 value 81.508323
iter  80 value 81.366925
iter  90 value 81.165610
iter 100 value 80.977201
final  value 80.977201 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.777722 
iter  10 value 94.817647
iter  20 value 92.699415
iter  30 value 85.025014
iter  40 value 83.055082
iter  50 value 82.027052
iter  60 value 81.649663
iter  70 value 81.306217
iter  80 value 81.216453
iter  90 value 81.167857
iter 100 value 81.154751
final  value 81.154751 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.994281 
iter  10 value 93.983815
iter  20 value 88.987506
iter  30 value 86.503708
iter  40 value 83.997427
iter  50 value 82.625640
iter  60 value 81.887206
iter  70 value 81.498280
iter  80 value 81.271753
iter  90 value 80.984421
iter 100 value 80.767267
final  value 80.767267 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.179740 
iter  10 value 94.160095
iter  20 value 94.063141
iter  30 value 91.153115
iter  40 value 85.099573
iter  50 value 84.197827
iter  60 value 83.550868
iter  70 value 82.287408
iter  80 value 81.857141
iter  90 value 81.415439
iter 100 value 80.968953
final  value 80.968953 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.457560 
iter  10 value 96.817417
iter  20 value 87.804437
iter  30 value 85.869050
iter  40 value 83.516460
iter  50 value 82.366804
iter  60 value 81.931764
iter  70 value 81.849563
iter  80 value 81.450032
iter  90 value 81.187624
iter 100 value 81.082098
final  value 81.082098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.170248 
iter  10 value 94.034672
iter  20 value 93.955967
iter  30 value 85.128752
iter  40 value 84.946028
iter  50 value 84.937689
iter  60 value 84.934879
iter  70 value 84.934653
iter  80 value 84.934012
iter  90 value 84.933206
iter 100 value 84.932937
final  value 84.932937 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.973552 
final  value 94.054381 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.219852 
final  value 94.054955 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.736619 
iter  10 value 93.970817
iter  20 value 93.969584
iter  30 value 93.967896
final  value 93.967868 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.275097 
final  value 94.054461 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.614761 
iter  10 value 94.057494
iter  20 value 93.975890
iter  30 value 93.805378
iter  40 value 93.804968
iter  50 value 93.794349
final  value 93.792136 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.032653 
iter  10 value 84.659942
iter  20 value 84.063780
iter  20 value 84.063780
final  value 84.063780 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.480100 
iter  10 value 94.057713
iter  20 value 94.052092
iter  30 value 87.976679
iter  40 value 84.947280
iter  50 value 84.148511
final  value 84.146801 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.806458 
iter  10 value 94.057458
iter  20 value 94.052951
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.701922 
iter  10 value 94.057315
iter  20 value 88.081439
iter  30 value 85.860152
iter  40 value 85.841083
final  value 85.841045 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.481397 
iter  10 value 94.061363
iter  20 value 94.038018
iter  30 value 91.052970
iter  40 value 87.433208
iter  50 value 87.391086
iter  60 value 87.380836
iter  70 value 86.273245
iter  80 value 86.195858
iter  90 value 86.189961
iter  90 value 86.189961
final  value 86.189961 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.147847 
iter  10 value 93.889647
iter  20 value 93.815473
iter  30 value 93.789508
iter  40 value 93.786371
iter  50 value 93.740600
iter  60 value 88.714680
iter  70 value 84.773667
iter  80 value 82.702500
iter  90 value 82.244159
iter 100 value 82.242699
final  value 82.242699 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.449813 
iter  10 value 93.812813
iter  20 value 93.798636
iter  30 value 93.794578
iter  40 value 93.794209
iter  50 value 93.735434
iter  60 value 93.734506
iter  70 value 93.734400
iter  80 value 93.734171
iter  80 value 93.734171
iter  80 value 93.734171
final  value 93.734171 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.788007 
iter  10 value 94.060737
iter  20 value 94.042875
iter  30 value 94.039687
iter  40 value 93.983040
iter  50 value 87.383833
iter  60 value 87.376941
iter  70 value 86.176721
final  value 86.174375 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.433165 
iter  10 value 94.060943
iter  20 value 94.053661
iter  30 value 93.636039
iter  40 value 87.374840
final  value 87.374837 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.709352 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.034922 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.253512 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.053084 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.215203 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.916877 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.204078 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.156137 
iter  10 value 94.479532
iter  10 value 94.479532
iter  10 value 94.479532
final  value 94.479532 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.254310 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.434076 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.623839 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.960472 
iter  10 value 92.021328
