##############################################################################
##############################################################################
###
### 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_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* 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 ... NOTE
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       55.465  1.999  57.512
FSmethod      52.348  1.959  54.420
corr_plot     51.733  2.133  53.981
pred_ensembel 16.028  0.320  13.575
enrichfindP    0.462  0.073   7.870
* 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: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.19-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/4.4-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** 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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 101.855268 
iter  10 value 94.013956
iter  20 value 93.610297
iter  30 value 90.643440
iter  30 value 90.643440
iter  30 value 90.643440
final  value 90.643440 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.460530 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.484598 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.389589 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.777053 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.861574 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.399766 
iter  10 value 93.582421
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.299720 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.950365 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.053711 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.670134 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.072236 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.226130 
iter  10 value 93.582417
iter  10 value 93.582417
iter  10 value 93.582417
final  value 93.582417 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.135728 
iter  10 value 93.582429
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 93.710159 
iter  10 value 91.801808
iter  20 value 90.415675
iter  30 value 90.136860
iter  40 value 89.857114
final  value 89.856915 
converged
Fitting Repeat 1 

# weights:  103
initial  value 127.710400 
iter  10 value 90.559966
iter  20 value 88.558361
iter  30 value 86.401700
iter  40 value 84.037149
iter  50 value 83.786940
iter  60 value 83.514145
iter  70 value 83.462696
final  value 83.459097 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.436308 
iter  10 value 93.982956
iter  20 value 90.347075
iter  30 value 88.073997
iter  40 value 87.342525
iter  50 value 87.038995
iter  60 value 85.879918
iter  70 value 85.355480
iter  80 value 85.351007
final  value 85.351005 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.420331 
iter  10 value 93.752236
iter  20 value 93.415874
iter  30 value 87.549248
iter  40 value 85.886726
iter  50 value 83.396921
iter  60 value 83.357165
iter  70 value 83.204587
iter  80 value 83.167439
iter  90 value 83.027659
iter 100 value 83.016310
final  value 83.016310 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.137410 
iter  10 value 94.057433
iter  20 value 94.056604
iter  30 value 90.769906
iter  40 value 85.309100
iter  50 value 84.388690
iter  60 value 83.942417
iter  70 value 83.774306
iter  80 value 83.587875
iter  90 value 83.575448
final  value 83.575440 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.029874 
iter  10 value 94.056163
iter  20 value 93.850858
iter  30 value 93.634405
iter  40 value 93.628658
iter  50 value 93.622280
iter  60 value 92.940154
iter  70 value 85.233104
iter  80 value 84.769886
iter  90 value 83.982925
iter 100 value 83.823453
final  value 83.823453 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.149383 
iter  10 value 94.048061
iter  20 value 90.186207
iter  30 value 84.845605
iter  40 value 82.116951
iter  50 value 81.894088
iter  60 value 81.121727
iter  70 value 80.055179
iter  80 value 79.659488
iter  90 value 79.487879
iter 100 value 79.383250
final  value 79.383250 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.960872 
iter  10 value 94.164945
iter  20 value 91.203364
iter  30 value 86.052571
iter  40 value 84.486853
iter  50 value 81.689743
iter  60 value 80.555922
iter  70 value 80.432306
iter  80 value 80.358597
iter  90 value 80.087119
iter 100 value 79.897650
final  value 79.897650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.862983 
iter  10 value 94.247383
iter  20 value 93.820117
iter  30 value 92.178092
iter  40 value 87.024612
iter  50 value 83.843395
iter  60 value 82.057528
iter  70 value 80.450635
iter  80 value 80.118744
iter  90 value 79.799933
iter 100 value 79.728212
final  value 79.728212 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.632865 
iter  10 value 94.096924
iter  20 value 91.231462
iter  30 value 86.025189
iter  40 value 84.195283
iter  50 value 83.155501
iter  60 value 81.789064
iter  70 value 80.907741
iter  80 value 80.673457
iter  90 value 80.554868
iter 100 value 80.462282
final  value 80.462282 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.490665 
iter  10 value 93.751629
iter  20 value 86.491257
iter  30 value 85.157701
iter  40 value 83.780498
iter  50 value 83.455279
iter  60 value 83.263860
iter  70 value 81.545262
iter  80 value 80.640043
iter  90 value 80.275134
iter 100 value 80.078538
final  value 80.078538 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.606982 
iter  10 value 94.014858
iter  20 value 88.942396
iter  30 value 85.859079
iter  40 value 85.678021
iter  50 value 85.363938
iter  60 value 84.802836
iter  70 value 83.326780
iter  80 value 81.909658
iter  90 value 81.493763
iter 100 value 80.604855
final  value 80.604855 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.729170 
iter  10 value 95.562232
iter  20 value 91.847799
iter  30 value 88.524854
iter  40 value 87.765827
iter  50 value 86.331021
iter  60 value 83.685610
iter  70 value 81.735194
iter  80 value 80.622664
iter  90 value 80.202976
iter 100 value 79.894167
final  value 79.894167 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.860767 
iter  10 value 94.949072
iter  20 value 92.383065
iter  30 value 88.517645
iter  40 value 87.176976
