Matineh Rahmatbakhsh
| Snapshot Date: 2026-03-09 13:45 -0400 (Mon, 09 Mar 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_22 |
| git_last_commit: 6cf0d22 |
| git_last_commit_date: 2025-12-28 18:31:13 -0400 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-03-10 11:57 -0400 (Tue, 10 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4892 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 1006/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.16.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.16.1 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz |
| StartedAt: 2026-03-10 00:23:56 -0400 (Tue, 10 Mar 2026) |
| EndedAt: 2026-03-10 00:38:58 -0400 (Tue, 10 Mar 2026) |
| EllapsedTime: 902.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* 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 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* 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
corr_plot 34.772 0.526 35.298
var_imp 33.141 0.664 33.807
FSmethod 33.106 0.464 33.574
pred_ensembel 12.867 0.375 11.969
enrichfindP 0.598 0.052 12.986
* 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-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.16.1’ ** 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)
HPiP.Rcheck/tests/runTests.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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 99.438417
final value 94.052448
converged
Fitting Repeat 2
# weights: 103
initial value 94.248455
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 92.640010
iter 10 value 84.356478
iter 20 value 82.463912
final value 82.432103
converged
Fitting Repeat 4
# weights: 103
initial value 99.046722
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.880021
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 96.642767
final value 93.582418
converged
Fitting Repeat 2
# weights: 305
initial value 98.295846
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 101.243641
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 95.245629
iter 10 value 90.540677
iter 20 value 82.632395
iter 30 value 82.387533
iter 40 value 82.385655
final value 82.385624
converged
Fitting Repeat 5
# weights: 305
initial value 96.763216
iter 10 value 93.582456
final value 93.582418
converged
Fitting Repeat 1
# weights: 507
initial value 122.941581
iter 10 value 92.861583
iter 10 value 92.861582
iter 10 value 92.861582
final value 92.861582
converged
Fitting Repeat 2
# weights: 507
initial value 99.224051
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 112.901249
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 96.125800
iter 10 value 91.792327
iter 20 value 82.713601
iter 30 value 82.491523
iter 40 value 82.466005
final value 82.465907
converged
Fitting Repeat 5
# weights: 507
initial value 112.438403
iter 10 value 93.304336
iter 20 value 89.373557
iter 30 value 89.057098
iter 40 value 87.421421
iter 50 value 87.363579
iter 60 value 87.362789
final value 87.362744
converged
Fitting Repeat 1
# weights: 103
initial value 102.131233
iter 10 value 93.901723
iter 20 value 93.684572
iter 30 value 91.645397
iter 40 value 88.988508
iter 50 value 88.658396
iter 60 value 88.142976
iter 70 value 84.367383
iter 80 value 84.238377
iter 90 value 81.444996
iter 100 value 80.711352
final value 80.711352
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.803127
iter 10 value 93.703505
iter 20 value 93.259216
iter 30 value 93.031899
iter 40 value 92.995388
iter 50 value 86.144435
iter 60 value 83.961243
iter 70 value 83.810984
iter 80 value 83.768562
final value 83.767400
converged
Fitting Repeat 3
# weights: 103
initial value 96.581241
iter 10 value 94.056527
iter 20 value 93.958885
iter 30 value 93.799552
iter 40 value 93.689468
iter 50 value 93.617160
iter 60 value 90.161264
iter 70 value 88.366212
iter 80 value 88.123370
iter 90 value 87.761120
iter 100 value 85.741299
final value 85.741299
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.399176
iter 10 value 94.054964
iter 20 value 93.986022
iter 30 value 93.203193
iter 40 value 93.028126
iter 50 value 92.521838
iter 60 value 87.721736
iter 70 value 85.991480
iter 80 value 85.929020
iter 90 value 85.816306
iter 100 value 82.578766
final value 82.578766
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.014923
iter 10 value 93.563033
iter 20 value 86.424832
iter 30 value 85.038850
iter 40 value 83.747490
iter 50 value 82.369353
iter 60 value 81.245962
iter 70 value 80.664402
iter 80 value 80.631052
iter 90 value 80.611140
final value 80.609600
converged
Fitting Repeat 1
# weights: 305
initial value 103.229477
iter 10 value 95.889978
iter 20 value 86.523950
iter 30 value 84.590695
iter 40 value 83.800855
iter 50 value 83.195371
iter 60 value 82.777869
iter 70 value 82.420377
iter 80 value 82.253876
iter 90 value 82.232948
iter 100 value 82.031785
final value 82.031785
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.562568
iter 10 value 93.614619
iter 20 value 93.090971
iter 30 value 91.450020
iter 40 value 90.195847
iter 50 value 88.836219
iter 60 value 88.398915
iter 70 value 87.071787
iter 80 value 83.025386
iter 90 value 82.611512
iter 100 value 81.656329
final value 81.656329
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.093572
iter 10 value 94.101718
iter 20 value 91.621904
iter 30 value 86.979419
iter 40 value 86.012845
iter 50 value 85.589658
iter 60 value 85.507354
iter 70 value 85.088907
iter 80 value 82.188059
iter 90 value 81.575305
iter 100 value 80.562388
final value 80.562388
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.076777
iter 10 value 94.062881
iter 20 value 93.719783
iter 30 value 93.692395
iter 40 value 93.022573
iter 50 value 85.973733
iter 60 value 85.528665
iter 70 value 85.402527
iter 80 value 84.885816
iter 90 value 83.667606
iter 100 value 82.563713
final value 82.563713
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.095079
iter 10 value 93.900457
iter 20 value 87.220536
iter 30 value 85.636249
iter 40 value 83.710522
iter 50 value 82.743520
iter 60 value 81.881522
iter 70 value 80.782113
iter 80 value 79.905168
iter 90 value 79.741223
iter 100 value 79.592491
final value 79.592491
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.549030
iter 10 value 93.672061
iter 20 value 90.595472
iter 30 value 86.687157