iter  20 value 89.844558
iter  30 value 89.842140
iter  40 value 89.835855
final  value 89.835831 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.285178 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.540344 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.719260 
iter  10 value 94.466827
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.395197 
iter  10 value 94.118065
iter  20 value 86.590119
iter  30 value 85.883814
iter  40 value 85.069906
iter  50 value 85.031942
iter  60 value 84.492917
final  value 84.491879 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.307041 
iter  10 value 96.499017
iter  20 value 94.488611
iter  30 value 93.279922
iter  40 value 91.810057
iter  50 value 91.001006
iter  60 value 90.946133
iter  70 value 90.819952
iter  80 value 90.750060
iter  90 value 90.745783
final  value 90.745779 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.014336 
iter  10 value 94.483910
iter  20 value 89.712979
iter  30 value 87.751662
iter  40 value 85.527013
iter  50 value 84.649395
iter  60 value 84.497432
iter  70 value 84.491958
final  value 84.491877 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.181315 
iter  10 value 94.488087
iter  20 value 93.860804
iter  30 value 87.242505
iter  40 value 85.538143
iter  50 value 85.112578
iter  60 value 84.626878
iter  70 value 84.524263
iter  80 value 84.492007
final  value 84.491877 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.232077 
iter  10 value 94.331991
iter  20 value 89.923819
iter  30 value 87.670607
iter  40 value 85.887732
iter  50 value 84.158041
iter  60 value 83.595672
iter  70 value 83.289314
iter  80 value 83.191840
iter  90 value 83.126908
final  value 83.126904 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.781914 
iter  10 value 93.768078
iter  20 value 86.711896
iter  30 value 85.836188
iter  40 value 85.104012
iter  50 value 85.031289
iter  60 value 83.810286
iter  70 value 83.325796
final  value 83.203662 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.010544 
iter  10 value 94.398905
iter  20 value 89.868318
iter  30 value 87.091185
iter  40 value 85.350569
iter  50 value 84.865622
iter  60 value 84.328258
iter  70 value 83.866431
iter  80 value 82.974512
iter  90 value 82.835462
iter 100 value 82.677709
final  value 82.677709 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.367510 
iter  10 value 92.489614
iter  20 value 88.155350
iter  30 value 86.317328
iter  40 value 84.461083
iter  50 value 84.210971
iter  60 value 83.369489
iter  70 value 81.083409
iter  80 value 80.646494
iter  90 value 80.489906
iter 100 value 80.206378
final  value 80.206378 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.811319 
iter  10 value 94.463759
iter  20 value 88.819963
iter  30 value 85.903928
iter  40 value 84.271983
iter  50 value 83.951398
iter  60 value 83.814339
iter  70 value 83.429722
iter  80 value 83.226040
iter  90 value 82.231389
iter 100 value 81.148335
final  value 81.148335 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.801929 
iter  10 value 94.972039
iter  20 value 94.482601
iter  30 value 94.182881
iter  40 value 92.550969
iter  50 value 86.752448
iter  60 value 84.055717
iter  70 value 81.767428
iter  80 value 81.032899
iter  90 value 80.876406
iter 100 value 80.755145
final  value 80.755145 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.333510 
iter  10 value 90.844253
iter  20 value 87.389288
iter  30 value 83.429411
iter  40 value 81.849313
iter  50 value 80.950477
iter  60 value 80.682846
iter  70 value 80.465885
iter  80 value 80.374443
iter  90 value 80.324440
iter 100 value 80.259281
final  value 80.259281 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.122542 
iter  10 value 94.747989
iter  20 value 94.409251
iter  30 value 93.709686
iter  40 value 84.701143
iter  50 value 84.469813
iter  60 value 83.303065
iter  70 value 83.090071
iter  80 value 82.960318
iter  90 value 82.732456
iter 100 value 82.222395
final  value 82.222395 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.452914 
iter  10 value 94.557507
iter  20 value 93.488331
iter  30 value 88.467477
iter  40 value 85.506374
iter  50 value 84.388837
iter  60 value 83.110174
iter  70 value 81.553603
iter  80 value 81.065619
iter  90 value 80.718896
iter 100 value 80.605034
final  value 80.605034 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.654448 
iter  10 value 96.188526
iter  20 value 89.697320
iter  30 value 86.881909
iter  40 value 85.120226
iter  50 value 84.691436
iter  60 value 84.251970
iter  70 value 84.158122
iter  80 value 84.134949
iter  90 value 83.827715
iter 100 value 82.176311
final  value 82.176311 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.053433 
iter  10 value 94.609782
iter  20 value 86.526458
iter  30 value 85.078479
iter  40 value 82.164158
iter  50 value 81.642101
iter  60 value 81.503010
iter  70 value 81.342480
iter  80 value 80.919216
iter  90 value 80.438854
iter 100 value 80.342161
final  value 80.342161 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.687747 
final  value 94.485544 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.599134 
final  value 94.485765 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.586457 
final  value 94.485893 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.928174 
final  value 94.485630 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.886188 
iter  10 value 94.485877
