##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-03-13 r87965)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.2 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.13.0’
* 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 ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       34.307  0.513  34.822
corr_plot     33.443  0.309  33.757
FSmethod      32.530  0.408  32.940
pred_ensembel 13.214  0.278  12.156
enrichfindP    0.588  0.021   8.026
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.13.0’
** 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 Under development (unstable) (2025-03-13 r87965) -- "Unsuffered Consequences"
Copyright (C) 2025 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 107.230588 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.467994 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.048370 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.119847 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.222977 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.343900 
iter  10 value 85.651309
iter  20 value 84.744029
final  value 84.533333 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.876683 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.129440 
iter  10 value 91.324491
iter  20 value 91.183759
iter  30 value 90.819379
iter  40 value 90.806410
iter  50 value 90.714094
final  value 90.711328 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.765987 
iter  10 value 93.264418
iter  20 value 92.908958
iter  30 value 92.829411
iter  40 value 91.486392
iter  50 value 91.041088
iter  60 value 91.003670
iter  70 value 91.003373
final  value 91.003368 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.093785 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.829603 
final  value 94.482478 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.708405 
iter  10 value 91.440714
iter  20 value 91.430809
final  value 91.430671 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.530982 
final  value 93.701657 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.233754 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 124.941644 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.644733 
iter  10 value 94.486487
iter  20 value 93.760345
iter  30 value 92.240863
iter  40 value 88.501838
iter  50 value 86.780164
iter  60 value 85.553820
iter  70 value 85.040159
iter  80 value 83.684813
iter  90 value 83.421332
iter 100 value 83.378320
final  value 83.378320 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.819854 
iter  10 value 94.572736
iter  20 value 94.488929
iter  30 value 94.484589
iter  40 value 94.304071
iter  50 value 92.609288
iter  60 value 92.225233
iter  70 value 90.008928
iter  80 value 84.629512
iter  90 value 84.396947
iter 100 value 83.980848
final  value 83.980848 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.797492 
iter  10 value 95.391637
iter  20 value 94.195489
iter  30 value 92.915475
iter  40 value 90.442619
iter  50 value 85.372367
iter  60 value 83.025856
iter  70 value 82.587053
iter  80 value 81.968524
iter  90 value 81.533561
iter 100 value 81.167472
final  value 81.167472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.262726 
iter  10 value 94.473991
iter  20 value 93.498040
iter  30 value 92.986497
iter  40 value 92.929803
iter  50 value 88.977769
iter  60 value 85.726743
iter  70 value 85.024869
iter  80 value 84.292348
iter  90 value 83.622880
iter 100 value 83.354856
final  value 83.354856 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.171963 
iter  10 value 94.538044
iter  20 value 94.475481
iter  30 value 89.798731
iter  40 value 84.801945
iter  50 value 84.508668
iter  60 value 84.463453
iter  70 value 83.879385
iter  80 value 83.365791
final  value 83.350473 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.177876 
iter  10 value 95.274923
iter  20 value 90.288851
iter  30 value 87.998011
iter  40 value 86.265146
iter  50 value 85.373069
iter  60 value 84.190572
iter  70 value 83.573975
iter  80 value 83.309272
iter  90 value 83.055445
iter 100 value 83.004852
final  value 83.004852 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.182928 
iter  10 value 94.490493
iter  20 value 93.723841
iter  30 value 89.839615
iter  40 value 85.413032
iter  50 value 83.048530
iter  60 value 81.642474
iter  70 value 80.995955
iter  80 value 80.218870
iter  90 value 79.895411
iter 100 value 79.694754
final  value 79.694754 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.397605 
iter  10 value 94.589778
iter  20 value 91.478729
iter  30 value 85.191793
iter  40 value 83.377126
iter  50 value 82.585642
iter  60 value 81.427974
iter  70 value 80.688480
iter  80 value 80.390129
iter  90 value 80.253604
iter 100 value 80.222319
final  value 80.222319 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.844419 
iter  10 value 94.556956
iter  20 value 92.399721
iter  30 value 88.533239
iter  40 value 85.330141
iter  50 value 82.930043
iter  60 value 81.349855
iter  70 value 81.040645
iter  80 value 80.330868
iter  90 value 79.824685
iter 100 value 79.769888
final  value 79.769888 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.093565 
iter  10 value 94.917920
iter  20 value 94.415936
iter  30 value 91.180003
iter  40 value 88.051581
iter  50 value 87.751819
iter  60 value 87.353532
iter  70 value 81.778267
iter  80 value 80.910073
iter  90 value 80.567990
iter 100 value 80.373304
final  value 80.373304 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.704623 
iter  10 value 97.011871
iter  20 value 87.194281
iter  30 value 84.233926
iter  40 value 81.756270
iter  50 value 81.221855
iter  60 value 81.040436
iter  70 value 80.746731
iter  80 value 80.225319
iter  90 value 79.949238
iter 100 value 79.615026
final  value 79.615026 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.986745 
iter  10 value 93.890531
iter  20 value 87.253555
iter  30 value 85.488515
iter  40 value 85.117888
iter  50 value 83.366003
iter  60 value 82.148292
iter  70 value 80.651559
