SequenceSpikeSlab: Exact Bayesian Model Selection Methods for the Sparse Normal Sequence Model

Contains fast functions to calculate the exact Bayes posterior for the Sparse Normal Sequence Model, which implement the algorithms described in Van Erven and Szabo (2018) <arXiv:1810.10883>. For general hierarchical priors, sample sizes up to 10,000 are feasible within half an hour on a standard laptop. For beta-binomial spike-and-slab priors, a faster algorithm is provided, which can handle sample sizes of 100,000 in half an hour. In the implementation, special care has been taken to assure numerical stability of the methods even for such large sample sizes.

Version: 0.1.1
Imports: Rcpp (≥ 0.12.18), RcppProgress (≥ 0.4.1), selectiveInference (≥ 1.2.5)
LinkingTo: Rcpp, RcppProgress
Suggests: knitr, rmarkdown
Published: 2020-01-08
Author: Steven de Rooij [cre, aut], Tim van Erven [aut], Botond Szabo [aut]
Maintainer: Steven de Rooij <steven.de.rooij at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: SequenceSpikeSlab citation info
Materials: NEWS
CRAN checks: SequenceSpikeSlab results

Downloads:

Reference manual: SequenceSpikeSlab.pdf
Vignettes: SequenceSpikeSlab-vignette
Package source: SequenceSpikeSlab_0.1.1.tar.gz
Windows binaries: r-prerelease: SequenceSpikeSlab_0.1.1.zip, r-release: SequenceSpikeSlab_0.1.1.zip, r-oldrel: SequenceSpikeSlab_0.1.1.zip
macOS binaries: r-prerelease: SequenceSpikeSlab_0.1.1.tgz, r-release: SequenceSpikeSlab_0.1.1.tgz, r-oldrel: SequenceSpikeSlab_0.1.1.tgz
Old sources: SequenceSpikeSlab archive

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