iter  50 value 84.419187
iter  60 value 81.554217
iter  70 value 80.544475
iter  80 value 80.239577
iter  90 value 80.150787
iter 100 value 79.826135
final  value 79.826135 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.348942 
iter  10 value 94.026842
iter  20 value 93.680532
iter  30 value 87.383077
iter  40 value 86.783965
iter  50 value 85.104055
iter  60 value 82.076985
iter  70 value 81.350916
iter  80 value 80.688176
iter  90 value 80.273968
iter 100 value 80.192309
final  value 80.192309 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.030301 
iter  10 value 97.188092
iter  20 value 93.296571
iter  30 value 89.724080
iter  40 value 85.959037
iter  50 value 83.284685
iter  60 value 82.503054
iter  70 value 82.213242
iter  80 value 81.958799
iter  90 value 81.851819
iter 100 value 81.394674
final  value 81.394674 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.676514 
iter  10 value 94.054321
iter  20 value 93.883280
iter  30 value 88.885969
iter  40 value 88.842349
iter  50 value 87.911217
iter  60 value 87.903796
final  value 87.903790 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.769209 
final  value 94.054458 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.031943 
final  value 94.054618 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.088762 
iter  10 value 94.054640
iter  20 value 94.038770
final  value 93.584080 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.784892 
final  value 94.054001 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.333360 
iter  10 value 94.057964
iter  20 value 92.919459
iter  30 value 92.547694
iter  40 value 89.969713
iter  50 value 89.964385
final  value 89.964322 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.101760 
iter  10 value 94.057212
iter  20 value 94.048682
iter  30 value 90.939704
iter  40 value 90.878915
iter  50 value 89.927615
final  value 89.883590 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.072049 
iter  10 value 94.057768
iter  20 value 94.052901
iter  30 value 85.247592
iter  40 value 85.225929
iter  50 value 85.225286
iter  60 value 85.103184
iter  70 value 84.821128
iter  80 value 82.479566
iter  90 value 82.341258
iter 100 value 81.658905
final  value 81.658905 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.580646 
iter  10 value 94.057241
iter  20 value 93.605518
final  value 93.605215 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.952104 
iter  10 value 93.587809
iter  20 value 93.582763
iter  30 value 93.568654
iter  40 value 86.766018
iter  50 value 86.764707
iter  60 value 85.871084
iter  70 value 82.582122
iter  80 value 82.453403
iter  90 value 82.437597
final  value 82.437569 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.589423 
iter  10 value 93.591142
iter  20 value 93.456399
iter  30 value 86.641564
iter  40 value 86.340858
iter  50 value 85.062364
iter  60 value 84.514808
iter  70 value 83.673845
iter  80 value 83.672740
final  value 83.672558 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.032575 
iter  10 value 90.501594
iter  20 value 87.936011
iter  30 value 87.919140
iter  40 value 86.689662
iter  50 value 85.410293
iter  60 value 82.959656
iter  70 value 80.284352
iter  80 value 79.716018
iter  90 value 79.691454
iter 100 value 79.672986
final  value 79.672986 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.042772 
iter  10 value 93.868682
iter  20 value 93.589590
iter  30 value 93.580537
final  value 93.580085 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.798697 
iter  10 value 94.061125
iter  20 value 94.052931
iter  30 value 93.582790
final  value 93.582783 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.989697 
iter  10 value 94.063193
iter  20 value 94.054148
iter  30 value 88.668453
iter  40 value 86.951370
iter  50 value 86.943387
iter  60 value 86.942549
iter  70 value 86.939416
iter  80 value 85.203340
iter  90 value 85.116492
final  value 85.116425 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.394661 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.499885 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.768070 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.839505 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.786488 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.927958 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.555014 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.745987 
final  value 93.587879 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.924991 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.682134 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.811435 
final  value 93.604520 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.009189 
iter  10 value 89.452864
iter  20 value 84.976818
iter  30 value 84.955826
iter  40 value 84.738693
final  value 84.738619 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.113202 
iter  10 value 93.656596
iter  10 value 93.656596
iter  10 value 93.656596
final  value 93.656596 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.259235 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.843496 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.299076 
iter  10 value 94.017548
iter  20 value 93.164449
iter  30 value 92.232214
iter  40 value 87.926142
iter  50 value 83.650674
iter  60 value 82.488241
iter  70 value 82.030510
iter  80 value 81.081670
iter  90 value 80.873468
iter 100 value 80.732137
final  value 80.732137 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.902839 
iter  10 value 94.057315
iter  20 value 93.973043
iter  30 value 93.943899
iter  40 value 89.302508
iter  50 value 83.801180
iter  60 value 83.472108
iter  70 value 82.714315
iter  80 value 82.383523
iter  90 value 82.311398
final  value 82.311358 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.257261 
iter  10 value 94.106307
iter  20 value 94.039501
iter  30 value 92.648257
iter  40 value 90.787727
iter  50 value 89.659995
iter  60 value 89.256073
iter  70 value 89.239013
iter  80 value 89.237201
iter  90 value 89.236034
iter 100 value 89.217280
final  value 89.217280 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.264822 
iter  10 value 93.966950
iter  20 value 93.702042
iter  30 value 93.137986