iter  80 value 80.290084
iter  90 value 79.924623
iter 100 value 79.770011
final  value 79.770011 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.028164 
iter  10 value 94.123462
iter  20 value 87.732679
iter  30 value 84.611164
iter  40 value 83.604341
iter  50 value 81.637577
iter  60 value 81.208892
iter  70 value 80.910293
iter  80 value 80.612573
iter  90 value 80.305227
iter 100 value 79.831893
final  value 79.831893 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.555397 
iter  10 value 92.275988
iter  20 value 87.626806
iter  30 value 87.113701
iter  40 value 86.440336
iter  50 value 83.495776
iter  60 value 82.961663
iter  70 value 81.948232
iter  80 value 80.564568
iter  90 value 80.060326
iter 100 value 79.794139
final  value 79.794139 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.624794 
iter  10 value 94.465373
iter  20 value 89.136701
iter  30 value 88.024204
iter  40 value 86.989448
iter  50 value 84.189625
iter  60 value 82.132603
iter  70 value 80.564029
iter  80 value 80.364637
iter  90 value 80.173660
iter 100 value 80.099074
final  value 80.099074 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.391593 
final  value 94.485768 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.495901 
final  value 94.486333 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.409204 
final  value 94.485907 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.146827 
iter  10 value 94.485849
iter  20 value 94.451428
iter  30 value 94.065567
final  value 94.064480 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.169534 
final  value 94.485816 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.635117 
iter  10 value 94.489162
iter  20 value 94.178093
iter  30 value 92.109902
iter  40 value 91.953947
iter  50 value 91.308538
iter  60 value 90.801071
iter  70 value 90.764969
iter  80 value 88.581970
iter  90 value 87.335516
iter 100 value 85.788710
final  value 85.788710 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.972494 
iter  10 value 94.472163
iter  20 value 94.469217
iter  30 value 94.316540
iter  40 value 92.520856
iter  50 value 91.954272
iter  60 value 91.802448
final  value 91.800362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.879776 
iter  10 value 93.095772
iter  20 value 87.839021
iter  30 value 87.837970
iter  40 value 87.366007
iter  50 value 86.330008
iter  60 value 86.254691
final  value 86.254517 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.398728 
iter  10 value 94.472047
iter  20 value 93.793852
iter  30 value 87.062165
iter  40 value 83.550375
iter  50 value 83.549467
iter  60 value 82.180195
iter  70 value 81.731739
iter  80 value 79.552769
iter  90 value 79.016152
iter 100 value 78.843347
final  value 78.843347 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.988019 
iter  10 value 94.481496
iter  20 value 94.479364
iter  30 value 94.477650
iter  40 value 93.677281
iter  50 value 91.977179
iter  60 value 91.317797
iter  70 value 91.080532
iter  80 value 91.079070
iter  90 value 91.045651
final  value 91.044986 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.200153 
iter  10 value 94.493401
iter  20 value 93.531783
iter  30 value 84.116540
iter  40 value 82.706668
iter  50 value 82.662016
final  value 82.661253 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.117102 
iter  10 value 94.492871
iter  20 value 94.436390
iter  30 value 85.990802
iter  40 value 85.960588
iter  50 value 85.960027
iter  60 value 85.709885
iter  70 value 84.737460
iter  80 value 84.604905
iter  90 value 84.604625
iter 100 value 84.601049
final  value 84.601049 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.623726 
iter  10 value 94.485701
iter  20 value 94.483898
iter  30 value 94.375281
final  value 94.367925 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.844122 
iter  10 value 93.781562
iter  20 value 93.589154
iter  30 value 93.585495
iter  40 value 93.551594
iter  50 value 93.235961
final  value 93.235711 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.823067 
iter  10 value 94.493822
iter  20 value 94.479157
iter  30 value 94.357123
iter  40 value 93.105782
iter  50 value 86.826491
iter  60 value 82.223226
iter  70 value 81.518399
iter  80 value 81.351467
iter  90 value 81.227494
iter 100 value 81.127371
final  value 81.127371 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.853229 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.667535 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.056061 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.545284 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.128319 
final  value 94.252920 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.776365 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.245009 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.229681 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.717786 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.306141 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.692205 
iter  10 value 94.483214
iter  20 value 94.467737
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.221531 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.109229 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.870008 
iter  10 value 94.291057
iter  20 value 94.268310
final  value 94.268289 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.026006 
iter  10 value 94.027803
iter  20 value 93.737964
iter  30 value 93.737376
final  value 93.737374 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.779545 
iter  10 value 94.490535
iter  20 value 93.710177
iter  30 value 85.186875
iter  40 value 84.779361
iter  50 value 84.055040
iter  60 value 84.035694
iter  70 value 83.933792
final  value 83.932394 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.401583 
iter  10 value 87.161615
iter  20 value 85.533053
iter  30 value 83.176168
iter  40 value 81.758766
iter  50 value 80.908445
iter  60 value 80.792401
iter  70 value 80.504115
iter  80 value 80.499379
iter  90 value 80.493449
