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

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 form https://CRAN.R-project.org/package=xnet to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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