iter  20 value 93.073857
iter  30 value 88.938432
iter  40 value 88.923404
iter  50 value 86.540436
iter  60 value 86.458740
iter  70 value 85.400135
iter  80 value 85.391981
final  value 85.388156 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.351211 
iter  10 value 90.247812
iter  20 value 86.282373
iter  30 value 86.227683
iter  40 value 86.196006
iter  50 value 84.614847
iter  60 value 84.579849
iter  70 value 84.499032
iter  80 value 82.544119
iter  90 value 82.467742
iter 100 value 82.466926
final  value 82.466926 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.912198 
iter  10 value 93.697250
iter  20 value 93.697053
iter  30 value 92.738978
iter  40 value 91.810369
iter  50 value 91.560664
iter  60 value 91.545256
final  value 91.545060 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.972819 
iter  10 value 94.488881
iter  20 value 93.790488
iter  30 value 89.467802
final  value 89.425804 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.972655 
iter  10 value 94.488491
iter  20 value 87.279998
iter  30 value 86.336617
iter  40 value 86.335655
iter  50 value 85.995899
iter  60 value 85.990626
iter  70 value 85.965627
iter  80 value 85.946565
final  value 85.946517 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.572192 
iter  10 value 94.488848
final  value 94.484199 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.629592 
iter  10 value 94.475905
iter  20 value 88.999674
iter  30 value 87.227748
iter  40 value 84.658903
iter  50 value 84.656867
iter  60 value 84.656364
iter  70 value 84.369991
iter  80 value 84.364573
iter  90 value 84.167322
iter 100 value 83.370922
final  value 83.370922 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.909445 
iter  10 value 94.463631
iter  20 value 94.432786
iter  30 value 94.395838
iter  40 value 84.774501
iter  50 value 84.400990
iter  60 value 84.366415
iter  70 value 84.356645
iter  80 value 84.355377
iter  90 value 84.354682
iter 100 value 84.354630
final  value 84.354630 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.996638 
iter  10 value 94.475246
iter  20 value 94.177781
iter  30 value 86.319851
iter  40 value 85.530377
iter  50 value 84.267337
iter  60 value 84.118876
iter  70 value 84.117704
final  value 84.117702 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.722681 
iter  10 value 94.475138
iter  20 value 94.421183
iter  30 value 91.985318
iter  40 value 91.980290
iter  50 value 84.445310
iter  60 value 84.360514
iter  70 value 84.056555
iter  80 value 84.015614
iter  90 value 84.009534
iter 100 value 83.750660
final  value 83.750660 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.297239 
iter  10 value 94.490788
iter  20 value 93.431841
iter  30 value 85.525304
iter  40 value 84.401040
iter  50 value 83.793098
iter  60 value 83.216304
iter  70 value 82.754961
iter  80 value 82.709930
iter  90 value 82.427494
iter 100 value 80.784708
final  value 80.784708 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.294067 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.937536 
final  value 93.701657 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.234487 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.554111 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.907871 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.219473 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.551105 
iter  10 value 93.683610
iter  20 value 93.431371
iter  30 value 93.428563
iter  40 value 93.427741
final  value 93.427739 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.139511 
iter  10 value 90.859667
iter  20 value 86.886925
iter  30 value 86.729178
iter  40 value 86.728693
iter  40 value 86.728693
iter  40 value 86.728693
final  value 86.728693 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.960961 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.631428 
iter  10 value 92.110886
iter  20 value 91.868459
iter  30 value 91.853294
final  value 91.853281 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.996347 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.435259 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.750394 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.013426 
iter  10 value 93.692955
final  value 93.692939 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.122125 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.878017 
iter  10 value 94.172982
iter  20 value 87.793050
iter  30 value 86.601341
iter  40 value 85.902398
iter  50 value 85.572804
final  value 85.564024 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.317940 
iter  10 value 94.493051
iter  20 value 94.422472
iter  30 value 90.117193
iter  40 value 88.409867
iter  50 value 88.279410
iter  60 value 87.866039
iter  70 value 85.652486
iter  80 value 85.567029
final  value 85.564024 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.043086 
iter  10 value 94.486086
iter  20 value 86.963062
iter  30 value 85.903517
iter  40 value 85.710939
iter  50 value 85.585678
iter  60 value 85.564035
final  value 85.564024 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.922054 
iter  10 value 94.206049
iter  20 value 89.556065
iter  30 value 89.372553
iter  40 value 89.195412
iter  50 value 88.170656
iter  60 value 86.118171
iter  70 value 85.794356
iter  80 value 85.591354
iter  90 value 85.538175
iter  90 value 85.538174
iter  90 value 85.538174
