##############################################################################
##############################################################################
###
### 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_1.11.0.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 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* 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 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
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.685  1.004  36.691
FSmethod      33.524  0.612  34.137
corr_plot     33.574  0.388  33.962
pred_ensembel 13.356  0.578  10.709
enrichfindP    0.535  0.049   8.682
* 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 100.859911 
final  value 93.653871 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.622885 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.133809 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.250006 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.064465 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.118297 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.942501 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.233594 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.622144 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.269797 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.472589 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.788540 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.251756 
iter  10 value 93.122180
final  value 93.090905 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.920154 
iter  10 value 93.925825
iter  20 value 93.890136
final  value 93.890111 
converged
Fitting Repeat 5 

# weights:  507
initial  value 124.911094 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.674553 
iter  10 value 87.412384
iter  20 value 86.972667
iter  30 value 86.718309
iter  40 value 86.623619
iter  50 value 86.237366
iter  60 value 85.737165
iter  70 value 85.262113
iter  80 value 85.221442
final  value 85.208465 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.920555 
iter  10 value 94.029329
iter  20 value 88.166487
iter  30 value 86.997892
iter  40 value 86.403643
iter  50 value 84.482003
iter  60 value 84.089702
iter  70 value 84.044718
iter  80 value 84.031166
iter  90 value 84.026803
iter  90 value 84.026802
iter  90 value 84.026802
final  value 84.026802 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.932685 
iter  10 value 93.872459
iter  20 value 86.530349
iter  30 value 85.408800
iter  40 value 85.101792
iter  50 value 84.637114
iter  60 value 82.446607
iter  70 value 82.005630
iter  80 value 81.936232
iter  90 value 81.469091
iter 100 value 81.335479
final  value 81.335479 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.387604 
iter  10 value 94.058083
iter  20 value 94.019823
iter  30 value 93.722942
iter  40 value 93.656794
iter  50 value 92.402432
iter  60 value 87.330671
iter  70 value 86.679113
iter  80 value 86.017848
iter  90 value 85.996752
final  value 85.996740 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.754578 
iter  10 value 94.054857
iter  20 value 93.305990
iter  30 value 93.169006
iter  40 value 93.151009
iter  50 value 87.645932
iter  60 value 86.850480
iter  70 value 85.512181
iter  80 value 85.483956
iter  90 value 85.093168
iter 100 value 84.929306
final  value 84.929306 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.510744 
iter  10 value 94.152215
iter  20 value 92.393266
iter  30 value 90.383361
iter  40 value 86.841719
iter  50 value 84.890097
iter  60 value 84.069187
iter  70 value 81.858005
iter  80 value 81.146004
iter  90 value 80.643957
iter 100 value 80.467800
final  value 80.467800 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.912978 
iter  10 value 94.091770
iter  20 value 93.929608
iter  30 value 92.016457
iter  40 value 88.619187
iter  50 value 88.196246
iter  60 value 84.276284
iter  70 value 82.020807
iter  80 value 81.063761
iter  90 value 80.982550
iter 100 value 80.889705
final  value 80.889705 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.059747 
iter  10 value 94.397336
iter  20 value 92.991801
iter  30 value 86.615304
iter  40 value 83.145389
iter  50 value 82.426643
iter  60 value 82.195509
iter  70 value 82.045039
iter  80 value 81.961037
iter  90 value 81.331898
iter 100 value 80.428604
final  value 80.428604 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.735461 
iter  10 value 94.168648
iter  20 value 93.215192
iter  30 value 88.964980
iter  40 value 83.827379
iter  50 value 83.152690
iter  60 value 81.704101
iter  70 value 80.949931
iter  80 value 80.700468
iter  90 value 80.387795
iter 100 value 80.234276
final  value 80.234276 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.883843 
iter  10 value 94.198058
iter  20 value 94.057183
iter  30 value 93.871628
iter  40 value 92.292328
iter  50 value 88.576852
iter  60 value 86.263215
iter  70 value 84.307788
iter  80 value 82.861205
iter  90 value 81.289940
iter 100 value 81.035040
final  value 81.035040 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.940735 
iter  10 value 94.226238
iter  20 value 92.009953
iter  30 value 90.355059
iter  40 value 88.259138
iter  50 value 84.473156
iter  60 value 83.859115
iter  70 value 83.131412
iter  80 value 82.222231
iter  90 value 81.747844
iter 100 value 81.138852
final  value 81.138852 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.606195 
iter  10 value 94.461379
iter  20 value 93.823624
iter  30 value 89.206632
iter  40 value 87.119271
iter  50 value 82.768444
iter  60 value 81.733133
iter  70 value 81.437208
iter  80 value 80.870116
iter  90 value 80.530969
iter 100 value 80.273363
final  value 80.273363 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.073051 
iter  10 value 94.109274
iter  20 value 92.996386
iter  30 value 86.440306
iter  40 value 84.071493
iter  50 value 81.562002
iter  60 value 80.831636
iter  70 value 80.541815
iter  80 value 80.234012
iter  90 value 80.104343
iter 100 value 79.887199
final  value 79.887199 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.773688 
