log_marg_likel {bayesmove}

Internal function that calculates the log marginal likelihood of each model being compared

Description

An internal function that is used to calculate the log marginal likelihood of models for the current and proposed sets of breakpoints. Called within samp_move.

Usage

log_marg_likel(alpha, summary.stats, nbins, ndata.types)

Arguments

alpha

numeric. A single value used to specify the hyperparameter for the prior distribution. A standard value for alpha is typically 1, which corresponds with a vague prior on the Dirichlet distribution.

summary.stats

A matrix of sufficient statistics returned from get_summary_stats.

nbins

numeric. A vector of the number of bins used to discretize each movement variable.

ndata.types

numeric. The length of nbins.

Value

The log marginal likelihood is calculated for a model with a given set of breakpoints and the discretized data.