dCategorical

<p>Calculate probability masses for integer valued Categorical random samples.
For a random variable x, the density function of categorical distribution is defined as
  $$prod_{k in 1:K} p_k^{I(x=k)}$$
Where K is the number of unique values.</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

dCategorical: Probability mass function for Categorical distribution

Description

Usage

Arguments

Value

See Also

Examples