iter  10 value 97.290035
iter  20 value 89.300422
iter  30 value 86.805088
iter  40 value 86.294997
iter  50 value 85.920795
iter  60 value 85.072989
iter  70 value 82.734601
iter  80 value 81.554851
iter  90 value 81.137441
iter 100 value 80.885454
final  value 80.885454 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.146772 
iter  10 value 94.680917
iter  20 value 93.962429
iter  30 value 93.493907
iter  40 value 88.112161
iter  50 value 86.254401
iter  60 value 82.596525
iter  70 value 81.535582
iter  80 value 80.680524
iter  90 value 80.425335
iter 100 value 80.225381
final  value 80.225381 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.042506 
final  value 94.054542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.071536 
final  value 94.054409 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.970364 
final  value 94.054538 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.917351 
iter  10 value 94.054574
iter  20 value 94.052917
iter  20 value 94.052917
iter  20 value 94.052917
final  value 94.052917 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.492868 
iter  10 value 94.052914
iter  20 value 85.882535
iter  30 value 85.605701
final  value 85.605695 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.040719 
iter  10 value 94.057571
iter  20 value 93.103927
iter  30 value 85.154649
iter  40 value 84.857767
iter  50 value 84.186550
iter  60 value 84.047329
iter  70 value 84.045195
final  value 84.044826 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.789660 
iter  10 value 94.037855
iter  20 value 86.649511
iter  30 value 84.887769
iter  40 value 83.743538
iter  50 value 80.640466
iter  60 value 80.619850
iter  70 value 80.619758
iter  80 value 80.619106
final  value 80.619076 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.396047 
iter  10 value 94.037285
iter  20 value 93.220276
iter  30 value 92.998263
iter  40 value 92.983201
iter  50 value 85.178760
iter  60 value 85.159771
iter  70 value 85.158996
iter  80 value 85.155830
final  value 85.155747 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.283359 
iter  10 value 94.037805
iter  20 value 91.975764
iter  30 value 84.614685
final  value 84.605088 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.878797 
iter  10 value 94.054554
iter  20 value 93.742523
iter  30 value 87.724626
iter  40 value 87.719891
iter  50 value 85.956849
iter  60 value 85.323987
iter  70 value 84.511996
iter  80 value 82.562408
iter  90 value 82.494450
iter 100 value 82.494025
final  value 82.494025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.965705 
iter  10 value 94.041542
iter  20 value 93.442810
iter  30 value 88.055852
iter  40 value 85.594017
iter  50 value 84.214700
iter  60 value 84.183973
iter  70 value 83.589866
iter  80 value 82.484542
iter  90 value 82.481895
iter  90 value 82.481895
final  value 82.481895 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.784183 
iter  10 value 94.061377
iter  20 value 94.051075
iter  30 value 93.092133
iter  40 value 93.091508
final  value 93.091499 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.914796 
iter  10 value 94.040982
iter  20 value 93.994559
iter  30 value 86.275743
iter  40 value 85.984047
iter  50 value 85.407659
iter  50 value 85.407659
final  value 85.407659 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.188248 
iter  10 value 94.060735
iter  20 value 94.052994
iter  30 value 89.508588
iter  40 value 85.247027
iter  50 value 81.720674
iter  60 value 79.897519
iter  70 value 79.569702
iter  80 value 79.558156
iter  90 value 79.435763
iter 100 value 79.346794
final  value 79.346794 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.548666 
iter  10 value 85.218905
iter  20 value 84.895570
final  value 84.891666 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.983955 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.187555 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.527135 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.058502 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.199626 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.442930 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.730426 
final  value 94.484212 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.910877 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.940975 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.708765 
iter  10 value 94.275366
iter  10 value 94.275365
iter  10 value 94.275365
final  value 94.275365 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.538569 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.552077 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.605504 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.027083 
iter  10 value 92.529570
final  value 92.452063 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.900627 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.607089 
iter  10 value 88.338675
iter  20 value 86.249350
iter  30 value 84.252503
iter  40 value 82.253441
iter  50 value 81.633325
iter  60 value 81.077729
iter  70 value 80.952906
iter  80 value 80.919343
iter  90 value 80.886257
iter  90 value 80.886256
iter  90 value 80.886256
final  value 80.886256 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.380837 
iter  10 value 89.771691
iter  20 value 88.237852
iter  30 value 83.989241
iter  40 value 83.453834
iter  50 value 83.392132
iter  60 value 82.962461
iter  70 value 82.864827
iter  80 value 82.859392
final  value 82.859198 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.722390 
iter  10 value 94.478268
iter  20 value 86.276486
iter  30 value 84.673788
iter  40 value 83.870966
iter  50 value 83.397740
iter  60 value 83.196565
iter  70 value 83.193980
iter  80 value 83.176394
iter  90 value 83.160452
final  value 83.160401 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.516467 
iter  10 value 94.486554
iter  20 value 89.521785
iter  30 value 83.804869
iter  40 value 83.318677
iter  50 value 83.132472
iter  60 value 82.738479
iter  70 value 82.357233
