##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* 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 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* 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
corr_plot     52.549  2.017  54.671
FSmethod      52.247  1.907  54.249
var_imp       49.518  1.856  51.532
pred_ensembel 16.738  0.526  15.187
enrichfindP    0.475  0.075   6.385
* 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-3.20-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 4.4.2 (2024-10-31) -- "Pile of Leaves"
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 103.900381 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.849035 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.171375 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.148228 
final  value 94.305882 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.293641 
iter  10 value 91.736947
iter  20 value 83.122289
iter  30 value 83.037810
iter  40 value 83.037364
final  value 83.037362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.202980 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.265743 
final  value 94.305882 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.372894 
iter  10 value 94.132718
iter  20 value 94.040584
iter  30 value 93.909678
iter  30 value 93.909677
iter  30 value 93.909677
final  value 93.909677 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.218870 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.227967 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.420068 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.814363 
iter  10 value 94.450262
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.486499 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.900627 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.544587 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.883410 
iter  10 value 94.463546
iter  20 value 87.497057
iter  30 value 85.567349
iter  40 value 83.888897
iter  50 value 83.578413
iter  60 value 83.505709
iter  70 value 83.493052
final  value 83.491682 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.491596 
iter  10 value 94.355870
iter  20 value 87.504667
iter  30 value 86.521013
iter  40 value 84.718633
iter  50 value 84.062709
iter  60 value 83.935075
iter  70 value 83.919059
final  value 83.915541 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.337050 
iter  10 value 94.510778
iter  20 value 94.439349
iter  30 value 90.947289
iter  40 value 88.309767
iter  50 value 86.368244
iter  60 value 84.957656
iter  70 value 83.964324
iter  80 value 83.916261
iter  90 value 83.915551
final  value 83.915541 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.433335 
iter  10 value 94.442469
iter  20 value 92.192091
iter  30 value 91.955462
iter  40 value 85.994423
iter  50 value 85.635219
iter  60 value 84.680046
iter  70 value 84.140770
iter  80 value 83.940743
iter  90 value 83.929423
iter 100 value 83.916037
final  value 83.916037 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.398246 
iter  10 value 94.344502
iter  20 value 87.898507
iter  30 value 87.257496
iter  40 value 86.344182
iter  50 value 86.111110
iter  60 value 86.045632
iter  70 value 85.912060
iter  80 value 85.201191
iter  90 value 85.131238
final  value 85.130875 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.042680 
iter  10 value 94.168875
iter  20 value 85.520366
iter  30 value 83.276817
iter  40 value 82.273590
iter  50 value 81.359266
iter  60 value 80.797155
iter  70 value 80.748245
iter  80 value 80.721133
iter  90 value 80.709024
iter 100 value 80.688977
final  value 80.688977 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.750570 
iter  10 value 92.665995
iter  20 value 86.019479
iter  30 value 85.207010
iter  40 value 83.615328
iter  50 value 82.743576
iter  60 value 82.612443
iter  70 value 82.434473
iter  80 value 82.136033
iter  90 value 81.898683
iter 100 value 81.823463
final  value 81.823463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.536768 
iter  10 value 94.439573
iter  20 value 91.552016
iter  30 value 85.515350
iter  40 value 84.814563
iter  50 value 84.132063
iter  60 value 83.150853
iter  70 value 82.279755
iter  80 value 81.582240
iter  90 value 80.939240
iter 100 value 80.859225
final  value 80.859225 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.145226 
iter  10 value 94.330535
iter  20 value 86.454228
iter  30 value 85.997100
iter  40 value 85.714761
iter  50 value 84.623874
iter  60 value 82.840457
iter  70 value 81.417256
iter  80 value 80.793116
iter  90 value 80.393454
iter 100 value 80.356986
final  value 80.356986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.887560 
iter  10 value 94.430676
iter  20 value 92.944987
iter  30 value 87.680234
iter  40 value 87.039273
iter  50 value 85.567263
iter  60 value 83.862972
iter  70 value 83.692473
iter  80 value 83.690222
iter  90 value 83.634259
iter 100 value 83.618838
final  value 83.618838 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.767163 
iter  10 value 94.579446
iter  20 value 86.191152
iter  30 value 84.803979
iter  40 value 84.321309
iter  50 value 83.604611
iter  60 value 83.264149
iter  70 value 82.934667
iter  80 value 82.789549
iter  90 value 82.694621
iter 100 value 82.678970
final  value 82.678970 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.711069 
iter  10 value 94.523302
iter  20 value 87.337211
iter  30 value 85.839723
iter  40 value 85.284518
iter  50 value 83.429858
iter  60 value 80.991436
iter  70 value 80.435228
iter  80 value 80.278996
iter  90 value 80.224789
iter 100 value 80.072034
final  value 80.072034 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.040795 
iter  10 value 92.968833
iter  20 value 86.699897
iter  30 value 85.154548
iter  40 value 83.005652
iter  50 value 81.684249
iter  60 value 81.060806
iter  70 value 80.948356
iter  80 value 80.653367
iter  90 value 80.464208
iter 100 value 80.333727
final  value 80.333727 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.553241 
iter  10 value 94.509618
iter  20 value 88.443907
iter  30 value 87.037380
iter  40 value 86.849102
iter  50 value 86.275313
iter  60 value 85.555740
iter  70 value 84.365631