final  value 80.493262 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.560760 
iter  10 value 94.492764
iter  20 value 94.232034
iter  30 value 93.743217
iter  40 value 91.561919
iter  50 value 88.246585
iter  60 value 87.864120
iter  70 value 87.780385
iter  80 value 85.177505
iter  90 value 85.005503
iter 100 value 84.780126
final  value 84.780126 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.256183 
iter  10 value 94.302720
iter  20 value 86.322752
iter  30 value 84.599986
iter  40 value 84.510976
iter  50 value 84.096235
iter  60 value 83.922828
iter  70 value 83.906884
final  value 83.906778 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.166423 
iter  10 value 94.327830
iter  20 value 92.290905
iter  30 value 91.407742
iter  40 value 84.643615
iter  50 value 83.604828
iter  60 value 81.065652
iter  70 value 81.039683
final  value 81.039506 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.371059 
iter  10 value 94.548277
iter  20 value 90.119278
iter  30 value 87.288938
iter  40 value 87.189592
iter  50 value 84.712380
iter  60 value 82.718028
iter  70 value 81.525954
iter  80 value 81.142674
iter  90 value 80.965451
iter 100 value 80.705407
final  value 80.705407 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.955123 
iter  10 value 94.462599
iter  20 value 93.763039
iter  30 value 87.362089
iter  40 value 85.293135
iter  50 value 84.796537
iter  60 value 82.329566
iter  70 value 80.646662
iter  80 value 80.156608
iter  90 value 79.748021
iter 100 value 79.224529
final  value 79.224529 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.004974 
iter  10 value 94.572063
iter  20 value 93.982557
iter  30 value 87.462453
iter  40 value 85.703893
iter  50 value 83.913437
iter  60 value 83.686073
iter  70 value 83.629111
iter  80 value 82.464552
iter  90 value 81.383718
iter 100 value 81.252561
final  value 81.252561 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.249209 
iter  10 value 94.537341
iter  20 value 87.335309
iter  30 value 84.707725
iter  40 value 83.272944
iter  50 value 81.581493
iter  60 value 81.252189
iter  70 value 80.768197
iter  80 value 80.417673
iter  90 value 80.095494
iter 100 value 79.973380
final  value 79.973380 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.022070 
iter  10 value 94.542165
iter  20 value 88.350133
iter  30 value 87.479874
iter  40 value 82.155246
iter  50 value 81.313935
iter  60 value 80.408641
iter  70 value 79.901386
iter  80 value 79.615564
iter  90 value 79.332963
iter 100 value 79.316537
final  value 79.316537 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.836940 
iter  10 value 99.985004
iter  20 value 85.113348
iter  30 value 83.960531
iter  40 value 83.611141
iter  50 value 82.212515
iter  60 value 81.725942
iter  70 value 81.560570
iter  80 value 81.181772
iter  90 value 80.315224
iter 100 value 79.427626
final  value 79.427626 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.438670 
iter  10 value 95.666142
iter  20 value 88.307791
iter  30 value 86.335001
iter  40 value 85.194332
iter  50 value 83.325572
iter  60 value 82.044000
iter  70 value 80.528246
iter  80 value 80.238069
iter  90 value 80.201132
iter 100 value 80.076317
final  value 80.076317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.280117 
iter  10 value 94.387521
iter  20 value 93.445794
iter  30 value 87.121977
iter  40 value 84.363683
iter  50 value 83.740675
iter  60 value 83.211637
iter  70 value 82.157408
iter  80 value 80.783023
iter  90 value 80.326230
iter 100 value 79.788367
final  value 79.788367 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.813542 
iter  10 value 94.513310
iter  20 value 85.407245
iter  30 value 83.923557
iter  40 value 82.285360
iter  50 value 80.814431
iter  60 value 80.566990
iter  70 value 80.316378
iter  80 value 79.341989
iter  90 value 78.904612
iter 100 value 78.855908
final  value 78.855908 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.204463 
iter  10 value 94.838260
iter  20 value 94.347124
iter  30 value 94.136659
iter  40 value 93.621617
iter  50 value 88.914628
iter  60 value 86.930319
iter  70 value 85.255243
iter  80 value 84.525910
iter  90 value 84.378634
iter 100 value 83.941129
final  value 83.941129 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.816064 
final  value 94.468207 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.260606 
iter  10 value 94.486005
iter  20 value 94.484212
iter  30 value 93.106030
iter  40 value 92.897886
iter  50 value 83.687731
iter  60 value 83.590577
iter  70 value 82.750296
iter  80 value 82.726503
final  value 82.726023 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.368465 
final  value 94.485843 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.857836 
final  value 94.485646 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.342607 
final  value 94.478118 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.949713 
iter  10 value 94.489045
iter  20 value 94.484299
final  value 94.484266 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.065602 
iter  10 value 94.490896
iter  20 value 94.477788
iter  30 value 90.420457
iter  40 value 84.812337
iter  50 value 84.685041
iter  60 value 84.680702
iter  70 value 84.629375
iter  80 value 84.608926
iter  90 value 84.607384
final  value 84.605951 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.043592 
iter  10 value 94.488011
iter  20 value 90.647120
iter  30 value 89.734138
iter  40 value 88.914000
iter  50 value 87.924945
iter  60 value 87.922368
final  value 87.922262 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.927660 
iter  10 value 94.468535
iter  20 value 92.995323
iter  30 value 92.898479
iter  40 value 92.898129
final  value 92.898127 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.591267 
iter  10 value 93.996146
iter  20 value 93.889782
iter  30 value 90.736882
iter  40 value 86.954125
iter  50 value 86.732692
iter  60 value 86.700006
iter  70 value 86.699162
final  value 86.699159 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.836913 
