##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* 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 ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 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 loading without being on the library search path ... 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
Unknown package ‘ftrCOOL’ in Rd xrefs
* 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       33.299  0.362  33.662
FSmethod      32.845  0.641  33.487
corr_plot     32.215  0.190  32.407
pred_ensembel 13.559  0.304  10.408
enrichfindP    0.589  0.030   8.787
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 101.208721 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.378740 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.231343 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.752261 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.057741 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.581434 
iter  10 value 94.062288
final  value 94.062249 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.083501 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.685144 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.247211 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.269077 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.872546 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.424771 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.354424 
iter  10 value 89.900148
iter  20 value 85.424705
iter  30 value 85.424428
final  value 85.424426 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.056099 
iter  10 value 94.443207
final  value 94.443183 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.665031 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.635352 
iter  10 value 94.358095
iter  20 value 92.335383
iter  30 value 92.070401
iter  40 value 91.799490
final  value 91.784980 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.306489 
iter  10 value 94.237841
iter  20 value 91.956176
iter  30 value 85.959411
iter  40 value 84.271890
iter  50 value 83.988170
iter  60 value 83.138586
iter  70 value 82.736341
final  value 82.729630 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.087029 
iter  10 value 94.506233
iter  20 value 90.700031
iter  30 value 85.995591
iter  40 value 84.870687
iter  50 value 83.948011
iter  60 value 83.802000
iter  70 value 83.799248
iter  80 value 83.795800
final  value 83.795799 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.020472 
iter  10 value 94.486938
iter  20 value 88.169019
iter  30 value 87.145356
iter  40 value 85.753264
iter  50 value 85.656502
iter  60 value 84.511977
iter  70 value 84.192087
final  value 84.169219 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.797836 
iter  10 value 94.337260
iter  20 value 88.729632
iter  30 value 85.429224
iter  40 value 84.662767
iter  50 value 84.206445
iter  60 value 83.947080
iter  70 value 83.795922
final  value 83.795799 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.835189 
iter  10 value 93.286334
iter  20 value 87.972789
iter  30 value 86.544735
iter  40 value 86.398827
iter  50 value 83.960610
iter  60 value 82.398819
iter  70 value 81.494716
iter  80 value 81.194326
iter  90 value 81.144073
iter 100 value 81.134257
final  value 81.134257 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.865669 
iter  10 value 94.493330
iter  20 value 87.082575
iter  30 value 86.890705
iter  40 value 85.953915
iter  50 value 84.897627
iter  60 value 84.355004
iter  70 value 84.171262
iter  80 value 82.943947
iter  90 value 82.499384
iter 100 value 82.359224
final  value 82.359224 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.098397 
iter  10 value 94.866478
iter  20 value 91.820999
iter  30 value 87.373884
iter  40 value 85.962032
iter  50 value 84.745018
iter  60 value 84.311891
iter  70 value 83.796340
iter  80 value 83.716444
iter  90 value 83.703691
iter 100 value 83.457192
final  value 83.457192 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 134.687134 
iter  10 value 94.257741
iter  20 value 86.855012
iter  30 value 85.137534
iter  40 value 84.599485
iter  50 value 83.720620
iter  60 value 82.660432
iter  70 value 82.285733
iter  80 value 81.665705
iter  90 value 81.392618
iter 100 value 81.158751
final  value 81.158751 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.387662 
iter  10 value 94.411032
iter  20 value 91.998870
iter  30 value 88.117772
iter  40 value 87.159396
iter  50 value 86.086417
iter  60 value 82.478321
iter  70 value 81.714680
iter  80 value 81.287770
iter  90 value 81.163754
iter 100 value 81.092619
final  value 81.092619 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.926118 
iter  10 value 95.991097
iter  20 value 90.772670
iter  30 value 85.023324
iter  40 value 84.552321
iter  50 value 83.774660
iter  60 value 81.884852
iter  70 value 81.234403
iter  80 value 81.042492
iter  90 value 80.959441
iter 100 value 80.772771
final  value 80.772771 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.863452 
iter  10 value 94.326920
iter  20 value 91.423517
iter  30 value 86.598421
iter  40 value 84.996285
iter  50 value 83.724850
iter  60 value 82.978564
iter  70 value 82.622165
iter  80 value 82.114419
iter  90 value 81.699405
iter 100 value 81.278659
final  value 81.278659 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.333766 
iter  10 value 96.570330
iter  20 value 92.269257
iter  30 value 90.262779
iter  40 value 87.689973
iter  50 value 84.807140
iter  60 value 83.870637
iter  70 value 83.697318
iter  80 value 82.820797
iter  90 value 82.464384
iter 100 value 81.950950
final  value 81.950950 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.230185 
iter  10 value 94.356469
iter  20 value 90.259765
iter  30 value 86.073059
iter  40 value 84.474095
iter  50 value 83.639958
iter  60 value 82.253249
iter  70 value 81.946535
iter  80 value 81.533306
iter  90 value 81.146696
iter 100 value 81.051180