iter  80 value 82.326955
iter  90 value 81.989564
iter 100 value 80.860720
final  value 80.860720 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.786337 
iter  10 value 94.626038
iter  20 value 91.555313
iter  30 value 88.984975
iter  40 value 84.801617
iter  50 value 83.011442
iter  60 value 81.950720
iter  70 value 81.047933
iter  80 value 80.809686
iter  90 value 80.755901
iter 100 value 80.654822
final  value 80.654822 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.973694 
final  value 94.486110 
converged
Fitting Repeat 2 

# weights:  103
initial  value 119.780312 
final  value 94.485590 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.923285 
iter  10 value 94.444770
iter  20 value 94.260827
iter  30 value 84.911583
final  value 83.795241 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.352287 
iter  10 value 94.485703
iter  20 value 94.438615
iter  30 value 87.506609
iter  40 value 86.543415
iter  50 value 86.541969
iter  60 value 86.485469
iter  70 value 86.466541
final  value 86.466443 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.333276 
final  value 94.401626 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.309691 
iter  10 value 94.488908
iter  20 value 94.484214
iter  20 value 94.484214
final  value 94.484214 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.004874 
iter  10 value 94.540055
iter  20 value 94.429622
iter  30 value 86.143563
iter  40 value 85.859867
iter  50 value 85.753980
iter  60 value 85.620726
iter  70 value 85.617784
iter  80 value 85.605074
iter  90 value 85.598650
iter 100 value 85.590879
final  value 85.590879 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.096541 
iter  10 value 94.448420
iter  20 value 94.444348
iter  30 value 94.404069
iter  40 value 86.056920
final  value 86.056296 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.819401 
iter  10 value 94.310475
iter  20 value 94.258530
iter  30 value 94.254663
iter  30 value 94.254662
final  value 94.254662 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.768428 
iter  10 value 93.760835
iter  20 value 93.755120
iter  30 value 87.518442
iter  40 value 86.916337
iter  50 value 86.913648
iter  60 value 86.913590
final  value 86.913446 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.632036 
iter  10 value 94.490323
iter  20 value 93.317902
iter  30 value 84.266133
iter  40 value 82.785646
iter  50 value 82.669307
iter  50 value 82.669306
iter  50 value 82.669306
final  value 82.669306 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.162418 
iter  10 value 94.491649
iter  20 value 93.866183
iter  30 value 84.895001
iter  40 value 83.929731
iter  50 value 83.895527
iter  60 value 83.881895
iter  70 value 83.878633
iter  80 value 83.878281
iter  90 value 83.729940
iter 100 value 82.951352
final  value 82.951352 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.030145 
iter  10 value 94.364697
iter  20 value 94.361904
iter  30 value 94.361068
iter  40 value 94.356403
iter  50 value 93.885294
iter  60 value 87.214775
iter  70 value 87.184972
iter  80 value 86.170871
iter  90 value 85.898160
iter 100 value 85.888803
final  value 85.888803 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.095330 
iter  10 value 94.493664
iter  20 value 94.456738
iter  30 value 87.655744
iter  40 value 85.971897
iter  50 value 85.968289
iter  60 value 82.469445
iter  70 value 82.221121
iter  80 value 82.163542
iter  90 value 81.984409
iter 100 value 81.496088
final  value 81.496088 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.729636 
iter  10 value 94.491578
iter  20 value 94.481172
final  value 94.256112 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.770883 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.086029 
final  value 93.567525 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.953804 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.958459 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.472061 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.979905 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.409736 
iter  10 value 94.683288
iter  20 value 91.877209
iter  30 value 89.504540
iter  40 value 86.842047
iter  50 value 86.812920
iter  60 value 86.812629
iter  70 value 86.812583
iter  70 value 86.812582
iter  70 value 86.812582
final  value 86.812582 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.955916 
final  value 94.254545 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.639630 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.647372 
iter  10 value 93.538060
final  value 93.538042 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.641631 
iter  10 value 94.027074
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.291174 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.279768 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.972609 
iter  10 value 85.286993
final  value 84.616652 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.433254 
iter  10 value 94.484137
iter  10 value 94.484137
iter  10 value 94.484137
final  value 94.484137 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.826992 
iter  10 value 94.495299
iter  20 value 94.488614
iter  30 value 94.327730
iter  40 value 88.091212
iter  50 value 86.141641
iter  60 value 85.937522
iter  70 value 85.619340
iter  80 value 85.209505
iter  90 value 85.079203
iter 100 value 83.561065
final  value 83.561065 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.379307 
iter  10 value 94.225308
iter  20 value 87.748839
iter  30 value 85.401045
iter  40 value 85.053185
iter  50 value 84.899013
iter  60 value 84.254666
iter  70 value 83.919556
iter  80 value 83.848959
iter  90 value 83.840422
iter 100 value 83.839529
final  value 83.839529 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 119.937378 
iter  10 value 94.497756
iter  20 value 94.239446
iter  30 value 94.084664
iter  40 value 93.770557
iter  50 value 92.480243
iter  60 value 91.331480
iter  70 value 85.951341
iter  80 value 84.701280
iter  90 value 84.613024
iter 100 value 84.292056
final  value 84.292056 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.735408 
iter  10 value 93.913986
iter  20 value 85.924053
iter  30 value 84.586014
