Contains an implementation of 'StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2021) <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.
Package details |
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Author | Niklas Pfister [aut, cre], Evan Williams [ctb] |
Maintainer | Niklas Pfister <np@math.ku.dk> |
License | GPL-3 |
Version | 1.1 |
Package repository | View on CRAN |
Installation |
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