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) . 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.


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install.packages("SequenceSpikeSlab")

0.1.1 by Steven de Rooij, 10 months ago


Browse source code at https://github.com/cran/SequenceSpikeSlab


Authors: Steven de Rooij [cre, aut] , Tim van Erven [aut] , Botond Szabo [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, RcppProgress, selectiveInference

Suggests knitr, rmarkdown

Linking to Rcpp, RcppProgress


See at CRAN