iter  40 value 84.144580
iter  50 value 83.472504
iter  60 value 82.087974
iter  70 value 81.742158
iter  80 value 81.687800
iter  90 value 81.613437
final  value 81.611128 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.518826 
iter  10 value 94.198126
iter  20 value 94.075353
iter  30 value 90.842883
iter  40 value 86.619638
iter  50 value 86.482005
iter  60 value 85.345116
iter  70 value 84.657105
iter  80 value 83.404356
iter  90 value 82.042989
iter 100 value 81.849109
final  value 81.849109 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.300028 
iter  10 value 94.490868
iter  20 value 94.277212
iter  30 value 94.095480
iter  40 value 94.016685
iter  50 value 89.201260
iter  60 value 85.405870
iter  70 value 84.953932
iter  80 value 84.518952
iter  90 value 84.230924
iter 100 value 84.008635
final  value 84.008635 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.142194 
iter  10 value 93.489365
iter  20 value 90.266364
iter  30 value 84.341825
iter  40 value 81.463180
iter  50 value 80.712802
iter  60 value 80.289678
iter  70 value 80.159452
iter  80 value 80.069877
iter  90 value 80.050633
iter 100 value 80.012238
final  value 80.012238 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.342588 
iter  10 value 94.669935
iter  20 value 94.299234
iter  30 value 89.598589
iter  40 value 88.372403
iter  50 value 85.633115
iter  60 value 82.532557
iter  70 value 82.069440
iter  80 value 81.728279
iter  90 value 81.154794
iter 100 value 81.053711
final  value 81.053711 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.122151 
iter  10 value 94.851916
iter  20 value 90.334348
iter  30 value 86.791294
iter  40 value 85.808509
iter  50 value 85.613201
iter  60 value 85.589599
iter  70 value 85.452295
iter  80 value 85.419256
iter  90 value 85.230335
iter 100 value 84.464742
final  value 84.464742 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.826517 
iter  10 value 95.064378
iter  20 value 94.282219
iter  30 value 94.056751
iter  40 value 91.976364
iter  50 value 87.432668
iter  60 value 86.319675
iter  70 value 85.402231
iter  80 value 85.171253
iter  90 value 84.793429
iter 100 value 82.659307
final  value 82.659307 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.344847 
iter  10 value 94.669578
iter  20 value 87.539048
iter  30 value 86.659746
iter  40 value 84.484736
iter  50 value 82.412904
iter  60 value 81.565405
iter  70 value 80.893052
iter  80 value 80.375375
iter  90 value 80.132883
iter 100 value 79.928540
final  value 79.928540 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.571896 
iter  10 value 95.409071
iter  20 value 93.400766
iter  30 value 85.510081
iter  40 value 83.029895
iter  50 value 82.525790
iter  60 value 82.315024
iter  70 value 81.355419
iter  80 value 81.100447
iter  90 value 80.685700
iter 100 value 80.531986
final  value 80.531986 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.962514 
iter  10 value 93.173608
iter  20 value 92.503429
iter  30 value 85.088186
iter  40 value 84.880604
iter  50 value 84.462855
iter  60 value 83.113873
iter  70 value 81.653779
iter  80 value 81.060505
iter  90 value 80.931018
iter 100 value 80.855953
final  value 80.855953 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.264995 
iter  10 value 95.721350
iter  20 value 89.954129
iter  30 value 88.336509
iter  40 value 84.989006
iter  50 value 83.586932
iter  60 value 83.179345
iter  70 value 82.690989
iter  80 value 82.481227
iter  90 value 81.934821
iter 100 value 81.601163
final  value 81.601163 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.564535 
iter  10 value 94.267658
iter  20 value 93.161259
iter  30 value 89.926485
iter  40 value 84.549804
iter  50 value 82.608844
iter  60 value 82.235146
iter  70 value 81.830451
iter  80 value 81.218826
iter  90 value 80.730768
iter 100 value 80.318753
final  value 80.318753 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.951447 
final  value 94.485595 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.889494 
final  value 94.486008 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.499708 
iter  10 value 94.486063
iter  20 value 94.484293
final  value 94.484218 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.788196 
final  value 94.486004 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.130682 
iter  10 value 94.485843
iter  20 value 94.484221
final  value 94.484216 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.465008 
iter  10 value 93.642873
iter  20 value 87.452902
iter  30 value 86.678034
iter  40 value 86.677344
iter  50 value 85.754357
iter  60 value 85.680079
iter  70 value 85.675853
iter  80 value 85.553756
iter  90 value 83.091248
iter 100 value 82.557377
final  value 82.557377 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.229334 
iter  10 value 94.488779
iter  20 value 94.432158
final  value 94.026745 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.844843 
iter  10 value 94.489033
iter  20 value 93.324175
iter  30 value 85.841687
final  value 85.841617 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.906649 
iter  10 value 94.488421
iter  20 value 85.610037
iter  30 value 84.976435
iter  30 value 84.976435
iter  30 value 84.976435
final  value 84.976435 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.720191 
iter  10 value 94.487319
iter  20 value 93.476669
iter  30 value 91.821626
iter  40 value 91.819736
iter  50 value 91.819116
iter  60 value 85.849691
iter  70 value 84.653990
iter  80 value 84.590882
iter  90 value 84.589890
final  value 84.589886 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.727431 
iter  10 value 94.033456
iter  20 value 94.025871
iter  30 value 88.307613
iter  40 value 87.397254
iter  50 value 86.837594
iter  60 value 86.819983
iter  70 value 85.922714
iter  80 value 85.223559
iter  90 value 85.182735
iter 100 value 85.164064
final  value 85.164064 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.621006 
iter  10 value 94.491101
iter  20 value 94.484268
iter  30 value 94.323601
final  value 93.406379 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.503017 
iter  10 value 94.035004
iter  20 value 94.023003
iter  30 value 84.798013
iter  40 value 84.791504