final  value 85.538174 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.283871 
iter  10 value 94.273358
iter  20 value 86.557807
iter  30 value 85.671102
iter  40 value 85.272245
iter  50 value 85.170680
final  value 85.170654 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.041481 
iter  10 value 94.502751
iter  20 value 89.741611
iter  30 value 86.707099
iter  40 value 85.647815
iter  50 value 85.091940
iter  60 value 84.951761
iter  70 value 83.758592
iter  80 value 82.557569
iter  90 value 82.378799
iter 100 value 82.105309
final  value 82.105309 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.579768 
iter  10 value 94.497562
iter  20 value 87.852608
iter  30 value 86.696602
iter  40 value 85.750993
iter  50 value 85.400939
iter  60 value 85.162418
iter  70 value 85.081197
iter  80 value 84.980245
iter  90 value 84.779638
iter 100 value 82.760308
final  value 82.760308 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.873715 
iter  10 value 95.062590
iter  20 value 92.484257
iter  30 value 90.636922
iter  40 value 89.670313
iter  50 value 89.128079
iter  60 value 88.798820
iter  70 value 85.318289
iter  80 value 84.638140
iter  90 value 84.404954
iter 100 value 83.718509
final  value 83.718509 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.094163 
iter  10 value 94.385305
iter  20 value 87.872807
iter  30 value 86.946602
iter  40 value 85.948066
iter  50 value 85.545599
iter  60 value 85.384341
iter  70 value 85.342671
iter  80 value 84.813732
iter  90 value 84.436459
iter 100 value 84.128498
final  value 84.128498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.068115 
iter  10 value 94.828195
iter  20 value 94.503869
iter  30 value 93.811364
iter  40 value 89.389787
iter  50 value 86.915065
iter  60 value 86.722140
iter  70 value 85.894433
iter  80 value 83.937578
iter  90 value 82.913298
iter 100 value 82.328049
final  value 82.328049 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.297694 
iter  10 value 97.461270
iter  20 value 89.800269
iter  30 value 86.911519
iter  40 value 86.090359
iter  50 value 84.402165
iter  60 value 83.839960
iter  70 value 83.738312
iter  80 value 83.282444
iter  90 value 82.672899
iter 100 value 82.371677
final  value 82.371677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.315459 
iter  10 value 94.545162
iter  20 value 86.849295
iter  30 value 86.434337
iter  40 value 85.541269
iter  50 value 84.147606
iter  60 value 83.670102
iter  70 value 83.483262
iter  80 value 83.257998
iter  90 value 83.211717
iter 100 value 83.162925
final  value 83.162925 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.208962 
iter  10 value 94.505940
iter  20 value 94.306629
iter  30 value 86.978326
iter  40 value 86.713111
iter  50 value 86.546274
iter  60 value 84.628437
iter  70 value 83.357404
iter  80 value 82.622381
iter  90 value 82.392210
iter 100 value 82.149300
final  value 82.149300 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.627165 
iter  10 value 94.524481
iter  20 value 91.431041
iter  30 value 86.372798
iter  40 value 85.148039
iter  50 value 83.851782
iter  60 value 82.562959
iter  70 value 82.164655
iter  80 value 82.096118
iter  90 value 82.013480
iter 100 value 81.921269
final  value 81.921269 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.343371 
iter  10 value 94.142512
iter  20 value 91.789313
iter  30 value 85.936700
iter  40 value 85.692085
iter  50 value 85.314442
iter  60 value 83.897862
iter  70 value 82.830799
iter  80 value 82.636082
iter  90 value 82.312546
iter 100 value 82.075186
final  value 82.075186 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.639691 
iter  10 value 94.485980
iter  20 value 94.484251
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.546962 
final  value 94.486179 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.500876 
final  value 94.486132 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.406339 
final  value 94.485875 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.753446 
final  value 94.485823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.144735 
iter  10 value 87.949691
iter  20 value 87.943539
iter  30 value 86.822362
iter  40 value 86.747540
iter  50 value 86.747446
final  value 86.747415 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.449792 
iter  10 value 94.488969
iter  20 value 94.160949
final  value 93.702911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.436413 
iter  10 value 94.490805
final  value 94.489796 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.187248 
iter  10 value 94.489260
iter  20 value 94.481032
iter  30 value 86.535792
final  value 85.778816 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.599842 
iter  10 value 93.706693
iter  20 value 93.703902
final  value 93.702902 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.490941 
iter  10 value 87.756237
iter  20 value 87.602824
iter  30 value 87.602118
iter  40 value 87.508806
iter  50 value 87.500990
iter  60 value 86.879131
iter  70 value 86.749936
iter  80 value 86.747563
iter  90 value 86.713285
iter 100 value 86.633747
final  value 86.633747 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.675158 
iter  10 value 85.187520
iter  20 value 84.926707
iter  30 value 84.772148
iter  40 value 84.765341
iter  50 value 84.736046
iter  60 value 83.818205
iter  70 value 83.296999
iter  80 value 82.424911
iter  90 value 82.202867
iter 100 value 82.123975