iter  80 value 82.305387
final  value 82.305347 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.194610 
iter  10 value 94.493907
iter  20 value 94.341600
iter  30 value 94.331067
iter  40 value 94.328512
iter  50 value 94.327935
iter  60 value 90.806617
iter  70 value 84.108300
iter  80 value 83.483753
iter  90 value 83.139246
iter 100 value 82.811528
final  value 82.811528 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.972795 
iter  10 value 94.450481
iter  20 value 90.089108
iter  30 value 89.430604
iter  40 value 88.648864
iter  50 value 84.794470
iter  60 value 83.504309
iter  70 value 82.548659
iter  80 value 80.546775
iter  90 value 80.123636
iter 100 value 80.079987
final  value 80.079987 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.146094 
iter  10 value 94.496652
iter  20 value 92.656454
iter  30 value 89.409495
iter  40 value 87.982679
iter  50 value 83.256742
iter  60 value 82.715857
iter  70 value 82.194054
iter  80 value 81.726113
iter  90 value 80.760254
iter 100 value 80.129369
final  value 80.129369 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.551575 
iter  10 value 94.245395
iter  20 value 88.129541
iter  30 value 86.169273
iter  40 value 83.874238
iter  50 value 82.902365
iter  60 value 81.459354
iter  70 value 80.975610
iter  80 value 80.789806
iter  90 value 80.650105
iter 100 value 80.482895
final  value 80.482895 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.582099 
iter  10 value 94.548308
iter  20 value 94.129669
iter  30 value 90.279608
iter  40 value 86.531870
iter  50 value 84.816138
iter  60 value 83.044395
iter  70 value 81.710536
iter  80 value 81.437911
iter  90 value 81.086559
iter 100 value 80.877183
final  value 80.877183 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.245474 
iter  10 value 94.438289
iter  20 value 84.301964
iter  30 value 83.789164
iter  40 value 83.382255
iter  50 value 82.652750
iter  60 value 82.194703
iter  70 value 81.636855
iter  80 value 81.246131
iter  90 value 81.002869
iter 100 value 80.746475
final  value 80.746475 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.612650 
iter  10 value 92.043548
iter  20 value 91.167806
iter  30 value 88.729093
iter  40 value 83.708715
iter  50 value 81.842681
iter  60 value 80.838650
iter  70 value 80.416336
iter  80 value 79.684799
iter  90 value 79.394348
iter 100 value 79.234289
final  value 79.234289 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.387110 
iter  10 value 95.220483
iter  20 value 94.335753
iter  30 value 94.091016
iter  40 value 88.740798
iter  50 value 85.045396
iter  60 value 82.590087
iter  70 value 81.930504
iter  80 value 81.319373
iter  90 value 80.128360
iter 100 value 79.869055
final  value 79.869055 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.407747 
iter  10 value 94.203477
iter  20 value 89.183873
iter  30 value 84.499888
iter  40 value 82.948549
iter  50 value 81.629891
iter  60 value 81.207213
iter  70 value 81.136046
iter  80 value 80.964575
iter  90 value 80.656666
iter 100 value 80.122734
final  value 80.122734 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.265594 
iter  10 value 91.715235
iter  20 value 89.604547
iter  30 value 88.066024
iter  40 value 84.918453
iter  50 value 84.232250
iter  60 value 84.077776
iter  70 value 82.685999
iter  80 value 81.952395
iter  90 value 80.485951
iter 100 value 79.985060
final  value 79.985060 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.613039 
iter  10 value 96.055501
iter  20 value 94.481747
iter  30 value 93.314364
iter  40 value 87.511669
iter  50 value 83.998701
iter  60 value 83.568068
iter  70 value 83.196863
iter  80 value 80.935250
iter  90 value 79.947556
iter 100 value 79.717800
final  value 79.717800 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.985933 
final  value 94.485776 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.702024 
final  value 94.444847 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.588244 
final  value 94.485589 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.648588 
final  value 94.486109 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.639642 
final  value 94.485783 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.205117 
iter  10 value 94.488801
iter  20 value 94.364388
final  value 94.275758 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.791249 
iter  10 value 94.489414
iter  20 value 91.326191
iter  30 value 83.292517
iter  40 value 83.291202
iter  40 value 83.291202
final  value 83.291202 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.107830 
iter  10 value 89.535496
iter  20 value 85.419935
iter  30 value 85.369438
iter  40 value 85.131270
iter  50 value 82.891462
iter  60 value 82.404907
iter  70 value 81.392685
iter  80 value 81.190733
iter  90 value 81.190162
final  value 81.189866 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.830738 
iter  10 value 92.996739
iter  20 value 92.759064
iter  30 value 83.508356
iter  40 value 83.409568
iter  50 value 83.409344
iter  60 value 83.406282
iter  70 value 82.894459
final  value 82.894366 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.616268 
iter  10 value 94.489289
iter  20 value 94.226895
iter  30 value 91.011376
iter  40 value 89.927291
iter  50 value 89.585607
iter  60 value 89.397674
iter  70 value 85.197489
iter  80 value 85.152674
iter  90 value 84.627540
iter 100 value 84.372705
final  value 84.372705 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.751333 
iter  10 value 94.283864
iter  20 value 94.276699
final  value 94.275712 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.556816 
iter  10 value 92.623241
iter  20 value 91.136764
iter  30 value 84.374657
iter  40 value 84.134777
iter  50 value 83.615951
iter  60 value 83.570554
final  value 83.570474 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.355561 
iter  10 value 86.423404
iter  20 value 83.542996
iter  30 value 83.155617
iter  40 value 83.035626
iter  50 value 82.410907
iter  60 value 82.393924
iter  70 value 82.392193
iter  80 value 82.386425
iter  90 value 82.380273
