Performs variable selection with data from Genome-wide association studies (GWAS) combining, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of nonlocal priors, as described in Sanyal et al. (2018).
|Author:||Nilotpal Sanyal [aut, cre]|
|Maintainer:||Nilotpal Sanyal <nilotpal.sanyal at gmail.com>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|CRAN checks:||GWASinlps results|
|Windows binaries:||r-devel: GWASinlps_1.2.zip, r-release: GWASinlps_1.2.zip, r-oldrel: GWASinlps_1.2.zip|
|macOS binaries:||r-release (arm64): GWASinlps_1.2.tgz, r-oldrel (arm64): GWASinlps_1.2.tgz, r-release (x86_64): GWASinlps_1.2.tgz, r-oldrel (x86_64): GWASinlps_1.2.tgz|
|Old sources:||GWASinlps archive|
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