final  value 82.123975 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.082962 
iter  10 value 88.395678
iter  20 value 88.048682
iter  30 value 87.826234
iter  40 value 87.595388
iter  50 value 87.550663
iter  60 value 85.518995
iter  70 value 85.397263
iter  80 value 85.396447
iter  90 value 85.285913
iter 100 value 84.928719
final  value 84.928719 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.484587 
iter  10 value 94.487443
iter  20 value 87.867718
iter  30 value 86.413461
iter  40 value 86.412308
iter  50 value 86.370428
iter  60 value 86.166635
iter  70 value 85.657752
iter  80 value 85.474532
iter  90 value 84.756181
iter 100 value 84.646682
final  value 84.646682 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.098052 
iter  10 value 94.491519
iter  20 value 92.598670
iter  30 value 86.647796
iter  40 value 86.629270
iter  50 value 86.604285
iter  60 value 86.602339
iter  70 value 86.469854
iter  80 value 83.828559
iter  90 value 82.460614
iter 100 value 81.496610
final  value 81.496610 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.166467 
final  value 94.165117 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.416873 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.849542 
iter  10 value 94.264419
iter  20 value 94.220788
final  value 94.220410 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.721539 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.694314 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.911400 
final  value 94.484209 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.080115 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.646198 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.596358 
final  value 94.381462 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.297528 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.695104 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.218333 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.639447 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.993853 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.780671 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.632089 
iter  10 value 86.800866
iter  20 value 85.746786
iter  30 value 85.504286
iter  40 value 84.812647
iter  50 value 84.667124
final  value 84.666886 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.762028 
iter  10 value 94.482875
iter  20 value 91.874321
iter  30 value 88.973890
iter  40 value 88.636687
iter  50 value 87.089708
iter  60 value 84.862666
iter  70 value 83.385151
iter  80 value 82.773770
iter  90 value 82.645208
iter 100 value 82.607147
final  value 82.607147 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.887977 
iter  10 value 94.488343
iter  20 value 92.019001
iter  30 value 90.661410
iter  40 value 89.824990
iter  50 value 86.468454
iter  60 value 85.381947
iter  70 value 84.723029
iter  80 value 84.669001
final  value 84.667057 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.793562 
iter  10 value 94.490203
iter  20 value 94.400562
iter  30 value 94.028350
iter  40 value 94.015770
iter  50 value 94.014267
iter  60 value 92.131211
iter  70 value 88.574253
iter  80 value 85.434928
iter  90 value 85.357080
iter 100 value 85.252254
final  value 85.252254 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.358855 
iter  10 value 94.404945
iter  20 value 94.085568
iter  30 value 87.950967
iter  40 value 86.146220
iter  50 value 85.641722
iter  60 value 84.829728
iter  70 value 84.667107
final  value 84.666887 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.200426 
iter  10 value 95.027342
iter  20 value 94.896005
iter  30 value 86.947185
iter  40 value 84.503434
iter  50 value 83.816503
iter  60 value 82.807396
iter  70 value 82.219627
iter  80 value 82.204113
iter  90 value 81.736142
iter 100 value 81.444914
final  value 81.444914 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.393922 
iter  10 value 94.404814
iter  20 value 93.466581
iter  30 value 90.351170
iter  40 value 87.319705
iter  50 value 85.518211
iter  60 value 84.465633
iter  70 value 84.106445
iter  80 value 83.525993
iter  90 value 82.733372
iter 100 value 81.993797
final  value 81.993797 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.300239 
iter  10 value 94.078213
iter  20 value 91.747012
iter  30 value 89.946943
iter  40 value 85.040749
iter  50 value 84.930900
iter  60 value 84.915382
iter  70 value 84.429497
iter  80 value 84.316632
iter  90 value 84.198446
iter 100 value 84.041271
final  value 84.041271 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.515659 
iter  10 value 94.473712
iter  20 value 86.366237
iter  30 value 85.905278
iter  40 value 85.301679
iter  50 value 85.099679
iter  60 value 84.752152
iter  70 value 84.519921
iter  80 value 83.299871
iter  90 value 83.204090
iter 100 value 82.955933
final  value 82.955933 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.080631 
iter  10 value 94.284907
iter  20 value 87.078577
iter  30 value 86.122803
iter  40 value 85.182235
iter  50 value 85.064063
iter  60 value 84.967544
iter  70 value 84.611976
iter  80 value 84.472113
iter  90 value 84.426764
iter 100 value 84.411342
final  value 84.411342 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.137237 
iter  10 value 94.753713
iter  20 value 92.690211
iter  30 value 88.818633
iter  40 value 85.921017
iter  50 value 83.880473
iter  60 value 82.173175