iter 40 value 82.943648
iter 50 value 80.970775
iter 60 value 80.309165
iter 70 value 79.446342
iter 80 value 79.269283
iter 90 value 79.145091
iter 100 value 78.969793
final value 78.969793
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.321943
iter 10 value 94.008510
iter 20 value 93.092079
iter 30 value 92.468662
iter 40 value 86.352002
iter 50 value 81.587846
iter 60 value 80.787686
iter 70 value 79.905049
iter 80 value 79.341006
iter 90 value 79.131574
iter 100 value 79.078953
final value 79.078953
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.099475
iter 10 value 95.786427
iter 20 value 88.983552
iter 30 value 83.900014
iter 40 value 83.271617
iter 50 value 82.625661
iter 60 value 82.412066
iter 70 value 80.212181
iter 80 value 79.702198
iter 90 value 79.611484
iter 100 value 79.564281
final value 79.564281
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 123.959514
iter 10 value 95.148044
iter 20 value 88.859367
iter 30 value 86.008927
iter 40 value 85.125695
iter 50 value 84.121512
iter 60 value 83.436241
iter 70 value 82.486595
iter 80 value 81.002308
iter 90 value 79.934331
iter 100 value 79.544806
final value 79.544806
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.337603
iter 10 value 93.547469
iter 20 value 88.184608
iter 30 value 86.149629
iter 40 value 84.459087
iter 50 value 83.354733
iter 60 value 82.345477
iter 70 value 81.726162
iter 80 value 81.010612
iter 90 value 80.044587
iter 100 value 79.846987
final value 79.846987
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.640049
iter 10 value 94.054667
iter 20 value 94.047874
iter 30 value 89.429233
iter 40 value 86.863768
iter 50 value 86.042954
iter 60 value 85.808164
iter 70 value 85.792610
iter 80 value 85.791722
iter 90 value 85.727745
iter 100 value 85.004626
final value 85.004626
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 105.191169
iter 10 value 94.054722
iter 20 value 94.052913
iter 20 value 94.052913
iter 20 value 94.052913
final value 94.052913
converged
Fitting Repeat 3
# weights: 103
initial value 94.145675
iter 10 value 93.584093
iter 20 value 93.166562
final value 92.861887
converged
Fitting Repeat 4
# weights: 103
initial value 106.352565
iter 10 value 94.054859
iter 20 value 94.052966
final value 94.052921
converged
Fitting Repeat 5
# weights: 103
initial value 100.076536
final value 94.055073
converged
Fitting Repeat 1
# weights: 305
initial value 95.047708
iter 10 value 94.057593
iter 20 value 94.046784
iter 30 value 93.411688
iter 40 value 93.113654
final value 92.852175
converged
Fitting Repeat 2
# weights: 305
initial value 99.525447
iter 10 value 93.587375
iter 20 value 92.864400
iter 30 value 87.061333
iter 40 value 85.939867
iter 50 value 85.696881
iter 60 value 85.694473
final value 85.694456
converged
Fitting Repeat 3
# weights: 305
initial value 95.630949
iter 10 value 93.588085
iter 20 value 93.533972
iter 30 value 92.932094
iter 40 value 92.758072
iter 50 value 92.752848
iter 60 value 92.752767
final value 92.752543
converged
Fitting Repeat 4
# weights: 305
initial value 96.620923
iter 10 value 93.232139
iter 20 value 93.229417
iter 30 value 93.220285
iter 40 value 93.214608
final value 93.214570
converged
Fitting Repeat 5
# weights: 305
initial value 100.632866
iter 10 value 93.587613
iter 20 value 93.583283
final value 93.582870
converged
Fitting Repeat 1
# weights: 507
initial value 99.058815
iter 10 value 93.594195
iter 20 value 93.590101
iter 30 value 93.588294
iter 40 value 93.584735
iter 50 value 93.553729
iter 60 value 93.550964
iter 70 value 93.550593
final value 93.550549
converged
Fitting Repeat 2
# weights: 507
initial value 99.114886
iter 10 value 93.590961
iter 20 value 93.560158
iter 30 value 93.556183
iter 40 value 93.555810
iter 40 value 93.555810
iter 40 value 93.555809
final value 93.555809
converged
Fitting Repeat 3
# weights: 507
initial value 97.326058
final value 93.418390
converged
Fitting Repeat 4
# weights: 507
initial value 95.234080
iter 10 value 87.323785
iter 20 value 86.656080
final value 86.655007
converged
Fitting Repeat 5
# weights: 507
initial value 99.106177
iter 10 value 93.590452
iter 20 value 92.865499
iter 30 value 92.401228
iter 40 value 84.935529
iter 50 value 84.118859
iter 60 value 84.099784
iter 70 value 84.074739
final value 84.074061
converged
Fitting Repeat 1
# weights: 103
initial value 97.171590
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 98.657282
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 108.245639
iter 10 value 92.211115
final value 92.211111
converged
Fitting Repeat 4
# weights: 103
initial value 101.701945
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.981150
iter 10 value 92.014505
iter 20 value 91.892359
final value 91.892340
converged
Fitting Repeat 1
# weights: 305
initial value 112.527413
final value 94.032967
converged
Fitting Repeat 2
# weights: 305
initial value 96.085012
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 94.111093
iter 10 value 81.782499
iter 20 value 77.966341
iter 30 value 77.913733
final value 77.913683
converged
Fitting Repeat 4
# weights: 305
initial value 94.717214
final value 94.032967
converged
Fitting Repeat 5
# weights: 305
initial value 95.992966
final value 94.032967
converged
Fitting Repeat 1
# weights: 507
initial value 100.684054
final value 94.032967
converged
Fitting Repeat 2
# weights: 507
initial value 103.936630
iter 10 value 88.537835
iter 20 value 85.820158
iter 30 value 85.818049
final value 85.817952
converged
Fitting Repeat 3
# weights: 507
initial value 133.089548
iter 10 value 83.896227
iter 20 value 83.567946
iter 30 value 83.567837
iter 30 value 83.567837
iter 30 value 83.567837
final value 83.567837
converged
Fitting Repeat 4
# weights: 507
initial value 109.820839
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 119.546556
iter 10 value 88.627869
final value 88.204980
converged
Fitting Repeat 1
# weights: 103
initial value 95.952020
iter 10 value 94.028693
iter 20 value 93.648092
iter 30 value 89.153832
iter 40 value 80.884273
iter 50 value 80.720987
iter 60 value 80.692257
iter 70 value 80.685362
iter 80 value 80.045846
iter 90 value 78.121397
iter 100 value 77.773224
final value 77.773224
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 105.475071
iter 10 value 94.056718
