pr_MLiG {mcmcsae}

Create an object representing a Multivariate Log inverse Gamma (MLiG) prior distribution

Description

Create an object representing a Multivariate Log inverse Gamma (MLiG) prior distribution

Usage

pr_MLiG(mean = 0, precision = 0, labels = NULL, a = 1000)

Arguments

mean

scalar or vector parameter for the mean in the large a limit, when the distribution approaches a normal distribution.

precision

scalar or vector parameter for the precision in the large a limit, when the distribution approaches a normal distribution.

labels

optional character vector with coefficient labels. If specified, it should have the same length as at least one of mean and precision, and in that case the MLiG prior with these parameters is assigned to these coefficients, while any coefficients not present in labels will be assigned a non-informative prior with mean 0 and precision 0.

a

scalar parameter that controls how close the prior is to independent normal priors with mean and precision parameters. The larger this value (default is 1000), the closer.

Value

An environment representing the specified prior, for internal use.

References

J.R. Bradley, S.H. Holan and C.K. Wikle (2018). Computationally efficient multivariate spatio-temporal models for high-dimensional count-valued data (with discussion). Bayesian Analysis 13(1), 253-310.