##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 Patched (2026-05-01 r89994)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-05-19 02:02:18 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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
corr_plot     16.951  0.075  17.054
var_imp       16.890  0.087  17.121
FSmethod      16.897  0.066  17.187
pred_ensembel  6.087  0.179   5.535
enrichfindP    0.200  0.034  12.945
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** 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 version 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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
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 112.172807 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.178724 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.763529 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.548114 
iter  10 value 93.502281
final  value 93.221050 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.075620 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.360348 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.334028 
final  value 94.449438 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.331082 
iter  10 value 94.379623
iter  20 value 93.743443
iter  30 value 92.993707
iter  40 value 92.911447
final  value 92.911240 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.371911 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.124475 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.322991 
final  value 94.442074 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.913440 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.651972 
final  value 94.248062 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.468137 
iter  10 value 85.747644
final  value 85.226615 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.340000 
iter  10 value 93.228271
iter  20 value 85.887761
iter  30 value 85.761036
iter  40 value 85.719380
iter  50 value 85.226626
iter  60 value 85.226564
final  value 85.226560 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.612545 
iter  10 value 94.486885
iter  20 value 94.329097
iter  30 value 94.328092
iter  40 value 91.835512
iter  50 value 88.137503
iter  60 value 86.909121
iter  70 value 85.823039
iter  80 value 85.639472
iter  90 value 85.616340
iter  90 value 85.616340
iter  90 value 85.616340
final  value 85.616340 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.049991 
iter  10 value 93.852469
iter  20 value 90.114321
iter  30 value 87.338242
iter  40 value 86.944287
iter  50 value 86.745646
iter  60 value 86.713112
iter  70 value 86.707970
iter  70 value 86.707970
iter  70 value 86.707970
final  value 86.707970 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.864773 
iter  10 value 90.619119
iter  20 value 88.538437
iter  30 value 87.798475
iter  40 value 87.244492
iter  50 value 86.652774
iter  60 value 84.281982
iter  70 value 84.223547
final  value 84.218704 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.602666 
iter  10 value 94.321228
iter  20 value 93.307176
iter  30 value 91.161897
iter  40 value 90.986339
iter  50 value 86.462591
iter  60 value 85.161323
iter  70 value 84.594182
iter  80 value 84.097049
iter  90 value 83.901803
final  value 83.900758 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.910246 
iter  10 value 94.426745
iter  20 value 90.009969
iter  30 value 88.839467
iter  40 value 88.037426
iter  50 value 87.110663
iter  60 value 84.399402
iter  70 value 84.195685
final  value 84.195264 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.210145 
iter  10 value 94.454725
iter  20 value 92.753581
iter  30 value 87.823850
iter  40 value 86.197333
iter  50 value 85.945477
iter  60 value 85.670369
iter  70 value 84.759062
iter  80 value 84.481943
iter  90 value 84.289714
iter 100 value 83.829139
final  value 83.829139 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.252227 
iter  10 value 94.516166
iter  20 value 91.004525
iter  30 value 88.975482
iter  40 value 87.104134
iter  50 value 86.389646
iter  60 value 85.540209
iter  70 value 85.252167
iter  80 value 84.816957
iter  90 value 84.613540
iter 100 value 84.515730
final  value 84.515730 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.398869 
iter  10 value 95.287032
iter  20 value 93.407622
iter  30 value 88.520034
iter  40 value 85.584320
iter  50 value 85.170594
iter  60 value 84.731889
iter  70 value 83.562561
iter  80 value 83.279535
iter  90 value 83.171946
iter 100 value 82.977573
final  value 82.977573 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.726091 
iter  10 value 94.427162
iter  20 value 92.060197
iter  30 value 86.332289
iter  40 value 84.179941
iter  50 value 82.971023
iter  60 value 82.687619
iter  70 value 82.524284
iter  80 value 82.440474
iter  90 value 82.408523
iter 100 value 82.338551
final  value 82.338551 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.874496 
iter  10 value 94.354523
iter  20 value 87.515878
iter  30 value 86.611397
iter  40 value 85.725610
iter  50 value 83.370419
iter  60 value 82.761337
iter  70 value 82.587058
iter  80 value 82.560102
iter  90 value 82.476811
iter 100 value 82.441100
final  value 82.441100 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.735529 
iter  10 value 89.996929
iter  20 value 87.489422
iter  30 value 86.788408
iter  40 value 85.921044
iter  50 value 83.163549
iter  60 value 82.549249
iter  70 value 82.191899
iter  80 value 82.161613
iter  90 value 82.115418
iter 100 value 81.979136
final  value 81.979136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 145.184018 
iter  10 value 94.880640
iter  20 value 94.055020
iter  30 value 87.519492
iter  40 value 86.258566
iter  50 value 85.136832
iter  60 value 84.259251
iter  70 value 83.918176
iter  80 value 83.266800
iter  90 value 82.990970
iter 100 value 82.720949
final  value 82.720949 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.272531 
iter  10 value 94.426585
iter  20 value 94.269575
iter  30 value 87.330971