iter  40 value 90.784426
iter  50 value 83.589063
iter  60 value 83.492791
iter  70 value 83.266594
iter  80 value 82.807045
iter  90 value 82.501609
iter 100 value 81.149391
final  value 81.149391 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.502779 
iter  10 value 94.054173
iter  20 value 84.405314
iter  30 value 83.779098
iter  40 value 83.503070
iter  50 value 82.981239
iter  60 value 82.571418
iter  70 value 82.538004
iter  80 value 82.374547
iter  90 value 82.311703
iter 100 value 82.311098
final  value 82.311098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.913885 
iter  10 value 94.038581
iter  20 value 92.575310
iter  30 value 86.439362
iter  40 value 83.415510
iter  50 value 82.109385
iter  60 value 81.153512
iter  70 value 80.029348
iter  80 value 79.737490
iter  90 value 79.606627
iter 100 value 79.593617
final  value 79.593617 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 128.355751 
iter  10 value 94.120425
iter  20 value 91.375510
iter  30 value 90.722570
iter  40 value 90.263449
iter  50 value 90.041935
iter  60 value 89.806222
iter  70 value 89.540012
iter  80 value 86.307760
iter  90 value 83.032704
iter 100 value 82.701865
final  value 82.701865 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.752045 
iter  10 value 94.027360
iter  20 value 92.469164
iter  30 value 89.090667
iter  40 value 87.207332
iter  50 value 83.514304
iter  60 value 82.977324
iter  70 value 82.334358
iter  80 value 82.264751
iter  90 value 82.084467
iter 100 value 81.176619
final  value 81.176619 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.774557 
iter  10 value 94.111784
iter  20 value 93.837333
iter  30 value 93.645109
iter  40 value 88.820536
iter  50 value 83.834772
iter  60 value 80.476075
iter  70 value 80.149886
iter  80 value 79.843779
iter  90 value 79.707471
iter 100 value 79.704688
final  value 79.704688 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.185837 
iter  10 value 93.848878
iter  20 value 89.587699
iter  30 value 85.775702
iter  40 value 85.533875
iter  50 value 85.300809
iter  60 value 84.802174
iter  70 value 82.737811
iter  80 value 81.287227
iter  90 value 80.404977
iter 100 value 79.992617
final  value 79.992617 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.042319 
iter  10 value 94.171184
iter  20 value 88.960512
iter  30 value 86.330402
iter  40 value 85.101070
iter  50 value 83.651489
iter  60 value 82.931026
iter  70 value 82.071525
iter  80 value 81.389718
iter  90 value 80.304252
iter 100 value 79.961520
final  value 79.961520 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.547668 
iter  10 value 94.054024
iter  20 value 92.312498
iter  30 value 87.758327
iter  40 value 85.292898
iter  50 value 82.911305
iter  60 value 82.285372
iter  70 value 79.640722
iter  80 value 79.536553
iter  90 value 79.496330
iter 100 value 79.465196
final  value 79.465196 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.214212 
iter  10 value 94.203343
iter  20 value 93.614447
iter  30 value 84.125505
iter  40 value 83.631873
iter  50 value 83.480372
iter  60 value 82.514753
iter  70 value 81.789490
iter  80 value 81.287605
iter  90 value 79.997962
iter 100 value 79.794571
final  value 79.794571 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.066456 
iter  10 value 93.910418
iter  20 value 93.272393
iter  30 value 88.495141
iter  40 value 85.099297
iter  50 value 83.508008
iter  60 value 80.733039
iter  70 value 80.405322
iter  80 value 80.266904
iter  90 value 79.593629
iter 100 value 79.373419
final  value 79.373419 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.060310 
iter  10 value 94.010793
iter  20 value 88.049162
iter  30 value 86.792499
iter  40 value 85.617079
iter  50 value 82.910391
iter  60 value 81.993627
iter  70 value 80.060948
iter  80 value 79.563817
iter  90 value 79.240359
iter 100 value 79.184021
final  value 79.184021 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.068484 
iter  10 value 94.054569
iter  20 value 94.003166
iter  30 value 90.714957
iter  40 value 90.006177
iter  50 value 90.004869
iter  60 value 90.004128
iter  70 value 90.003907
iter  80 value 90.003803
iter  90 value 90.003508
final  value 90.003486 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.821896 
final  value 94.054658 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.762531 
iter  10 value 94.054605
iter  20 value 94.052937
iter  30 value 83.279609
final  value 83.184531 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.753065 
final  value 94.054425 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.997332 
iter  10 value 94.054624
iter  20 value 94.052912
iter  30 value 91.829209
iter  40 value 86.276209
iter  50 value 86.266003
iter  60 value 86.264842
iter  70 value 86.263758
iter  80 value 86.260546
iter  90 value 86.022402
iter 100 value 85.996033
final  value 85.996033 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 97.124137 
iter  10 value 94.057422
iter  20 value 91.836325
iter  30 value 86.100167
iter  40 value 83.874222
iter  50 value 83.767531
iter  60 value 83.638704
iter  70 value 83.434941
iter  80 value 83.433102
iter  90 value 83.368273
iter 100 value 83.259732
final  value 83.259732 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.781580 
iter  10 value 93.920853
iter  20 value 93.916217
iter  30 value 93.493719
iter  40 value 88.182295
iter  50 value 85.246619
iter  60 value 83.722229
final  value 83.702903 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.790470 
iter  10 value 94.055989
iter  20 value 94.048863
iter  30 value 92.329899
final  value 88.348486 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.609304 
iter  10 value 94.010758
iter  20 value 90.280505
iter  30 value 90.099947
iter  40 value 90.099281
iter  50 value 88.071890
iter  60 value 88.036328
iter  70 value 87.469938
iter  80 value 86.914817
final  value 86.777553 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.478344 
iter  10 value 93.920218
iter  20 value 93.915843
iter  30 value 93.061886
iter  40 value 90.870391
iter  50 value 90.267055
iter  60 value 83.221158
iter  70 value 83.198300
iter  80 value 83.184094
final  value 83.183783 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.355512 
