SSS_discretize_Lambda: Given a prior Lambda on the alpha-parameter in the...

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

Given a prior Lambda on the alpha-parameter in the spike-and-slab model, make a discretized version of Lambda that is only supported on a grid of approximately m * sqrt(n) discrete values of alpha. This discretized version of Lambda is required as input for SSS_discrete_spike_slab. NB Lambda needs to satisfy a technical condition from the paper that guarantees its density does not vary too rapidly. For Lambda=Beta(kappa,lambda) use SSS_discretize_Lambda_beta instead.

Description

Given a prior Lambda on the alpha-parameter in the spike-and-slab model, make a discretized version of Lambda that is only supported on a grid of approximately m * sqrt(n) discrete values of alpha. This discretized version of Lambda is required as input for SSS_discrete_spike_slab. NB Lambda needs to satisfy a technical condition from the paper that guarantees its density does not vary too rapidly. For Lambda=Beta(kappa,lambda) use SSS_discretize_Lambda_beta instead.

Usage

SSS_discretize_Lambda(m = 20, n, log_Lambda_cdf)

Arguments

m	A multiplier for the number of discretization points
n	The sample size
log_Lambda_cdf	A function that takes as input a value of alpha and calculates the log of the cumulative distribution function of Lambda at alpha

Value

List (alpha_grid, log_probs), where alpha_grid is a vector with the generated grid points, and log_probs are the logs of the prior probabilities of these grid points for the discretized Lambda prior.

SequenceSpikeSlab documentation built on Sept. 8, 2023, 6:06 p.m.