iter  40 value 86.288971
iter  50 value 85.541005
iter  60 value 84.947169
iter  70 value 84.895048
iter  80 value 84.783664
iter  90 value 84.662186
iter 100 value 84.087338
final  value 84.087338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.020487 
iter  10 value 92.905663
iter  20 value 87.001086
iter  30 value 85.949203
iter  40 value 84.234808
iter  50 value 83.797341
iter  60 value 83.591698
iter  70 value 83.300777
iter  80 value 82.686648
iter  90 value 82.543118
iter 100 value 82.470807
final  value 82.470807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.379497 
iter  10 value 95.426019
iter  20 value 86.727311
iter  30 value 85.353113
iter  40 value 83.969086
iter  50 value 83.894196
iter  60 value 83.836818
iter  70 value 83.762285
iter  80 value 83.693061
iter  90 value 83.369643
iter 100 value 82.794205
final  value 82.794205 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.208450 
final  value 94.485882 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.688081 
final  value 94.485747 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.142720 
final  value 94.485726 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.072082 
final  value 94.276935 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.905172 
final  value 94.485651 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.161904 
iter  10 value 94.488502
iter  20 value 94.236353
iter  30 value 93.950926
iter  40 value 87.043796
iter  50 value 87.012893
iter  60 value 87.012123
iter  70 value 87.005426
iter  80 value 86.985287
iter  90 value 86.677879
iter 100 value 85.677340
final  value 85.677340 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.378105 
iter  10 value 94.489145
iter  20 value 94.448036
iter  30 value 94.189630
iter  40 value 93.936304
iter  50 value 93.935554
iter  60 value 87.038196
iter  70 value 86.683617
iter  80 value 86.628768
iter  90 value 86.468618
iter 100 value 86.465951
final  value 86.465951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.626810 
iter  10 value 94.093521
iter  20 value 93.177007
iter  30 value 92.530380
iter  40 value 92.529930
iter  40 value 92.529929
iter  40 value 92.529929
final  value 92.529929 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.446472 
iter  10 value 94.279802
iter  20 value 94.234141
iter  30 value 92.785920
iter  40 value 85.122361
iter  50 value 84.072994
iter  60 value 82.886072
iter  70 value 82.731072
final  value 82.730879 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.509551 
iter  10 value 94.297912
iter  20 value 94.257693
iter  30 value 94.231339
iter  40 value 94.230236
iter  50 value 90.309730
iter  60 value 86.697362
iter  70 value 86.578505
iter  80 value 86.382985
iter  90 value 86.382862
final  value 86.382749 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.700236 
iter  10 value 94.501689
iter  20 value 94.487608
iter  30 value 88.060295
iter  40 value 86.629455
iter  50 value 86.627499
iter  60 value 86.553877
iter  70 value 86.502080
iter  80 value 86.317552
iter  90 value 85.506207
iter 100 value 85.037248
final  value 85.037248 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.401690 
iter  10 value 94.289551
iter  20 value 89.840828
iter  30 value 87.744339
iter  40 value 86.093637
iter  50 value 85.793974
iter  60 value 85.619987
iter  70 value 85.618816
iter  80 value 85.618392
final  value 85.617218 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.420491 
iter  10 value 94.492875
iter  20 value 94.482231
iter  30 value 94.290931
iter  40 value 90.293815
iter  50 value 89.740198
iter  60 value 89.527757
iter  70 value 89.526877
iter  80 value 89.292705
iter  90 value 89.116948
iter 100 value 88.064751
final  value 88.064751 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.648958 
iter  10 value 94.492154
iter  20 value 94.343242
iter  30 value 93.584519
iter  40 value 93.366061
iter  50 value 86.563661
iter  60 value 85.934139
iter  70 value 85.013631
iter  80 value 85.001447
iter  80 value 85.001446
iter  80 value 85.001446
final  value 85.001446 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.936114 
iter  10 value 94.487957
iter  20 value 94.144911
iter  30 value 86.274322
iter  40 value 85.272498
iter  50 value 85.271277
final  value 85.271166 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.677192 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.038599 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.133166 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.121563 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.194183 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.937900 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.272731 
final  value 94.024690 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.348452 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.985937 
iter  10 value 86.372139
final  value 86.268065 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.762762 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.387736 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 92.470113 
iter  10 value 89.817934
final  value 89.817648 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.574951 
iter  10 value 93.755621
iter  20 value 92.835309
iter  30 value 92.781135
final  value 92.779912 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.405417 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.402698 
iter  10 value 93.438698
final  value 93.366019 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.095284 
iter  10 value 94.056769
iter  20 value 92.636407
iter  30 value 91.141998
iter  40 value 91.061931
iter  50 value 91.059584
iter  60 value 91.059345
iter  70 value 91.059097
iter  80 value 91.058928
final  value 91.058912 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.443374 
iter  10 value 93.576380
iter  20 value 91.287382
iter  30 value 84.395682
iter  40 value 81.664317
iter  50 value 80.872112
iter  60 value 79.400883
iter  70 value 79.323192
final  value 79.317794 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.862647 