iter  10 value 93.520441
iter  20 value 93.514352
iter  30 value 93.493120
iter  40 value 93.491186
iter  50 value 84.934476
iter  60 value 84.229742
iter  70 value 84.200328
final  value 84.200275 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.254512 
iter  10 value 91.386696
iter  20 value 87.533722
iter  30 value 87.530864
iter  40 value 84.907723
iter  50 value 84.292614
iter  60 value 84.178313
iter  70 value 83.948352
iter  80 value 83.947666
iter  90 value 83.946448
final  value 83.945398 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.795291 
iter  10 value 93.636898
iter  20 value 93.526631
iter  30 value 91.021372
iter  40 value 87.130490
iter  50 value 84.611416
iter  60 value 84.156398
iter  70 value 84.103800
iter  80 value 84.103222
iter  90 value 84.005592
iter 100 value 83.709291
final  value 83.709291 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.675257 
iter  10 value 93.515876
iter  20 value 93.512695
iter  30 value 90.814741
iter  40 value 88.536809
iter  50 value 86.952262
iter  60 value 85.817933
iter  70 value 82.264922
iter  80 value 82.091641
iter  90 value 81.971584
iter 100 value 81.971353
final  value 81.971353 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.866211 
iter  10 value 94.060478
iter  20 value 94.026422
iter  30 value 89.845062
iter  40 value 89.723610
iter  50 value 89.723307
iter  60 value 89.723027
iter  70 value 89.721862
final  value 89.721759 
converged
Fitting Repeat 1 

# weights:  103
initial  value 91.554604 
iter  10 value 82.862777
iter  20 value 82.664644
iter  30 value 82.361271
iter  40 value 82.353330
final  value 82.352776 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.376584 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.257267 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.506796 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.287205 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.176308 
iter  10 value 89.842014
iter  20 value 89.835867
final  value 89.835846 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.734889 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.718252 
iter  10 value 94.112644
final  value 94.112570 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.960001 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.566788 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.845802 
iter  10 value 94.312970
iter  20 value 94.312045
final  value 94.312039 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.732121 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.276152 
final  value 94.112570 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.034863 
iter  10 value 93.075517
iter  20 value 92.922940
iter  30 value 92.293639
final  value 92.293621 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.722396 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.383122 
iter  10 value 94.492532
iter  20 value 88.985206
iter  30 value 85.670006
iter  40 value 85.071729
iter  50 value 84.535268
iter  60 value 84.434448
iter  70 value 84.324227
final  value 84.324218 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.583400 
iter  10 value 94.535079
iter  20 value 94.488207
iter  30 value 94.191285
iter  40 value 88.973446
iter  50 value 86.074817
iter  60 value 85.857336
iter  70 value 85.745340
iter  80 value 84.656642
iter  90 value 84.325851
iter 100 value 84.324220
final  value 84.324220 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.317115 
iter  10 value 94.491681
iter  20 value 93.133347
iter  30 value 92.968731
iter  40 value 92.950999
iter  50 value 92.539577
iter  60 value 90.647769
iter  70 value 86.286118
iter  80 value 85.272188
iter  90 value 84.691874
iter 100 value 84.283341
final  value 84.283341 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.496356 
iter  10 value 92.019900
iter  20 value 85.670918
iter  30 value 85.226550
iter  40 value 84.792826
iter  50 value 84.637544
iter  60 value 84.608997
iter  70 value 84.587176
final  value 84.585599 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.616427 
iter  10 value 94.443271
iter  20 value 93.960700
iter  30 value 88.290349
iter  40 value 86.040413
iter  50 value 85.327891
iter  60 value 84.752281
iter  70 value 84.750551
final  value 84.750498 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.580647 
iter  10 value 91.724174
iter  20 value 83.524731
iter  30 value 81.725829
iter  40 value 81.532362
iter  50 value 80.665212
iter  60 value 80.294497
iter  70 value 80.022146
iter  80 value 79.962323
iter  90 value 79.867424
iter 100 value 79.854812
final  value 79.854812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.667688 
iter  10 value 94.542886
iter  20 value 92.742426
iter  30 value 91.158069
iter  40 value 90.795638
iter  50 value 83.551161
iter  60 value 83.043910
iter  70 value 82.080611
iter  80 value 80.761482
iter  90 value 80.590563
iter 100 value 80.529141
final  value 80.529141 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.788132 
iter  10 value 94.535163
iter  20 value 94.164320
iter  30 value 92.948714
iter  40 value 91.007209
iter  50 value 85.962822
iter  60 value 85.544204
iter  70 value 82.076115
iter  80 value 81.351779
iter  90 value 81.030915
iter 100 value 80.926555
final  value 80.926555 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.733663 
iter  10 value 93.921976
iter  20 value 89.430292
iter  30 value 86.546903
iter  40 value 85.263357
iter  50 value 84.283068
iter  60 value 84.044318
iter  70 value 83.490224
iter  80 value 81.323199
iter  90 value 80.370140
iter 100 value 80.232665
final  value 80.232665 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.543035 
iter  10 value 94.433561
iter  20 value 91.482993
iter  30 value 88.302389
iter  40 value 84.258343
iter  50 value 83.161585
iter  60 value 82.541999
iter  70 value 82.347883
iter  80 value 82.080196
iter  90 value 80.588597
iter 100 value 80.150073
final  value 80.150073 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.485307 
iter  10 value 94.533631
iter  20 value 92.544974
iter  30 value 87.902674
iter  40 value 87.073561
iter  50 value 86.784837
iter  60 value 86.732669
iter  70 value 85.713638
iter  80 value 84.239939
iter  90 value 83.111348
