marginalLikelihood.DP

<p>Additional arguments to be passed to other inherited types.</p>

<p>Marginal likelihood for Dirichlet Process(DP)</p>

A set of frequently used Bayesian parametric and nonparametric model structures, as well as a set of tools for common analytical tasks. Structures include linear Gaussian systems, Gaussian and Normal-Inverse-Wishart conjugate structure, Gaussian and Normal-Inverse-Gamma conjugate structure, Categorical and Dirichlet conjugate structure, Dirichlet Process on positive integers, Dirichlet Process in general, Hierarchical Dirichlet Process ... Tasks include updating posteriors, sampling from posteriors, calculating marginal likelihood, calculating posterior predictive densities, sampling from posterior predictive distributions, calculating "Maximum A Posteriori" (MAP) estimates ... See <https://chenhaotian.github.io/Bayesian-Bricks/> to get started.

Haotian Chen

marginalLikelihood.DP: Marginal likelihood for Dirichlet Process(DP)

Description

Usage

Arguments

Value