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


Reference manual: xnet.pdf
Vignettes: Preparation of the example data
xnet Class structure


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


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