iter 100 value 81.548807
final  value 81.548807 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.297561 
iter  10 value 93.946323
iter  20 value 91.482524
iter  30 value 86.456385
iter  40 value 83.862429
iter  50 value 81.909837
iter  60 value 81.046414
iter  70 value 80.509470
iter  80 value 80.310130
iter  90 value 79.826442
iter 100 value 79.467713
final  value 79.467713 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.599121 
iter  10 value 93.861347
iter  20 value 89.672254
iter  30 value 85.906050
iter  40 value 83.679059
iter  50 value 82.345006
iter  60 value 81.240849
iter  70 value 80.194190
iter  80 value 80.079009
iter  90 value 80.058805
iter 100 value 79.981299
final  value 79.981299 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.320514 
iter  10 value 94.537963
iter  20 value 89.309350
iter  30 value 85.953100
iter  40 value 83.313743
iter  50 value 81.726527
iter  60 value 81.253200
iter  70 value 80.879331
iter  80 value 80.745571
iter  90 value 80.711618
iter 100 value 80.520641
final  value 80.520641 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.559301 
iter  10 value 94.417007
iter  20 value 87.123387
iter  30 value 84.669252
iter  40 value 83.120140
iter  50 value 82.083196
iter  60 value 81.542060
iter  70 value 79.959799
iter  80 value 79.694005
iter  90 value 79.582490
iter 100 value 79.513343
final  value 79.513343 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.659160 
iter  10 value 94.485169
final  value 94.484215 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.806627 
final  value 94.468320 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.582367 
final  value 94.486074 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.927351 
iter  10 value 94.468237
iter  20 value 94.467248
final  value 94.467194 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.552438 
final  value 94.485952 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.514909 
iter  10 value 94.488876
iter  20 value 94.480533
iter  30 value 84.858263
iter  40 value 84.823633
final  value 84.823325 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.290405 
iter  10 value 94.488736
iter  20 value 93.093533
iter  30 value 89.758895
iter  40 value 89.237552
iter  50 value 87.808327
iter  60 value 87.774163
iter  70 value 87.773904
iter  80 value 87.766580
iter  90 value 87.765855
iter 100 value 87.673683
final  value 87.673683 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.392961 
iter  10 value 94.488574
iter  20 value 89.460354
iter  30 value 86.310660
iter  40 value 86.310466
iter  50 value 86.303069
final  value 86.302166 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.325384 
iter  10 value 94.294865
iter  20 value 94.292856
iter  30 value 94.264544
iter  40 value 84.427256
iter  50 value 84.344345
iter  60 value 84.325944
iter  70 value 84.320283
iter  80 value 84.316198
iter  90 value 83.787528
final  value 83.787478 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.798710 
iter  10 value 94.489020
iter  20 value 94.484225
iter  30 value 88.079684
iter  40 value 84.822890
iter  50 value 84.781182
iter  60 value 84.777354
iter  70 value 84.776511
iter  80 value 84.775031
iter  90 value 83.864302
iter 100 value 83.751106
final  value 83.751106 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.071667 
iter  10 value 94.475540
iter  20 value 94.137860
final  value 94.112912 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.044137 
iter  10 value 94.085040
iter  20 value 94.082544
iter  30 value 94.070046
iter  40 value 94.060934
iter  50 value 92.940249
iter  60 value 87.299926
iter  70 value 83.825300
iter  80 value 83.787618
iter  90 value 83.787528
iter 100 value 83.780119
final  value 83.780119 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.116246 
iter  10 value 94.492017
iter  20 value 94.435898
final  value 93.615365 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.506878 
iter  10 value 94.048548
iter  20 value 89.958330
iter  30 value 89.846902
iter  40 value 82.793026
iter  50 value 82.782699
iter  60 value 82.748708
iter  70 value 82.745374
iter  80 value 82.615878
iter  90 value 82.578684
iter 100 value 82.575981
final  value 82.575981 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.198335 
iter  10 value 94.491903
iter  20 value 94.484230
final  value 94.484221 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.156118 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.108976 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.372846 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.037946 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.880858 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.478323 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.467962 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.096099 
iter  10 value 94.028858
iter  20 value 94.024564
iter  20 value 94.024564
iter  20 value 94.024564
final  value 94.024564 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.308097 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.213486 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.622040 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.108895 
final  value 94.026541 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.795670 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.879247 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.638133 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.625738 
iter  10 value 94.193771
iter  20 value 94.114028
iter  30 value 86.401300
iter  40 value 85.958430
iter  50 value 85.508131
iter  60 value 85.238711
iter  70 value 85.086525
iter  80 value 84.791622
iter  90 value 84.661529
iter 100 value 84.630818
final  value 84.630818 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.285477 
iter  10 value 89.121535
iter  20 value 87.255483
iter  30 value 86.902831
iter  40 value 84.524263
iter  50 value 83.906284
iter  60 value 83.880164
iter  70 value 83.632196
iter  80 value 83.555918
iter  90 value 83.470886
iter 100 value 83.462980
final  value 83.462980 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.996718 
iter  10 value 94.495764
iter  20 value 89.720105
iter  30 value 88.966008