iter  10 value 87.650065
iter  20 value 86.753161
iter  30 value 85.593845
iter  40 value 83.495566
iter  50 value 81.152116
iter  60 value 80.026009
iter  70 value 79.397741
iter  80 value 79.343879
final  value 79.343876 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.584003 
iter  10 value 94.064098
iter  20 value 93.013224
iter  30 value 91.356342
iter  40 value 81.530300
iter  50 value 80.886895
iter  60 value 80.584419
iter  70 value 79.461077
iter  80 value 79.317826
final  value 79.317811 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.625619 
iter  10 value 93.949791
iter  20 value 91.549859
iter  30 value 85.794516
iter  40 value 85.733934
iter  50 value 85.453837
iter  60 value 84.717056
iter  70 value 82.856501
iter  80 value 82.671925
iter  90 value 82.637348
iter 100 value 82.553623
final  value 82.553623 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.853909 
iter  10 value 94.040280
iter  20 value 92.933270
iter  30 value 91.751163
iter  40 value 87.585803
iter  50 value 86.837852
iter  60 value 82.507797
iter  70 value 81.805656
iter  80 value 81.639750
iter  90 value 81.168689
iter 100 value 81.062406
final  value 81.062406 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.423184 
iter  10 value 93.783202
iter  20 value 92.937171
iter  30 value 92.581787
iter  40 value 86.429186
iter  50 value 84.264556
iter  60 value 81.654223
iter  70 value 80.983044
iter  80 value 79.989894
iter  90 value 79.176396
iter 100 value 79.045627
final  value 79.045627 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.370129 
iter  10 value 93.208950
iter  20 value 88.220470
iter  30 value 84.402137
iter  40 value 83.084196
iter  50 value 81.132137
iter  60 value 78.872324
iter  70 value 78.706401
iter  80 value 78.337895
iter  90 value 78.011507
iter 100 value 77.553107
final  value 77.553107 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.618218 
iter  10 value 93.778453
iter  20 value 88.767519
iter  30 value 85.389389
iter  40 value 83.743959
iter  50 value 83.496095
iter  60 value 82.528593
iter  70 value 82.417000
iter  80 value 82.240930
iter  90 value 81.499318
iter 100 value 79.012995
final  value 79.012995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.975057 
iter  10 value 94.861128
iter  20 value 93.989519
iter  30 value 87.277482
iter  40 value 83.796755
iter  50 value 82.986108
iter  60 value 82.868056
iter  70 value 81.932934
iter  80 value 80.732388
iter  90 value 79.361812
iter 100 value 79.209816
final  value 79.209816 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.838693 
iter  10 value 92.682088
iter  20 value 91.769674
iter  30 value 90.266684
iter  40 value 85.031601
iter  50 value 82.651441
iter  60 value 80.411266
iter  70 value 78.930019
iter  80 value 78.604776
iter  90 value 78.302119
iter 100 value 78.029598
final  value 78.029598 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.675951 
iter  10 value 94.324509
iter  20 value 87.157022
iter  30 value 85.054273
iter  40 value 83.830093
iter  50 value 80.807767
iter  60 value 79.322334
iter  70 value 78.579260
iter  80 value 78.181153
iter  90 value 77.944579
iter 100 value 77.816493
final  value 77.816493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.006871 
iter  10 value 93.924915
iter  20 value 88.662788
iter  30 value 86.819157
iter  40 value 84.855010
iter  50 value 82.516903
iter  60 value 80.443976
iter  70 value 79.233034
iter  80 value 78.735417
iter  90 value 78.614955
iter 100 value 78.459681
final  value 78.459681 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.230561 
iter  10 value 93.885153
iter  20 value 90.976833
iter  30 value 90.135819
iter  40 value 89.005181
iter  50 value 81.616184
iter  60 value 79.635898
iter  70 value 79.334486
iter  80 value 79.224974
iter  90 value 79.142148
iter 100 value 79.057158
final  value 79.057158 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.665531 
iter  10 value 92.943028
iter  20 value 86.088684
iter  30 value 83.745786
iter  40 value 81.030668
iter  50 value 79.701372
iter  60 value 79.086961
iter  70 value 78.401219
iter  80 value 78.118025
iter  90 value 77.922164
iter 100 value 77.689195
final  value 77.689195 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.254872 
final  value 94.054413 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.275894 
iter  10 value 94.053108
iter  20 value 92.688292
iter  30 value 85.185860
final  value 85.125142 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.314712 
final  value 94.054699 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.462646 
final  value 94.054578 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.059422 
final  value 94.054650 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.832785 
iter  10 value 93.588143
iter  20 value 93.585401
iter  30 value 86.303182
iter  40 value 82.768500
iter  50 value 82.492368
iter  60 value 81.805936
final  value 81.782268 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.096990 
iter  10 value 93.875067
iter  20 value 89.552647
iter  30 value 86.482612
iter  40 value 84.608535
iter  50 value 84.388066
iter  60 value 84.348342
iter  70 value 84.347762
iter  80 value 82.223236
iter  90 value 81.542788
iter 100 value 81.518201
final  value 81.518201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.937147 
iter  10 value 92.985807
iter  20 value 92.824650
iter  30 value 91.658038
iter  40 value 89.561838
iter  50 value 89.561320
iter  60 value 89.457681
iter  70 value 89.457217
iter  80 value 89.455783
final  value 89.455550 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.731073 
iter  10 value 92.867031
iter  20 value 92.844712
iter  30 value 92.605396
iter  30 value 92.605396
iter  30 value 92.605396
final  value 92.605396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.156261 
iter  10 value 94.057582
iter  20 value 93.763415
final  value 93.582740 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.735755 
iter  10 value 94.061267
iter  20 value 93.704938
iter  30 value 93.584305
iter  40 value 93.464933