final  value 81.051180 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.003022 
iter  10 value 94.384041
iter  20 value 87.876570
iter  30 value 86.446852
iter  40 value 85.871824
iter  50 value 84.758997
iter  60 value 83.107872
iter  70 value 82.693135
iter  80 value 82.339640
iter  90 value 82.176378
iter 100 value 81.606468
final  value 81.606468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.582885 
final  value 94.485772 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.182523 
final  value 94.485696 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.726421 
final  value 94.485500 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.083802 
iter  10 value 94.485818
iter  20 value 94.484220
final  value 94.484215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.279648 
final  value 94.485890 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.445496 
iter  10 value 94.489230
iter  20 value 94.484405
iter  30 value 93.697109
iter  40 value 91.205972
final  value 91.205871 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.905071 
iter  10 value 94.471837
iter  20 value 94.467172
final  value 94.467096 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.791432 
iter  10 value 94.488896
iter  20 value 94.227914
iter  30 value 92.963478
iter  40 value 92.892502
final  value 92.892244 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.026344 
iter  10 value 93.787848
iter  20 value 93.752668
iter  30 value 93.748525
iter  40 value 93.141156
iter  50 value 86.465874
iter  60 value 86.234248
iter  70 value 85.336757
iter  80 value 82.860120
iter  90 value 82.455779
iter 100 value 82.331617
final  value 82.331617 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.793558 
iter  10 value 94.474812
iter  20 value 94.252088
iter  30 value 86.095141
iter  40 value 84.968936
iter  50 value 84.918405
iter  60 value 84.875447
iter  70 value 84.845918
iter  80 value 84.839140
final  value 84.837853 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.669881 
iter  10 value 94.492817
iter  20 value 94.343077
iter  30 value 85.222794
iter  40 value 84.274557
iter  50 value 84.272952
final  value 84.272950 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.100991 
iter  10 value 94.490989
iter  20 value 90.038586
iter  30 value 84.757802
iter  40 value 83.057141
iter  50 value 82.687761
iter  60 value 82.669563
iter  70 value 82.407105
iter  80 value 82.254859
iter  90 value 82.246443
iter 100 value 82.246073
final  value 82.246073 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.754704 
iter  10 value 94.477652
iter  20 value 94.469945
iter  30 value 92.197961
iter  40 value 86.038098
iter  50 value 85.384903
iter  60 value 85.384510
iter  70 value 85.313804
iter  80 value 84.408365
iter  90 value 83.938065
iter 100 value 83.936647
final  value 83.936647 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.037117 
iter  10 value 92.792411
iter  20 value 92.756388
iter  30 value 91.668256
iter  40 value 91.312846
iter  50 value 91.304800
iter  60 value 91.255692
iter  70 value 91.250139
iter  80 value 91.249488
final  value 91.249155 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.138769 
iter  10 value 94.474654
iter  20 value 94.467076
iter  30 value 94.187209
iter  40 value 88.159750
iter  50 value 85.467059
iter  60 value 85.037775
iter  70 value 84.645150
final  value 84.641071 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.314610 
iter  10 value 93.794164
iter  20 value 93.785799
final  value 93.785768 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.153177 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.095280 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.956220 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.339734 
iter  10 value 83.587750
iter  20 value 78.918380
iter  30 value 78.561974
iter  40 value 78.221093
iter  50 value 78.218237
iter  60 value 78.218183
final  value 78.218178 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.970141 
iter  10 value 90.072778
iter  20 value 90.003475
final  value 90.002876 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.740489 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.266668 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.074620 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.309524 
iter  10 value 93.810010
iter  10 value 93.810010
iter  10 value 93.810010
final  value 93.810010 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.232198 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.402897 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.849184 
iter  10 value 90.648800
iter  20 value 89.986928
iter  30 value 89.985210
final  value 89.985186 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.549369 
iter  10 value 91.091175
final  value 91.090953 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.123121 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.375645 
iter  10 value 94.054988
iter  20 value 93.894184
iter  30 value 92.515711
iter  40 value 86.635139
iter  50 value 82.392106
iter  60 value 81.437447
iter  70 value 80.398713
iter  80 value 80.364773
final  value 80.361652 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.219810 
iter  10 value 94.056807
iter  20 value 93.678207
iter  30 value 85.822297
iter  40 value 82.754322
iter  50 value 80.396631
iter  60 value 79.678670
iter  70 value 79.530782
iter  80 value 79.505592
iter  90 value 79.494184
final  value 79.494135 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.382402 
iter  10 value 93.998037
iter  20 value 91.483556
iter  30 value 88.367060
iter  40 value 86.591129
iter  50 value 84.560796
iter  60 value 80.887882
iter  70 value 77.482678
iter  80 value 76.772429
iter  90 value 76.092658
iter 100 value 75.748235
final  value 75.748235 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.524508 
iter  10 value 93.986495
iter  20 value 93.529129
iter  30 value 83.391975
iter  40 value 80.883169