iter  50 value 83.696473
iter  60 value 80.927950
iter  70 value 80.337368
iter  80 value 80.270595
iter  90 value 80.207161
iter 100 value 80.188162
final  value 80.188162 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.687109 
iter  10 value 88.442414
iter  20 value 85.593494
iter  30 value 85.483847
iter  40 value 83.816736
iter  50 value 82.167423
iter  60 value 81.873327
iter  70 value 81.871555
iter  80 value 81.870033
final  value 81.869939 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.581902 
iter  10 value 89.850723
iter  20 value 86.849417
iter  30 value 86.036399
iter  40 value 85.038515
iter  50 value 81.786617
iter  60 value 81.263345
iter  70 value 81.257286
iter  80 value 81.254777
iter  90 value 80.752955
iter 100 value 80.091326
final  value 80.091326 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.574734 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.845034 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.908174 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.519543 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.715228 
iter  10 value 94.484235
iter  10 value 94.484235
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.524588 
iter  10 value 93.847301
iter  20 value 93.846804
final  value 93.846802 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.220132 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.062033 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.845601 
iter  10 value 94.427726
iter  10 value 94.427726
iter  10 value 94.427726
final  value 94.427726 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.977956 
iter  10 value 89.254163
final  value 88.527428 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.438752 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.221895 
iter  10 value 94.112571
iter  10 value 94.112570
iter  10 value 94.112570
final  value 94.112570 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.527068 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.648046 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.695896 
iter  10 value 94.354403
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.446354 
iter  10 value 94.423548
iter  20 value 87.524239
iter  30 value 86.724328
iter  40 value 86.575726
iter  50 value 86.376645
iter  60 value 86.331153
iter  70 value 86.329442
final  value 86.329432 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.820920 
iter  10 value 94.439553
iter  20 value 89.870795
iter  30 value 89.073219
iter  40 value 88.018859
iter  50 value 85.195786
iter  60 value 84.894383
iter  70 value 84.767652
iter  80 value 84.093275
iter  90 value 83.136252
iter 100 value 82.729854
final  value 82.729854 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.458078 
iter  10 value 94.552460
iter  20 value 94.454127
iter  30 value 88.858476
iter  40 value 86.757515
iter  50 value 86.469082
iter  60 value 86.332466
iter  70 value 86.330995
final  value 86.329432 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.160193 
iter  10 value 94.488865
iter  20 value 94.396735
iter  30 value 93.922728
iter  40 value 93.745207
iter  50 value 91.090777
iter  60 value 90.671430
iter  70 value 87.134407
iter  80 value 85.173099
iter  90 value 84.059271
iter 100 value 83.356381
final  value 83.356381 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.688645 
iter  10 value 94.490748
iter  20 value 94.321766
iter  30 value 92.024379
iter  40 value 89.545040
iter  50 value 86.742709
iter  60 value 84.551712
iter  70 value 83.746091
iter  80 value 82.694701
iter  90 value 82.520079
iter 100 value 82.402384
final  value 82.402384 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.320843 
iter  10 value 94.461576
iter  20 value 94.146524
iter  30 value 93.827677
iter  40 value 90.358030
iter  50 value 89.474900
iter  60 value 86.720739
iter  70 value 85.197546
iter  80 value 84.622423
iter  90 value 82.889682
iter 100 value 82.460285
final  value 82.460285 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.713636 
iter  10 value 94.419491
iter  20 value 87.737293
iter  30 value 86.281518
iter  40 value 84.294407
iter  50 value 82.791533
iter  60 value 82.332423
iter  70 value 82.211185
iter  80 value 82.016867
iter  90 value 81.720483
iter 100 value 81.578475
final  value 81.578475 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.887160 
iter  10 value 91.195276
iter  20 value 88.436785
iter  30 value 87.830468
iter  40 value 85.978877
iter  50 value 84.483240
iter  60 value 83.624066
iter  70 value 82.933696
iter  80 value 82.489346
iter  90 value 81.958261
iter 100 value 81.565538
final  value 81.565538 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.714911 
iter  10 value 95.742484
iter  20 value 94.410118
iter  30 value 87.938688
iter  40 value 86.057344
iter  50 value 85.802149
iter  60 value 85.612971
iter  70 value 85.445313
iter  80 value 85.331461
iter  90 value 84.449592
iter 100 value 82.500568
final  value 82.500568 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.676828 
iter  10 value 94.512942
iter  20 value 94.281418
iter  30 value 91.564093
iter  40 value 88.024209
iter  50 value 86.278150
iter  60 value 86.038989
iter  70 value 84.731408
iter  80 value 84.238237
iter  90 value 84.216833
iter 100 value 84.157517
final  value 84.157517 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.149868 
iter  10 value 93.619499
iter  20 value 93.188429
iter  30 value 92.611424
iter  40 value 91.828480
iter  50 value 86.434487
iter  60 value 84.735209
iter  70 value 83.597038
iter  80 value 82.807058
iter  90 value 82.043620
iter 100 value 81.874991
final  value 81.874991 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.973853 
iter  10 value 100.976845
iter  20 value 92.282843
iter  30 value 88.803726
iter  40 value 85.688959
iter  50 value 85.499242
iter  60 value 85.464975
iter  70 value 85.443720
iter  80 value 85.247144
iter  90 value 83.598150
iter 100 value 82.700702
final  value 82.700702 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.761413 
iter  10 value 94.774920
iter  20 value 92.932150
iter  30 value 89.850748
iter  40 value 85.886376
iter  50 value 83.515428
iter  60 value 82.886335
iter  70 value 82.259047