iter  50 value 82.610501
iter  60 value 82.191531
iter  70 value 82.138512
iter  80 value 81.793307
iter  90 value 81.207553
iter 100 value 80.883125
final  value 80.883125 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.002122 
iter  10 value 94.061421
iter  20 value 93.093761
iter  30 value 92.723613
iter  40 value 92.612944
iter  50 value 92.611760
iter  60 value 92.461411
iter  70 value 92.460932
iter  80 value 92.460240
iter  90 value 92.434047
iter 100 value 89.790557
final  value 89.790557 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.488778 
iter  10 value 93.591305
iter  20 value 92.928991
iter  30 value 84.304589
iter  40 value 84.202946
iter  50 value 84.202153
iter  60 value 84.193880
iter  70 value 83.846764
iter  80 value 79.010635
iter  90 value 78.577766
iter 100 value 78.020467
final  value 78.020467 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.451323 
iter  10 value 89.136143
iter  20 value 85.233765
iter  30 value 84.933893
iter  40 value 84.932809
iter  50 value 84.535880
iter  60 value 84.528346
iter  70 value 81.429793
iter  80 value 80.132086
iter  90 value 79.429297
iter 100 value 78.503507
final  value 78.503507 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.612057 
iter  10 value 90.651596
iter  20 value 90.458425
iter  30 value 90.457002
iter  40 value 90.451313
iter  50 value 90.407735
iter  60 value 88.970677
iter  70 value 80.184457
iter  80 value 79.462001
iter  90 value 79.459434
iter  90 value 79.459434
final  value 79.459434 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.987999 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.146886 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.863927 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.379448 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.578484 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.315968 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.659029 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.180172 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.432383 
iter  10 value 94.044034
final  value 93.991525 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.030245 
iter  10 value 94.032969
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.993246 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.122756 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.848213 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.270516 
iter  10 value 91.921418
final  value 91.845734 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.463138 
iter  10 value 93.539614
iter  20 value 91.701367
iter  30 value 86.256801
iter  40 value 84.762844
iter  50 value 84.756083
iter  60 value 81.479467
iter  70 value 81.177180
final  value 81.072076 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.699661 
iter  10 value 86.414205
iter  20 value 82.554834
iter  30 value 82.327151
iter  40 value 82.226969
iter  50 value 82.105811
final  value 82.105465 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.667188 
iter  10 value 94.056787
iter  20 value 91.097113
iter  30 value 83.066701
iter  40 value 82.817987
iter  50 value 81.783545
final  value 81.764641 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.760954 
iter  10 value 94.057265
iter  20 value 93.163883
iter  30 value 92.623089
iter  40 value 92.542928
iter  50 value 83.564920
iter  60 value 82.678181
iter  70 value 81.954162
iter  80 value 81.736599
iter  90 value 81.726364
final  value 81.726362 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.432241 
iter  10 value 93.986275
iter  20 value 92.567873
iter  30 value 87.377145
iter  40 value 86.846312
iter  50 value 83.800660
iter  60 value 82.381709
iter  70 value 82.109919
iter  80 value 82.100509
final  value 82.100151 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.415615 
iter  10 value 93.734690
iter  20 value 83.424772
iter  30 value 82.016939
iter  40 value 81.866257
iter  50 value 81.767350
final  value 81.764541 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.799510 
iter  10 value 94.040056
iter  20 value 90.338204
iter  30 value 87.251967
iter  40 value 82.871275
iter  50 value 81.144486
iter  60 value 80.083193
iter  70 value 78.816484
iter  80 value 78.366099
iter  90 value 78.273636
iter 100 value 78.039515
final  value 78.039515 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.084973 
iter  10 value 94.181495
iter  20 value 94.038582
iter  30 value 90.596182
iter  40 value 90.166311
iter  50 value 86.853611
iter  60 value 86.384387
iter  70 value 85.118910
iter  80 value 82.477977
iter  90 value 82.154889
iter 100 value 81.958762
final  value 81.958762 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.324209 
iter  10 value 94.061940
iter  20 value 92.642542
iter  30 value 91.689552
iter  40 value 86.483384
iter  50 value 84.461931
iter  60 value 82.202781
iter  70 value 81.799223
iter  80 value 81.544162
iter  90 value 81.309516
iter 100 value 79.020746
final  value 79.020746 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.513097 
iter  10 value 94.143248
iter  20 value 93.726914
iter  30 value 91.674147
iter  40 value 88.458451
iter  50 value 81.923205
iter  60 value 81.010374
iter  70 value 80.526615
iter  80 value 80.454331
iter  90 value 80.274988
iter 100 value 79.725575
final  value 79.725575 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.697213 
iter  10 value 94.061094
iter  20 value 94.050002
iter  30 value 87.244278
iter  40 value 83.655876
iter  50 value 81.878594
iter  60 value 81.328525
iter  70 value 79.953254
iter  80 value 78.611693
iter  90 value 77.931982
iter 100 value 77.575416
final  value 77.575416 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.168571 
iter  10 value 93.783136
iter  20 value 85.022184
iter  30 value 82.460988
iter  40 value 82.056969
iter  50 value 81.888302
iter  60 value 81.839324
iter  70 value 81.762411
iter  80 value 81.497206
iter  90 value 80.325730
iter 100 value 78.333196
final  value 78.333196 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.968557 