iter  50 value 80.571942
iter  60 value 80.229051
iter  70 value 80.193680
iter  80 value 79.993741
iter  90 value 76.205484
iter 100 value 75.939495
final  value 75.939495 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.614987 
iter  10 value 92.327402
iter  20 value 82.031575
iter  30 value 80.558335
iter  40 value 80.097404
iter  50 value 79.692075
iter  60 value 79.529184
iter  70 value 79.509086
final  value 79.508798 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.172902 
iter  10 value 94.059854
iter  20 value 93.972999
iter  30 value 84.441959
iter  40 value 76.928776
iter  50 value 76.617798
iter  60 value 76.182677
iter  70 value 76.042626
iter  80 value 75.840488
iter  90 value 75.763361
final  value 75.763274 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.519225 
iter  10 value 92.212763
iter  20 value 91.958905
iter  30 value 81.846810
iter  40 value 81.478655
iter  50 value 80.740318
iter  60 value 79.723567
iter  70 value 77.426457
iter  80 value 76.576880
iter  90 value 75.527934
iter 100 value 75.266750
final  value 75.266750 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.338616 
iter  10 value 94.212038
iter  20 value 93.154407
iter  30 value 83.196960
iter  40 value 81.511495
iter  50 value 80.302537
iter  60 value 78.944515
iter  70 value 75.791565
iter  80 value 75.191911
iter  90 value 74.785561
iter 100 value 74.670685
final  value 74.670685 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.886392 
iter  10 value 86.612701
iter  20 value 79.837152
iter  30 value 79.673062
iter  40 value 77.762530
iter  50 value 76.753371
iter  60 value 76.695049
iter  70 value 76.537516
iter  80 value 76.313902
iter  90 value 76.225438
iter 100 value 76.153764
final  value 76.153764 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.048774 
iter  10 value 93.595586
iter  20 value 88.269279
iter  30 value 82.158843
iter  40 value 78.735308
iter  50 value 77.942803
iter  60 value 76.712042
iter  70 value 76.383988
iter  80 value 75.755905
iter  90 value 75.477363
iter 100 value 74.994026
final  value 74.994026 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.234101 
iter  10 value 93.054539
iter  20 value 85.089506
iter  30 value 81.054191
iter  40 value 77.997463
iter  50 value 76.339363
iter  60 value 76.099431
iter  70 value 75.792331
iter  80 value 75.758413
iter  90 value 75.754091
iter 100 value 75.705216
final  value 75.705216 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.426838 
iter  10 value 94.817161
iter  20 value 80.213643
iter  30 value 78.673430
iter  40 value 76.802060
iter  50 value 76.703412
iter  60 value 76.375625
iter  70 value 76.174113
iter  80 value 76.154496
iter  90 value 76.145109
iter 100 value 76.020074
final  value 76.020074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.346708 
iter  10 value 93.975493
iter  20 value 83.747957
iter  30 value 82.968293
iter  40 value 79.718737
iter  50 value 77.531702
iter  60 value 75.724246
iter  70 value 75.369571
iter  80 value 75.289647
iter  90 value 75.120295
iter 100 value 74.952111
final  value 74.952111 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.105183 
iter  10 value 92.740241
iter  20 value 83.386436
iter  30 value 83.199415
iter  40 value 82.366316
iter  50 value 79.818265
iter  60 value 78.099618
iter  70 value 75.687504
iter  80 value 74.676236
iter  90 value 74.407851
iter 100 value 73.863936
final  value 73.863936 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.564449 
iter  10 value 93.898567
iter  20 value 85.883674
iter  30 value 79.502506
iter  40 value 78.646903
iter  50 value 77.558806
iter  60 value 76.761706
iter  70 value 75.413689
iter  80 value 74.969177
iter  90 value 74.776488
iter 100 value 74.302380
final  value 74.302380 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.445667 
final  value 94.054941 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.826599 
final  value 94.054406 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.730872 
final  value 94.054518 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.344567 
final  value 94.054620 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.737672 
final  value 94.054352 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.929658 
iter  10 value 93.807696
iter  20 value 93.802068
iter  30 value 93.797201
iter  40 value 93.796768
iter  50 value 93.796145
iter  60 value 93.795415
iter  70 value 93.790776
iter  80 value 93.783754
iter  90 value 93.780714
iter 100 value 88.659523
final  value 88.659523 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.877783 
iter  10 value 93.653776
iter  20 value 91.262405
iter  30 value 78.153886
iter  40 value 77.563162
iter  50 value 77.560809
iter  60 value 77.558295
iter  70 value 77.461575
final  value 77.448138 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.532814 
iter  10 value 94.057904
iter  20 value 94.053463
iter  30 value 92.963213
iter  40 value 91.255708
iter  50 value 91.254481
iter  60 value 89.486221
iter  70 value 82.198511
iter  80 value 80.125852
iter  90 value 80.078109
iter 100 value 80.070189
final  value 80.070189 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.193706 
iter  10 value 94.056895
iter  20 value 90.069522
iter  30 value 89.279751
final  value 89.278296 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.159299 
iter  10 value 94.058219
iter  20 value 94.053379
iter  30 value 93.971891
iter  40 value 81.643124
iter  50 value 81.628982
iter  60 value 81.591117
iter  70 value 81.497145
iter  80 value 81.179908
iter  90 value 79.223602
iter 100 value 78.470637
final  value 78.470637 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.321323 
iter  10 value 93.844139
iter  20 value 93.837509
iter  30 value 89.553909
iter  40 value 84.395144
iter  40 value 84.395143
final  value 84.395108 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.128076 
iter  10 value 94.062267
iter  20 value 93.747954
iter  30 value 83.368664
