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Last data update: 2014.03.03

R: Generate the posterior samples from the posterior...

CompWiseGibbsSimple

R Documentation

Generate the posterior samples from the posterior distribution using the component-wise Gibbs sampler (CWGS).

Description

Generate the posterior samples using MCMC procedures.

Usage

CompWiseGibbsSimple(Y, X, beta.value, r, tau2, rho, sigma2, nu, lambda,
                    num.of.inner.iter, num.of.iteration, MCSE.Sigma2.Given)

Arguments

`Y`	vector of observations of length n.
`X`	design matrix of dimension n \times p.
`beta.value`	Initial values of regression coefficients, β.
`r`	Initial values of indicator variables for individual regressors.
`tau2`	Variance in the prior distribution for regression coefficients.
`rho`	Prior probability including a variable.
`sigma2`	Initial value of σ^2.
`nu`	The hyperparameter in the prior distribution of σ^2.
`lambda`	The hyperparameter in the prior distribution of σ^2.
`num.of.inner.iter`	The number of iterations before sampling σ^2.
`num.of.iteration`	The number of iterations to be runned for sparse group variable selection.
`MCSE.Sigma2.Given`	Prespecified value which is used to stop simulating samples when the MCSE of estimate of σ^2 less then given values.

Value

A list is returned with posterior samples of regression coefficients, β, variance σ^2, binary variables, γ, the number of iterations performed, and the time in second required for the run.

Examples