dPosterior.GaussianNIW: Density function of the posterior distribution of a...

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

Description

Generate the the density value of the posterior distribution of the following 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.
Posterior density is the density function of NIW(mu,Sigma|m,k,v,S).

Usage

## S3 method for class 'GaussianNIW'
dPosterior(obj, mu, Sigma, LOG = TRUE, ...)

Arguments

obj	A "GaussianNIW" object.
mu	vector.
Sigma	matrix, nrow(Sigma) = length(mu).
LOG	Return the log density if set to "TRUE".
...	Additional arguments to be passed to other inherited types.

Value

numeric, the posterior density of (mu,Sigma).

See Also

GaussianNIW, rPosterior.GaussianNIW

Examples

obj <- GaussianNIW(gamma=list(m=c(0,0),k=1,v=2,S=diag(2)))
mu <- rnorm(2)
Sigma <- rInvWishart(df = 3,scale = diag(2))
dPosterior(obj = obj,mu=mu,Sigma = Sigma)

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