iter  40 value 79.702161
iter  50 value 78.880967
iter  60 value 77.808749
iter  70 value 77.801541
iter  80 value 77.798413
iter  90 value 77.785026
iter 100 value 77.783026
final  value 77.783026 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.901826 
iter  10 value 94.061110
iter  20 value 94.001881
iter  30 value 91.592896
iter  40 value 80.424526
iter  50 value 76.572431
iter  60 value 75.786981
iter  70 value 75.761092
final  value 75.760434 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.093095 
iter  10 value 93.844607
iter  20 value 93.315467
iter  30 value 92.260616
iter  40 value 92.225399
iter  50 value 92.223580
final  value 92.223569 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.874662 
iter  10 value 89.467950
iter  20 value 87.049893
iter  30 value 86.278434
iter  40 value 86.217257
iter  50 value 86.206862
iter  60 value 86.206067
iter  70 value 82.817951
iter  80 value 82.280290
iter  90 value 82.033065
iter 100 value 82.029075
final  value 82.029075 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.066682 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.689972 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.429214 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.811202 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.033042 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.816125 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.925957 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.435989 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.101419 
iter  10 value 93.553367
iter  20 value 93.552498
final  value 93.552493 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.902204 
final  value 94.313817 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.182673 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.211265 
iter  10 value 93.986292
final  value 93.976244 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.031175 
final  value 94.381567 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.672723 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.337635 
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 97.830314 
iter  10 value 94.540697
iter  20 value 94.462336
iter  30 value 92.082177
iter  40 value 90.570534
iter  50 value 90.469755
iter  60 value 87.669343
iter  70 value 86.571392
iter  80 value 86.253551
iter  90 value 85.497554
iter 100 value 84.580872
final  value 84.580872 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.598174 
iter  10 value 94.481227
iter  20 value 94.142371
iter  30 value 94.086813
iter  40 value 93.615429
iter  50 value 90.734714
iter  60 value 88.750306
iter  70 value 87.566884
iter  80 value 87.142036
iter  90 value 86.744929
iter 100 value 85.515030
final  value 85.515030 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 114.073852 
iter  10 value 90.220522
iter  20 value 88.318205
iter  30 value 87.761343
iter  40 value 86.797568
iter  50 value 86.539083
iter  60 value 86.503145
final  value 86.503071 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.455201 
iter  10 value 93.937507
iter  20 value 90.147374
iter  30 value 88.319703
iter  40 value 87.291177
iter  50 value 86.708454
iter  60 value 85.216105
iter  70 value 84.973782
iter  80 value 84.574985
iter  90 value 84.560251
final  value 84.559656 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.619117 
iter  10 value 94.488555
iter  20 value 94.293059
iter  30 value 94.123403
iter  40 value 94.078499
iter  50 value 92.284912
iter  60 value 91.470194
iter  70 value 88.806847
iter  80 value 88.419466
iter  90 value 88.031865
iter 100 value 88.013431
final  value 88.013431 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 130.072066 
iter  10 value 94.596614
iter  20 value 92.311614
iter  30 value 89.672007
iter  40 value 87.967073
iter  50 value 87.469239
iter  60 value 86.049788
iter  70 value 85.073502
iter  80 value 84.567534
iter  90 value 84.213582
iter 100 value 83.754357
final  value 83.754357 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.076236 
iter  10 value 93.675500
iter  20 value 89.369115
iter  30 value 88.140706
iter  40 value 87.783176
iter  50 value 86.340728
iter  60 value 85.695814
iter  70 value 84.912513
iter  80 value 84.094687
iter  90 value 83.265118
iter 100 value 83.034315
final  value 83.034315 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.659086 
iter  10 value 94.519665
iter  20 value 94.085924
iter  30 value 93.741287
iter  40 value 88.892013
iter  50 value 86.075102
iter  60 value 84.667422
iter  70 value 84.295178
iter  80 value 83.990442
iter  90 value 83.877032
iter 100 value 83.797423
final  value 83.797423 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.989808 
iter  10 value 94.486636
iter  20 value 92.999639
iter  30 value 89.045176
iter  40 value 88.140221
iter  50 value 86.992485
iter  60 value 85.502033
iter  70 value 84.718598
iter  80 value 83.817595
iter  90 value 83.639889
iter 100 value 83.422908
final  value 83.422908 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.573169 
iter  10 value 93.493760
iter  20 value 88.597646
iter  30 value 88.112327
iter  40 value 86.664177
iter  50 value 85.422498
iter  60 value 84.849114
iter  70 value 84.402581
iter  80 value 84.224886
iter  90 value 83.943075
iter 100 value 83.244468
final  value 83.244468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.572131 
iter  10 value 94.355767
iter  20 value 89.881565
iter  30 value 87.789335
iter  40 value 85.055102
iter  50 value 84.156561
iter  60 value 83.828875
iter  70 value 83.629940
iter  80 value 83.306053
iter  90 value 83.122311
iter 100 value 82.974745
final  value 82.974745 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.677180 
iter  10 value 94.495759
iter  20 value 90.522368
iter  30 value 89.732743
iter  40 value 89.025040
iter  50 value 87.082327
iter  60 value 84.979304
iter  70 value 83.842863
iter  80 value 83.340907
iter  90 value 83.176295
iter 100 value 82.944528