iter 20 value 94.055251
iter 30 value 86.260454
iter 40 value 85.077772
iter 50 value 80.170844
iter 60 value 77.428509
iter 70 value 76.202253
iter 80 value 75.969351
final value 75.969021
converged
Fitting Repeat 3
# weights: 103
initial value 96.876219
iter 10 value 92.478758
iter 20 value 89.804277
iter 30 value 89.661274
iter 40 value 89.647773
iter 50 value 87.281168
iter 60 value 87.261644
iter 70 value 79.597984
iter 80 value 77.842041
iter 90 value 76.898849
iter 100 value 76.261272
final value 76.261272
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 105.007204
iter 10 value 93.954604
iter 10 value 93.954603
iter 20 value 92.974034
iter 30 value 92.774877
iter 40 value 86.306010
iter 50 value 81.678540
iter 60 value 81.624669
iter 70 value 81.616112
iter 80 value 81.612277
iter 90 value 81.528696
iter 100 value 79.468161
final value 79.468161
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.362594
iter 10 value 94.039626
iter 20 value 93.041463
iter 30 value 92.905280
iter 40 value 92.881057
iter 50 value 85.411332
iter 60 value 85.034926
iter 70 value 81.302642
iter 80 value 77.982064
iter 90 value 77.568204
iter 100 value 77.175786
final value 77.175786
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.329548
iter 10 value 91.692987
iter 20 value 87.716518
iter 30 value 86.588811
iter 40 value 81.792508
iter 50 value 80.795425
iter 60 value 78.135710
iter 70 value 76.275422
iter 80 value 75.335012
iter 90 value 75.020831
iter 100 value 74.939169
final value 74.939169
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.981752
iter 10 value 89.198138
iter 20 value 80.461542
iter 30 value 77.672333
iter 40 value 76.703765
iter 50 value 75.853585
iter 60 value 74.958035
iter 70 value 74.739626
iter 80 value 74.477902
iter 90 value 74.472160
iter 100 value 74.421693
final value 74.421693
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.881877
iter 10 value 92.983651
iter 20 value 87.688473
iter 30 value 83.260668
iter 40 value 81.991840
iter 50 value 80.494794
iter 60 value 77.805103
iter 70 value 76.512407
iter 80 value 75.708183
iter 90 value 75.230881
iter 100 value 75.102359
final value 75.102359
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.318709
iter 10 value 94.185539
iter 20 value 93.052045
iter 30 value 92.391841
iter 40 value 81.446548
iter 50 value 78.818537
iter 60 value 76.915700
iter 70 value 75.887068
iter 80 value 75.356751
iter 90 value 75.253768
iter 100 value 75.200736
final value 75.200736
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 115.796531
iter 10 value 94.005567
iter 20 value 91.160109
iter 30 value 84.207134
iter 40 value 78.985621
iter 50 value 77.646157
iter 60 value 76.647349
iter 70 value 75.884508
iter 80 value 75.843927
iter 90 value 75.392490
iter 100 value 75.309807
final value 75.309807
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 134.562485
iter 10 value 94.160696
iter 20 value 84.001846
iter 30 value 80.152687
iter 40 value 77.626989
iter 50 value 75.793633
iter 60 value 75.485938
iter 70 value 75.004638
iter 80 value 74.649181
iter 90 value 74.230549
iter 100 value 74.081305
final value 74.081305
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.176507
iter 10 value 93.856711
iter 20 value 86.874394
iter 30 value 78.065211
iter 40 value 77.407136
iter 50 value 76.672287
iter 60 value 76.191657
iter 70 value 75.896118
iter 80 value 75.879435
iter 90 value 75.802266
iter 100 value 75.559728
final value 75.559728
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.686446
iter 10 value 94.113714
iter 20 value 82.892919
iter 30 value 78.688291
iter 40 value 77.105799
iter 50 value 75.315800
iter 60 value 74.451795
iter 70 value 74.174710
iter 80 value 73.973311
iter 90 value 73.761428
iter 100 value 73.643229
final value 73.643229
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.178839
iter 10 value 94.302104
iter 20 value 94.006086
iter 30 value 92.986229
iter 40 value 82.679504
iter 50 value 81.656701
iter 60 value 78.094437
iter 70 value 77.004950
iter 80 value 76.967606
iter 90 value 76.856321
iter 100 value 76.712741
final value 76.712741
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.847515
iter 10 value 93.768993
iter 20 value 81.229362
iter 30 value 79.426457
iter 40 value 78.654310
iter 50 value 76.966400
iter 60 value 76.422286
iter 70 value 76.099360
iter 80 value 75.346941
iter 90 value 74.804397
iter 100 value 74.635140
final value 74.635140
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.017024
final value 94.054656
converged
Fitting Repeat 2
# weights: 103
initial value 110.995342
final value 94.055309
converged
Fitting Repeat 3
# weights: 103
initial value 96.963046
final value 94.054646
converged
Fitting Repeat 4
# weights: 103
initial value 110.413464
iter 10 value 94.034760
iter 20 value 94.033183
iter 30 value 92.217179
final value 92.212109
converged
Fitting Repeat 5
# weights: 103
initial value 94.979402
iter 10 value 92.492907
iter 20 value 92.403052
final value 92.402908
converged
Fitting Repeat 1
# weights: 305
initial value 97.534789
iter 10 value 94.037832
iter 20 value 94.025538
iter 30 value 92.831560
final value 92.831537
converged
Fitting Repeat 2
# weights: 305
initial value 97.189877
iter 10 value 94.040676
iter 20 value 94.033370
iter 30 value 79.109864
iter 40 value 79.073245
iter 50 value 79.063242
iter 60 value 79.061144
iter 70 value 79.060740
iter 80 value 78.824402
iter 90 value 78.393164
iter 100 value 78.392693
final value 78.392693
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.010944
iter 10 value 94.058185
iter 20 value 94.053515
iter 30 value 85.046073
iter 40 value 79.100062
iter 50 value 78.307875
iter 60 value 78.286677
iter 70 value 78.284908
final value 78.282086
converged
Fitting Repeat 4
# weights: 305
initial value 98.008685
iter 10 value 94.037963
iter 20 value 92.268604
iter 30 value 92.147793
iter 40 value 89.259348
iter 50 value 82.389727
iter 60 value 82.387743
iter 70 value 79.647939
iter 80 value 79.259896
iter 90 value 79.259700
iter 100 value 79.217385
final value 79.217385
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 98.240193
iter 10 value 94.058039
iter 20 value 94.053422
iter 30 value 82.669340
iter 40 value 80.210452
iter 50 value 80.187760
iter 60 value 80.145658