iter  10 value 86.426886
iter  20 value 85.843551
iter  30 value 85.839085
iter  40 value 85.793895
iter  50 value 85.352218
iter  60 value 84.791494
iter  70 value 81.656289
iter  80 value 80.910846
iter  90 value 79.731512
iter 100 value 79.137842
final  value 79.137842 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.044434 
iter  10 value 87.942725
iter  20 value 87.246452
iter  30 value 87.245685
iter  40 value 87.226102
iter  50 value 87.171883
iter  60 value 87.163884
iter  70 value 85.408651
iter  80 value 85.376934
iter  90 value 85.359299
iter 100 value 85.308554
final  value 85.308554 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.051963 
iter  10 value 94.474462
iter  20 value 94.301312
final  value 94.057630 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.138620 
iter  10 value 94.492331
iter  20 value 94.069772
iter  30 value 87.916680
iter  40 value 87.248783
iter  50 value 85.584801
iter  60 value 85.560690
iter  70 value 85.553987
iter  80 value 83.392045
iter  90 value 83.344947
iter 100 value 83.309939
final  value 83.309939 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.692398 
iter  10 value 94.492513
iter  20 value 94.459114
iter  30 value 83.529647
iter  40 value 83.240560
iter  50 value 83.229588
iter  60 value 82.844997
iter  70 value 82.725533
final  value 82.725500 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.140886 
final  value 94.461539 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.084194 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.079943 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.798477 
final  value 94.312039 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.344320 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.672200 
iter  10 value 93.870371
iter  20 value 93.860416
final  value 93.860350 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.752476 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.593549 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.773222 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.737795 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.531948 
iter  10 value 89.619086
iter  20 value 83.140707
iter  30 value 83.132868
iter  40 value 83.126394
iter  50 value 79.672822
iter  60 value 78.760669
iter  70 value 78.760200
iter  80 value 78.752073
iter  80 value 78.752072
iter  80 value 78.752072
final  value 78.752072 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.051327 
iter  10 value 94.127165
iter  20 value 92.405098
iter  30 value 88.372891
iter  40 value 88.361581
final  value 88.361537 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.666838 
final  value 94.484212 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.258672 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.559861 
iter  10 value 94.484214
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.296968 
iter  10 value 94.488577
iter  20 value 94.076196
iter  30 value 93.990719
iter  40 value 93.988642
iter  50 value 89.931822
iter  60 value 85.667346
iter  70 value 85.257332
iter  80 value 85.019782
iter  90 value 83.505922
iter 100 value 82.320896
final  value 82.320896 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.982914 
iter  10 value 94.487720
iter  20 value 86.259622
iter  30 value 84.623129
iter  40 value 81.583287
iter  50 value 79.686632
iter  60 value 79.408338
iter  70 value 79.397531
iter  80 value 79.396523
final  value 79.396429 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.514045 
iter  10 value 94.083370
iter  20 value 84.715569
iter  30 value 81.080432
iter  40 value 79.657295
iter  50 value 79.304798
iter  60 value 79.208508
iter  70 value 78.865229
iter  80 value 78.650885
iter  90 value 78.541948
iter 100 value 78.492180
final  value 78.492180 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.941672 
iter  10 value 94.502653
iter  20 value 91.912051
iter  30 value 90.526350
iter  40 value 85.052971
iter  50 value 81.616118
iter  60 value 80.504492
iter  70 value 79.959172
iter  80 value 79.438764
iter  90 value 79.004504
iter 100 value 78.703846
final  value 78.703846 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.070104 
iter  10 value 94.490613
iter  20 value 94.483050
iter  30 value 94.237142
iter  40 value 94.151776
iter  50 value 93.863768
iter  60 value 93.727822
iter  70 value 85.522666
iter  80 value 84.978781
iter  90 value 84.881366
iter 100 value 84.793473
final  value 84.793473 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.456796 
iter  10 value 94.495948
iter  20 value 87.329475
iter  30 value 84.777066
iter  40 value 83.366645
iter  50 value 80.377779
iter  60 value 80.187403
iter  70 value 80.024510
iter  80 value 79.766403
iter  90 value 79.550415
iter 100 value 79.518636
final  value 79.518636 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.965520 
iter  10 value 94.411861
iter  20 value 92.285671
iter  30 value 87.073437
iter  40 value 85.448314
iter  50 value 84.948152
iter  60 value 84.461599
iter  70 value 83.993514
iter  80 value 81.308633
iter  90 value 79.463293
iter 100 value 79.046663
final  value 79.046663 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.911892 
iter  10 value 94.165004
iter  20 value 87.286544
iter  30 value 86.843228
iter  40 value 83.392347
iter  50 value 80.971269
iter  60 value 79.694103
iter  70 value 79.230032
iter  80 value 78.682522
iter  90 value 77.675016
iter 100 value 77.519924
final  value 77.519924 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.645549 
iter  10 value 95.853189
iter  20 value 94.765657
iter  30 value 94.312745
iter  40 value 91.157290
iter  50 value 85.140498
iter  60 value 83.015077
iter  70 value 82.615473
iter  80 value 80.666228
iter  90 value 79.623869
iter 100 value 79.002302
final  value 79.002302 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.930409 
iter  10 value 95.960217
iter  20 value 89.425884
iter  30 value 86.466654
iter  40 value 80.851515
iter  50 value 80.401720
iter  60 value 79.579820
iter  70 value 78.310066
