mmhhData

A list of 2-dimensional Gaussian mixture samples and the corresponding group labels. The samples are generated by 4 different Gaussian distributions. Each sample is assigned to a group and a subgroup. There are 2 groups, group 1 has 10 subgroups, group 2 has 20 subgroups.

datasets

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

bbricks

Bayesian Methods and Graphical Model Structures for Statistical
Modeling

mmhhData function

A list of three elements:<dl class="dl-horizontal">
 <dt>x</dt><dd>: matrix, 2-dimensional Gaussian samples, each row is a sample</dd>
 <dt>groupLabel</dt><dd>: integer, the group label of each Gaussian sample</dd>
 <dt>subGroupLabel</dt><dd>: integer, the subgroup label of each Gaussian sample</dd>
</dl>

Format

Samples from a hierarchical mixture model with two layers of hierarchies — mmhhData

A list of three elements:<dl class='dl-horizontal'>
 <dt>x</dt><dd>: matrix, 2-dimensional Gaussian samples, each row is a sample</dd>
 <dt>groupLabel</dt><dd>: integer, the group label of each Gaussian sample</dd>
 <dt>subGroupLabel</dt><dd>: integer, the subgroup label of each Gaussian sample</dd>
</dl>

mmhhData: Samples from a hierarchical mixture model with two layers of hierarchies

Description

Usage

Arguments

Format