iter 70 value 79.919262
iter 80 value 79.145916
iter 90 value 78.437121
final value 78.393170
converged
Fitting Repeat 1
# weights: 507
initial value 107.097295
iter 10 value 94.041218
iter 20 value 93.957748
iter 30 value 89.700656
iter 40 value 79.072269
iter 50 value 79.070676
iter 60 value 79.061485
iter 70 value 78.287514
iter 80 value 78.285704
final value 78.284671
converged
Fitting Repeat 2
# weights: 507
initial value 126.016736
iter 10 value 94.040994
iter 20 value 94.034277
iter 30 value 81.684081
iter 40 value 79.677276
iter 50 value 79.006860
iter 60 value 79.002789
iter 70 value 79.001179
iter 80 value 79.000879
iter 90 value 78.999541
iter 100 value 78.734637
final value 78.734637
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.929755
iter 10 value 83.130551
iter 20 value 79.340205
iter 30 value 78.435885
iter 40 value 78.425824
iter 50 value 78.420001
iter 60 value 77.543933
iter 70 value 76.366000
iter 80 value 75.364495
iter 90 value 74.647249
iter 100 value 74.411970
final value 74.411970
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.025833
iter 10 value 94.041106
iter 20 value 93.180798
iter 30 value 89.196018
iter 40 value 86.884686
iter 50 value 86.883274
final value 86.883248
converged
Fitting Repeat 5
# weights: 507
initial value 143.297650
iter 10 value 86.097330
iter 20 value 86.086589
iter 30 value 83.321168
iter 40 value 78.751230
iter 50 value 76.592505
iter 60 value 75.891147
iter 70 value 75.890612
iter 80 value 75.888403
iter 90 value 74.936999
iter 100 value 74.596108
final value 74.596108
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 111.522680
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.555334
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.468823
final value 94.466823
converged
Fitting Repeat 4
# weights: 103
initial value 96.327295
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 98.639888
final value 94.466823
converged
Fitting Repeat 1
# weights: 305
initial value 100.634612
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 99.669425
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 104.475654
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 101.061095
final value 93.701657
converged
Fitting Repeat 5
# weights: 305
initial value 108.273098
final value 94.483333
converged
Fitting Repeat 1
# weights: 507
initial value 120.992730
iter 10 value 94.466960
final value 94.466823
converged
Fitting Repeat 2
# weights: 507
initial value 100.619606
iter 10 value 94.140517
final value 94.138455
converged
Fitting Repeat 3
# weights: 507
initial value 108.595975
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 115.359974
iter 10 value 92.318707
iter 20 value 85.091773
iter 20 value 85.091773
iter 20 value 85.091773
final value 85.091773
converged
Fitting Repeat 5
# weights: 507
initial value 96.783276
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 104.199090
iter 10 value 94.210364
iter 20 value 91.081134
iter 30 value 88.566008
iter 40 value 87.974497
iter 50 value 87.472573
iter 60 value 86.685289
iter 70 value 85.636098
iter 80 value 85.044640
iter 90 value 84.835868
final value 84.833460
converged
Fitting Repeat 2
# weights: 103
initial value 104.257687
iter 10 value 91.264035
iter 20 value 87.867644
iter 30 value 87.223319
iter 40 value 86.432096
iter 50 value 86.120652
iter 60 value 85.754682
iter 70 value 85.671161
iter 80 value 85.587259
final value 85.586843
converged
Fitting Repeat 3
# weights: 103
initial value 101.340935
iter 10 value 94.571772
iter 20 value 91.774231
iter 30 value 87.409602
iter 40 value 87.234482
iter 50 value 87.145261
iter 60 value 86.241024
iter 70 value 85.484597
iter 80 value 84.894136
iter 90 value 84.834268
final value 84.834264
converged
Fitting Repeat 4
# weights: 103
initial value 109.616624
iter 10 value 94.489915
iter 20 value 92.710236
iter 30 value 91.866381
iter 40 value 91.641707
iter 50 value 91.633779
final value 91.633750
converged
Fitting Repeat 5
# weights: 103
initial value 98.522448
iter 10 value 94.481177
iter 20 value 87.373035
iter 30 value 87.159761
iter 40 value 87.054272
iter 50 value 86.717865
iter 60 value 85.656773
iter 70 value 85.563269
iter 80 value 85.423188
iter 90 value 85.096957
iter 100 value 85.076342
final value 85.076342
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.612148
iter 10 value 93.885203
iter 20 value 92.249964
iter 30 value 87.554860
iter 40 value 85.100468
iter 50 value 83.693074
iter 60 value 82.706723
iter 70 value 82.239393
iter 80 value 82.133752
iter 90 value 82.095934
iter 100 value 82.050376
final value 82.050376
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 116.723439
iter 10 value 96.439102
iter 20 value 91.188280
iter 30 value 90.510622
iter 40 value 90.391361
iter 50 value 90.269674
iter 60 value 90.203363
iter 70 value 90.171841
iter 80 value 90.053308
iter 90 value 89.850971
iter 100 value 88.830928
final value 88.830928
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.085952
iter 10 value 94.343486
iter 20 value 90.293621
iter 30 value 89.867725
iter 40 value 88.370018
iter 50 value 85.444714
iter 60 value 84.393604
iter 70 value 81.736679
iter 80 value 81.419196
iter 90 value 81.347451
iter 100 value 81.323122
final value 81.323122
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.111810
iter 10 value 94.606581
iter 20 value 90.626760
iter 30 value 89.514428
iter 40 value 88.424200
iter 50 value 86.673921
iter 60 value 84.706539
iter 70 value 83.932363
iter 80 value 83.699426
iter 90 value 83.536509
iter 100 value 83.388886
final value 83.388886
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.752455
iter 10 value 94.438825
iter 20 value 88.174064
iter 30 value 87.849947
iter 40 value 86.743803
iter 50 value 86.024538
iter 60 value 85.713662
iter 70 value 85.520691
iter 80 value 85.410715
iter 90 value 84.734898
iter 100 value 82.436091
final value 82.436091
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.004126
iter 10 value 94.459744
iter 20 value 94.135850
iter 30 value 88.043779
iter 40 value 84.751289
iter 50 value 83.769708
iter 60 value 81.801096
iter 70 value 81.291703
iter 80 value 81.127564
iter 90 value 81.047861
iter 100 value 80.986683
final value 80.986683
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.950398
