Contains an implementation of 'StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2019) <arXiv:1911.01850>. The procedure uses averaging to estimate a regression of a set of predictors X on a response variable Y by enforcing stability with respect to a given environment variable. The resulting regression leads to a variable selection procedure which allows to distinguish between stable and unstable predictors. The package further implements a visualization technique which illustrates the trade-off between stability and predictiveness of individual predictors.
| Version: | 1.0 |
| Depends: | R (≥ 3.5) |
| Imports: | MASS, R6, glmnet, corpcor, ggplot2, ggrepel |
| Published: | 2020-03-13 |
| Author: | Niklas Pfister [aut, cre], Evan Williams [ctb] |
| Maintainer: | Niklas Pfister <np at math.ku.dk> |
| BugReports: | https://github.com/NiklasPfister/StabilizedRegression-R/issues |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | StabilizedRegression results |
| Reference manual: | StabilizedRegression.pdf |
| Package source: | StabilizedRegression_1.0.tar.gz |
| Windows binaries: | r-devel: StabilizedRegression_1.0.zip, r-release: StabilizedRegression_1.0.zip, r-oldrel: StabilizedRegression_1.0.zip |
| macOS binaries: | r-release: StabilizedRegression_1.0.tgz, r-oldrel: StabilizedRegression_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=StabilizedRegression to link to this page.