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

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

Description

Generate the MPE of (mu,Sigma) in following GaussianNIW structure:

mu,Sigma|m,k,v,S \sim NIW(m,k,v,S)

x|mu,Sigma \sim Gaussian(mu,Sigma)

Where NIW() is the Normal-Inverse-Wishart distribution, Gaussian() is the Gaussian distribution. See ?dNIW and dGaussian for the definitions of these distribution.
The model structure and prior parameters are stored in a "GaussianNIW" object.
The MPE estimates are:

• (mu_MPE,Sigma_MPE) = E(mu,Sigma|m,k,v,S,x)

Usage

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

Arguments

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

Value

A named list, the MPE estimate of mu and Sigma.

References

Murphy, Kevin P. "Conjugate Bayesian analysis of the Gaussian distribution." def 1.22 (2007): 16.

Gelman, Andrew, et al. "Bayesian Data Analysis Chapman & Hall." CRC Texts in Statistical Science (2004).

See Also

GaussianNIW

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