iter  70 value 81.594345
iter  80 value 81.553215
iter  90 value 81.464798
iter 100 value 81.386604
final  value 81.386604 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.485293 
iter  10 value 94.414248
iter  20 value 92.678446
iter  30 value 84.692770
iter  40 value 84.314989
iter  50 value 84.065931
iter  60 value 83.731267
iter  70 value 82.102238
iter  80 value 81.852377
iter  90 value 81.770359
iter 100 value 81.569041
final  value 81.569041 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.838584 
iter  10 value 94.559318
iter  20 value 94.304793
iter  30 value 91.030881
iter  40 value 85.713097
iter  50 value 82.429788
iter  60 value 82.061372
iter  70 value 81.878326
iter  80 value 81.234669
iter  90 value 81.069844
iter 100 value 80.958689
final  value 80.958689 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.447542 
iter  10 value 94.468918
iter  20 value 91.990215
iter  30 value 85.977119
iter  40 value 85.185991
iter  50 value 85.086508
iter  60 value 83.884767
iter  70 value 83.168904
iter  80 value 82.345813
iter  90 value 81.414127
iter 100 value 81.230460
final  value 81.230460 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.304014 
iter  10 value 94.400380
iter  20 value 86.273540
iter  30 value 85.664582
iter  40 value 85.618705
iter  50 value 85.153425
iter  60 value 84.561789
iter  70 value 84.087173
iter  80 value 82.196702
iter  90 value 81.461428
iter 100 value 81.435016
final  value 81.435016 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.000461 
final  value 94.485751 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.371714 
final  value 94.485821 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.547055 
final  value 94.485792 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.395280 
iter  10 value 94.485960
iter  20 value 94.483808
final  value 94.275440 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.465355 
iter  10 value 94.485862
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.455475 
iter  10 value 94.280566
iter  20 value 94.266915
iter  30 value 87.718695
iter  40 value 87.280934
iter  50 value 87.277171
iter  60 value 87.208683
iter  70 value 86.288382
iter  80 value 85.869854
iter  90 value 85.863995
iter 100 value 85.863842
final  value 85.863842 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.027283 
iter  10 value 94.489377
iter  20 value 92.412498
iter  30 value 90.808440
iter  40 value 90.806821
iter  50 value 90.806536
final  value 90.806528 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.343131 
iter  10 value 94.484513
iter  20 value 94.428569
iter  30 value 91.749388
iter  40 value 91.610932
final  value 91.610705 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.863400 
iter  10 value 94.489261
iter  20 value 94.320752
iter  30 value 94.008056
final  value 94.007368 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.375772 
iter  10 value 94.489380
iter  20 value 94.472664
iter  30 value 87.394414
iter  40 value 86.349431
iter  50 value 86.347187
iter  60 value 85.651261
iter  70 value 85.279841
iter  80 value 85.082517
iter  90 value 84.974372
final  value 84.974269 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.145959 
iter  10 value 93.686125
iter  20 value 93.608022
iter  30 value 93.603197
iter  40 value 93.521027
iter  50 value 92.405365
iter  60 value 83.465093
iter  70 value 81.384309
iter  80 value 80.487058
iter  90 value 80.397751
iter 100 value 80.391517
final  value 80.391517 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.986560 
iter  10 value 94.283118
iter  20 value 94.275973
iter  30 value 85.861700
iter  40 value 85.054697
iter  50 value 84.666785
iter  60 value 83.127378
iter  70 value 83.125190
iter  80 value 83.119136
iter  90 value 83.113860
iter 100 value 83.097140
final  value 83.097140 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.444091 
iter  10 value 94.283670
iter  20 value 94.130761
iter  30 value 94.128268
iter  40 value 91.027966
iter  50 value 86.439655
iter  60 value 85.316967
iter  70 value 84.842699
iter  80 value 84.840466
iter  80 value 84.840466
final  value 84.840466 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.736617 
iter  10 value 94.285477
iter  20 value 94.282254
iter  30 value 94.274830
iter  40 value 93.746057
iter  50 value 93.692647
final  value 93.692616 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.224453 
iter  10 value 94.362913
iter  20 value 94.339794
iter  30 value 92.986429
iter  40 value 84.237069
iter  50 value 83.955377
iter  60 value 83.906841
iter  70 value 83.886505
iter  80 value 83.886185
iter  90 value 83.885283
final  value 83.884906 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.786660 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.304768 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.542920 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.510855 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.983919 
iter  10 value 93.328361
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.224258 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.021247 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.149333 
iter  10 value 92.637738
final  value 92.637734 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.325703 
iter  10 value 93.818911
final  value 93.818714 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.967602 
iter  10 value 92.701658
