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xnet: Two-Step Kernel Ridge Regression for Network Predictions

Fit a two-step kernel ridge regression model for predicting edges in networks, and carry out cross-validation using shortcuts for swift and accurate performance assessment (Stock et al, 2018 <doi:10.1093/bib/bby095> ).

Version:0.1.11
Depends:R (≥ 3.4.0)
Imports:methods, utils, graphics, stats, grDevices
Suggests:testthat,knitr,rmarkdown,ChemmineR,covr,fmcsR
Published:2020-02-03
DOI:10.32614/CRAN.package.xnet
Author:Joris Meys [cre, aut], Michiel Stock [aut]
Maintainer:Joris Meys <Joris.Meys at UGent.be>
BugReports:https://github.com/CenterForStatistics-UGent/xnet/issues
License:GPL-3
URL:https://github.com/CenterForStatistics-UGent/xnet
NeedsCompilation:no
Citation:xnet citation info
Materials:NEWS
CRAN checks:xnet results

Documentation:

Reference manual:xnet.html ,xnet.pdf
Vignettes:Preparation of the example data (source,R code)
xnet Class structure (source,R code)
xnet (source,R code)

Downloads:

Package source: xnet_0.1.11.tar.gz
Windows binaries: r-devel:xnet_0.1.11.zip, r-release:xnet_0.1.11.zip, r-oldrel:xnet_0.1.11.zip
macOS binaries: r-release (arm64):xnet_0.1.11.tgz, r-oldrel (arm64):xnet_0.1.11.tgz, r-release (x86_64):xnet_0.1.11.tgz, r-oldrel (x86_64):xnet_0.1.11.tgz
Old sources: xnet archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=xnetto link to this page.


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