iter  40 value 88.517315
iter  50 value 88.365528
iter  60 value 87.696230
iter  70 value 86.732996
iter  80 value 83.920114
iter  90 value 83.106759
iter 100 value 83.070430
final  value 83.070430 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.625477 
iter  10 value 94.480382
iter  20 value 94.290578
iter  30 value 94.130795
iter  40 value 94.124373
iter  50 value 89.288650
iter  60 value 88.207714
iter  70 value 88.101387
iter  80 value 88.096518
iter  90 value 88.075013
iter 100 value 87.740625
final  value 87.740625 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.338592 
iter  10 value 94.427099
iter  20 value 94.127189
iter  30 value 94.125364
iter  40 value 88.641180
iter  50 value 85.625000
iter  60 value 84.567354
iter  70 value 83.620254
iter  80 value 83.481072
iter  90 value 83.038058
iter 100 value 83.035321
final  value 83.035321 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.396407 
iter  10 value 91.251104
iter  20 value 86.115793
iter  30 value 85.598550
iter  40 value 83.988811
iter  50 value 83.522081
iter  60 value 83.459770
iter  70 value 83.211989
iter  80 value 83.079149
iter  90 value 83.034200
iter 100 value 82.851832
final  value 82.851832 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.760591 
iter  10 value 94.458907
iter  20 value 90.598490
iter  30 value 86.000081
iter  40 value 85.038677
iter  50 value 84.430188
iter  60 value 83.822125
iter  70 value 83.214310
iter  80 value 82.404894
iter  90 value 82.056694
iter 100 value 81.944761
final  value 81.944761 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.579574 
iter  10 value 94.632806
iter  20 value 91.216057
iter  30 value 85.545989
iter  40 value 83.596347
iter  50 value 82.900851
iter  60 value 82.465222
iter  70 value 82.335805
iter  80 value 81.935383
iter  90 value 81.907805
iter 100 value 81.866771
final  value 81.866771 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.371405 
iter  10 value 94.555580
iter  20 value 93.709699
iter  30 value 88.220226
iter  40 value 85.166114
iter  50 value 84.682893
iter  60 value 83.738486
iter  70 value 82.796009
iter  80 value 82.112428
iter  90 value 81.856016
iter 100 value 81.807198
final  value 81.807198 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.548000 
iter  10 value 94.502641
iter  20 value 90.332999
iter  30 value 89.004219
iter  40 value 88.718979
iter  50 value 86.901794
iter  60 value 86.147172
iter  70 value 85.461333
iter  80 value 84.573645
iter  90 value 83.870019
iter 100 value 83.049726
final  value 83.049726 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.866991 
iter  10 value 94.501676
iter  20 value 89.005967
iter  30 value 88.799707
iter  40 value 87.741472
iter  50 value 85.544191
iter  60 value 83.966732
iter  70 value 82.731640
iter  80 value 81.869302
iter  90 value 81.759371
iter 100 value 81.687276
final  value 81.687276 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.931926 
iter  10 value 96.714209
iter  20 value 88.798945
iter  30 value 86.925021
iter  40 value 86.421372
iter  50 value 84.846986
iter  60 value 82.990160
iter  70 value 82.310838
iter  80 value 82.190767
iter  90 value 82.037214
iter 100 value 81.933065
final  value 81.933065 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.971644 
iter  10 value 94.699613
iter  20 value 94.403064
iter  30 value 93.250644
iter  40 value 86.993377
iter  50 value 85.352239
iter  60 value 84.700236
iter  70 value 83.888898
iter  80 value 82.906699
iter  90 value 82.639204
iter 100 value 82.279044
final  value 82.279044 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.022880 
iter  10 value 94.236519
iter  20 value 87.861729
iter  30 value 86.883460
iter  40 value 86.576270
iter  50 value 85.349493
iter  60 value 83.970709
iter  70 value 83.174923
iter  80 value 82.537853
iter  90 value 81.968804
iter 100 value 81.610793
final  value 81.610793 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.537426 
iter  10 value 94.477041
iter  20 value 86.816004
iter  30 value 85.356552
iter  40 value 84.731126
iter  50 value 84.512348
iter  60 value 84.344834
iter  70 value 83.667479
iter  80 value 82.575209
iter  90 value 82.234816
iter 100 value 82.041920
final  value 82.041920 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.676683 
iter  10 value 94.486099
final  value 94.484455 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.937450 
final  value 94.485742 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.173961 
iter  10 value 94.028612
iter  20 value 94.027218
iter  30 value 94.019864
iter  40 value 86.060086
iter  50 value 85.959551
iter  60 value 85.955528
final  value 85.955469 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.547793 
final  value 94.324463 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.393289 
final  value 94.485970 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.003538 
iter  10 value 94.560438
iter  20 value 94.549156
iter  30 value 94.046390
iter  40 value 88.955804
iter  50 value 86.761283
iter  60 value 86.306398
iter  70 value 86.181247
iter  80 value 85.591017
iter  90 value 84.963373
iter 100 value 84.952157
final  value 84.952157 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.740025 
iter  10 value 94.489220
iter  20 value 94.378728
iter  30 value 85.484449
iter  40 value 85.414219
final  value 85.414129 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.484392 
iter  10 value 94.107943
iter  20 value 94.052486
final  value 94.052127 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.332986 
iter  10 value 94.488953
iter  20 value 94.484287
final  value 94.026865 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.288004 
iter  10 value 94.488795
iter  20 value 87.037124
iter  30 value 86.267505
iter  30 value 86.267504
iter  30 value 86.267504
final  value 86.267504 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.779735 
iter  10 value 94.035581
iter  20 value 94.027235
iter  30 value 92.676337
iter  40 value 92.622502
iter  50 value 92.601018
iter  60 value 92.534813
iter  70 value 89.193382
iter  80 value 86.586497
iter  90 value 86.384307
iter 100 value 86.363320
final  value 86.363320 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.076672 
iter  10 value 94.492280