iter  10 value 94.774515
iter  20 value 93.849099
iter  30 value 93.581709
iter  40 value 88.658224
iter  50 value 79.316505
iter  60 value 78.305999
iter  70 value 77.732117
iter  80 value 77.511012
iter  90 value 77.463965
iter 100 value 77.378472
final  value 77.378472 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.876570 
iter  10 value 93.757846
iter  20 value 86.991793
iter  30 value 85.574336
iter  40 value 85.430771
iter  50 value 82.449007
iter  60 value 82.076442
iter  70 value 79.963803
iter  80 value 78.755154
iter  90 value 78.349546
iter 100 value 78.062640
final  value 78.062640 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.074651 
iter  10 value 93.866615
iter  20 value 83.729658
iter  30 value 83.397752
iter  40 value 82.574748
iter  50 value 81.644822
iter  60 value 80.025658
iter  70 value 79.652050
iter  80 value 79.409101
iter  90 value 78.463997
iter 100 value 77.921520
final  value 77.921520 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.403733 
iter  10 value 93.871048
iter  20 value 87.810230
iter  30 value 85.168207
iter  40 value 83.279187
iter  50 value 82.127028
iter  60 value 80.344018
iter  70 value 79.350184
iter  80 value 79.061549
iter  90 value 78.496396
iter 100 value 78.201698
final  value 78.201698 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.255403 
final  value 94.054768 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.889721 
final  value 94.054719 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.315400 
final  value 94.054532 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.996551 
iter  10 value 94.054485
iter  20 value 94.052955
final  value 94.052912 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.178993 
final  value 94.054425 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.055603 
iter  10 value 93.609700
iter  20 value 93.605360
iter  30 value 88.555531
iter  40 value 83.624998
iter  50 value 83.621745
iter  60 value 83.621348
iter  60 value 83.621348
final  value 83.621348 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.617768 
iter  10 value 94.057659
iter  20 value 93.900982
iter  30 value 93.549667
iter  40 value 93.545009
final  value 93.544967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.168460 
iter  10 value 94.038421
iter  20 value 94.033372
iter  30 value 93.102405
iter  40 value 81.564266
iter  50 value 81.542626
iter  60 value 81.539696
iter  70 value 80.958603
iter  80 value 80.955871
iter  90 value 80.952089
final  value 80.951752 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.994478 
iter  10 value 94.058134
iter  20 value 94.052929
final  value 94.052913 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.906759 
iter  10 value 94.058534
iter  20 value 93.971928
iter  30 value 92.502519
iter  40 value 83.984598
iter  50 value 83.976935
iter  60 value 83.975557
iter  70 value 83.775278
iter  80 value 82.159570
iter  90 value 79.420030
iter 100 value 78.914447
final  value 78.914447 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.811483 
iter  10 value 92.685866
iter  20 value 92.223371
iter  30 value 92.217018
iter  40 value 92.185257
iter  50 value 89.882426
iter  60 value 79.940698
iter  70 value 79.813539
iter  80 value 79.797945
final  value 79.797514 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.295371 
iter  10 value 94.061720
iter  20 value 94.050281
iter  30 value 91.144086
iter  40 value 85.193443
iter  50 value 84.401498
iter  60 value 84.372123
iter  70 value 82.154114
iter  80 value 82.112625
iter  90 value 82.095045
iter 100 value 82.088307
final  value 82.088307 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.230100 
iter  10 value 94.041861
iter  20 value 93.935760
iter  30 value 91.551970
iter  40 value 89.977980
iter  50 value 89.847868
iter  60 value 89.452908
iter  70 value 82.496761
iter  80 value 82.495330
iter  90 value 82.113177
iter 100 value 81.898050
final  value 81.898050 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.890705 
iter  10 value 94.037161
iter  20 value 93.614069
iter  30 value 93.608409
iter  40 value 89.147730
iter  50 value 81.550917
iter  60 value 81.537219
iter  70 value 81.536815
iter  80 value 81.329104
final  value 80.940884 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.226004 
iter  10 value 94.060242
iter  20 value 93.735405
iter  30 value 93.601761
final  value 93.601752 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.409749 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.617599 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.838201 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.073730 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.829438 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.649296 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.958778 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.447723 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.113009 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.914440 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.328865 
iter  10 value 94.400069
final  value 94.400002 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.001403 
iter  10 value 94.323659
iter  20 value 84.641548
iter  30 value 82.095790
iter  40 value 82.044419
iter  50 value 82.043195
final  value 82.043171 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.385160 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.876433 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.570927 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.091094 
iter  10 value 93.177957
iter  20 value 86.098658
iter  30 value 85.036908
iter  40 value 84.953266
iter  50 value 84.809902
iter  60 value 84.337696
iter  70 value 83.813680
iter  80 value 83.726843
final  value 83.726506 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.293247 
iter  10 value 94.465010
iter  20 value 87.040681
iter  30 value 85.932277
iter  40 value 85.672440
iter  50 value 84.964535
iter  60 value 84.267156
iter  70 value 83.969140
iter  80 value 83.730352