iter 10 value 94.746512
iter 20 value 92.617349
iter 30 value 87.031530
iter 40 value 86.248217
iter 50 value 83.852732
iter 60 value 82.628996
iter 70 value 82.249652
iter 80 value 82.227789
iter 90 value 82.166866
iter 100 value 81.856191
final value 81.856191
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.554200
iter 10 value 102.306618
iter 20 value 91.976198
iter 30 value 91.606129
iter 40 value 88.456754
iter 50 value 87.377346
iter 60 value 85.032042
iter 70 value 82.308843
iter 80 value 82.088265
iter 90 value 82.007437
iter 100 value 81.728294
final value 81.728294
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 126.749886
iter 10 value 94.856103
iter 20 value 94.484552
iter 30 value 92.688820
iter 40 value 87.611574
iter 50 value 84.330065
iter 60 value 84.010062
iter 70 value 83.706654
iter 80 value 82.759727
iter 90 value 82.506077
iter 100 value 81.730271
final value 81.730271
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.113215
iter 10 value 95.059856
iter 20 value 92.913811
iter 30 value 86.925504
iter 40 value 86.645355
iter 50 value 85.477540
iter 60 value 84.903008
iter 70 value 82.653779
iter 80 value 82.324652
iter 90 value 82.008562
iter 100 value 81.886983
final value 81.886983
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.813386
final value 94.485657
converged
Fitting Repeat 2
# weights: 103
initial value 99.493451
final value 94.485701
converged
Fitting Repeat 3
# weights: 103
initial value 101.909797
final value 94.485811
converged
Fitting Repeat 4
# weights: 103
initial value 96.896579
final value 94.485875
converged
Fitting Repeat 5
# weights: 103
initial value 98.052125
final value 94.482212
converged
Fitting Repeat 1
# weights: 305
initial value 111.440068
iter 10 value 94.489145
iter 20 value 94.484403
iter 30 value 87.856753
iter 40 value 86.746428
iter 50 value 86.746372
final value 86.746368
converged
Fitting Repeat 2
# weights: 305
initial value 96.687479
iter 10 value 94.471415
iter 20 value 94.466951
final value 94.466944
converged
Fitting Repeat 3
# weights: 305
initial value 97.324507
iter 10 value 94.457377
iter 20 value 94.404555
iter 30 value 94.363206
iter 40 value 94.357012
iter 50 value 94.312565
iter 60 value 89.628117
iter 70 value 89.486065
iter 80 value 86.940836
iter 90 value 85.189706
iter 100 value 85.178647
final value 85.178647
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.419076
iter 10 value 94.488309
iter 20 value 91.653708
iter 30 value 89.280454
iter 40 value 87.834343
iter 50 value 83.120297
iter 60 value 82.790175
final value 82.778431
converged
Fitting Repeat 5
# weights: 305
initial value 100.974447
iter 10 value 94.488944
iter 20 value 94.476747
iter 30 value 93.860931
iter 40 value 91.756316
iter 50 value 87.201245
iter 60 value 86.560985
final value 86.560923
converged
Fitting Repeat 1
# weights: 507
initial value 96.116005
iter 10 value 94.178907
iter 20 value 94.132478
iter 30 value 93.218252
final value 93.213991
converged
Fitting Repeat 2
# weights: 507
initial value 107.709183
iter 10 value 94.475526
iter 20 value 94.472725
iter 30 value 94.466891
iter 40 value 89.060174
iter 50 value 88.239080
iter 60 value 87.226605
iter 70 value 84.343402
iter 80 value 83.369157
iter 90 value 82.573839
iter 100 value 82.500034
final value 82.500034
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.623811
iter 10 value 94.492812
iter 20 value 94.272143
iter 30 value 89.047693
iter 40 value 85.533854
iter 50 value 82.613381
iter 60 value 82.517103
final value 82.516446
converged
Fitting Repeat 4
# weights: 507
initial value 98.847015
iter 10 value 93.701209
iter 20 value 93.694515
iter 30 value 93.688450
final value 93.688363
converged
Fitting Repeat 5
# weights: 507
initial value 129.345468
iter 10 value 94.492265
iter 20 value 94.474912
iter 30 value 94.470585
iter 40 value 94.459760
iter 50 value 94.458065
iter 60 value 94.456861
iter 70 value 92.587888
iter 80 value 88.814695
final value 88.814296
converged
Fitting Repeat 1
# weights: 103
initial value 97.242237
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.676891
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.649154
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.194115
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.866575
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 97.426083
final value 93.300000
converged
Fitting Repeat 2
# weights: 305
initial value 100.429524
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 115.597433
iter 10 value 89.156863
final value 87.352505
converged
Fitting Repeat 4
# weights: 305
initial value 102.406135
final value 94.466823
converged
Fitting Repeat 5
# weights: 305
initial value 130.531781
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 115.015673
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 112.011000
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 116.944718
iter 10 value 94.443243
iter 10 value 94.443243
iter 10 value 94.443243
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 99.141642
final value 94.378861
converged
Fitting Repeat 5
# weights: 507
initial value 121.528307
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 102.089134
iter 10 value 94.488650
iter 20 value 94.428083
iter 30 value 93.848974
iter 40 value 93.567620
iter 50 value 93.562470
iter 60 value 92.568413
iter 70 value 84.976174
iter 80 value 84.536920
iter 90 value 84.397900
iter 100 value 84.194964
final value 84.194964
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.901819
iter 10 value 94.509938
iter 20 value 94.491412
iter 30 value 94.268107
iter 40 value 88.358559
iter 50 value 87.743060
iter 60 value 86.935432
iter 70 value 85.994664
iter 80 value 85.797151
final value 85.797033
converged
Fitting Repeat 3
# weights: 103
initial value 103.354951
iter 10 value 94.486109
iter 20 value 88.166700
iter 30 value 86.996544
iter 40 value 86.220345
iter 50 value 85.813801
final value 85.797033
converged
Fitting Repeat 4
# weights: 103
initial value 101.695772
iter 10 value 91.775115
iter 20 value 85.820611
iter 30 value 85.358075
iter 40 value 84.903332
iter 50 value 84.782797
iter 60 value 84.214569
iter 70 value 83.248896
iter 80 value 82.955106
iter 90 value 82.881693
iter 90 value 82.881692
iter 90 value 82.881692
final value 82.881692
converged
