SSS_make_beta_grid

Creates a vector of uniformly spaced grid points in the beta parametrization
Ensures the number of generated grid points is &gt;= mingridpoints (which does
not have to be integer), and that their number is always odd so there is always 
a grid point at pi/4.

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.

Tim van Erven

SequenceSpikeSlab

Exact Bayesian Model Selection Methods for the Sparse Normal
Sequence Model

Steven de Rooij

Botond Szabo

SSS_make_beta_grid function

<dl><dt>minngridpoints</dt>
<dd>Minimum number of grid points</dd></dl>

Arguments

Creates a vector of uniformly spaced grid points in the beta parametrization
Ensures the number of generated grid points is &gt;= mingridpoints (which does
not have to be integer), and that their number is always odd so there is always 
a grid point at pi/4. — SSS_make_beta_grid

<dl>

<dt>minngridpoints</dt>
<dd>Minimum number of grid points</dd>

</dl>

Creates a vector of uniformly spaced grid points in the beta parametrization
Ensures the number of generated grid points is &gt;= mingridpoints (which does
not have to be integer), and that their number is always odd so there is always 
a grid point at pi/4.

SSS_make_beta_grid: Creates a vector of uniformly spaced grid points in the beta parametrization Ensures the number of generated grid points is >= mingridpoints (which does not have to be integer), and that their number is always odd so there is always a grid point at pi/4.

Description

Usage

Value

Arguments