iter 100 value 82.379268
final  value 82.379268 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.257524 
iter  10 value 94.284223
iter  20 value 94.277026
iter  30 value 87.278546
iter  40 value 84.436099
iter  50 value 84.418797
iter  60 value 84.418238
iter  60 value 84.418238
final  value 84.418238 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.952423 
iter  10 value 94.492562
iter  20 value 94.326006
iter  30 value 90.243309
iter  40 value 83.593889
iter  50 value 82.987262
iter  60 value 82.843035
final  value 82.843016 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.460496 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.630327 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.896429 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.721786 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.773593 
final  value 94.483810 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.802071 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.095173 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.249796 
iter  10 value 91.908162
iter  20 value 83.479427
iter  30 value 82.880371
final  value 82.835465 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.338163 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.605853 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.960034 
iter  10 value 93.866582
final  value 93.866530 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.367316 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.245122 
final  value 94.057229 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.712866 
iter  10 value 93.805718
iter  20 value 93.777811
final  value 93.777778 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.687802 
iter  10 value 93.810742
iter  20 value 93.797253
iter  30 value 93.785598
final  value 93.785584 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.687266 
iter  10 value 95.227538
iter  20 value 94.500470
iter  30 value 94.416196
iter  40 value 94.139168
iter  50 value 93.893299
iter  60 value 91.427530
iter  70 value 87.458398
iter  80 value 86.882169
iter  90 value 86.548049
iter 100 value 86.539232
final  value 86.539232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.685981 
iter  10 value 94.373644
iter  20 value 86.663268
iter  30 value 85.866603
iter  40 value 85.605686
iter  50 value 83.769926
iter  60 value 82.623997
iter  70 value 81.965258
final  value 81.962284 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.981321 
iter  10 value 94.154182
iter  20 value 93.937569
iter  30 value 93.644258
iter  40 value 93.627184
iter  50 value 91.300022
iter  60 value 85.950715
iter  70 value 85.845496
iter  80 value 85.800437
iter  90 value 84.837336
iter 100 value 84.019899
final  value 84.019899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.150030 
iter  10 value 94.483804
iter  20 value 91.270375
iter  30 value 85.483531
iter  40 value 84.557945
iter  50 value 84.099992
iter  60 value 83.863997
iter  70 value 83.817958
iter  80 value 83.803949
final  value 83.803945 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.859938 
iter  10 value 94.400406
iter  20 value 85.202444
iter  30 value 84.560854
iter  40 value 84.342029
iter  50 value 83.954087
iter  60 value 83.766999
iter  70 value 83.646550
iter  80 value 83.628462
final  value 83.628455 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.220395 
iter  10 value 94.806982
iter  20 value 94.206228
iter  30 value 93.828981
iter  40 value 85.631030
iter  50 value 83.924814
iter  60 value 83.433886
iter  70 value 81.506322
iter  80 value 80.996553
iter  90 value 80.913206
iter 100 value 80.837647
final  value 80.837647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.072231 
iter  10 value 94.485887
iter  20 value 92.459204
iter  30 value 88.349745
iter  40 value 87.197663
iter  50 value 86.778958
iter  60 value 86.342368
iter  70 value 82.364743
iter  80 value 81.809608
iter  90 value 81.068303
iter 100 value 80.825549
final  value 80.825549 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.814733 
iter  10 value 89.823878
iter  20 value 87.228389
iter  30 value 86.458974
iter  40 value 85.983577
iter  50 value 85.789227
iter  60 value 84.544979
iter  70 value 82.740745
iter  80 value 82.210935
iter  90 value 81.371809
iter 100 value 81.013169
final  value 81.013169 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.170614 
iter  10 value 94.139267
iter  20 value 94.118842
iter  30 value 92.349100
iter  40 value 87.020083
iter  50 value 85.204784
iter  60 value 82.983541
iter  70 value 81.713254
iter  80 value 81.296462
iter  90 value 81.205673
iter 100 value 81.160633
final  value 81.160633 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.374513 
iter  10 value 94.622161
iter  20 value 94.314310
iter  30 value 91.900462
iter  40 value 90.221174
iter  50 value 87.723605
iter  60 value 85.961299
iter  70 value 85.564693
iter  80 value 84.666430
iter  90 value 84.516239
iter 100 value 82.341580
final  value 82.341580 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.878728 
iter  10 value 89.571986
iter  20 value 84.539079
iter  30 value 82.456283
iter  40 value 81.906943
iter  50 value 81.526046
iter  60 value 81.025722
iter  70 value 80.380368
iter  80 value 80.289710
iter  90 value 80.188748
iter 100 value 80.087249
final  value 80.087249 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.948996 
iter  10 value 94.889657
iter  20 value 87.453849
iter  30 value 84.592025
iter  40 value 84.402173
iter  50 value 84.321804
iter  60 value 83.536933
iter  70 value 83.195048
iter  80 value 82.687674
iter  90 value 82.544228
iter 100 value 82.381788
final  value 82.381788 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.187648 
iter  10 value 94.593610
iter  20 value 94.160786
iter  30 value 87.568978
iter  40 value 85.729572
iter  50 value 84.492827
iter  60 value 82.937294
iter  70 value 82.744520
iter  80 value 82.589925
iter  90 value 82.415579
iter 100 value 82.159696
final  value 82.159696 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.129643 