final  value 82.944528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.289338 
iter  10 value 94.693918
iter  20 value 94.238189
iter  30 value 93.653336
iter  40 value 92.122318
iter  50 value 90.824786
iter  60 value 86.797834
iter  70 value 84.989081
iter  80 value 84.395792
iter  90 value 84.154035
iter 100 value 83.746891
final  value 83.746891 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.297287 
iter  10 value 98.970774
iter  20 value 94.276383
iter  30 value 90.715499
iter  40 value 88.471937
iter  50 value 86.153491
iter  60 value 85.065133
iter  70 value 84.159191
iter  80 value 83.950285
iter  90 value 83.905886
iter 100 value 83.499502
final  value 83.499502 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.577931 
iter  10 value 97.174170
iter  20 value 93.735842
iter  30 value 93.486273
iter  40 value 91.759770
iter  50 value 89.508390
iter  60 value 87.623583
iter  70 value 87.062499
iter  80 value 86.783584
iter  90 value 85.567655
iter 100 value 84.857261
final  value 84.857261 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.691958 
final  value 94.485879 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.095882 
final  value 94.485741 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.213031 
final  value 94.485767 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.403031 
iter  10 value 94.486068
iter  20 value 94.072596
iter  30 value 87.642351
iter  40 value 87.312779
iter  50 value 87.307706
iter  50 value 87.307705
iter  50 value 87.307705
final  value 87.307705 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.664769 
final  value 94.486121 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.630216 
iter  10 value 94.032027
iter  20 value 94.028424
iter  30 value 93.954380
iter  40 value 90.453251
iter  50 value 87.341750
iter  60 value 86.352502
iter  70 value 86.347083
iter  80 value 84.878524
final  value 84.877247 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.302547 
iter  10 value 94.488605
iter  20 value 94.278659
iter  30 value 88.355074
iter  40 value 86.373164
iter  50 value 86.355525
iter  60 value 86.352852
iter  70 value 86.352802
iter  80 value 86.351869
iter  90 value 86.323367
final  value 86.321915 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.423058 
iter  10 value 94.032105
iter  20 value 93.979094
final  value 93.977000 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.673741 
iter  10 value 94.489175
iter  20 value 94.484696
iter  30 value 89.454838
final  value 87.868248 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.474076 
iter  10 value 94.318380
iter  20 value 90.625279
iter  30 value 87.973036
iter  40 value 86.431456
iter  50 value 86.329675
iter  60 value 85.792144
iter  70 value 85.140698
final  value 85.080167 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.367297 
iter  10 value 94.491794
iter  20 value 94.409254
iter  30 value 94.052624
iter  30 value 94.052624
iter  30 value 94.052624
final  value 94.052624 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.749439 
iter  10 value 94.749910
iter  20 value 94.349523
iter  30 value 94.263381
iter  40 value 94.033090
iter  50 value 90.225184
iter  60 value 89.142809
iter  70 value 88.924513
iter  80 value 88.886861
iter  90 value 86.601757
iter 100 value 83.980497
final  value 83.980497 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.396168 
iter  10 value 94.492200
iter  20 value 94.483103
iter  30 value 94.026915
final  value 94.026848 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.065125 
iter  10 value 94.492256
iter  20 value 94.421315
iter  30 value 90.729819
iter  40 value 88.886150
iter  50 value 88.773900
iter  60 value 88.769981
final  value 88.769770 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.678424 
iter  10 value 93.409846
iter  20 value 93.129872
iter  30 value 93.124083
iter  40 value 93.123205
iter  50 value 93.041850
iter  60 value 92.978292
final  value 92.978066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.672888 
final  value 93.900000 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.343281 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.307134 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.366622 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.022149 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.015732 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.576172 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.828376 
final  value 94.052873 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.940442 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.180648 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.045322 
final  value 93.782638 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.128565 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.268273 
final  value 93.782638 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.395580 
iter  10 value 92.591748
iter  20 value 92.205084
iter  30 value 92.204428
final  value 92.204422 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.054934 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.832863 
iter  10 value 94.197836
iter  20 value 93.859650
iter  30 value 87.328955
iter  40 value 85.029614
iter  50 value 84.351314
iter  60 value 84.194863
final  value 84.193920 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.486547 
iter  10 value 93.661000
iter  20 value 88.790799
iter  30 value 87.202523
iter  40 value 85.651115
iter  50 value 84.966026
iter  60 value 84.419753
iter  70 value 84.200980
iter  80 value 84.194022
iter  90 value 84.193920
iter  90 value 84.193920
iter  90 value 84.193920
final  value 84.193920 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.347473 
iter  10 value 94.055316
iter  20 value 93.632319
iter  30 value 93.353620
iter  40 value 89.220571
iter  50 value 86.827573
iter  60 value 86.348430
iter  70 value 84.470384
iter  80 value 84.194673