iter  10 value 92.701657
iter  10 value 92.701657
final  value 92.701657 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.421903 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.473180 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.361063 
iter  10 value 93.328264
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.494289 
iter  10 value 93.790798
iter  20 value 80.854885
iter  30 value 80.648744
final  value 80.647832 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.990349 
iter  10 value 81.004568
iter  20 value 77.318883
iter  30 value 76.916619
iter  40 value 76.726838
iter  50 value 76.705201
iter  60 value 76.480962
iter  70 value 76.298613
iter  80 value 76.298364
iter  80 value 76.298364
final  value 76.298364 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.849921 
iter  10 value 94.058979
iter  20 value 93.975765
iter  30 value 93.358822
iter  40 value 93.151548
iter  50 value 93.129771
iter  60 value 93.128393
iter  70 value 93.126389
iter  80 value 93.124422
iter  90 value 87.560331
iter 100 value 78.734485
final  value 78.734485 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.834155 
iter  10 value 94.058121
iter  20 value 94.024093
iter  30 value 93.757117
iter  40 value 93.705835
iter  50 value 93.680943
iter  60 value 93.294863
iter  70 value 83.486673
iter  80 value 81.988238
iter  90 value 81.832426
iter 100 value 81.574105
final  value 81.574105 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.140876 
iter  10 value 94.050659
iter  20 value 90.613143
iter  30 value 85.668537
iter  40 value 85.291341
iter  50 value 84.964994
iter  60 value 81.935955
iter  70 value 81.447762
iter  80 value 80.454476
iter  90 value 77.628087
iter 100 value 76.984853
final  value 76.984853 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.959372 
iter  10 value 93.660759
iter  20 value 93.534469
iter  30 value 92.684518
iter  40 value 86.531758
iter  50 value 83.281140
iter  60 value 81.118169
iter  70 value 79.722741
iter  80 value 77.895526
iter  90 value 77.337425
iter 100 value 77.049125
final  value 77.049125 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.764814 
iter  10 value 94.256226
iter  20 value 93.977710
iter  30 value 93.340863
iter  40 value 86.987723
iter  50 value 84.574438
iter  60 value 84.077529
iter  70 value 80.393645
iter  80 value 79.954789
iter  90 value 78.158192
iter 100 value 77.457648
final  value 77.457648 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.657111 
iter  10 value 93.866502
iter  20 value 83.102777
iter  30 value 81.606471
iter  40 value 79.152328
iter  50 value 78.908165
iter  60 value 77.069369
iter  70 value 76.663482
iter  80 value 76.539105
iter  90 value 76.477023
iter 100 value 76.393514
final  value 76.393514 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.730746 
iter  10 value 94.074473
iter  20 value 93.830099
iter  30 value 91.429909
iter  40 value 84.447220
iter  50 value 80.596098
iter  60 value 79.422488
iter  70 value 79.186680
iter  80 value 78.588870
iter  90 value 77.569379
iter 100 value 77.198318
final  value 77.198318 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.854700 
iter  10 value 94.125648
iter  20 value 89.393451
iter  30 value 86.909998
iter  40 value 85.024384
iter  50 value 82.913074
iter  60 value 81.745974
iter  70 value 81.229417
iter  80 value 81.154525
iter  90 value 80.887239
iter 100 value 77.906169
final  value 77.906169 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.792321 
iter  10 value 94.638349
iter  20 value 82.655717
iter  30 value 82.049309
iter  40 value 81.676262
iter  50 value 81.338255
iter  60 value 78.157739
iter  70 value 77.721445
iter  80 value 77.379529
iter  90 value 77.217946
iter 100 value 76.984038
final  value 76.984038 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.731842 
iter  10 value 93.903379
iter  20 value 86.884610
iter  30 value 82.321266
iter  40 value 81.559472
iter  50 value 81.264099
iter  60 value 79.582861
iter  70 value 78.087987
iter  80 value 76.397960
iter  90 value 75.631386
iter 100 value 75.472706
final  value 75.472706 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.723233 
iter  10 value 91.935328
iter  20 value 89.502053
iter  30 value 83.479660
iter  40 value 80.490889
iter  50 value 79.130124
iter  60 value 78.527542
iter  70 value 76.529315
iter  80 value 75.818420
iter  90 value 75.616487
iter 100 value 75.581434
final  value 75.581434 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.679095 
iter  10 value 96.388873
iter  20 value 85.028329
iter  30 value 82.530324
iter  40 value 80.722459
iter  50 value 80.069614
iter  60 value 79.549090
iter  70 value 78.311331
iter  80 value 77.819566
iter  90 value 77.633985
iter 100 value 77.532458
final  value 77.532458 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.787463 
iter  10 value 94.229825
iter  20 value 93.582022
iter  30 value 88.080381
iter  40 value 84.538542
iter  50 value 82.947896
iter  60 value 80.882734
iter  70 value 79.084365
iter  80 value 77.536185
iter  90 value 76.919677
iter 100 value 76.646713
final  value 76.646713 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.039974 
iter  10 value 93.420909
iter  20 value 91.202798
iter  30 value 85.460669
iter  40 value 83.924065
iter  50 value 79.575960
iter  60 value 78.043171
iter  70 value 76.694324
iter  80 value 75.706764
iter  90 value 75.471990