final  value 83.726506 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.729866 
iter  10 value 94.486628
iter  20 value 94.427946
iter  30 value 90.397965
iter  40 value 86.365033
iter  50 value 85.902345
iter  60 value 85.779212
iter  70 value 84.435750
iter  80 value 84.025823
iter  90 value 83.760981
iter 100 value 83.727785
final  value 83.727785 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.615001 
iter  10 value 94.515435
iter  20 value 94.071442
iter  30 value 91.848734
iter  40 value 88.858115
iter  50 value 84.516535
iter  60 value 84.158460
iter  70 value 83.491874
iter  80 value 83.291902
iter  90 value 83.280134
final  value 83.279150 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.663111 
iter  10 value 94.489802
iter  20 value 94.099943
iter  30 value 90.914295
iter  40 value 87.074412
iter  50 value 86.303487
iter  60 value 85.912467
iter  70 value 85.700330
iter  80 value 83.694682
iter  90 value 82.750760
iter 100 value 82.742643
final  value 82.742643 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 119.392881 
iter  10 value 94.491424
iter  20 value 94.021882
iter  30 value 90.051794
iter  40 value 89.298159
iter  50 value 88.454028
iter  60 value 87.414205
iter  70 value 86.542129
iter  80 value 83.140993
iter  90 value 81.266654
iter 100 value 80.620396
final  value 80.620396 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.893321 
iter  10 value 94.619080
iter  20 value 85.546395
iter  30 value 85.213281
iter  40 value 84.101586
iter  50 value 81.966292
iter  60 value 81.056197
iter  70 value 80.835199
iter  80 value 80.635160
iter  90 value 80.550965
iter 100 value 80.544405
final  value 80.544405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.733835 
iter  10 value 94.920191
iter  20 value 87.390970
iter  30 value 85.249947
iter  40 value 83.242021
iter  50 value 82.302550
iter  60 value 82.155613
iter  70 value 82.097799
iter  80 value 82.073600
iter  90 value 82.035550
iter 100 value 81.709484
final  value 81.709484 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.529824 
iter  10 value 94.007467
iter  20 value 88.050248
iter  30 value 86.857422
iter  40 value 86.036077
iter  50 value 85.225902
iter  60 value 84.702333
iter  70 value 82.839144
iter  80 value 81.832713
iter  90 value 81.661454
iter 100 value 81.608405
final  value 81.608405 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.856193 
iter  10 value 94.527388
iter  20 value 88.765928
iter  30 value 85.243695
iter  40 value 85.003924
iter  50 value 84.928272
iter  60 value 83.965733
iter  70 value 81.861152
iter  80 value 80.635933
iter  90 value 80.371331
iter 100 value 80.276560
final  value 80.276560 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.038514 
iter  10 value 94.483241
iter  20 value 93.822600
iter  30 value 90.307765
iter  40 value 86.610435
iter  50 value 84.715343
iter  60 value 84.066911
iter  70 value 83.742244
iter  80 value 83.563877
iter  90 value 83.105343
iter 100 value 82.160285
final  value 82.160285 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.049050 
iter  10 value 94.181938
iter  20 value 84.326878
iter  30 value 82.732944
iter  40 value 81.387904
iter  50 value 80.279279
iter  60 value 79.614753
iter  70 value 79.495406
iter  80 value 79.404887
iter  90 value 79.326586
iter 100 value 79.274744
final  value 79.274744 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.577762 
iter  10 value 94.661489
iter  20 value 94.313061
iter  30 value 91.231432
iter  40 value 83.464572
iter  50 value 82.100171
iter  60 value 81.526040
iter  70 value 80.604540
iter  80 value 80.185177
iter  90 value 79.824296
iter 100 value 79.456212
final  value 79.456212 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.928068 
iter  10 value 94.819452
iter  20 value 93.069818
iter  30 value 86.614363
iter  40 value 83.916244
iter  50 value 81.770546
iter  60 value 80.775793
iter  70 value 79.835161
iter  80 value 79.570731
iter  90 value 79.472363
iter 100 value 79.435635
final  value 79.435635 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.347588 
iter  10 value 95.523487
iter  20 value 87.734893
iter  30 value 85.116772
iter  40 value 82.740876
iter  50 value 81.319730
iter  60 value 81.041006
iter  70 value 80.622005
iter  80 value 80.308070
iter  90 value 80.149657
iter 100 value 79.932826
final  value 79.932826 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.886140 
final  value 94.485842 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.780680 
iter  10 value 94.486040
iter  20 value 94.484283
iter  30 value 94.428005
iter  40 value 86.011608
iter  50 value 86.007189
iter  60 value 86.007076
iter  70 value 85.889015
iter  80 value 85.234529
iter  90 value 85.202360
iter 100 value 85.202223
final  value 85.202223 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.906212 
final  value 94.485707 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.774416 
final  value 94.485665 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.222240 
final  value 94.485992 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.211096 
iter  10 value 94.448005
iter  20 value 94.443899
iter  30 value 94.336526
iter  40 value 86.084527
iter  50 value 84.814402
iter  60 value 81.501662
iter  70 value 81.164966
iter  80 value 81.159742
iter  90 value 81.117517
iter 100 value 80.558849
final  value 80.558849 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.420607 
iter  10 value 94.487312
iter  20 value 92.480988
iter  30 value 92.299177
iter  40 value 92.262561
iter  50 value 92.257420
iter  60 value 92.087737
iter  70 value 86.740155
iter  80 value 85.891792
iter  90 value 85.851412
iter 100 value 84.726260
final  value 84.726260 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.457137 
iter  10 value 94.448010
iter  20 value 94.098387
iter  30 value 92.938702
iter  40 value 92.137684
iter  50 value 91.855951
final  value 91.844613 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.551355 
iter  10 value 94.488989
iter  20 value 94.484397
iter  30 value 87.956389
