gibbsmix

A function that samples marginal mixture densities via a
marginal Gibbs sampler.

Performs Bayesian nonparametric density estimation using Martingale
posterior distributions including the Copula Resampling (CopRe) algorithm.
Also included are a Gibbs sampler for the marginal Gibbs-type mixture model and
an extension to include full uncertainty quantification via a predictive
sequence resampling (SeqRe) algorithm. The CopRe and SeqRe samplers generate
random nonparametric distributions as output, leading to complete nonparametric
inference on posterior summaries. Routines for calculating arbitrary
functionals from the sampled distributions are included as well as an important
algorithm for finding the number and location of modes, which can then be used
to estimate the clusters in the data using, for example, k-means.
Implements work developed in Moya B., Walker S. G. (2022).
<doi:10.48550/arxiv.2206.08418>, Fong, E., Holmes, C., Walker, S. G. (2021)
<doi:10.48550/arxiv.2103.15671>, and Escobar M. D., West, M. (1995)
<doi:10.1080/01621459.1995.10476550>.

Blake Moya

copre

Tools for Nonparametric Martingale Posterior Sampling

The University of Texas at Austin 

gibbsmix function

<dl><dt>data</dt>
<dd>The data from which to sample predictive distributions.</dd>
<dt>k</dt>
<dd>The number of predictive samples to draw.</dd>
<dt>b_msr</dt>
<dd>A <code>base_measure</code> object.</dd>
<dt>s_msr</dt>
<dd>A <code>seq_measure</code> object.</dd>
<dt>burn</dt>
<dd>The number of initial sampling iterations to discard, will be
truncated if a non-integer.</dd>
<dt>thin</dt>
<dd>The number of sampling iterations to discard between records,
will be truncated if a non-integer.</dd></dl>

Arguments

Marginal Gibbs-type Mixture Model Sampler — gibbsmix

<dl>

<dt>data</dt>
<dd>The data from which to sample predictive distributions.</dd>


<dt>k</dt>
<dd>The number of predictive samples to draw.</dd>


<dt>b_msr</dt>
<dd>A <code>base_measure</code> object.</dd>


<dt>s_msr</dt>
<dd>A <code>seq_measure</code> object.</dd>


<dt>burn</dt>
<dd>The number of initial sampling iterations to discard, will be
truncated if a non-integer.</dd>


<dt>thin</dt>
<dd>The number of sampling iterations to discard between records,
will be truncated if a non-integer.</dd>

</dl>

gibbsmix: Marginal Gibbs-type Mixture Model Sampler

Description

Usage

Value

Arguments

See Also