final  value 84.193920 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.340621 
iter  10 value 94.136017
iter  20 value 94.053974
iter  30 value 93.185650
iter  40 value 88.350749
iter  50 value 86.212695
iter  60 value 84.776394
iter  70 value 82.736052
iter  80 value 80.795283
iter  90 value 80.524963
iter 100 value 80.516913
final  value 80.516913 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.654188 
iter  10 value 94.002562
iter  20 value 87.282625
iter  30 value 84.124178
iter  40 value 83.847954
iter  50 value 82.150642
iter  60 value 81.530984
iter  70 value 80.768983
iter  80 value 80.521098
final  value 80.516839 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.327472 
iter  10 value 94.057368
iter  20 value 93.271064
iter  30 value 86.764975
iter  40 value 83.375769
iter  50 value 82.429438
iter  60 value 81.726977
iter  70 value 81.494393
iter  80 value 80.624234
iter  90 value 80.383271
iter 100 value 80.220246
final  value 80.220246 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.552282 
iter  10 value 94.070328
iter  20 value 93.823699
iter  30 value 93.610479
iter  40 value 88.684805
iter  50 value 86.809570
iter  60 value 83.946361
iter  70 value 81.535403
iter  80 value 81.116558
iter  90 value 80.354123
iter 100 value 79.685618
final  value 79.685618 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.213214 
iter  10 value 93.740827
iter  20 value 90.108578
iter  30 value 82.587371
iter  40 value 82.000197
iter  50 value 81.596202
iter  60 value 81.146634
iter  70 value 80.448972
iter  80 value 79.926266
iter  90 value 79.668826
iter 100 value 79.600110
final  value 79.600110 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.335685 
iter  10 value 94.081944
iter  20 value 90.085632
iter  30 value 87.408231
iter  40 value 86.388080
iter  50 value 82.561439
iter  60 value 80.436113
iter  70 value 79.853829
iter  80 value 79.720629
iter  90 value 79.407185
iter 100 value 79.373755
final  value 79.373755 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.491064 
iter  10 value 94.068531
iter  20 value 94.029614
iter  30 value 88.453984
iter  40 value 86.609535
iter  50 value 85.255658
iter  60 value 84.859826
iter  70 value 84.786935
iter  80 value 82.835084
iter  90 value 81.874399
iter 100 value 81.791504
final  value 81.791504 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.521951 
iter  10 value 93.907230
iter  20 value 86.389471
iter  30 value 84.900791
iter  40 value 84.690861
iter  50 value 83.885241
iter  60 value 83.276507
iter  70 value 83.186281
iter  80 value 82.454668
iter  90 value 80.659151
iter 100 value 80.155003
final  value 80.155003 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.757387 
iter  10 value 89.015397
iter  20 value 84.734255
iter  30 value 82.399098
iter  40 value 81.238012
iter  50 value 81.004366
iter  60 value 80.647188
iter  70 value 80.223988
iter  80 value 79.976114
iter  90 value 79.649529
iter 100 value 79.555735
final  value 79.555735 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.063774 
iter  10 value 94.758347
iter  20 value 87.822006
iter  30 value 85.243605
iter  40 value 84.730155
iter  50 value 83.858368
iter  60 value 82.991128
iter  70 value 81.679656
iter  80 value 80.464701
iter  90 value 79.604761
iter 100 value 79.234727
final  value 79.234727 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.096475 
iter  10 value 96.009012
iter  20 value 94.024302
iter  30 value 89.116157
iter  40 value 86.161933
iter  50 value 82.413495
iter  60 value 81.076501
iter  70 value 80.228838
iter  80 value 79.826214
iter  90 value 79.777950
iter 100 value 79.690576
final  value 79.690576 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.996009 
iter  10 value 96.184305
iter  20 value 90.202509
iter  30 value 88.133221
iter  40 value 84.604422
iter  50 value 82.863080
iter  60 value 81.989980
iter  70 value 81.446089
iter  80 value 80.243513
iter  90 value 79.843703
iter 100 value 79.688470
final  value 79.688470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.586017 
final  value 94.034149 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.415647 
final  value 94.054699 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.522328 
final  value 94.054548 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.467294 
final  value 94.054487 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.798625 
final  value 94.054464 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.588655 
iter  10 value 94.057975
iter  20 value 94.052915
iter  30 value 93.631406
iter  40 value 93.601682
iter  50 value 92.913999
iter  60 value 91.891912
iter  70 value 91.492789
iter  80 value 86.645802
iter  90 value 81.304013
iter 100 value 80.706255
final  value 80.706255 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.585904 
iter  10 value 94.038384
iter  20 value 94.034279
final  value 94.033704 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.328890 
iter  10 value 92.044070
iter  20 value 92.040708
iter  30 value 92.037083
iter  40 value 91.753060
iter  50 value 89.588136
iter  60 value 81.846997
iter  70 value 81.557641
iter  80 value 81.479653
iter  90 value 81.427900
iter 100 value 81.415249
final  value 81.415249 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.345589 
iter  10 value 94.057613
iter  20 value 94.025581
iter  30 value 89.212474
iter  40 value 89.210500
iter  50 value 89.114996
iter  60 value 87.827572
iter  70 value 86.901093
iter  80 value 86.899823
iter  90 value 86.860964
iter 100 value 86.847345
final  value 86.847345 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.764325 
iter  10 value 94.057863
iter  20 value 93.098889
iter  30 value 86.281472
iter  40 value 83.073659
iter  50 value 82.638675
final  value 82.637289 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.555675 
iter  10 value 94.075502
iter  20 value 94.019794
iter  30 value 93.903473
iter  40 value 93.901945
final  value 93.900254 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.323371 
