Contains fast functions to calculate the exact Bayes posterior for the Sparse Normal Sequence Model, implementing the algorithms described in Van Erven and Szabo (2021, <doi:10.1214/20-BA1227>). 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: | 1.0.1 |
Imports: | Rcpp (≥ 0.12.18), RcppProgress (≥ 0.4.1), selectiveInference (≥ 1.2.5) |
LinkingTo: | Rcpp, RcppProgress |
Suggests: | knitr, rmarkdown |
Published: | 2023-09-08 |
DOI: | 10.32614/CRAN.package.SequenceSpikeSlab |
Author: | Steven de Rooij [aut], Tim van Erven [cre, aut], Botond Szabo [aut] |
Maintainer: | Tim van Erven <tim at timvanerven.nl> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Citation: | SequenceSpikeSlab citation info |
Materials: | NEWS |
In views: | Bayesian |
CRAN checks: | SequenceSpikeSlab results |
Reference manual: | SequenceSpikeSlab.pdf |
Vignettes: |
SequenceSpikeSlab-vignette |
Package source: | SequenceSpikeSlab_1.0.1.tar.gz |
Windows binaries: | r-devel: SequenceSpikeSlab_1.0.1.zip, r-release: SequenceSpikeSlab_1.0.1.zip, r-oldrel: SequenceSpikeSlab_1.0.1.zip |
macOS binaries: | r-release (arm64): SequenceSpikeSlab_1.0.1.tgz, r-oldrel (arm64): SequenceSpikeSlab_1.0.1.tgz, r-release (x86_64): SequenceSpikeSlab_1.0.1.tgz, r-oldrel (x86_64): SequenceSpikeSlab_1.0.1.tgz |
Old sources: | SequenceSpikeSlab archive |
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