p6_big_bern

p6_big_bern_1

p6_big_bern_2

p6_big_bern_3

Multivariate categorical data, generated as five clusters of independent variables with different
 success probabilities.

datasets

Markov chain Monte Carlo samplers for posterior simulations of conjugate Bayesian nonparametric
mixture models. Functionality is provided for Gibbs sampling as in Algorithm 3 of Neal (2000)
<DOI:10.1080/10618600.2000.10474879>, restricted Gibbs merge-split sampling as described in Jain & Neal
(2004) <DOI:10.1198/1061860043001>, and sequentially-allocated merge-split sampling <DOI:10.1080/00949655.2021.1998502>, as well as
summary and utility functions.

David B Dahl

sams

Merge-Split Samplers for Conjugate Bayesian Nonparametric Models

Spencer Newcomb

David B. Dahl

p6_big_bern function

An object of class <code>data.frame</code> with 1000 rows and 6 columns.
An object of class <code>data.frame</code> with 1000 rows and 6 columns.
An object of class <code>data.frame</code> with 1000 rows and 6 columns.

Format

Large Sample Multivariate Independent Bernoulli Data (p = 6) — p6_big_bern

Large Sample Multivariate Independent Bernoulli Data (p = 6)

p6_big_bern: Large Sample Multivariate Independent Bernoulli Data (p = 6)

Description

Usage

Arguments

Format