AM_plot_chaincor

An <code><a rd-options="" href="/link/AM_mcmc_output?package=AntMAN&version=1.1.0" data-mini-rdoc="AntMAN::AM_mcmc_output">AM_mcmc_output</a></code> object, produced by calling <code><a rd-options="" href="/link/AM_mcmc_fit?package=AntMAN&version=1.1.0" data-mini-rdoc="AntMAN::AM_mcmc_fit">AM_mcmc_fit</a></code>.

A list of variables to consider. This function only produces meaningful plots for variables that have fixed dimension across the draws. If not specified, plots pertaining to M and K will be produced.
This function is built upon bayesplot's <code>mcmc_acf_bar</code>.

lags

title

Given an <code><a rd-options="" href="/link/AM_mcmc_output?package=AntMAN&version=1.1.0" data-mini-rdoc="AntMAN::AM_mcmc_output">AM_mcmc_output</a></code> object, this function produces the autocorrelation function bars describing the MCMC results. AM_plot_chaincor makes use of bayesplot&lt;U+2019&gt;s
plotting function mcmc_acf_bar bayesplotAntMAN.

Fits finite Bayesian mixture models with a random number of components. The MCMC algorithm implemented is based on point processes as proposed by Argiento and De Iorio (2019) <arXiv:1904.09733> and offers a more computationally efficient alternative to reversible jump. Different mixture kernels can be specified: univariate Gaussian, multivariate Gaussian, univariate Poisson, and multivariate Bernoulli (latent class analysis). For the parameters characterising the mixture kernel, we specify conjugate priors, with possibly user specified hyper-parameters. We allow for different choices for the prior on the number of components: shifted Poisson, negative binomial, and point masses (i.e. mixtures with fixed number of components).

Bruno Bodin

AntMAN

Anthology of Mixture Analysis Tools

Priscilla Ong

Raffaele Argiento

Maria De Iorio

AM_plot_chaincor function

An <code><a rd-options='' href='AM_mcmc_output'>AM_mcmc_output</a></code> object, produced by calling <code><a rd-options='' href='AM_mcmc_fit'>AM_mcmc_fit</a></code>.

Given an <code><a rd-options='' href='AM_mcmc_output'>AM_mcmc_output</a></code> object, this function produces the autocorrelation function bars describing the MCMC results. AM_plot_chaincor makes use of bayesplot&lt;U+2019&gt;s
plotting function mcmc_acf_bar bayesplotAntMAN.

AM_plot_chaincor: Plot the Autocorrelation function

Description

Usage

Arguments

Value