iter  80 value 81.690545
iter  90 value 81.437676
iter 100 value 81.398223
final  value 81.398223 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.938293 
iter  10 value 90.299210
iter  20 value 87.396046
iter  30 value 84.939825
iter  40 value 82.798634
iter  50 value 82.189496
iter  60 value 82.055443
iter  70 value 81.793807
iter  80 value 81.705717
iter  90 value 81.287992
iter 100 value 80.942882
final  value 80.942882 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.076817 
iter  10 value 94.600740
iter  20 value 94.379673
iter  30 value 93.161670
iter  40 value 87.659359
iter  50 value 83.996942
iter  60 value 83.579970
iter  70 value 82.822957
iter  80 value 82.318144
iter  90 value 82.064017
iter 100 value 81.536526
final  value 81.536526 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.948151 
final  value 94.485706 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.664693 
final  value 94.485844 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.401843 
iter  10 value 94.431836
iter  20 value 94.431648
iter  30 value 88.465105
iter  40 value 87.303137
iter  50 value 86.944375
final  value 86.944357 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.317685 
final  value 94.485786 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.202921 
final  value 94.485741 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.783841 
iter  10 value 94.488887
iter  20 value 94.315825
iter  30 value 94.112810
iter  40 value 94.104385
iter  50 value 94.055484
iter  60 value 94.053738
final  value 94.053728 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.539209 
iter  10 value 93.840746
iter  20 value 93.815197
iter  30 value 93.809907
iter  40 value 86.597413
iter  50 value 84.710399
iter  60 value 84.448811
final  value 84.434581 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.134188 
iter  10 value 94.359719
iter  20 value 94.307149
iter  30 value 93.033734
iter  40 value 88.525315
iter  50 value 87.697952
iter  60 value 87.656633
iter  70 value 87.458833
iter  80 value 86.392423
iter  90 value 86.300443
final  value 86.296684 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.930714 
iter  10 value 94.488538
iter  20 value 94.280412
final  value 93.810778 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.498615 
iter  10 value 94.359476
iter  20 value 94.354780
final  value 94.354488 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.938865 
iter  10 value 94.494729
iter  20 value 94.320126
iter  30 value 86.700672
iter  40 value 86.032341
iter  50 value 84.263981
iter  60 value 83.420492
iter  70 value 83.376958
iter  80 value 83.258850
iter  90 value 82.668730
iter 100 value 80.883099
final  value 80.883099 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.833871 
iter  10 value 93.813361
iter  20 value 93.808219
iter  30 value 93.742780
iter  40 value 86.267740
iter  50 value 85.409534
iter  60 value 85.035279
iter  70 value 83.796868
iter  80 value 83.790710
iter  90 value 83.788748
iter 100 value 83.772357
final  value 83.772357 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.704984 
iter  10 value 94.362399
iter  20 value 94.004745
iter  30 value 93.805358
iter  40 value 93.761567
iter  50 value 92.740810
iter  60 value 86.716745
iter  70 value 85.316376
iter  80 value 85.221453
iter  90 value 85.219542
final  value 85.219540 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.032225 
iter  10 value 93.818153
iter  20 value 93.810644
iter  30 value 93.182946
iter  40 value 89.588760
iter  50 value 83.718817
iter  60 value 82.886080
iter  70 value 81.239199
iter  80 value 80.820432
iter  90 value 80.760745
iter 100 value 80.652636
final  value 80.652636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 135.646901 
iter  10 value 94.492137
iter  20 value 89.562821
iter  30 value 88.591504
iter  40 value 88.587516
iter  50 value 88.502598
final  value 88.502564 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.650497 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.687827 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.517928 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.545227 
iter  10 value 94.008750
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.625994 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.870921 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.122400 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.764491 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.295691 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 130.546353 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.130354 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.687493 
iter  10 value 93.637904
iter  20 value 88.109569
iter  30 value 87.333107
iter  40 value 87.326163
final  value 87.326151 
converged
Fitting Repeat 3 

# weights:  507
initial  value 133.391224 
iter  10 value 93.011268
iter  20 value 90.409376
iter  30 value 89.308515
iter  40 value 82.880177
iter  50 value 81.480820
iter  60 value 80.805798
iter  70 value 80.522845
iter  80 value 80.512619
iter  90 value 80.512063
iter 100 value 80.511962
final  value 80.511962 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.979925 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.940525 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.389624 
iter  10 value 94.054527
iter  20 value 84.270678
iter  30 value 83.200994
iter  40 value 82.312324
iter  50 value 82.279607
final  value 82.279603 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.982080 
iter  10 value 93.938904
iter  20 value 93.242447
iter  30 value 89.616650
iter  40 value 88.040655
iter  50 value 87.883143
iter  60 value 83.687048
iter  70 value 82.711457
iter  80 value 82.657701
iter  90 value 82.355666
iter 100 value 82.179647
final  value 82.179647 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 108.040251 
iter  10 value 94.056201
iter  20 value 93.930096
iter  30 value 91.446883
iter  40 value 84.565113
iter  50 value 82.941277
iter  60 value 82.907085
final  value 82.907027 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.815947 
iter  10 value 94.056354
iter  20 value 94.022918
iter  30 value 92.191575
iter  40 value 89.969706
