MPE.GaussianNIG: Mean Posterior Estimate (MPE) of a "GaussianNIG" object

In bbricks: Bayesian Methods and Graphical Model Structures for Statistical Modeling

Description

Generate the MPE estimate of (beta,sigma^2) in following Gaussian-NIG structure:

x \sim Gaussian(X beta,sigma^2)

sigma^2 \sim InvGamma(a,b)

beta \sim Gaussian(m,sigma^2 V)

Where X is a row vector, or a design matrix where each row is an obervation. InvGamma() is the Inverse-Gamma distribution, Gaussian() is the Gaussian distribution. See ?dInvGamma and dGaussian for the definitions of these distribution.
The model structure and prior parameters are stored in a "GaussianNIG" object.
The MPEs are E(beta,sigma^2|m,V,a,b,X,x)

Usage

## S3 method for class 'GaussianNIG'
MPE(obj, ...)

Arguments

obj	A "GaussianNIG" object.
...	Additional arguments to be passed to other inherited types.

Value

A named list, the MPE estimate of beta and sigma^2.

References

Banerjee, Sudipto. "Bayesian Linear Model: Gory Details." Downloaded from http://www. biostat. umn. edu/~ph7440 (2008).

See Also

GaussianNIG

bbricks documentation built on July 8, 2020, 7:29 p.m.