iter  10 value 94.372222
iter  20 value 86.660090
iter  30 value 85.264401
iter  40 value 84.548432
iter  50 value 84.049149
iter  60 value 83.318680
iter  70 value 82.457416
iter  80 value 82.103460
iter  90 value 81.516183
iter 100 value 81.080770
final  value 81.080770 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.856263 
iter  10 value 94.215156
iter  20 value 86.995684
iter  30 value 84.121371
iter  40 value 82.531610
iter  50 value 81.635538
iter  60 value 81.456741
iter  70 value 81.184686
iter  80 value 80.715494
iter  90 value 80.478329
iter 100 value 80.374513
final  value 80.374513 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.490661 
final  value 94.485637 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.041009 
iter  10 value 94.485952
iter  20 value 94.463486
iter  30 value 94.023219
final  value 93.795296 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.406453 
final  value 94.485812 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.911100 
iter  10 value 84.722546
iter  20 value 83.098700
iter  30 value 82.213794
iter  40 value 81.815948
final  value 81.602022 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.696657 
final  value 94.485632 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.198121 
iter  10 value 94.488438
iter  20 value 94.438755
iter  30 value 93.809036
iter  40 value 91.365983
iter  50 value 91.092923
iter  60 value 86.381876
iter  70 value 85.582063
iter  80 value 85.564957
iter  90 value 85.539177
iter 100 value 85.538647
final  value 85.538647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.680839 
iter  10 value 89.798978
iter  20 value 86.925600
iter  30 value 86.205509
iter  40 value 86.204344
iter  50 value 86.145655
iter  60 value 85.920060
iter  70 value 85.908763
iter  80 value 85.904403
iter  90 value 85.892411
iter 100 value 85.884822
final  value 85.884822 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.719662 
iter  10 value 94.488992
iter  20 value 94.484354
iter  30 value 93.831428
iter  40 value 92.298882
iter  50 value 88.121823
iter  60 value 87.770122
iter  70 value 87.472861
iter  80 value 87.448482
iter  90 value 87.328688
iter 100 value 87.241538
final  value 87.241538 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.609084 
iter  10 value 94.486384
iter  20 value 91.979311
iter  30 value 85.880392
iter  40 value 84.151887
iter  50 value 84.003887
iter  60 value 84.002784
iter  70 value 83.127229
iter  80 value 82.244916
iter  90 value 80.322075
iter 100 value 79.798830
final  value 79.798830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.324631 
iter  10 value 94.488945
iter  20 value 94.480602
iter  30 value 88.873485
iter  40 value 86.093004
iter  50 value 86.083549
iter  60 value 83.423868
iter  70 value 82.593992
iter  80 value 82.593674
iter  90 value 82.560683
iter 100 value 82.437059
final  value 82.437059 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.637825 
iter  10 value 94.490682
iter  20 value 94.375517
iter  30 value 88.709286
iter  40 value 85.906630
final  value 85.886984 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.025814 
iter  10 value 94.035817
iter  20 value 94.027837
iter  30 value 90.744115
iter  40 value 87.333025
iter  50 value 87.227784
iter  60 value 86.408184
iter  70 value 86.169476
iter  80 value 86.161821
iter  90 value 86.141120
final  value 86.133681 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.092437 
iter  10 value 94.034637
iter  20 value 94.029442
final  value 94.027853 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.775606 
iter  10 value 94.493591
iter  20 value 94.485660
final  value 94.484734 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.329145 
iter  10 value 94.228139
iter  20 value 89.226801
iter  30 value 85.675352
iter  40 value 83.779720
iter  50 value 82.608335
iter  60 value 82.603304
iter  70 value 82.456134
iter  80 value 82.450458
iter  90 value 82.449037
iter 100 value 81.759122
final  value 81.759122 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.036475 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.202434 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.842409 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.388192 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.145584 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.461230 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.537539 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.918580 
iter  10 value 93.704969
iter  10 value 93.704969
iter  10 value 93.704969
final  value 93.704969 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.115541 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.125674 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.329948 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.982389 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.085092 
iter  10 value 91.545783
iter  20 value 91.406705
iter  30 value 91.406348
iter  40 value 91.223676
iter  50 value 89.779417
final  value 89.456725 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.303904 
final  value 93.604520 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.709750 
final  value 93.799152 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.005994 
iter  10 value 94.045412
iter  20 value 88.230874
iter  30 value 87.167021
iter  40 value 82.874630
iter  50 value 81.352462
iter  60 value 81.023792
iter  70 value 80.803986
iter  80 value 80.228193
iter  90 value 80.163656
iter 100 value 80.111932
final  value 80.111932 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.794043 
iter  10 value 94.056943
iter  20 value 93.975846
iter  30 value 88.718569
iter  40 value 87.614966
iter  50 value 87.071474
iter  60 value 86.899930
iter  70 value 86.483425
iter  80 value 83.299793
iter  90 value 83.249754
iter 100 value 83.144730
final  value 83.144730 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.842124 
iter  10 value 93.866055
iter  20 value 87.256512
iter  30 value 85.727144
iter  40 value 83.836444
iter  50 value 81.671738
