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SequenceSpikeSlab  

Exact Bayesian Model Selection Methods for the Sparse Normal Sequence Model
View on CRAN: Click here


Download and install SequenceSpikeSlab package within the R console
Install from CRAN:
install.packages("SequenceSpikeSlab")

Install from Github:
library("remotes")
install_github("cran/SequenceSpikeSlab")

Install by package version:
library("remotes")
install_version("SequenceSpikeSlab", "1.0.1")



Attach the package and use:
library("SequenceSpikeSlab")
Maintained by
Tim van Erven
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-13
Latest Update: 2023-09-08
Description:
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, ). 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.
How to cite:
Tim van Erven (2019). SequenceSpikeSlab: Exact Bayesian Model Selection Methods for the Sparse Normal Sequence Model. R package version 1.0.1, https://cran.r-project.org/web/packages/SequenceSpikeSlab. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.1 (2020-01-08 11:40), 0.1 (2019-12-13 15:20), 1.0.0 (2022-01-23 16:22)
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