iter  50 value 89.596701
iter  60 value 86.606101
iter  70 value 83.209321
iter  80 value 81.862906
iter  90 value 81.010712
iter 100 value 80.849155
final  value 80.849155 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.534836 
iter  10 value 94.056688
iter  20 value 88.948833
iter  30 value 84.285835
iter  40 value 82.670455
iter  50 value 82.257680
iter  60 value 82.139426
iter  70 value 81.361870
iter  80 value 80.767742
iter  90 value 80.718992
iter 100 value 80.629033
final  value 80.629033 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 116.447074 
iter  10 value 94.226405
iter  20 value 85.838006
iter  30 value 83.575845
iter  40 value 83.176325
iter  50 value 83.005428
iter  60 value 80.702151
iter  70 value 79.267267
iter  80 value 78.884493
iter  90 value 78.743680
iter 100 value 78.579321
final  value 78.579321 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.125333 
iter  10 value 92.821830
iter  20 value 89.787007
iter  30 value 89.016415
iter  40 value 88.814202
iter  50 value 87.222536
iter  60 value 81.176112
iter  70 value 80.755228
iter  80 value 80.498862
iter  90 value 80.182372
iter 100 value 78.881289
final  value 78.881289 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.573558 
iter  10 value 93.872921
iter  20 value 88.279048
iter  30 value 84.269535
iter  40 value 83.384737
iter  50 value 82.302538
iter  60 value 81.953813
iter  70 value 79.803089
iter  80 value 79.273795
iter  90 value 78.756231
iter 100 value 78.360986
final  value 78.360986 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.922136 
iter  10 value 94.076564
iter  20 value 89.516569
iter  30 value 86.009957
iter  40 value 84.729374
iter  50 value 82.668252
iter  60 value 81.905393
iter  70 value 80.425637
iter  80 value 79.663301
iter  90 value 78.355198
iter 100 value 78.100019
final  value 78.100019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.469206 
iter  10 value 93.370719
iter  20 value 88.043816
iter  30 value 85.404970
iter  40 value 83.290259
iter  50 value 82.764904
iter  60 value 82.507989
iter  70 value 82.485444
iter  70 value 82.485444
final  value 82.485444 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.320604 
iter  10 value 94.009439
iter  20 value 87.718522
iter  30 value 84.576796
iter  40 value 82.749688
iter  50 value 81.020718
iter  60 value 79.892468
iter  70 value 79.377770
iter  80 value 78.945330
iter  90 value 78.761458
iter 100 value 78.170213
final  value 78.170213 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.739767 
iter  10 value 90.928280
iter  20 value 86.216027
iter  30 value 85.173482
iter  40 value 83.602698
iter  50 value 80.470429
iter  60 value 79.666156
iter  70 value 78.798754
iter  80 value 78.449667
iter  90 value 78.327935
iter 100 value 78.057098
final  value 78.057098 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.319402 
iter  10 value 93.953879
iter  20 value 86.662928
iter  30 value 85.407952
iter  40 value 84.864504
iter  50 value 83.557373
iter  60 value 81.654334
iter  70 value 80.292275
iter  80 value 78.954352
iter  90 value 78.416505
iter 100 value 77.967798
final  value 77.967798 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.010348 
iter  10 value 94.450911
iter  20 value 85.765541
iter  30 value 84.093854
iter  40 value 80.980410
iter  50 value 79.196633
iter  60 value 78.976051
iter  70 value 78.882028
iter  80 value 78.557030
iter  90 value 78.406509
iter 100 value 78.369265
final  value 78.369265 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.517731 
iter  10 value 92.676852
iter  20 value 85.499665
iter  30 value 81.757172
iter  40 value 81.172353
iter  50 value 79.997216
iter  60 value 79.623186
iter  70 value 79.531581
iter  80 value 79.070930
iter  90 value 78.288498
iter 100 value 77.775234
final  value 77.775234 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.186548 
final  value 94.054386 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.181418 
final  value 94.054219 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.162109 
final  value 94.054551 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.351722 
final  value 94.054379 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.110772 
iter  10 value 94.054711
iter  20 value 94.052896
iter  30 value 87.888382
iter  40 value 87.532062
iter  50 value 85.881806
iter  60 value 85.142620
iter  70 value 84.766719
iter  80 value 84.765838
final  value 84.765808 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.449422 
iter  10 value 94.055890
iter  20 value 91.031381
iter  30 value 87.038410
iter  40 value 87.031172
iter  50 value 85.458740
iter  60 value 85.191056
iter  70 value 85.027720
iter  80 value 84.593043
iter  90 value 82.339691
iter 100 value 82.213293
final  value 82.213293 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.780548 
iter  10 value 94.057917
iter  20 value 94.053029
iter  20 value 94.053029
final  value 94.053029 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.033229 
iter  10 value 94.057976
final  value 94.052975 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.662712 
iter  10 value 94.057089
iter  20 value 92.132706
iter  30 value 89.298932
iter  40 value 87.940143
iter  50 value 87.931302
iter  60 value 87.208017
iter  70 value 86.912447
iter  80 value 85.909937
iter  90 value 83.716171
iter 100 value 83.500604
final  value 83.500604 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.987594 
iter  10 value 94.013899
iter  20 value 94.009097
final  value 94.008768 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.114673 
iter  10 value 94.060226
iter  20 value 93.929520
iter  30 value 88.778911
iter  40 value 80.001168
iter  50 value 77.113877
iter  60 value 76.019391
iter  70 value 75.913067
iter  80 value 75.866802
iter  90 value 75.796429
iter 100 value 75.752546
final  value 75.752546 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.489038 
iter  10 value 94.061143
iter  20 value 94.053058
iter  30 value 91.986555
iter  40 value 91.229522
iter  50 value 91.227428
iter  60 value 90.803713
iter  70 value 90.612711
iter  80 value 87.170751
iter  90 value 84.289255
iter 100 value 84.188355
final  value 84.188355 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.240788 