iter  60 value 81.003151
iter  70 value 80.440023
iter  80 value 80.123005
final  value 80.111876 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.643211 
iter  10 value 94.051120
iter  20 value 93.705289
iter  30 value 93.650922
iter  40 value 93.566225
iter  50 value 90.966571
iter  60 value 90.778488
iter  70 value 82.599187
iter  80 value 80.799535
iter  90 value 80.626337
iter 100 value 80.366874
final  value 80.366874 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.685702 
iter  10 value 93.447690
iter  20 value 83.784759
iter  30 value 82.989089
iter  40 value 82.627249
iter  50 value 82.553642
iter  60 value 82.455371
iter  70 value 81.336789
iter  80 value 80.256122
iter  90 value 80.112508
final  value 80.111876 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.014086 
iter  10 value 94.107229
iter  20 value 91.276187
iter  30 value 90.227243
iter  40 value 89.717237
iter  50 value 89.188249
iter  60 value 85.811281
iter  70 value 82.585029
iter  80 value 81.480588
iter  90 value 81.108926
iter 100 value 80.634997
final  value 80.634997 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.141123 
iter  10 value 93.982615
iter  20 value 85.324854
iter  30 value 84.671990
iter  40 value 83.102045
iter  50 value 80.626444
iter  60 value 79.793509
iter  70 value 79.207986
iter  80 value 78.825221
iter  90 value 78.660157
iter 100 value 78.447560
final  value 78.447560 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 127.487906 
iter  10 value 94.059969
iter  20 value 91.448776
iter  30 value 86.284117
iter  40 value 85.791986
iter  50 value 85.274357
iter  60 value 85.000623
iter  70 value 84.830878
iter  80 value 84.762597
iter  90 value 83.480042
iter 100 value 82.665801
final  value 82.665801 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 122.327478 
iter  10 value 95.012712
iter  20 value 93.970915
iter  30 value 91.936889
iter  40 value 90.433873
iter  50 value 82.895112
iter  60 value 82.222002
iter  70 value 82.101330
iter  80 value 81.816291
iter  90 value 80.667626
iter 100 value 80.034372
final  value 80.034372 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.892872 
iter  10 value 94.054230
iter  20 value 87.092814
iter  30 value 83.091761
iter  40 value 82.618496
iter  50 value 81.769893
iter  60 value 80.700864
iter  70 value 80.381529
iter  80 value 80.252425
iter  90 value 80.247442
iter 100 value 80.228505
final  value 80.228505 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.987912 
iter  10 value 94.266473
iter  20 value 93.858771
iter  30 value 86.129654
iter  40 value 84.625178
iter  50 value 83.770110
iter  60 value 81.879743
iter  70 value 80.773935
iter  80 value 79.987882
iter  90 value 79.154342
iter 100 value 79.046931
final  value 79.046931 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.891426 
iter  10 value 94.012086
iter  20 value 93.450959
iter  30 value 88.144105
iter  40 value 85.918027
iter  50 value 84.907770
iter  60 value 83.790511
iter  70 value 83.502615
iter  80 value 82.699547
iter  90 value 81.559635
iter 100 value 79.514405
final  value 79.514405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.193819 
iter  10 value 97.474923
iter  20 value 93.257710
iter  30 value 86.728591
iter  40 value 84.349397
iter  50 value 80.271281
iter  60 value 79.804523
iter  70 value 79.702528
iter  80 value 79.155649
iter  90 value 78.953280
iter 100 value 78.849694
final  value 78.849694 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.601342 
iter  10 value 94.537035
iter  20 value 88.239784
iter  30 value 84.354749
iter  40 value 81.784296
iter  50 value 79.977020
iter  60 value 78.859451
iter  70 value 78.365952
iter  80 value 77.992224
iter  90 value 77.878984
iter 100 value 77.757819
final  value 77.757819 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.128444 
iter  10 value 88.099224
iter  20 value 85.693724
iter  30 value 82.379785
iter  40 value 80.068718
iter  50 value 79.586654
iter  60 value 79.044859
iter  70 value 78.908696
iter  80 value 78.649804
iter  90 value 78.307503
iter 100 value 78.131621
final  value 78.131621 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.744230 
iter  10 value 94.054797
final  value 94.052985 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.935083 
final  value 94.054523 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.599617 
iter  10 value 93.838028
iter  20 value 93.836647
iter  30 value 90.852539
iter  40 value 83.445958
iter  50 value 83.429837
final  value 83.429767 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.507203 
final  value 94.054320 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.003741 
final  value 94.054602 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.990454 
iter  10 value 94.068999
iter  20 value 94.062354
iter  30 value 93.716643
iter  40 value 93.693530
iter  50 value 93.690318
iter  60 value 93.689698
iter  70 value 93.686011
iter  80 value 93.684804
final  value 93.683285 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.023599 
iter  10 value 94.057076
iter  20 value 91.071374
iter  30 value 90.395935
iter  40 value 90.378491
iter  40 value 90.378490
iter  40 value 90.378490
final  value 90.378490 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.279332 
iter  10 value 93.898616
iter  20 value 93.879314
iter  30 value 93.801095
iter  40 value 93.800131
iter  50 value 93.433363
iter  60 value 91.693424
iter  70 value 91.194708
final  value 91.191071 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.384060 
iter  10 value 94.057060
iter  20 value 94.052923
iter  20 value 94.052923
iter  20 value 94.052923
final  value 94.052923 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.345125 
iter  10 value 94.057802
iter  20 value 94.052934
iter  30 value 88.534898
iter  40 value 87.098178
iter  50 value 87.063666
iter  60 value 86.787176
iter  70 value 86.756140
iter  70 value 86.756139
final  value 86.756139 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.784358 
iter  10 value 93.613880
iter  20 value 87.374659
iter  30 value 85.478777
iter  40 value 85.358557
