AM_demo_mvn_poi

<p>This function allows us to generate a sample output of fitting the multivariate Gaussian model. No arguments are needed to be passed.
The purpose of this function is to serve as a demo for users to understand the model's output, without diving too deep into details. By default,
this demo generates a sample dataset of dimension 500x2, where the MCMC sampler is specified to run for 2000 iterations, with a burn-in of 1000, and a thinning interval of 10. All possible outputs
that can be produced by <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> are returned (see return value below).</p>

demo

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_demo_mvn_poi function

<p>This function allows us to generate a sample output of fitting the multivariate Gaussian model. No arguments are needed to be passed.
The purpose of this function is to serve as a demo for users to understand the model's output, without diving too deep into details. By default,
this demo generates a sample dataset of dimension 500x2, where the MCMC sampler is specified to run for 2000 iterations, with a burn-in of 1000, and a thinning interval of 10. All possible outputs
that can be produced by <code><a rd-options='' href='AM_mcmc_fit'>AM_mcmc_fit</a></code> are returned (see return value below).</p>

Returns an example of <code><a rd-options='' href='AM_mcmc_fit'>AM_mcmc_fit</a></code> output produced by the multivariate gaussian model — AM_demo_mvn_poi

Returns an example of <code><a rd-options='' href='AM_mcmc_fit'>AM_mcmc_fit</a></code> output produced by the multivariate gaussian model

Returns an example of <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> output produced by the multivariate gaussian model

AM_demo_mvn_poi: Returns an example of `AM_mcmc_fit` output produced by the multivariate gaussian model

Description

Usage

Arguments

Value

Examples