Fitting Repeat 5
# weights: 103
initial value 102.164191
iter 10 value 93.388808
iter 20 value 86.683509
iter 30 value 86.274368
iter 40 value 84.509745
iter 50 value 83.994893
iter 60 value 83.981038
final value 83.980308
converged
Fitting Repeat 1
# weights: 305
initial value 103.820442
iter 10 value 94.452472
iter 20 value 85.547484
iter 30 value 85.416401
iter 40 value 84.015608
iter 50 value 83.893688
iter 60 value 83.849954
iter 70 value 83.534077
iter 80 value 82.481117
iter 90 value 82.081095
iter 100 value 81.911875
final value 81.911875
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.735923
iter 10 value 94.631691
iter 20 value 92.563804
iter 30 value 88.059475
iter 40 value 85.367220
iter 50 value 83.916796
iter 60 value 82.842269
iter 70 value 82.497618
iter 80 value 82.184459
iter 90 value 82.137226
final value 82.136909
converged
Fitting Repeat 3
# weights: 305
initial value 101.859629
iter 10 value 94.552861
iter 20 value 94.359326
iter 30 value 86.836666
iter 40 value 86.216423
iter 50 value 84.777791
iter 60 value 83.964423
iter 70 value 83.772532
iter 80 value 83.573556
iter 90 value 83.265670
iter 100 value 82.409537
final value 82.409537
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.279411
iter 10 value 94.456919
iter 20 value 87.275129
iter 30 value 84.845548
iter 40 value 83.928819
iter 50 value 82.537310
iter 60 value 81.910329
iter 70 value 81.618883
iter 80 value 81.497758
iter 90 value 81.434712
iter 100 value 81.398690
final value 81.398690
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.601478
iter 10 value 93.936773
iter 20 value 85.776459
iter 30 value 85.276717
iter 40 value 84.116344
iter 50 value 83.732703
iter 60 value 83.592927
iter 70 value 83.578859
iter 80 value 83.405551
iter 90 value 83.080381
iter 100 value 83.016518
final value 83.016518
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 116.656527
iter 10 value 94.741075
iter 20 value 87.225345
iter 30 value 85.593359
iter 40 value 85.140176
iter 50 value 82.604982
iter 60 value 81.874163
iter 70 value 81.684345
iter 80 value 81.630381
iter 90 value 81.560501
iter 100 value 81.302627
final value 81.302627
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.420087
iter 10 value 89.716157
iter 20 value 86.753335
iter 30 value 84.440142
iter 40 value 84.182859
iter 50 value 84.009416
iter 60 value 83.954047
iter 70 value 83.787048
iter 80 value 83.525854
iter 90 value 83.056483
iter 100 value 82.187211
final value 82.187211
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.447475
iter 10 value 94.677967
iter 20 value 87.920665
iter 30 value 84.285756
iter 40 value 83.775360
iter 50 value 82.943519
iter 60 value 82.688454
iter 70 value 82.627543
iter 80 value 82.377195
iter 90 value 82.036077
iter 100 value 81.772857
final value 81.772857
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.116130
iter 10 value 94.500217
iter 20 value 93.802008
iter 30 value 93.566563
iter 40 value 93.487805
iter 50 value 90.704528
iter 60 value 85.840884
iter 70 value 84.841891
iter 80 value 82.670668
iter 90 value 82.078733
iter 100 value 81.615809
final value 81.615809
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.112127
iter 10 value 94.508267
iter 20 value 93.574616
iter 30 value 89.709487
iter 40 value 86.910905
iter 50 value 85.174440
iter 60 value 84.393849
iter 70 value 83.833444
iter 80 value 83.581816
iter 90 value 83.250655
iter 100 value 83.221355
final value 83.221355
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.483989
final value 94.485816
converged
Fitting Repeat 2
# weights: 103
initial value 107.338834
final value 94.485770
converged
Fitting Repeat 3
# weights: 103
initial value 98.009901
final value 94.485644
converged
Fitting Repeat 4
# weights: 103
initial value 98.171891
final value 94.485583
converged
Fitting Repeat 5
# weights: 103
initial value 97.492334
final value 94.485959
converged
Fitting Repeat 1
# weights: 305
initial value 111.283739
iter 10 value 94.471490
iter 20 value 94.465075
iter 30 value 94.455744
iter 40 value 94.453173
iter 50 value 92.863139
iter 60 value 85.163536
iter 70 value 84.825456
iter 80 value 84.716289
iter 90 value 83.248409
iter 100 value 82.831361
final value 82.831361
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.255207
iter 10 value 94.305884
iter 20 value 93.215912
iter 30 value 92.963616
iter 40 value 92.874372
iter 50 value 92.870690
iter 60 value 92.868515
iter 60 value 92.868515
final value 92.868515
converged
Fitting Repeat 3
# weights: 305
initial value 114.317160
iter 10 value 94.489566
iter 20 value 94.455696
iter 30 value 91.277397
iter 40 value 87.080672
iter 50 value 87.030959
iter 60 value 86.859152
iter 70 value 86.766859
iter 80 value 86.147985
iter 90 value 86.141940
final value 86.141807
converged
Fitting Repeat 4
# weights: 305
initial value 96.798362
iter 10 value 91.114841
iter 20 value 90.979895
iter 30 value 90.106685
iter 40 value 89.652694
iter 50 value 89.465100
iter 60 value 89.449880
iter 70 value 89.448196
iter 80 value 87.515354
final value 87.496778
converged
Fitting Repeat 5
# weights: 305
initial value 104.443160
iter 10 value 94.471525
iter 20 value 94.411590
iter 30 value 89.094700
iter 40 value 88.679131
iter 50 value 87.161673
iter 60 value 87.041319
iter 60 value 87.041318
iter 60 value 87.041318
final value 87.041318
converged
Fitting Repeat 1
# weights: 507
initial value 105.708440
iter 10 value 94.491428
iter 20 value 91.820215
iter 30 value 85.159676
iter 40 value 84.874106
iter 50 value 84.850788
iter 60 value 83.328524
iter 70 value 83.226889
iter 80 value 83.115138
iter 90 value 82.844173
iter 100 value 82.678261
final value 82.678261
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.706515
iter 10 value 94.477750
iter 20 value 94.471483
iter 30 value 94.468910
final value 94.466866
converged
Fitting Repeat 3
# weights: 507
initial value 96.571640
iter 10 value 94.491958
iter 20 value 94.368016
iter 30 value 85.778881
iter 40 value 84.880658
iter 50 value 84.765589
iter 60 value 84.127484
iter 70 value 83.006175
iter 80 value 82.377497
iter 90 value 81.624462
iter 100 value 81.147598
final value 81.147598
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 100.903582
iter 10 value 94.441240
iter 20 value 94.368715
iter 30 value 94.346742