iter  40 value 87.284525
final  value 87.246045 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.336474 
iter  10 value 94.447824
iter  20 value 94.444569
iter  30 value 94.437103
iter  40 value 93.278727
iter  50 value 85.230727
iter  60 value 85.218107
iter  70 value 85.217359
iter  80 value 84.760373
iter  90 value 84.697683
iter 100 value 84.526837
final  value 84.526837 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.549992 
iter  10 value 88.680374
iter  20 value 87.320504
iter  30 value 87.192808
iter  40 value 87.191006
iter  50 value 87.186117
iter  60 value 87.177285
iter  70 value 87.175312
iter  80 value 83.717054
iter  90 value 80.774438
iter 100 value 79.924907
final  value 79.924907 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.829269 
iter  10 value 94.489812
iter  20 value 87.346799
iter  30 value 87.073846
iter  40 value 86.067669
iter  50 value 85.456174
iter  60 value 85.449142
iter  70 value 85.439382
final  value 85.439163 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.785599 
iter  10 value 94.451802
iter  20 value 88.540618
iter  30 value 84.420225
iter  40 value 82.890288
iter  50 value 80.896714
iter  60 value 80.154823
iter  70 value 79.499242
iter  80 value 78.997414
iter  90 value 78.837567
iter 100 value 78.353971
final  value 78.353971 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.948921 
iter  10 value 94.451261
iter  20 value 94.444365
final  value 94.443201 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.328163 
iter  10 value 90.828972
iter  20 value 83.852750
iter  30 value 83.458977
iter  40 value 83.429177
iter  50 value 83.416219
final  value 83.415693 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.723938 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.372195 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.424373 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.715757 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.008394 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.384420 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.934717 
final  value 94.466822 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.025917 
iter  10 value 94.428373
final  value 94.427726 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.490531 
final  value 94.466822 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.782661 
final  value 94.456504 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.599669 
final  value 94.484206 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.929077 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.206221 
final  value 94.305883 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.558577 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.916905 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.823668 
iter  10 value 94.489014
iter  20 value 94.467715
iter  30 value 89.660265
iter  40 value 87.763282
iter  50 value 86.804321
iter  60 value 86.432731
iter  70 value 86.377056
iter  80 value 86.343702
final  value 86.343096 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.353417 
iter  10 value 94.457835
iter  20 value 89.216965
iter  30 value 88.096565
iter  40 value 87.877697
iter  50 value 87.602041
iter  60 value 86.472431
iter  70 value 86.165812
final  value 86.165475 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.205410 
iter  10 value 94.486452
iter  20 value 93.290002
iter  30 value 90.928360
iter  40 value 87.586077
iter  50 value 86.601376
iter  60 value 86.004240
iter  70 value 85.603259
iter  80 value 84.240435
iter  90 value 83.617719
final  value 83.609428 
converged
Fitting Repeat 4 

# weights:  103
initial  value 117.557813 
iter  10 value 94.463957
iter  20 value 89.759387
iter  30 value 89.012825
iter  40 value 87.713651
iter  50 value 84.511624
iter  60 value 84.100214
iter  70 value 84.005712
iter  80 value 83.610066
final  value 83.609428 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.669948 
iter  10 value 94.506666
iter  20 value 88.785348
iter  30 value 87.669791
iter  40 value 87.023472
iter  50 value 84.503568
iter  60 value 84.359825
iter  70 value 84.322834
iter  80 value 84.026025
iter  90 value 83.420859
final  value 83.397100 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.298083 
iter  10 value 94.385027
iter  20 value 93.992634
iter  30 value 91.785872
iter  40 value 91.340020
iter  50 value 86.074770
iter  60 value 84.379585
iter  70 value 83.877241
iter  80 value 83.618049
iter  90 value 83.500046
iter 100 value 83.207578
final  value 83.207578 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.787464 
iter  10 value 94.540086
iter  20 value 90.749887
iter  30 value 88.330707
iter  40 value 88.122742
iter  50 value 87.844756
iter  60 value 86.313664
iter  70 value 84.485660
iter  80 value 84.271917
iter  90 value 84.016490
iter 100 value 83.118830
final  value 83.118830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.165961 
iter  10 value 94.282288
iter  20 value 89.920726
iter  30 value 88.938446
iter  40 value 88.855850
iter  50 value 87.602395
iter  60 value 86.751793
iter  70 value 86.519942
iter  80 value 85.313160
iter  90 value 83.885717
iter 100 value 83.110039
final  value 83.110039 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.120549 
iter  10 value 94.550116
iter  20 value 89.833760
iter  30 value 88.737792
iter  40 value 88.041037
iter  50 value 87.228826
iter  60 value 86.568688
iter  70 value 85.443887
iter  80 value 83.614715
iter  90 value 82.671328
iter 100 value 82.249984
final  value 82.249984 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.294749 
iter  10 value 94.786414
iter  20 value 89.840674
iter  30 value 88.966375
iter  40 value 86.650824
iter  50 value 84.689540
iter  60 value 84.016337
iter  70 value 83.291316
iter  80 value 83.007562
iter  90 value 82.839012
iter 100 value 82.734262
final  value 82.734262 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.345256 
iter  10 value 94.511742
iter  20 value 90.916463
iter  30 value 87.082129
iter  40 value 86.896915
