xnet: Two-Step Kernel Ridge Regression for Network Predictions (original) (raw)
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 |
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