iter  80 value 78.099002
iter  90 value 77.769226
iter 100 value 77.695066
final  value 77.695066 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.163417 
iter  10 value 96.363866
iter  20 value 93.956158
iter  30 value 93.881239
iter  40 value 85.283963
iter  50 value 84.282717
iter  60 value 83.552222
iter  70 value 81.733431
iter  80 value 79.896360
iter  90 value 79.470706
iter 100 value 78.041303
final  value 78.041303 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 138.443457 
iter  10 value 94.994351
iter  20 value 91.361435
iter  30 value 87.253034
iter  40 value 84.737727
iter  50 value 79.994009
iter  60 value 78.472373
iter  70 value 78.006599
iter  80 value 77.800944
iter  90 value 77.683912
iter 100 value 77.502568
final  value 77.502568 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.976592 
iter  10 value 95.589396
iter  20 value 83.322167
iter  30 value 79.186035
iter  40 value 78.578860
iter  50 value 78.048783
iter  60 value 77.997041
iter  70 value 77.870622
iter  80 value 77.705155
iter  90 value 77.652437
iter 100 value 77.625662
final  value 77.625662 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.483974 
iter  10 value 94.311425
iter  20 value 87.934598
iter  30 value 83.283737
iter  40 value 81.244581
iter  50 value 79.797253
iter  60 value 79.135529
iter  70 value 78.360322
iter  80 value 77.837309
iter  90 value 77.474233
iter 100 value 77.151508
final  value 77.151508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.592142 
iter  10 value 94.331552
iter  20 value 91.114337
iter  30 value 82.720801
iter  40 value 80.186460
iter  50 value 79.379987
iter  60 value 79.015940
iter  70 value 78.898248
iter  80 value 78.631537
iter  90 value 78.450645
iter 100 value 78.187870
final  value 78.187870 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.723031 
final  value 94.485888 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.888370 
final  value 94.486064 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.415029 
final  value 94.485826 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.257675 
final  value 94.485877 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.398516 
final  value 94.485803 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.867100 
iter  10 value 94.489046
iter  20 value 94.459494
iter  30 value 94.159821
iter  30 value 94.159821
iter  30 value 94.159821
final  value 94.159821 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.166360 
iter  10 value 94.488573
iter  20 value 90.060959
iter  30 value 83.091932
iter  40 value 83.045049
iter  50 value 82.839203
iter  60 value 79.702456
final  value 79.378003 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.140251 
iter  10 value 94.489148
iter  20 value 94.480655
iter  30 value 90.928738
iter  40 value 84.847043
final  value 84.652178 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.577294 
iter  10 value 94.488971
iter  20 value 94.483994
final  value 94.483858 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.236270 
iter  10 value 94.489265
iter  20 value 94.484353
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.199741 
iter  10 value 94.489786
iter  20 value 94.369109
iter  30 value 93.588249
iter  40 value 93.331533
iter  50 value 93.331271
final  value 93.331267 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.810466 
iter  10 value 94.486470
iter  20 value 93.620914
iter  30 value 83.178761
iter  40 value 82.650647
iter  50 value 82.603212
iter  60 value 82.590915
iter  70 value 82.573324
iter  80 value 82.566321
iter  90 value 82.018140
iter 100 value 79.908014
final  value 79.908014 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.203889 
iter  10 value 94.491782
iter  20 value 94.436598
iter  30 value 93.807601
iter  40 value 93.549817
iter  40 value 93.549817
final  value 93.549817 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.481429 
iter  10 value 93.629768
iter  20 value 93.270234
iter  30 value 84.465239
iter  40 value 83.157988
iter  50 value 82.757281
iter  60 value 82.735615
iter  70 value 82.734460
iter  80 value 82.733007
final  value 82.732519 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.351926 
iter  10 value 94.493157
iter  20 value 94.484840
iter  30 value 93.984366
iter  40 value 93.782540
iter  50 value 93.504771
iter  60 value 93.444259
iter  70 value 93.440033
iter  80 value 93.432574
iter  90 value 93.432244
final  value 93.432187 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.267993 
final  value 93.722223 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.470540 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.979057 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.347335 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.525385 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.369780 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.731493 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.750367 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.958915 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.919935 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.906624 
final  value 93.328261 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.469404 
final  value 93.912644 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.741503 
iter  10 value 93.219075
final  value 93.214674 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.635753 
iter  10 value 93.298760
iter  20 value 93.155302
iter  30 value 93.155035
final  value 93.155030 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.936649 
iter  10 value 94.346978
iter  20 value 93.734480
final  value 93.734322 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.714043 
iter  10 value 93.987975
iter  20 value 89.699717
iter  30 value 85.093208
iter  40 value 84.897950
iter  50 value 84.638334
iter  60 value 84.545133
iter  70 value 84.312519
iter  80 value 84.276332
final  value 84.271382 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.055856 
iter  10 value 93.618219
iter  20 value 93.460232