iter  10 value 93.877989
iter  20 value 93.819546
iter  30 value 93.818384
iter  40 value 93.818252
iter  50 value 93.817961
iter  60 value 93.817457
iter  60 value 93.817457
iter  60 value 93.817457
final  value 93.817457 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.991962 
iter  10 value 82.899600
iter  20 value 82.167813
iter  30 value 82.167186
iter  40 value 81.680718
iter  50 value 81.677409
iter  60 value 81.470173
iter  70 value 81.417945
iter  80 value 81.322030
iter  90 value 81.292764
iter 100 value 81.291576
final  value 81.291576 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.340734 
iter  10 value 94.061376
iter  20 value 93.978462
iter  30 value 87.005877
final  value 86.927375 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.394345 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.407265 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.560153 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.456002 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.598330 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.993411 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.401493 
final  value 94.027933 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.881716 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.206163 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.614812 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.540092 
iter  10 value 94.023571
final  value 94.023310 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.946103 
iter  10 value 94.032818
iter  20 value 93.299877
final  value 93.299763 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.051663 
final  value 93.893849 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.533222 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.668674 
iter  10 value 86.509124
iter  20 value 86.364264
iter  30 value 84.923559
final  value 84.898025 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.222560 
iter  10 value 94.044410
iter  20 value 92.279487
iter  30 value 86.371343
iter  40 value 84.584942
iter  50 value 84.376580
iter  60 value 82.946958
iter  70 value 82.145875
iter  80 value 82.121015
final  value 82.118030 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.368186 
iter  10 value 94.068967
iter  20 value 93.779840
iter  30 value 86.463307
iter  40 value 86.132329
iter  50 value 83.619673
iter  60 value 82.824958
iter  70 value 82.728758
final  value 82.728756 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.766268 
iter  10 value 92.773203
iter  20 value 86.773239
iter  30 value 84.984159
iter  40 value 84.084571
iter  50 value 83.936535
iter  60 value 83.449054
iter  70 value 83.183003
iter  80 value 83.109403
final  value 83.109381 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.212726 
iter  10 value 93.790622
iter  20 value 92.608033
iter  30 value 92.275837
iter  40 value 85.620700
iter  50 value 84.599554
iter  60 value 83.222267
iter  70 value 82.668758
iter  80 value 81.345751
iter  90 value 81.115360
iter 100 value 80.909412
final  value 80.909412 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.596381 
iter  10 value 94.059493
iter  20 value 92.814336
iter  30 value 88.801751
iter  40 value 83.879230
iter  50 value 83.434071
iter  60 value 82.359996
iter  70 value 82.134954
iter  80 value 81.378747
iter  90 value 80.783870
iter 100 value 80.751648
final  value 80.751648 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.971176 
iter  10 value 94.191540
iter  20 value 84.849173
iter  30 value 83.824116
iter  40 value 83.493476
iter  50 value 82.183967
iter  60 value 81.472110
iter  70 value 81.073700
iter  80 value 80.730554
iter  90 value 80.129586
iter 100 value 79.684308
final  value 79.684308 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.798375 
iter  10 value 93.914988
iter  20 value 88.109808
iter  30 value 86.781958
iter  40 value 83.928636
iter  50 value 82.867938
iter  60 value 81.047165
iter  70 value 80.719426
iter  80 value 80.557919
iter  90 value 80.545845
iter 100 value 80.498238
final  value 80.498238 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.026282 
iter  10 value 93.890744
iter  20 value 91.197028
iter  30 value 88.731236
iter  40 value 85.527500
iter  50 value 84.027911
iter  60 value 82.208305
iter  70 value 80.254697
iter  80 value 79.874894
iter  90 value 79.682166
iter 100 value 79.651465
final  value 79.651465 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.523517 
iter  10 value 94.015124
iter  20 value 91.456223
iter  30 value 85.506093
iter  40 value 83.801026
iter  50 value 83.721046
iter  60 value 83.538551
iter  70 value 82.991022
iter  80 value 81.163145
iter  90 value 80.319994
iter 100 value 80.191121
final  value 80.191121 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.102665 
iter  10 value 96.644934
iter  20 value 86.971395
iter  30 value 86.745080
iter  40 value 85.432545
iter  50 value 81.603117
iter  60 value 80.762434
iter  70 value 79.964248
iter  80 value 79.744143
iter  90 value 79.635732
iter 100 value 79.568517
final  value 79.568517 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.609495 
iter  10 value 93.715243
iter  20 value 83.815455
iter  30 value 83.258113
iter  40 value 83.163545
iter  50 value 81.463075
iter  60 value 80.163936
iter  70 value 79.726979
iter  80 value 79.619584
iter  90 value 79.541373
iter 100 value 79.405175
final  value 79.405175 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.791147 
iter  10 value 94.237486
iter  20 value 88.676450
iter  30 value 87.053146
iter  40 value 85.328015
iter  50 value 80.105480
iter  60 value 79.513582
iter  70 value 79.353977
iter  80 value 79.230695
iter  90 value 79.155421
iter 100 value 78.976831
final  value 78.976831 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.906687 
iter  10 value 95.531997
iter  20 value 93.794727
iter  30 value 85.557625
iter  40 value 84.308615
iter  50 value 83.738857
iter  60 value 83.231422
iter  70 value 81.933804
iter  80 value 80.546972
iter  90 value 80.366052
iter 100 value 80.207147
final  value 80.207147 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.422177 
iter  10 value 94.229408
