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mombf (version 2.2.3)

Bayesian Model Selection and Averaging for Non-Local and Local Priors

Description

Bayesian model selection and averaging for regression and mixtures for non-local and selected local priors.

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Version

Install

install.packages('mombf')

Monthly Downloads

278

Version

2.2.3

License

GPL (>= 2)

Maintainer

David Rossell

Last Published

April 28th, 2019

Functions in mombf (2.2.3)

mixturebf-class

Class "mixturebf"

priorp2g

Moment and inverse moment prior elicitation

mombf

Moment and inverse moment Bayes factors for linear models.

bfnormmix

Number of Normal mixture components under Normal-IW and Non-local priors

modelSelection

Bayesian variable selection for linear models via non-local priors.

momknown

Bayes factors for moment, inverse moment and Zellner-Siow g-prior.

msPriorSpec-class

Class "msPriorSpec"

postModeOrtho

Bayesian model selection and averaging under block-diagonal X'X for linear models.

postProb

Obtain posterior model probabilities

pmomLM

Bayesian variable selection and model averaging for linear and probit models via non-local priors.

nlpmarginals

Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors

msfit-class

Class "msfit"

postSamples

Extract posterior samples from an object

rnlp

Posterior sampling for Non-Local Priors

bbPrior

Priors on model space for variable selection problems

dalapl

Density and random draws from the asymmetric Laplace distribution

ddir

Dirichlet density

diwish

Density for Inverse Wishart distribution

dmom

Non-local prior density, cdf and quantile functions.

dpostNIW

Posterior Normal-IWishart density

eprod

Expectation of a product of powers of Normal or T random variables

hald

Hald Data

marginalNIW

Marginal likelihood under a multivariate Normal likelihood and a conjugate Normal-inverse Wishart prior.