iter  10 value 94.062247
iter  20 value 94.027015
iter  30 value 91.427686
iter  40 value 90.179916
iter  50 value 90.176729
iter  60 value 87.750031
iter  70 value 81.972064
iter  80 value 81.599830
iter  90 value 81.419395
iter 100 value 81.324201
final  value 81.324201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.747757 
iter  10 value 94.060502
iter  20 value 93.843022
iter  30 value 93.624833
iter  40 value 85.964772
iter  50 value 84.348901
iter  60 value 84.314535
final  value 84.313098 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.709663 
iter  10 value 94.061057
iter  20 value 94.053194
iter  30 value 93.679907
iter  40 value 93.038264
iter  50 value 89.783500
iter  60 value 89.745477
final  value 89.745218 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.652050 
iter  10 value 94.061370
iter  20 value 94.051418
iter  30 value 92.151921
iter  40 value 91.302142
iter  50 value 91.253534
iter  60 value 90.016144
iter  70 value 84.536063
iter  80 value 84.056824
iter  90 value 83.898317
iter 100 value 81.276405
final  value 81.276405 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.934687 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.947310 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.542165 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.214006 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.380571 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.963348 
final  value 94.484214 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.154561 
iter  10 value 86.733813
iter  20 value 85.605402
final  value 85.604060 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.988018 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.432362 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.382312 
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.103410 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.712616 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.919698 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.168911 
iter  10 value 93.206252
iter  20 value 92.539920
iter  30 value 92.393371
iter  40 value 92.202600
final  value 92.202562 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.365417 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.281586 
iter  10 value 93.616445
iter  20 value 89.729816
iter  30 value 86.994130
iter  40 value 86.071140
iter  50 value 85.418735
iter  60 value 85.131702
iter  70 value 85.013406
final  value 85.007037 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.779996 
iter  10 value 94.502404
iter  20 value 93.565802
iter  30 value 88.700830
iter  40 value 88.341435
iter  50 value 87.678650
iter  60 value 84.786572
iter  70 value 84.724794
iter  80 value 84.713832
iter  90 value 84.663096
final  value 84.658073 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.757615 
iter  10 value 94.145394
iter  20 value 89.413288
iter  30 value 86.337387
iter  40 value 86.145798
iter  50 value 85.834662
iter  60 value 85.777190
iter  70 value 85.761177
iter  70 value 85.761176
iter  70 value 85.761176
final  value 85.761176 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.104271 
iter  10 value 93.148133
iter  20 value 88.960578
iter  30 value 85.500897
iter  40 value 85.096589
iter  50 value 85.026197
iter  60 value 85.007039
final  value 85.007037 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.275925 
iter  10 value 94.487861
iter  20 value 88.723363
iter  30 value 86.352133
iter  40 value 85.843821
iter  50 value 85.603228
iter  60 value 85.083983
iter  70 value 84.624212
iter  80 value 84.275504
iter  90 value 83.509852
iter 100 value 83.329212
final  value 83.329212 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.923075 
iter  10 value 94.487112
iter  20 value 87.788076
iter  30 value 86.413484
iter  40 value 84.616627
iter  50 value 83.745478
iter  60 value 82.957669
iter  70 value 82.868665
iter  80 value 82.667483
iter  90 value 82.371399
iter 100 value 82.270845
final  value 82.270845 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.631907 
iter  10 value 94.554717
iter  20 value 89.839493
iter  30 value 89.191525
iter  40 value 84.952148
iter  50 value 83.969362
iter  60 value 82.853484
iter  70 value 82.548459
iter  80 value 82.325308
iter  90 value 82.129851
iter 100 value 81.981583
final  value 81.981583 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.876378 
iter  10 value 95.289784
iter  20 value 88.209596
iter  30 value 85.308102
iter  40 value 84.752517
iter  50 value 83.871171
iter  60 value 83.569430
iter  70 value 83.442771
iter  80 value 83.191475
iter  90 value 82.781606
iter 100 value 82.274568
final  value 82.274568 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.762466 
iter  10 value 94.457040
iter  20 value 93.905507
iter  30 value 90.538489
iter  40 value 84.670518
iter  50 value 84.291756
iter  60 value 83.875680
iter  70 value 82.877275
iter  80 value 82.673127
iter  90 value 82.565842
iter 100 value 82.551963
final  value 82.551963 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.641972 
iter  10 value 94.768995
iter  20 value 92.999743
iter  30 value 88.814887
iter  40 value 86.203490
iter  50 value 83.963677
iter  60 value 82.992613
iter  70 value 82.543009
iter  80 value 82.077062
iter  90 value 81.818609
iter 100 value 81.711042
final  value 81.711042 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.864386 
iter  10 value 94.650158
iter  20 value 94.117892
iter  30 value 92.814014
iter  40 value 90.690074
iter  50 value 90.046357
iter  60 value 88.611731
iter  70 value 84.773463
iter  80 value 84.056050
iter  90 value 83.797593
iter 100 value 83.185217
final  value 83.185217 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.496571 
iter  10 value 94.116290
iter  20 value 87.133309
iter  30 value 86.194440
iter  40 value 84.570741
iter  50 value 83.081786
iter  60 value 82.859006
iter  70 value 82.374552
iter  80 value 82.059224