iter  30 value 87.869976
iter  40 value 86.387244
iter  50 value 86.124543
iter  60 value 84.574546
iter  70 value 84.257901
iter  80 value 84.052060
iter  90 value 83.889906
final  value 83.886553 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.157949 
iter  10 value 94.054861
iter  20 value 93.556794
iter  30 value 93.535111
iter  40 value 93.482328
iter  50 value 90.607221
iter  60 value 86.601871
iter  70 value 85.306924
iter  80 value 84.227725
iter  90 value 83.430765
iter 100 value 83.298470
final  value 83.298470 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.468341 
iter  10 value 93.591745
iter  20 value 93.519990
iter  30 value 93.516592
iter  40 value 93.514439
iter  50 value 92.761474
iter  60 value 89.276271
iter  70 value 89.165547
iter  80 value 86.801625
iter  90 value 85.437102
iter 100 value 84.796619
final  value 84.796619 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 111.020288 
iter  10 value 93.961249
iter  20 value 87.875056
iter  30 value 84.135429
iter  40 value 83.105142
iter  50 value 82.537172
iter  60 value 81.487561
iter  70 value 80.988177
iter  80 value 80.560922
iter  90 value 80.399925
final  value 80.399102 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.773374 
iter  10 value 94.063164
iter  20 value 93.927044
iter  30 value 93.424265
iter  40 value 93.348760
iter  50 value 91.395115
iter  60 value 88.590432
iter  70 value 87.432726
iter  80 value 86.449192
iter  90 value 85.096149
iter 100 value 83.456879
final  value 83.456879 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.849070 
iter  10 value 93.773358
iter  20 value 93.491801
iter  30 value 83.684096
iter  40 value 82.049581
iter  50 value 81.919538
iter  60 value 81.344072
iter  70 value 80.455546
iter  80 value 79.667669
iter  90 value 79.323794
iter 100 value 79.182479
final  value 79.182479 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.218022 
iter  10 value 94.021527
iter  20 value 88.746982
iter  30 value 87.115402
iter  40 value 85.235242
iter  50 value 84.850264
iter  60 value 84.731739
iter  70 value 84.303108
iter  80 value 83.929825
iter  90 value 83.762291
iter 100 value 82.219747
final  value 82.219747 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.988563 
iter  10 value 94.139391
iter  20 value 91.743071
iter  30 value 91.635250
iter  40 value 86.612094
iter  50 value 84.432323
iter  60 value 81.473923
iter  70 value 80.238465
iter  80 value 79.941351
iter  90 value 79.634237
iter 100 value 79.569931
final  value 79.569931 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.996350 
iter  10 value 93.074740
iter  20 value 86.467544
iter  30 value 84.814701
iter  40 value 84.489705
iter  50 value 84.217020
iter  60 value 84.007035
iter  70 value 83.939174
iter  80 value 83.804048
iter  90 value 83.372500
iter 100 value 81.867330
final  value 81.867330 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.651442 
iter  10 value 93.742916
iter  20 value 93.326188
iter  30 value 83.443832
iter  40 value 81.955718
iter  50 value 80.611458
iter  60 value 79.763932
iter  70 value 79.431132
iter  80 value 79.365364
iter  90 value 79.269587
iter 100 value 79.026755
final  value 79.026755 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.080709 
iter  10 value 88.305751
iter  20 value 85.978717
iter  30 value 85.230832
iter  40 value 84.860128
iter  50 value 82.146485
iter  60 value 80.777083
iter  70 value 79.571695
iter  80 value 79.058474
iter  90 value 78.928828
iter 100 value 78.877467
final  value 78.877467 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.366639 
iter  10 value 94.070828
iter  20 value 91.660248
iter  30 value 83.230997
iter  40 value 81.314953
iter  50 value 80.745722
iter  60 value 79.595964
iter  70 value 78.975953
iter  80 value 78.876116
iter  90 value 78.799909
iter 100 value 78.746127
final  value 78.746127 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.165126 
iter  10 value 93.994369
iter  20 value 88.767383
iter  30 value 84.772269
iter  40 value 83.327427
iter  50 value 81.384530
iter  60 value 81.188486
iter  70 value 80.820447
iter  80 value 79.943282
iter  90 value 79.605269
iter 100 value 79.185547
final  value 79.185547 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.601870 
iter  10 value 93.987651
iter  20 value 93.013286
iter  30 value 92.837561
iter  40 value 92.426906
iter  50 value 88.928677
iter  60 value 86.677380
iter  70 value 86.542039
iter  80 value 85.413944
iter  90 value 82.191883
iter 100 value 80.434470
final  value 80.434470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.010586 
iter  10 value 93.330517
iter  20 value 93.330048
iter  30 value 93.329020
iter  40 value 93.189496
iter  50 value 92.515470
iter  60 value 89.744165
iter  70 value 82.488994
iter  80 value 81.390691
iter  90 value 81.313822
iter 100 value 81.313665
final  value 81.313665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 94.494697 
final  value 92.894622 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.864737 
iter  10 value 94.054537
iter  20 value 91.510436
iter  30 value 84.016817
iter  30 value 84.016817
iter  30 value 84.016817
final  value 84.016817 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.771311 
final  value 94.054349 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.007604 
iter  10 value 93.168517
iter  20 value 93.156963
iter  30 value 93.155410
final  value 93.155374 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.148394 
iter  10 value 93.333360
iter  20 value 93.330095
iter  30 value 91.811806
iter  40 value 87.360703
iter  50 value 87.359844
iter  60 value 87.359217
iter  70 value 85.989723
iter  80 value 85.437380
iter  90 value 85.185767
final  value 85.185013 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.377743 
iter  10 value 94.057608
iter  20 value 94.016234
iter  30 value 93.331012
iter  40 value 93.161168
iter  50 value 93.157677
iter  60 value 85.314293
iter  70 value 85.074090
iter  80 value 84.720547
iter  90 value 84.501667
iter 100 value 84.436720