iter  50 value 85.355594
iter  60 value 84.628517
iter  70 value 83.426926
iter  80 value 82.053557
iter  90 value 81.852348
iter 100 value 81.835482
final  value 81.835482 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.061015 
iter  10 value 93.844533
iter  20 value 93.787935
iter  30 value 85.307142
iter  40 value 84.988248
iter  50 value 84.962177
iter  60 value 84.376046
iter  70 value 82.570635
iter  80 value 82.511592
iter  90 value 82.496138
iter 100 value 80.552215
final  value 80.552215 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.365930 
iter  10 value 93.586470
iter  20 value 90.051200
iter  30 value 89.042635
iter  40 value 87.842139
iter  50 value 84.923616
iter  60 value 83.966193
iter  70 value 83.602247
iter  80 value 83.002052
iter  90 value 78.937644
iter 100 value 78.739930
final  value 78.739930 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.118992 
iter  10 value 93.884870
iter  20 value 93.523086
iter  30 value 91.198412
iter  40 value 90.435715
iter  50 value 90.435488
iter  60 value 90.432619
final  value 90.432582 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.984070 
iter  10 value 94.059853
iter  20 value 94.051429
iter  30 value 92.604182
iter  40 value 90.420211
iter  50 value 90.033577
iter  60 value 84.417882
iter  70 value 83.986802
iter  80 value 82.515872
iter  90 value 82.025548
iter 100 value 81.945953
final  value 81.945953 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.059150 
iter  10 value 94.105263
iter  10 value 94.105263
iter  10 value 94.105263
final  value 94.105263 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.029990 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.581635 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.098617 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.853068 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.909580 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.763407 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.261735 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.029408 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.267469 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.172125 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.994398 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.032478 
iter  10 value 94.352794
iter  20 value 93.946518
iter  30 value 93.930701
final  value 93.930686 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.779536 
iter  10 value 93.623396
final  value 93.592492 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.892108 
iter  10 value 94.378797
final  value 94.378788 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.219843 
iter  10 value 93.927945
iter  20 value 88.008281
iter  30 value 87.119234
iter  40 value 86.084597
iter  50 value 85.808548
iter  60 value 85.699029
iter  70 value 85.674392
iter  80 value 85.653127
final  value 85.649140 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.831448 
iter  10 value 94.489034
iter  20 value 94.484249
iter  30 value 94.146056
iter  40 value 93.324489
iter  50 value 93.250722
iter  60 value 93.203282
iter  70 value 92.578541
iter  80 value 92.549422
iter  90 value 92.542446
final  value 92.542337 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.929219 
iter  10 value 94.832325
iter  20 value 94.460955
iter  30 value 92.854892
iter  40 value 88.819441
iter  50 value 86.065861
iter  60 value 85.691768
iter  70 value 85.567518
iter  80 value 85.545467
final  value 85.545417 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.859070 
iter  10 value 93.975113
iter  20 value 87.485324
iter  30 value 87.147637
iter  40 value 87.031021
iter  50 value 86.918790
iter  60 value 85.995904
final  value 85.994140 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.824876 
iter  10 value 94.450986
iter  20 value 93.276960
iter  30 value 93.076235
iter  40 value 92.767112
iter  50 value 92.608176
final  value 92.608015 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.844600 
iter  10 value 93.739600
iter  20 value 89.785942
iter  30 value 88.019016
iter  40 value 86.860918
iter  50 value 86.189710
iter  60 value 85.553107
iter  70 value 84.314852
iter  80 value 82.904987
iter  90 value 82.425287
iter 100 value 82.185927
final  value 82.185927 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.557388 
iter  10 value 94.248866
iter  20 value 88.257226
iter  30 value 85.675826
iter  40 value 83.949399
iter  50 value 83.327404
iter  60 value 82.937727
iter  70 value 82.879088
iter  80 value 82.818694
iter  90 value 82.706228
iter 100 value 82.536962
final  value 82.536962 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.212312 
iter  10 value 94.892421
iter  20 value 88.900244
iter  30 value 86.851437
iter  40 value 86.680072
iter  50 value 86.531132
iter  60 value 85.659835
iter  70 value 83.803183
iter  80 value 82.858779
iter  90 value 82.517949
iter 100 value 82.506258
final  value 82.506258 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.163990 
iter  10 value 94.488623
iter  20 value 91.021995
iter  30 value 89.314049
iter  40 value 87.902934
iter  50 value 86.726434
iter  60 value 83.574301
iter  70 value 82.627422
iter  80 value 82.220368
iter  90 value 82.064957
iter 100 value 82.009728
final  value 82.009728 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.319797 
iter  10 value 94.480718
iter  20 value 90.474196
iter  30 value 85.229978
iter  40 value 83.642024
iter  50 value 83.342995
iter  60 value 82.993002
iter  70 value 82.783399
iter  80 value 82.646824
iter  90 value 82.614642
iter 100 value 82.535113
final  value 82.535113 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.222453 
iter  10 value 95.239550
iter  20 value 91.622819
iter  30 value 88.580574
iter  40 value 86.879372
iter  50 value 85.060583
iter  60 value 83.483299
iter  70 value 82.816828
iter  80 value 82.027432
iter  90 value 81.626925
iter 100 value 81.505022
final  value 81.505022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.279800 
iter  10 value 94.962750