iter  90 value 81.941281
iter 100 value 81.798285
final  value 81.798285 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.591122 
iter  10 value 94.741128
iter  20 value 88.128524
iter  30 value 86.123702
iter  40 value 85.233806
iter  50 value 84.775306
iter  60 value 84.235062
iter  70 value 83.176930
iter  80 value 82.786038
iter  90 value 82.464384
iter 100 value 82.019666
final  value 82.019666 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.570090 
iter  10 value 95.224122
iter  20 value 92.846679
iter  30 value 89.107025
iter  40 value 87.345679
iter  50 value 85.833301
iter  60 value 85.418912
iter  70 value 85.063932
iter  80 value 84.800906
iter  90 value 82.645577
iter 100 value 82.294257
final  value 82.294257 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.573511 
iter  10 value 94.631923
iter  20 value 94.407192
iter  30 value 90.015788
iter  40 value 84.910675
iter  50 value 84.207928
iter  60 value 83.207334
iter  70 value 82.702014
iter  80 value 81.982435
iter  90 value 81.708532
iter 100 value 81.662208
final  value 81.662208 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.954869 
final  value 94.215830 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.962053 
final  value 94.485959 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.167590 
final  value 94.486005 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.959202 
iter  10 value 88.557556
iter  20 value 88.270721
iter  30 value 88.201775
final  value 88.201611 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.563794 
final  value 94.485905 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.105165 
iter  10 value 94.488951
iter  20 value 94.484353
final  value 94.484220 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.062147 
iter  10 value 94.488520
iter  20 value 94.349938
iter  30 value 88.391900
iter  40 value 88.382234
final  value 88.382084 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.213135 
iter  10 value 94.489170
iter  20 value 94.312718
iter  30 value 87.460552
iter  40 value 85.868879
iter  50 value 84.770587
iter  60 value 84.754894
iter  70 value 84.099049
iter  80 value 84.004666
iter  90 value 83.990352
iter 100 value 83.500043
final  value 83.500043 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.741708 
iter  10 value 94.489248
iter  20 value 92.777017
iter  30 value 86.152370
iter  40 value 85.615629
iter  50 value 85.109371
iter  60 value 85.022964
iter  70 value 84.969503
iter  80 value 84.938003
iter  90 value 84.934896
final  value 84.934012 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.079378 
iter  10 value 93.863528
iter  20 value 92.655548
iter  30 value 92.469435
iter  40 value 92.464977
iter  50 value 92.134192
final  value 92.129573 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.351109 
iter  10 value 94.451537
iter  20 value 94.446138
iter  30 value 87.487099
iter  40 value 85.250607
iter  50 value 84.851532
iter  60 value 84.633901
iter  70 value 84.629298
iter  80 value 84.580529
iter  90 value 84.574191
final  value 84.574137 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.289058 
iter  10 value 89.956137
iter  20 value 88.666470
final  value 88.646986 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.824444 
iter  10 value 94.451203
iter  20 value 94.150908
iter  30 value 87.863404
iter  40 value 85.189775
iter  50 value 85.014998
iter  60 value 85.007867
iter  70 value 85.007500
final  value 85.007487 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.408124 
iter  10 value 86.246760
iter  20 value 86.154221
iter  30 value 86.151783
iter  40 value 85.731291
iter  50 value 85.262770
iter  60 value 85.262209
iter  70 value 85.260192
iter  80 value 84.663625
iter  90 value 84.267977
iter 100 value 84.261448
final  value 84.261448 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.810596 
iter  10 value 94.488089
iter  20 value 93.322655
iter  30 value 90.297272
iter  40 value 86.886456
iter  50 value 86.331755
iter  60 value 85.939768
iter  70 value 85.905208
final  value 85.904745 
converged
Fitting Repeat 1 

# weights:  305
initial  value 132.967401 
iter  10 value 115.482715
iter  20 value 109.004153
iter  30 value 108.655186
iter  40 value 104.884040
iter  50 value 103.473076
iter  60 value 102.502134
iter  70 value 101.981735
iter  80 value 101.573465
iter  90 value 101.151145
iter 100 value 101.108212
final  value 101.108212 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 124.680799 
iter  10 value 110.254760
iter  20 value 108.861919
iter  30 value 108.499879
iter  40 value 107.170713
iter  50 value 105.262049
iter  60 value 103.908660
iter  70 value 102.368214
iter  80 value 101.777343
iter  90 value 101.138869
iter 100 value 100.952375
final  value 100.952375 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.488372 
iter  10 value 118.060228
iter  20 value 117.710262
iter  30 value 117.226839
iter  40 value 114.820070
iter  50 value 106.903469
iter  60 value 103.590639
iter  70 value 103.349620
iter  80 value 103.129577
iter  90 value 102.347175
iter 100 value 101.957706
final  value 101.957706 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 143.915818 
iter  10 value 117.664982
iter  20 value 111.342275
iter  30 value 109.324124
iter  40 value 108.820391
iter  50 value 108.332719
iter  60 value 106.335704
iter  70 value 106.113608
iter  80 value 102.643798
iter  90 value 101.606682
iter 100 value 101.420105
final  value 101.420105 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 133.954035 
iter  10 value 110.424857
iter  20 value 107.626217
iter  30 value 103.652552
iter  40 value 102.302267
iter  50 value 102.059591
iter  60 value 101.606574
iter  70 value 101.539164
iter  80 value 101.403528
iter  90 value 101.242346
iter 100 value 101.021825
final  value 101.021825 
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 -- Tue Nov  5 01:30:34 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 
 41.508   1.584  40.916