final  value 84.436720 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.886980 
iter  10 value 84.948247
iter  20 value 83.769300
iter  30 value 83.766884
iter  40 value 83.765659
iter  50 value 83.536846
iter  60 value 83.534331
iter  70 value 83.533957
iter  80 value 83.529422
iter  90 value 83.407844
final  value 83.407698 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.366451 
iter  10 value 93.460413
iter  20 value 93.384902
final  value 93.155436 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.832606 
iter  10 value 94.056135
final  value 94.053995 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.032630 
iter  10 value 93.336709
iter  20 value 93.335409
iter  30 value 92.609070
iter  40 value 88.356171
iter  50 value 88.154430
iter  60 value 88.152090
iter  70 value 88.151866
final  value 88.151832 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.301098 
iter  10 value 92.587638
iter  20 value 92.364102
iter  30 value 92.362418
iter  40 value 92.311615
iter  50 value 92.308776
iter  60 value 92.306442
final  value 92.306067 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.415490 
iter  10 value 94.060529
iter  20 value 93.764288
final  value 93.328814 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.608544 
iter  10 value 92.914089
iter  20 value 92.899370
iter  30 value 92.844368
final  value 92.237856 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.508796 
iter  10 value 92.020051
iter  20 value 91.483355
iter  30 value 91.447896
iter  40 value 91.429597
final  value 91.429340 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.421879 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.174331 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 116.211953 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.668323 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.221445 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.732708 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.151780 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.384697 
final  value 93.604520 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.833416 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.844018 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.092443 
iter  10 value 93.836089
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.730976 
iter  10 value 93.836097
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.412816 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.630366 
iter  10 value 89.800435
iter  20 value 87.202284
iter  30 value 87.197495
final  value 87.197327 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.403520 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.379958 
iter  10 value 94.054930
iter  20 value 94.010544
iter  30 value 92.406875
iter  40 value 88.443521
iter  50 value 87.665068
iter  60 value 86.308686
iter  70 value 86.251070
final  value 86.251033 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.325706 
iter  10 value 94.056836
iter  20 value 93.863154
iter  30 value 89.578789
iter  40 value 87.975985
iter  50 value 87.704977
iter  60 value 87.670427
iter  60 value 87.670427
iter  60 value 87.670427
final  value 87.670427 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.615863 
iter  10 value 93.800898
iter  20 value 89.515487
iter  30 value 88.189551
iter  40 value 87.965926
iter  50 value 87.828560
iter  60 value 87.618374
iter  70 value 87.494121
final  value 87.493738 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.702794 
iter  10 value 94.079122
iter  20 value 93.999541
iter  30 value 92.018212
iter  40 value 88.287206
iter  50 value 87.941613
iter  60 value 87.797352
iter  70 value 87.722303
iter  80 value 86.275902
iter  90 value 85.507714
iter 100 value 85.069840
final  value 85.069840 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.328260 
iter  10 value 92.921889
iter  20 value 88.593983
iter  30 value 87.812233
iter  40 value 87.558794
iter  50 value 87.419843
iter  60 value 87.413535
final  value 87.412015 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.332995 
iter  10 value 94.055535
iter  20 value 93.083453
iter  30 value 90.083708
iter  40 value 89.218540
iter  50 value 89.096685
iter  60 value 88.513556
iter  70 value 85.842199
iter  80 value 84.837688
iter  90 value 84.223618
iter 100 value 84.004333
final  value 84.004333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.143727 
iter  10 value 94.603056
iter  20 value 94.081333
iter  30 value 90.861683
iter  40 value 88.564302
iter  50 value 87.840642
iter  60 value 87.033441
iter  70 value 86.691625
iter  80 value 86.667384
iter  90 value 86.614302
iter 100 value 86.138120
final  value 86.138120 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.715633 
iter  10 value 93.259391
iter  20 value 88.278189
iter  30 value 87.271944
iter  40 value 85.382416
iter  50 value 84.835114
iter  60 value 84.430487
iter  70 value 84.288528
iter  80 value 84.270146
iter  90 value 84.201812
iter 100 value 83.976004
final  value 83.976004 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.910924 
iter  10 value 94.061800
iter  20 value 93.979102
iter  30 value 89.769851
iter  40 value 88.050850
iter  50 value 87.821879
iter  60 value 87.286279
iter  70 value 87.046708
iter  80 value 86.909839
iter  90 value 86.647140
iter 100 value 86.123485
final  value 86.123485 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.562906 
iter  10 value 94.198976
iter  20 value 92.696159
iter  30 value 91.630727
iter  40 value 87.282993
iter  50 value 86.621970
iter  60 value 86.050906
iter  70 value 85.648869
iter  80 value 85.553572
iter  90 value 85.099629
iter 100 value 84.317819
final  value 84.317819 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.585220 
iter  10 value 94.154627
iter  20 value 88.975726
iter  30 value 88.053039
iter  40 value 86.645484
iter  50 value 85.542079
iter  60 value 84.622968
iter  70 value 84.237239
iter  80 value 84.091775
iter  90 value 83.864461
iter 100 value 83.824714