iter 100 value 75.339083
final  value 75.339083 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.041361 
iter  10 value 99.257577
iter  20 value 86.543675
iter  30 value 84.001827
iter  40 value 83.616675
iter  50 value 80.866590
iter  60 value 80.193511
iter  70 value 77.804377
iter  80 value 76.694460
iter  90 value 75.955648
iter 100 value 75.304349
final  value 75.304349 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.159680 
final  value 94.054377 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.831128 
iter  10 value 93.536565
iter  10 value 93.536564
iter  10 value 93.536564
final  value 93.536564 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.887036 
final  value 94.054616 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.759132 
iter  10 value 94.054868
final  value 94.053135 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.966387 
final  value 94.054598 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.319628 
iter  10 value 94.057319
iter  20 value 93.726871
iter  30 value 92.933784
final  value 92.926470 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.351271 
iter  10 value 94.058082
iter  20 value 93.382819
iter  30 value 83.462453
iter  40 value 83.462015
iter  50 value 83.460514
iter  60 value 83.459115
iter  70 value 83.162468
iter  80 value 80.741295
iter  90 value 77.431546
iter 100 value 76.694650
final  value 76.694650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.960926 
iter  10 value 94.057735
iter  20 value 94.053800
iter  30 value 94.052912
iter  40 value 93.329621
final  value 93.329307 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.242484 
iter  10 value 94.063539
iter  20 value 93.398839
iter  30 value 93.374318
iter  40 value 93.367271
iter  50 value 93.348977
iter  60 value 93.344276
iter  70 value 93.342776
iter  80 value 89.734762
iter  90 value 82.980355
iter 100 value 82.298534
final  value 82.298534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.387986 
iter  10 value 94.058137
iter  20 value 93.939448
iter  30 value 84.842935
iter  40 value 84.351271
iter  50 value 84.351094
iter  60 value 84.350699
iter  70 value 81.341013
iter  80 value 80.399410
iter  90 value 77.421144
iter 100 value 76.818335
final  value 76.818335 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.537846 
final  value 94.061284 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.741678 
iter  10 value 93.777893
iter  20 value 92.846783
iter  30 value 92.838752
iter  40 value 92.838333
iter  50 value 85.149401
iter  60 value 83.969119
iter  70 value 79.165775
iter  80 value 76.647151
iter  90 value 75.907342
iter 100 value 74.662619
final  value 74.662619 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.855939 
iter  10 value 94.060666
iter  20 value 94.017751
iter  30 value 89.001455
iter  40 value 88.418640
iter  50 value 88.412657
iter  60 value 83.115735
iter  70 value 82.838306
iter  80 value 79.207243
iter  90 value 78.998826
iter 100 value 78.997026
final  value 78.997026 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.054653 
iter  10 value 94.061555
iter  20 value 93.932813
iter  30 value 91.529678
iter  40 value 91.510731
final  value 91.510716 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.636201 
iter  10 value 93.561462
iter  20 value 93.541462
iter  30 value 93.500639
iter  40 value 93.260870
iter  50 value 93.065524
iter  60 value 91.350064
iter  70 value 79.448282
iter  80 value 79.066675
iter  90 value 79.002813
final  value 79.002375 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.581732 
iter  10 value 117.901914
iter  20 value 117.756253
iter  30 value 108.675590
iter  40 value 106.631931
iter  50 value 105.128695
iter  60 value 104.254384
iter  70 value 103.815526
iter  80 value 103.695547
iter  90 value 103.446054
iter 100 value 103.147798
final  value 103.147798 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.502101 
iter  10 value 117.942669
iter  20 value 117.653006
iter  30 value 117.488732
iter  40 value 109.230697
iter  50 value 107.579242
iter  60 value 102.953646
iter  70 value 102.105923
iter  80 value 101.620085
iter  90 value 101.401601
iter 100 value 101.238034
final  value 101.238034 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 137.646237 
iter  10 value 110.454715
iter  20 value 109.641417
iter  30 value 109.507835
iter  40 value 107.387675
iter  50 value 106.172284
iter  60 value 104.266154
iter  70 value 103.336157
iter  80 value 102.345279
iter  90 value 101.681089
iter 100 value 101.209831
final  value 101.209831 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.947957 
iter  10 value 118.019284
iter  20 value 115.986666
iter  30 value 114.446613
iter  40 value 104.998448
iter  50 value 102.081291
iter  60 value 101.904035
iter  70 value 101.811322
iter  80 value 101.326346
iter  90 value 100.808186
iter 100 value 100.564990
final  value 100.564990 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.324791 
iter  10 value 117.789056
iter  20 value 110.830320
iter  30 value 104.309556
iter  40 value 102.674474
iter  50 value 102.081736
iter  60 value 101.595453
iter  70 value 101.307657
iter  80 value 100.856982
iter  90 value 100.494749
iter 100 value 100.354932
final  value 100.354932 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Apr 22 20:18:45 2026 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 19.777   0.719  80.643