iter  20 value 94.484262
iter  30 value 94.386978
iter  40 value 88.930140
iter  50 value 88.177387
iter  60 value 86.922710
iter  70 value 86.273620
iter  80 value 84.838405
iter  90 value 83.743162
iter 100 value 83.676048
final  value 83.676048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.235577 
iter  10 value 92.813081
iter  20 value 92.737981
iter  30 value 92.239903
iter  40 value 92.002577
iter  50 value 91.994146
iter  60 value 91.933351
iter  70 value 91.731370
iter  80 value 91.730905
iter  90 value 91.730786
final  value 91.730529 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.337133 
iter  10 value 94.313971
iter  20 value 94.196494
iter  30 value 86.538180
iter  40 value 83.740499
iter  50 value 81.433969
iter  60 value 80.721428
iter  70 value 80.203914
iter  80 value 80.179575
iter  90 value 80.174883
iter 100 value 80.158835
final  value 80.158835 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.584623 
iter  10 value 94.150608
iter  20 value 94.052636
iter  30 value 93.095100
iter  40 value 93.093621
iter  50 value 93.088867
iter  60 value 93.088703
iter  70 value 93.087922
iter  80 value 92.247397
iter  90 value 92.094779
iter 100 value 92.027215
final  value 92.027215 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.128809 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.289311 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.479561 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.966346 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.155793 
iter  10 value 86.158330
iter  20 value 85.335970
iter  30 value 83.845035
iter  40 value 83.517895
final  value 83.517788 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.672131 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.314587 
iter  10 value 94.325113
iter  20 value 94.320332
final  value 94.320310 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.728041 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.057913 
iter  10 value 94.231734
final  value 94.231729 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.369598 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.075382 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.486537 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.362256 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.779444 
iter  10 value 94.231743
final  value 94.231729 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.389508 
final  value 94.231729 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.617245 
iter  10 value 94.320392
iter  20 value 93.510246
iter  30 value 88.342853
iter  40 value 83.831680
iter  50 value 83.149410
iter  60 value 82.593627
iter  70 value 82.362900
iter  80 value 81.606414
iter  90 value 81.512491
iter 100 value 81.371333
final  value 81.371333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.840548 
iter  10 value 94.429728
iter  20 value 86.848456
iter  30 value 86.191953
iter  40 value 84.460332
iter  50 value 83.763268
iter  60 value 83.460891
iter  70 value 83.202621
iter  80 value 83.165382
iter  90 value 83.141757
final  value 83.141521 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.555056 
iter  10 value 94.230720
iter  20 value 86.983424
iter  30 value 85.037022
iter  40 value 83.989060
iter  50 value 83.955454
iter  60 value 82.840447
iter  70 value 82.107886
iter  80 value 81.594704
iter  90 value 81.280467
final  value 81.280129 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.977087 
iter  10 value 94.489788
iter  20 value 93.989741
iter  30 value 93.831132
iter  40 value 93.764025
iter  50 value 90.414832
iter  60 value 88.314594
iter  70 value 87.368574
iter  80 value 86.596368
iter  90 value 83.182395
iter 100 value 82.581953
final  value 82.581953 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.638241 
iter  10 value 94.483008
iter  20 value 93.713181
iter  30 value 89.259092
iter  40 value 85.702573
iter  50 value 84.537762
iter  60 value 84.260304
iter  70 value 84.251619
final  value 84.251564 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.632920 
iter  10 value 94.469692
iter  20 value 88.842327
iter  30 value 86.001790
iter  40 value 84.569667
iter  50 value 82.955102
iter  60 value 82.680550
iter  70 value 82.213379
iter  80 value 81.818684
iter  90 value 81.781548
iter 100 value 81.742708
final  value 81.742708 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.928063 
iter  10 value 94.390179
iter  20 value 91.829873
iter  30 value 88.219676
iter  40 value 86.382288
iter  50 value 84.841786
iter  60 value 82.005702
iter  70 value 81.249006
iter  80 value 80.696049
iter  90 value 79.960088
iter 100 value 79.797014
final  value 79.797014 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 129.779512 
iter  10 value 94.991226
iter  20 value 89.202280
iter  30 value 86.021535
iter  40 value 84.870494
iter  50 value 83.949479
iter  60 value 82.487582
iter  70 value 81.478450
iter  80 value 80.551006
iter  90 value 80.152532
iter 100 value 79.914335
final  value 79.914335 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.225093 
iter  10 value 94.477880
iter  20 value 92.884806
iter  30 value 89.146863
iter  40 value 86.056519
iter  50 value 85.115012
iter  60 value 84.565503
iter  70 value 84.356806
iter  80 value 83.260272
iter  90 value 81.227150
iter 100 value 80.642770
final  value 80.642770 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.798733 
iter  10 value 94.647050
iter  20 value 87.576003
iter  30 value 86.326429
iter  40 value 85.890185
iter  50 value 84.756703
iter  60 value 82.370433
iter  70 value 81.287202
iter  80 value 81.050672
iter  90 value 80.555712
iter 100 value 80.328223
final  value 80.328223 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.855222 
iter  10 value 94.392537
iter  20 value 93.923418
iter  30 value 93.749365
iter  40 value 88.296746
iter  50 value 86.979680
iter  60 value 85.730360
iter  70 value 83.430768
iter  80 value 81.927068
iter  90 value 81.645931
iter 100 value 81.082645
final  value 81.082645 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.132584 
iter  10 value 94.200114
iter  20 value 90.272124
iter  30 value 84.483927
iter  40 value 83.013840
iter  50 value 82.413430