final  value 83.824714 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 142.932801 
iter  10 value 94.461913
iter  20 value 90.763017
iter  30 value 89.234766
iter  40 value 87.404975
iter  50 value 87.045707
iter  60 value 86.888006
iter  70 value 85.825996
iter  80 value 84.807484
iter  90 value 84.351524
iter 100 value 83.952091
final  value 83.952091 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.236091 
iter  10 value 91.583928
iter  20 value 88.179047
iter  30 value 86.423338
iter  40 value 84.897772
iter  50 value 84.575763
iter  60 value 84.133738
iter  70 value 83.790103
iter  80 value 83.704675
iter  90 value 83.628717
iter 100 value 83.601516
final  value 83.601516 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.925966 
iter  10 value 92.480924
iter  20 value 89.010212
iter  30 value 87.318341
iter  40 value 85.902471
iter  50 value 85.288674
iter  60 value 85.020832
iter  70 value 84.487279
iter  80 value 84.086168
iter  90 value 83.760933
iter 100 value 83.551952
final  value 83.551952 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.081103 
iter  10 value 94.158578
iter  20 value 94.064127
iter  30 value 92.865902
iter  40 value 88.949885
iter  50 value 87.059873
iter  60 value 85.873032
iter  70 value 84.666803
iter  80 value 84.237018
iter  90 value 84.029396
iter 100 value 83.934217
final  value 83.934217 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.944846 
final  value 94.054572 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.794892 
iter  10 value 94.054659
iter  20 value 94.009603
final  value 93.604699 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.034754 
final  value 94.054314 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.048515 
iter  10 value 94.054627
iter  20 value 94.052988
iter  30 value 88.779341
final  value 88.775449 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.935364 
final  value 94.054817 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.875462 
iter  10 value 94.021514
iter  20 value 92.068594
iter  30 value 88.227303
final  value 88.222227 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.747037 
iter  10 value 94.057369
iter  20 value 91.897544
iter  30 value 89.220722
iter  40 value 88.322752
iter  50 value 85.901910
iter  60 value 84.628475
iter  70 value 84.000520
iter  80 value 83.908638
iter  90 value 83.858104
iter 100 value 83.857351
final  value 83.857351 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.100668 
iter  10 value 94.057729
iter  20 value 93.998805
iter  30 value 93.219452
iter  40 value 90.035477
final  value 90.029493 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.394465 
iter  10 value 94.056549
iter  20 value 92.484121
iter  30 value 92.342399
iter  40 value 92.338850
iter  50 value 92.331337
iter  60 value 92.055660
iter  70 value 91.588501
iter  80 value 91.588006
final  value 91.587980 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.157924 
iter  10 value 94.057688
iter  20 value 94.052704
final  value 93.836186 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.757495 
iter  10 value 94.045120
iter  20 value 93.217522
iter  30 value 92.704618
iter  40 value 92.287843
iter  50 value 92.052575
iter  60 value 92.049577
iter  70 value 91.881027
final  value 91.865993 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.075776 
iter  10 value 93.878237
iter  20 value 93.641348
iter  30 value 90.439810
iter  40 value 86.339033
iter  50 value 85.767699
iter  60 value 85.665873
iter  70 value 85.292665
iter  80 value 85.135945
iter  90 value 85.120348
iter 100 value 85.119828
final  value 85.119828 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.652590 
iter  10 value 94.059113
iter  20 value 94.027782
iter  30 value 89.448849
iter  40 value 88.079402
iter  50 value 87.148442
iter  60 value 85.909595
iter  70 value 85.897713
final  value 85.897655 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.559963 
iter  10 value 92.389799
iter  20 value 91.924673
iter  30 value 91.868685
iter  40 value 91.749274
iter  50 value 91.744542
iter  60 value 91.743921
iter  70 value 91.737411
final  value 91.736870 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.470236 
iter  10 value 93.483270
iter  20 value 93.247719
iter  30 value 93.240966
iter  40 value 93.232866
iter  50 value 93.217331
iter  60 value 91.725704
iter  70 value 85.899427
iter  80 value 85.578934
iter  90 value 83.170027
iter 100 value 82.602292
final  value 82.602292 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 118.947915 
iter  10 value 117.763503
iter  20 value 111.963037
iter  30 value 104.886977
iter  40 value 104.449366
iter  50 value 104.294893
iter  60 value 104.294260
iter  70 value 104.175622
iter  80 value 104.057487
final  value 104.057483 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.137736 
iter  10 value 117.894055
iter  20 value 117.763205
iter  30 value 112.086835
iter  40 value 107.743906
iter  50 value 105.267138
iter  60 value 104.838400
iter  70 value 104.783682
iter  80 value 104.781108
iter  90 value 104.551125
iter 100 value 102.326987
final  value 102.326987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 134.028900 
iter  10 value 117.763601
iter  20 value 117.665475
iter  30 value 116.437551
iter  40 value 107.329249
iter  50 value 99.770134
iter  60 value 99.398019
iter  70 value 99.391074
iter  80 value 99.388195
iter  90 value 99.387319
iter 100 value 99.386827
final  value 99.386827 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 132.018824 
iter  10 value 117.895926
iter  20 value 117.691052
iter  30 value 105.367915
final  value 105.343478 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.521699 
iter  10 value 117.895172
iter  20 value 117.890302
iter  20 value 117.890301
iter  20 value 117.890300
final  value 117.890300 
converged
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 -- Sun Mar 23 23:09:05 2025 
*********************************************** 
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 
 38.698   1.243 132.218