iter  20 value 88.764544
iter  30 value 87.036548
iter  40 value 84.473296
iter  50 value 81.066737
iter  60 value 80.500381
iter  70 value 79.950317
iter  80 value 79.894725
iter  90 value 79.866478
iter 100 value 79.521763
final  value 79.521763 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.717432 
iter  10 value 93.826469
iter  20 value 88.751238
iter  30 value 87.264678
iter  40 value 85.968056
iter  50 value 82.049029
iter  60 value 80.964910
iter  70 value 80.879575
iter  80 value 80.652400
iter  90 value 80.002092
iter 100 value 79.742330
final  value 79.742330 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.639955 
final  value 94.054553 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.708491 
iter  10 value 90.586029
iter  20 value 86.263730
iter  30 value 86.256012
iter  40 value 86.254893
iter  50 value 86.206294
iter  60 value 85.002602
iter  70 value 84.769682
iter  80 value 84.768267
final  value 84.767193 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.362856 
iter  10 value 94.054501
iter  20 value 94.052936
iter  30 value 93.604784
iter  30 value 93.604784
iter  30 value 93.604784
final  value 93.604784 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.071192 
final  value 94.054564 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.778587 
iter  10 value 94.054494
iter  20 value 94.052914
iter  30 value 85.728356
iter  40 value 84.733885
iter  50 value 84.435730
iter  60 value 84.282445
iter  70 value 84.277418
iter  80 value 84.276574
final  value 84.276572 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.619387 
iter  10 value 94.057996
iter  20 value 94.050904
iter  30 value 93.677879
iter  40 value 93.604690
iter  50 value 93.333455
final  value 93.328824 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.915297 
iter  10 value 94.056289
iter  20 value 92.463933
iter  30 value 89.077221
iter  40 value 89.074624
iter  50 value 87.024345
iter  60 value 86.475625
iter  70 value 86.473900
iter  80 value 86.468051
iter  90 value 86.449109
iter 100 value 86.448317
final  value 86.448317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.485083 
iter  10 value 93.949327
iter  20 value 93.804831
iter  30 value 93.335429
iter  40 value 93.304554
iter  50 value 90.537028
iter  60 value 81.080477
iter  70 value 80.976635
iter  80 value 80.882965
iter  90 value 80.872671
iter 100 value 79.110231
final  value 79.110231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.308911 
iter  10 value 94.042228
iter  20 value 94.036913
iter  30 value 94.034077
iter  40 value 94.033433
iter  50 value 94.030988
iter  60 value 85.630707
iter  70 value 82.166185
iter  80 value 81.561265
iter  90 value 80.967621
iter 100 value 80.679539
final  value 80.679539 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.279545 
iter  10 value 94.057860
iter  20 value 93.874605
iter  30 value 84.613358
iter  40 value 84.612143
iter  50 value 84.611876
iter  60 value 84.610509
iter  70 value 83.768478
iter  80 value 83.745856
iter  90 value 83.743343
final  value 83.743011 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.602379 
iter  10 value 92.546997
iter  20 value 92.036264
iter  30 value 92.029902
iter  40 value 91.957561
iter  50 value 91.956252
iter  60 value 91.794383
iter  70 value 91.654717
final  value 91.654704 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.909164 
iter  10 value 94.035488
iter  20 value 94.033825
iter  30 value 94.032890
iter  40 value 92.340203
iter  50 value 91.953479
final  value 91.953449 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.056985 
iter  10 value 92.941245
iter  20 value 92.669599
iter  30 value 92.661810
iter  40 value 92.661178
iter  50 value 92.656706
final  value 92.656662 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.407815 
iter  10 value 93.680120
iter  20 value 93.676632
iter  30 value 93.493502
iter  40 value 85.127329
iter  50 value 82.502034
iter  60 value 82.427944
final  value 82.426620 
converged
Fitting Repeat 5 

# weights:  507
initial  value 127.390155 
iter  10 value 94.043953
iter  20 value 94.027262
iter  30 value 92.286852
iter  40 value 86.748159
iter  50 value 86.316791
iter  60 value 86.167774
iter  70 value 86.149587
iter  80 value 85.924626
iter  90 value 82.939841
iter 100 value 82.127541
final  value 82.127541 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 156.098859 
iter  10 value 117.689361
iter  20 value 114.494486
iter  30 value 111.863760
iter  40 value 110.704330
iter  50 value 105.674862
iter  60 value 103.585587
iter  70 value 103.178662
iter  80 value 102.857231
iter  90 value 102.079981
iter 100 value 101.919655
final  value 101.919655 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 153.729344 
iter  10 value 117.848777
iter  20 value 117.425886
iter  30 value 113.947498
iter  40 value 112.693389
iter  50 value 107.800053
iter  60 value 106.955899
iter  70 value 106.191884
iter  80 value 105.768225
iter  90 value 102.432937
iter 100 value 101.475758
final  value 101.475758 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 134.033599 
iter  10 value 110.065016
iter  20 value 107.922226
iter  30 value 105.031648
iter  40 value 103.566370
iter  50 value 101.649984
iter  60 value 100.932628
iter  70 value 100.630835
iter  80 value 100.478577
iter  90 value 100.320636
iter 100 value 100.185660
final  value 100.185660 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.449983 
iter  10 value 117.565995
iter  20 value 107.392827
iter  30 value 105.598220
iter  40 value 104.248923
iter  50 value 103.642866
iter  60 value 102.905690
iter  70 value 102.195008
iter  80 value 101.897120
iter  90 value 101.758835
iter 100 value 101.701252
final  value 101.701252 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.838399 
iter  10 value 119.996116
iter  20 value 111.533293
iter  30 value 108.048637
iter  40 value 106.283547
iter  50 value 103.663443
iter  60 value 102.190946
iter  70 value 101.802005
iter  80 value 101.418185
iter  90 value 100.965808
iter 100 value 100.675080
final  value 100.675080 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Dec 20 22:24:17 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 
 51.662   1.783  56.058