mixturebf-class: Class "mixturebf"

In mombf: Model Selection with Bayesian Methods and Information Criteria

Class "mixturebf"

Description

Stores the output of Bayesian model selection for mixture models, e.g. as produced by function bfnormmix.

Methods are provided for retrieving the posterior probability of a given number of mixture components, posterior means and posterior samples of the mixture model parameters.

Objects from the Class

Typically objects are automatically created by a call to bfnormmix.

Slots

The class has the following slots:

postprob

data.frame containing posterior probabilities for different numbers of components (k) and log-posterior probability of a component being empty (contain no individuals)

p

Number of variables in the data to which the model was fit

n

Number of observations in the data to which the model was fit

priorpars

Prior parameters used when fitting the model

postpars

Posterior parameters for a 1-component mixture, e.g. for a Normal mixture the posterior is N(mu1,Sigma/prec) IW(nu1,S1)

mcmc

For each considered value of k, posterior samples for the parameters of the k-component model are stored

Methods

coef

Computes posterior means for all parameters

show

signature(object = "mixturebf"): Displays general information about the object.

postProb

signature(object = "mixturebf"): Extracts posterior model probabilities, Bayes factors and posterior probability of a cluster being empty

postSamples

signature(object = "mixturebf"): Extracts posterior samples

Author(s)

David Rossell

References

Fuquene J., Steel M.F.J., Rossell D. On choosing mixture components via non-local priors. 2018. arXiv

See Also

See also bfnormmix

Examples

showClass("mixturebf")

mombf documentation built on May 29, 2024, 11:01 a.m.