iter  60 value 81.970269
iter  70 value 80.180145
iter  80 value 79.586361
iter  90 value 79.400109
iter 100 value 79.277979
final  value 79.277979 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.225659 
iter  10 value 94.460697
iter  20 value 88.283852
iter  30 value 85.467295
iter  40 value 80.853110
iter  50 value 80.390267
iter  60 value 80.245188
iter  70 value 79.790051
iter  80 value 79.618585
iter  90 value 79.542234
iter 100 value 79.512675
final  value 79.512675 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.823433 
iter  10 value 94.955825
iter  20 value 93.615216
iter  30 value 89.652312
iter  40 value 85.848512
iter  50 value 84.755132
iter  60 value 83.575567
iter  70 value 82.368302
iter  80 value 81.661229
iter  90 value 80.910273
iter 100 value 80.490729
final  value 80.490729 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.989721 
iter  10 value 94.894796
iter  20 value 94.356903
iter  30 value 88.903738
iter  40 value 87.206203
iter  50 value 86.559170
iter  60 value 84.586646
iter  70 value 82.031933
iter  80 value 80.833293
iter  90 value 80.068704
iter 100 value 79.848729
final  value 79.848729 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.216289 
final  value 94.485646 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.641725 
final  value 94.485827 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.447269 
final  value 94.485879 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.470415 
iter  10 value 94.485790
iter  20 value 94.484250
final  value 94.484207 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.048038 
final  value 94.486040 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.419839 
iter  10 value 93.706792
iter  20 value 88.872463
iter  30 value 85.765924
iter  40 value 85.449685
iter  50 value 85.170598
iter  60 value 85.169209
final  value 85.167579 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.808942 
iter  10 value 94.350291
iter  20 value 94.170290
iter  30 value 94.167441
iter  40 value 93.329080
iter  50 value 87.267626
iter  60 value 87.262170
iter  70 value 87.260611
iter  80 value 87.260341
iter  90 value 86.658410
final  value 86.642550 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.204525 
iter  10 value 94.489223
iter  20 value 94.427732
iter  30 value 85.138555
final  value 83.757146 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.411846 
iter  10 value 94.489149
iter  20 value 93.761067
iter  30 value 86.148329
iter  40 value 84.978199
iter  50 value 84.549296
iter  60 value 84.540684
iter  70 value 84.331213
iter  80 value 81.769199
iter  90 value 81.562256
iter 100 value 80.892754
final  value 80.892754 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.872235 
iter  10 value 94.491614
iter  20 value 94.392736
iter  30 value 86.801734
iter  40 value 85.448156
iter  50 value 85.438634
iter  60 value 85.114712
iter  70 value 84.894205
iter  80 value 84.877794
iter  90 value 83.190314
iter 100 value 82.872133
final  value 82.872133 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.691363 
iter  10 value 94.088679
iter  20 value 94.084223
iter  30 value 94.079996
iter  40 value 94.041821
iter  50 value 89.450561
iter  60 value 84.119957
iter  70 value 81.890062
iter  80 value 80.656353
iter  90 value 80.653962
final  value 80.653743 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.229815 
iter  10 value 94.469954
iter  20 value 94.339523
iter  30 value 94.165537
final  value 94.165387 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.922421 
iter  10 value 93.748151
iter  20 value 93.422444
iter  30 value 93.282379
iter  40 value 93.278626
iter  50 value 91.012889
iter  60 value 89.008642
iter  70 value 83.882321
iter  80 value 81.452509
iter  90 value 78.577036
iter 100 value 78.461193
final  value 78.461193 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.790019 
iter  10 value 94.491690
iter  20 value 94.217477
iter  30 value 93.702089
final  value 93.702088 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.687212 
iter  10 value 93.597197
iter  20 value 90.308769
iter  30 value 89.753516
iter  40 value 87.781363
iter  50 value 85.664354
iter  60 value 83.161815
iter  70 value 82.375168
iter  80 value 81.895043
iter  90 value 81.888435
iter 100 value 81.602481
final  value 81.602481 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 134.329432 
iter  10 value 114.889102
iter  20 value 108.490839
iter  30 value 107.287220
iter  40 value 104.957062
iter  50 value 102.253650
iter  60 value 101.208572
iter  70 value 101.029264
iter  80 value 100.967618
iter  90 value 100.941771
iter 100 value 100.901450
final  value 100.901450 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.738788 
iter  10 value 110.840517
iter  20 value 107.829658
iter  30 value 106.441542
iter  40 value 105.526140
iter  50 value 105.331010
iter  60 value 105.261857
iter  70 value 105.234064
iter  80 value 105.099841
iter  90 value 105.011568
iter 100 value 104.926478
final  value 104.926478 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 140.338676 
iter  10 value 118.135007
iter  20 value 117.749199
iter  30 value 116.661077
iter  40 value 109.182952
iter  50 value 107.805864
iter  60 value 107.523264
iter  70 value 106.368623
iter  80 value 106.010968
iter  90 value 105.485612
iter 100 value 103.571110
final  value 103.571110 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 139.801192 
iter  10 value 114.894511
iter  20 value 108.793600
iter  30 value 105.828994
iter  40 value 105.117628
iter  50 value 105.001761
iter  60 value 103.156279
iter  70 value 102.728909
iter  80 value 102.458624
iter  90 value 102.025379
final  value 102.024334 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.712813 
iter  10 value 117.879278
iter  20 value 115.998279
iter  30 value 107.474843
iter  40 value 106.894498
iter  50 value 104.875022
iter  60 value 103.741693
iter  70 value 102.928491
iter  80 value 102.822156
iter  90 value 102.767221
iter 100 value 102.695839
final  value 102.695839 
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 -- Mon Jun 24 22:50:49 2024 
*********************************************** 
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 
 47.721   1.198  49.885