iter  50 value 85.419912
iter  60 value 83.401845
iter  70 value 82.905930
iter  80 value 82.548295
iter  90 value 82.265689
iter 100 value 82.160022
final  value 82.160022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.232135 
iter  10 value 94.225042
iter  20 value 88.093804
iter  30 value 87.075547
iter  40 value 86.024229
iter  50 value 84.683371
iter  60 value 83.887525
iter  70 value 83.424366
iter  80 value 83.099331
iter  90 value 82.952639
iter 100 value 82.668288
final  value 82.668288 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.601168 
iter  10 value 94.145554
iter  20 value 91.009538
iter  30 value 86.689118
iter  40 value 84.526908
iter  50 value 84.328935
iter  60 value 83.807783
iter  70 value 83.268281
iter  80 value 82.744558
iter  90 value 82.410675
iter 100 value 82.252588
final  value 82.252588 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.817758 
iter  10 value 93.669803
iter  20 value 87.846327
iter  30 value 86.968050
iter  40 value 86.723311
iter  50 value 86.594371
iter  60 value 85.582032
iter  70 value 85.172649
iter  80 value 84.981343
iter  90 value 84.897656
iter 100 value 84.743851
final  value 84.743851 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.312157 
iter  10 value 94.448418
iter  20 value 88.180108
iter  30 value 87.843831
iter  40 value 87.338692
iter  50 value 85.140423
iter  60 value 84.544627
iter  70 value 84.089522
iter  80 value 83.771097
iter  90 value 82.823826
iter 100 value 82.631112
final  value 82.631112 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.852092 
final  value 94.485632 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.434345 
final  value 94.485762 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.498359 
final  value 94.485951 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.933917 
final  value 94.485886 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.554998 
final  value 94.485832 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.340195 
iter  10 value 94.300071
iter  20 value 94.293027
final  value 94.291067 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.537307 
iter  10 value 94.488330
iter  20 value 94.332699
iter  30 value 94.288659
final  value 94.288654 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.329286 
iter  10 value 94.452908
iter  20 value 94.450265
iter  30 value 94.439893
iter  40 value 89.352633
iter  50 value 87.145356
iter  60 value 86.841791
final  value 86.833885 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.285897 
iter  10 value 94.293959
iter  20 value 88.423979
iter  30 value 87.953468
iter  40 value 87.944692
iter  50 value 87.902926
iter  60 value 87.832168
iter  70 value 87.736787
iter  80 value 87.234164
iter  90 value 84.330990
iter 100 value 83.800318
final  value 83.800318 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.701439 
iter  10 value 94.472104
iter  20 value 94.296703
iter  30 value 94.278916
final  value 94.262858 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.056117 
iter  10 value 94.243424
iter  20 value 94.212210
iter  30 value 92.619245
iter  40 value 86.719607
iter  50 value 84.271192
iter  60 value 83.935214
iter  70 value 83.904149
iter  80 value 83.795392
iter  90 value 83.792675
iter 100 value 83.791999
final  value 83.791999 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.747397 
iter  10 value 94.492478
iter  20 value 94.450509
iter  30 value 93.568117
iter  40 value 92.223312
final  value 92.221254 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.615492 
iter  10 value 94.492658
iter  20 value 94.474564
iter  30 value 92.790808
final  value 92.787209 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.097772 
iter  10 value 93.954655
iter  20 value 92.878396
iter  30 value 92.830591
iter  40 value 92.826995
iter  50 value 92.823717
iter  60 value 92.811052
iter  70 value 92.785580
iter  80 value 92.784865
iter  90 value 92.784827
final  value 92.784826 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.576561 
iter  10 value 94.492649
iter  20 value 94.462521
iter  30 value 94.450215
final  value 94.448556 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.485595 
iter  10 value 111.269920
iter  20 value 109.782259
iter  30 value 106.599397
iter  40 value 105.276352
iter  50 value 104.838549
iter  60 value 104.548915
iter  70 value 102.902055
iter  80 value 101.977791
iter  90 value 101.495163
iter 100 value 101.160718
final  value 101.160718 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.475222 
iter  10 value 118.823251
iter  20 value 117.721293
iter  30 value 109.254322
iter  40 value 106.177151
iter  50 value 104.851717
iter  60 value 102.756447
iter  70 value 102.334339
iter  80 value 101.930971
iter  90 value 101.631468
iter 100 value 101.478864
final  value 101.478864 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.172479 
iter  10 value 117.924231
iter  20 value 115.402740
iter  30 value 108.052768
iter  40 value 107.313107
iter  50 value 105.937484
iter  60 value 103.130963
iter  70 value 101.725882
iter  80 value 101.145991
iter  90 value 100.909032
iter 100 value 100.497224
final  value 100.497224 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.205741 
iter  10 value 117.829855
iter  20 value 107.836537
iter  30 value 105.971100
iter  40 value 105.608715
iter  50 value 104.204377
iter  60 value 103.950681
iter  70 value 103.500794
iter  80 value 102.021048
iter  90 value 101.579798
iter 100 value 101.500272
final  value 101.500272 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.406933 
iter  10 value 117.608297
iter  20 value 108.590652
iter  30 value 106.980378
iter  40 value 105.523041
iter  50 value 104.149039
iter  60 value 101.753913
iter  70 value 101.408239
iter  80 value 100.845492
iter  90 value 100.449913
iter 100 value 100.418678
final  value 100.418678 
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 May 18 22:05:28 2026 
*********************************************** 
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 
 19.666   0.649  75.238