iter  20 value 94.480515
iter  30 value 94.451559
iter  40 value 92.467925
iter  50 value 87.048590
iter  60 value 84.483656
iter  70 value 84.273385
iter  80 value 83.909228
iter  90 value 82.438782
iter 100 value 82.161166
final  value 82.161166 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.610412 
iter  10 value 94.503196
iter  20 value 87.796168
iter  30 value 86.628023
iter  40 value 83.895131
iter  50 value 83.334077
iter  60 value 82.838212
iter  70 value 82.505657
iter  80 value 82.140370
iter  90 value 81.730862
iter 100 value 81.497885
final  value 81.497885 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.116021 
iter  10 value 94.600126
iter  20 value 89.365842
iter  30 value 87.579774
iter  40 value 86.446259
iter  50 value 86.022249
iter  60 value 85.913589
iter  70 value 85.841394
iter  80 value 85.737312
iter  90 value 85.654642
iter 100 value 85.542172
final  value 85.542172 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.289772 
iter  10 value 94.489135
iter  20 value 91.050199
iter  30 value 84.118908
iter  40 value 83.844691
iter  50 value 83.274430
iter  60 value 82.911906
iter  70 value 82.636557
iter  80 value 82.488922
iter  90 value 82.425020
iter 100 value 82.177429
final  value 82.177429 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.544161 
final  value 94.485971 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.672415 
final  value 94.485873 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.991129 
final  value 94.488133 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.491311 
final  value 94.485645 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.354519 
final  value 94.485907 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.431624 
iter  10 value 94.484698
iter  20 value 86.698053
iter  30 value 86.555148
iter  40 value 86.374649
iter  50 value 86.252736
iter  60 value 86.238285
iter  70 value 86.169185
iter  80 value 86.021351
iter  90 value 84.369441
iter 100 value 84.253041
final  value 84.253041 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.157943 
iter  10 value 94.488328
iter  20 value 93.057566
iter  30 value 91.115636
iter  40 value 91.100417
iter  50 value 90.116535
iter  60 value 90.078128
final  value 90.077088 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.118869 
iter  10 value 94.487833
iter  20 value 94.472602
iter  30 value 91.223883
iter  40 value 89.996364
iter  50 value 85.087528
iter  60 value 85.083612
iter  70 value 84.707416
iter  80 value 82.629073
iter  90 value 82.275918
iter 100 value 82.270943
final  value 82.270943 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.321612 
iter  10 value 94.327559
iter  20 value 94.322287
iter  30 value 90.367829
iter  40 value 87.915695
iter  50 value 86.509473
iter  60 value 85.758785
iter  70 value 82.764682
iter  80 value 81.986518
iter  90 value 81.719531
iter 100 value 81.719157
final  value 81.719157 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.480440 
iter  10 value 94.488796
iter  20 value 91.759474
iter  30 value 87.335103
iter  40 value 87.334592
final  value 87.334552 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.311551 
iter  10 value 92.603534
iter  20 value 87.237975
iter  30 value 87.236869
iter  40 value 87.234198
iter  50 value 86.414028
iter  60 value 86.378814
iter  70 value 86.378083
iter  80 value 86.377659
final  value 86.376963 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.648435 
iter  10 value 94.493215
iter  20 value 94.476892
iter  30 value 94.474974
iter  40 value 94.467585
iter  50 value 87.967704
iter  60 value 87.885145
iter  70 value 87.782150
iter  80 value 87.374379
iter  90 value 87.270963
iter 100 value 83.608317
final  value 83.608317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.618806 
iter  10 value 94.497806
iter  20 value 94.480379
iter  30 value 94.470205
iter  40 value 94.333642
iter  50 value 92.080383
iter  60 value 84.789651
iter  70 value 84.358072
iter  80 value 84.356516
iter  90 value 84.191477
iter  90 value 84.191477
iter 100 value 83.141944
final  value 83.141944 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.515916 
iter  10 value 94.491629
iter  20 value 94.481450
iter  30 value 88.592558
iter  40 value 87.860591
iter  50 value 83.782231
iter  60 value 81.247321
iter  70 value 80.917390
iter  80 value 80.864864
iter  90 value 80.286733
iter 100 value 80.139522
final  value 80.139522 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.128347 
iter  10 value 94.492490
iter  20 value 94.477087
final  value 94.467696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.270430 
iter  10 value 117.898335
iter  20 value 117.865324
iter  30 value 116.370403
iter  40 value 106.966203
iter  50 value 106.828636
iter  60 value 106.806706
final  value 106.806354 
converged
Fitting Repeat 2 

# weights:  507
initial  value 150.719289 
iter  10 value 117.900913
iter  20 value 117.892718
iter  30 value 110.505350
iter  40 value 108.530948
iter  50 value 108.528046
iter  60 value 107.187139
final  value 107.182013 
converged
Fitting Repeat 3 

# weights:  507
initial  value 132.624980 
iter  10 value 117.589177
iter  20 value 117.564381
iter  30 value 117.561728
iter  40 value 117.560769
iter  50 value 112.614675
iter  60 value 111.660555
iter  70 value 111.643347
iter  80 value 111.642181
iter  90 value 110.742050
iter 100 value 110.423916
final  value 110.423916 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.054228 
iter  10 value 117.508258
iter  20 value 117.503380
iter  30 value 117.500972
final  value 117.500653 
converged
Fitting Repeat 5 

# weights:  507
initial  value 158.672148 
iter  10 value 117.894508
iter  20 value 117.780818
iter  30 value 117.767232
iter  40 value 117.763848
iter  50 value 117.762297
iter  60 value 117.758956
iter  70 value 117.567170
iter  80 value 107.186101
iter  90 value 107.153323
iter 100 value 106.517789
final  value 106.517789 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Mon Jul 15 23:48:55 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 
 41.338   1.893  42.480