iter 40 value 93.926454
iter 50 value 93.393619
iter 60 value 93.387481
final value 93.387205
converged
Fitting Repeat 5
# weights: 507
initial value 105.611625
iter 10 value 94.475053
iter 20 value 94.465882
iter 30 value 93.923670
iter 40 value 92.079818
iter 50 value 92.060472
final value 92.060114
converged
Fitting Repeat 1
# weights: 103
initial value 99.621742
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.228911
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 120.169785
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.246776
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.616480
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 97.374098
final value 94.484137
converged
Fitting Repeat 2
# weights: 305
initial value 98.978557
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 96.642293
iter 10 value 94.112914
final value 94.112903
converged
Fitting Repeat 4
# weights: 305
initial value 111.201057
iter 10 value 94.154646
final value 94.142590
converged
Fitting Repeat 5
# weights: 305
initial value 113.947604
iter 10 value 94.112925
final value 94.112903
converged
Fitting Repeat 1
# weights: 507
initial value 100.426312
iter 10 value 94.112905
final value 94.112903
converged
Fitting Repeat 2
# weights: 507
initial value 98.691052
iter 10 value 90.585135
iter 20 value 89.239258
iter 30 value 87.232637
iter 40 value 86.055694
final value 86.055470
converged
Fitting Repeat 3
# weights: 507
initial value 100.868562
iter 10 value 94.133810
final value 94.112903
converged
Fitting Repeat 4
# weights: 507
initial value 95.472991
iter 10 value 93.809733
final value 93.808422
converged
Fitting Repeat 5
# weights: 507
initial value 109.115996
final value 94.325945
converged
Fitting Repeat 1
# weights: 103
initial value 104.141343
iter 10 value 94.530355
iter 20 value 94.486440
iter 30 value 89.152189
iter 40 value 87.531120
iter 50 value 87.436446
iter 60 value 86.874489
iter 70 value 85.995038
final value 85.988851
converged
Fitting Repeat 2
# weights: 103
initial value 99.563898
iter 10 value 89.549932
iter 20 value 87.331534
iter 30 value 86.103856
iter 40 value 85.674261
iter 50 value 85.435129
iter 60 value 85.253324
iter 70 value 85.239253
iter 80 value 85.202653
final value 85.191004
converged
Fitting Repeat 3
# weights: 103
initial value 94.806703
iter 10 value 88.591690
iter 20 value 87.905310
iter 30 value 86.900835
iter 40 value 86.596746
iter 50 value 86.472903
iter 60 value 86.011593
iter 70 value 85.988860
final value 85.988851
converged
Fitting Repeat 4
# weights: 103
initial value 103.794213
iter 10 value 94.558650
iter 20 value 94.488892
iter 30 value 94.488551
iter 40 value 90.228663
iter 50 value 87.207940
iter 60 value 86.794404
iter 70 value 86.080142
iter 80 value 85.543208
final value 85.537872
converged
Fitting Repeat 5
# weights: 103
initial value 102.050597
iter 10 value 94.515437
iter 20 value 94.432857
iter 30 value 94.211763
iter 40 value 94.166570
iter 50 value 92.558386
iter 60 value 89.625617
iter 70 value 88.846398
iter 80 value 84.634110
iter 90 value 84.362604
iter 100 value 84.316830
final value 84.316830
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 103.364506
iter 10 value 95.200194
iter 20 value 94.286732
iter 30 value 89.520003
iter 40 value 86.885771
iter 50 value 86.156746
iter 60 value 85.752262
iter 70 value 84.045128
iter 80 value 83.416923
iter 90 value 83.274067
iter 100 value 83.132879
final value 83.132879
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.756045
iter 10 value 94.596370
iter 20 value 88.749793
iter 30 value 87.514550
iter 40 value 87.264813
iter 50 value 86.554576
iter 60 value 85.036254
iter 70 value 84.086833
iter 80 value 82.946625
iter 90 value 82.372373
iter 100 value 82.326673
final value 82.326673
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.269261
iter 10 value 94.439928
iter 20 value 92.338813
iter 30 value 89.139299
iter 40 value 87.856699
iter 50 value 84.290612
iter 60 value 83.545272
iter 70 value 83.216460
iter 80 value 83.031570
iter 90 value 83.012071
iter 100 value 82.957358
final value 82.957358
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.948258
iter 10 value 94.562163
iter 20 value 93.809815
iter 30 value 91.385240
iter 40 value 87.936281
iter 50 value 85.454537
iter 60 value 84.314483
iter 70 value 83.987033
iter 80 value 83.318946
iter 90 value 83.293968
final value 83.293960
converged
Fitting Repeat 5
# weights: 305
initial value 100.733286
iter 10 value 94.494656
iter 20 value 91.883782
iter 30 value 88.464165
iter 40 value 86.804132
iter 50 value 85.616624
iter 60 value 84.826499
iter 70 value 84.554703
iter 80 value 83.931908
iter 90 value 82.996763
iter 100 value 82.722293
final value 82.722293
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.294299
iter 10 value 95.603511
iter 20 value 88.379029
iter 30 value 87.371146
iter 40 value 85.735327
iter 50 value 85.161813
iter 60 value 84.077015
iter 70 value 83.228570
iter 80 value 83.020877
iter 90 value 82.920537
iter 100 value 82.777537
final value 82.777537
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.026233
iter 10 value 94.452304
iter 20 value 87.581802
iter 30 value 86.640500
iter 40 value 84.496666
iter 50 value 83.545394
iter 60 value 83.247757
iter 70 value 83.035405
iter 80 value 82.602375
iter 90 value 82.309970
iter 100 value 82.185648
final value 82.185648
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.010296
iter 10 value 95.952481
iter 20 value 91.762334
iter 30 value 85.964334
iter 40 value 83.819882
iter 50 value 83.197143
iter 60 value 82.956542
iter 70 value 82.887791
iter 80 value 82.848948
iter 90 value 82.793350
iter 100 value 82.749279
final value 82.749279
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.198476
iter 10 value 95.027481
iter 20 value 94.545460
iter 30 value 91.805518
iter 40 value 86.179174
iter 50 value 85.337502
iter 60 value 84.305923
iter 70 value 83.460498
iter 80 value 83.098406
iter 90 value 82.819349
iter 100 value 82.690518
final value 82.690518
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.291270
iter 10 value 94.759311
iter 20 value 94.461920
iter 30 value 92.898518
iter 40 value 89.647813
iter 50 value 85.842079
iter 60 value 84.957009
iter 70 value 84.431965
iter 80 value 84.185441
iter 90 value 84.065131
iter 100 value 84.059682
final value 84.059682
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.980232
iter 10 value 94.485981
final value 94.484330
converged
Fitting Repeat 2
# weights: 103
initial value 93.800371
iter 10 value 87.954534
final value 87.858051
converged
Fitting Repeat 3
# weights: 103
initial value 99.516461
iter 10 value 94.485962
iter 20 value 94.269526
iter 30 value 88.308060
iter 40 value 88.255771
iter 50 value 88.254522
iter 60 value 88.253827
iter 70 value 85.981227
final value 85.842806
converged
Fitting Repeat 4
# weights: 103
initial value 95.882301
final value 94.485795
converged
Fitting Repeat 5
# weights: 103
initial value 94.551475
final value 94.485871
converged
Fitting Repeat 1
# weights: 305
initial value 100.390285
iter 10 value 94.488868
iter 20 value 94.268502
iter 30 value 88.865553
iter 40 value 86.868428
iter 50 value 86.849315
iter 60 value 86.829574
iter 60 value 86.829573
iter 60 value 86.829573
final value 86.829573
converged
Fitting Repeat 2
# weights: 305
initial value 104.278562
iter 10 value 94.487825
iter 20 value 93.554148
iter 30 value 87.971567
iter 40 value 87.675616
iter 50 value 87.673603
final value 87.673446
converged
Fitting Repeat 3
# weights: 305
initial value 103.877885
iter 10 value 94.117936
iter 20 value 94.115195
iter 30 value 94.113304
iter 40 value 86.637124
iter 50 value 85.683887
iter 60 value 84.779681
iter 70 value 84.610634
iter 80 value 84.610049
iter 90 value 84.510599
iter 100 value 82.301176
final value 82.301176
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 121.872556
iter 10 value 94.482531
iter 20 value 94.442705
iter 30 value 92.633399
iter 40 value 86.702954
iter 50 value 86.623351
iter 60 value 86.614702
iter 70 value 85.430853
iter 80 value 85.289177
iter 90 value 84.976162
iter 100 value 82.397497
final value 82.397497
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 96.739376
iter 10 value 94.294658
iter 20 value 94.120187
iter 30 value 94.114835
iter 40 value 87.372933
iter 50 value 86.169168
iter 60 value 86.059147
iter 70 value 86.058939
iter 80 value 86.058317
iter 90 value 84.276678
iter 100 value 83.038758
final value 83.038758
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 98.309501
iter 10 value 94.121269
iter 20 value 94.115814
iter 30 value 94.055165
iter 40 value 94.054770
iter 50 value 90.213488
iter 60 value 86.837692
iter 70 value 85.888254
iter 80 value 84.948501
iter 90 value 84.818729
final value 84.817975
converged
Fitting Repeat 2
# weights: 507
initial value 97.848075
iter 10 value 94.121030
iter 20 value 94.113345
iter 30 value 88.943331
iter 40 value 87.309305
iter 50 value 87.309101
iter 60 value 86.671162
iter 70 value 86.612953
iter 80 value 86.594389
final value 86.593687
converged
Fitting Repeat 3
# weights: 507
initial value 99.085798
iter 10 value 93.975249
iter 20 value 93.972243
iter 30 value 90.691419
iter 40 value 86.770330
iter 50 value 84.233345
iter 60 value 82.897134
iter 70 value 82.054874
iter 80 value 81.618079
iter 90 value 81.502508
iter 100 value 81.405284
final value 81.405284
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 95.273388
iter 10 value 94.488942
iter 20 value 91.822876
iter 30 value 89.293217
iter 40 value 89.281126
iter 40 value 89.281126
iter 50 value 89.264979
iter 60 value 88.787198
iter 70 value 88.700587
iter 80 value 86.159823
iter 90 value 85.716442
final value 85.711413
converged
Fitting Repeat 5
# weights: 507
initial value 99.706180
iter 10 value 94.174223
iter 20 value 94.074336
iter 30 value 94.071632
iter 40 value 91.048880
iter 50 value 87.654493
iter 60 value 87.530515
iter 70 value 87.530072
iter 80 value 87.529351
final value 87.529243
converged
Fitting Repeat 1
# weights: 305
initial value 117.241373
iter 10 value 116.473135
iter 20 value 114.737031
iter 30 value 114.731092
final value 114.727809
converged
Fitting Repeat 2
# weights: 305
initial value 122.554718
iter 10 value 117.894767
iter 20 value 117.718726
iter 30 value 113.409480
iter 40 value 108.974777
iter 50 value 106.545323
iter 60 value 106.177881
iter 70 value 106.166779
final value 106.166771
converged
Fitting Repeat 3
# weights: 305
initial value 126.484375
iter 10 value 117.893523
iter 20 value 117.875913
iter 30 value 115.599457
iter 40 value 115.184855
final value 115.157402
converged
Fitting Repeat 4
# weights: 305
initial value 120.216433
iter 10 value 117.894683
iter 20 value 117.744206
iter 30 value 105.863213
iter 40 value 105.040447
iter 50 value 104.837016
iter 60 value 104.826373
iter 70 value 104.215291
iter 80 value 103.609632
iter 90 value 103.608703
iter 100 value 103.606498
final value 103.606498
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 122.230581
iter 10 value 117.763584
iter 20 value 117.759138
iter 30 value 117.728666
iter 40 value 116.298492
iter 50 value 111.772780
iter 60 value 111.680253
final value 111.670650
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 -- Tue Mar 10 00:29:16 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
40.616 1.519 94.506
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.106 | 0.464 | 33.574 | |
| FreqInteractors | 0.471 | 0.023 | 0.495 | |
| calculateAAC | 0.034 | 0.000 | 0.034 | |
| calculateAutocor | 0.297 | 0.012 | 0.310 | |
| calculateCTDC | 0.073 | 0.001 | 0.074 | |
| calculateCTDD | 0.516 | 0.003 | 0.518 | |
| calculateCTDT | 0.188 | 0.007 | 0.194 | |
| calculateCTriad | 0.370 | 0.011 | 0.381 | |
| calculateDC | 0.083 | 0.001 | 0.083 | |
| calculateF | 0.318 | 0.002 | 0.320 | |
| calculateKSAAP | 0.108 | 0.000 | 0.107 | |
| calculateQD_Sm | 1.785 | 0.011 | 1.796 | |
| calculateTC | 1.502 | 0.026 | 1.527 | |
| calculateTC_Sm | 0.261 | 0.001 | 0.262 | |
| corr_plot | 34.772 | 0.526 | 35.298 | |
| enrichfindP | 0.598 | 0.052 | 12.986 | |
| enrichfind_hp | 0.081 | 0.002 | 2.538 | |
| enrichplot | 0.606 | 0.151 | 0.757 | |
| filter_missing_values | 0.002 | 0.000 | 0.002 | |
| getFASTA | 0.387 | 0.032 | 3.355 | |
| getHPI | 0.001 | 0.000 | 0.002 | |
| get_negativePPI | 0.003 | 0.000 | 0.004 | |
| get_positivePPI | 0.000 | 0.001 | 0.000 | |
| impute_missing_data | 0.002 | 0.001 | 0.003 | |
| plotPPI | 0.104 | 0.016 | 0.122 | |
| pred_ensembel | 12.867 | 0.375 | 11.969 | |
| var_imp | 33.141 | 0.664 | 33.807 | |