dPosterior: Get the density from the posterior distribution.

Description Usage Arguments Value See Also

View source: R/Bayesian_Bricks.r

Description

This is a generic function that will generate the the density value of the posterior distribution. i.e. for the model structure:

theta|gamma \sim H(gamma)

x|theta \sim F(theta)

get the probability density/mass from the distribution theta \sim H(gamma). For a given Bayesian bricks object obj and an observation of theta, dPosterior() will calculate the density value for different model structures:

class(obj)="LinearGaussianGaussian"

Where

x \sim Gaussian(A z + b, Sigma)

z \sim Gaussian(m,S)

dPosterior() will return p(theta|m,S) See ?dPosterior.LinearGaussianGaussian for details.

class(obj)="GaussianGaussian"

Where

x \sim Gaussian(mu,Sigma)

mu \sim Gaussian(m,S)

Sigma is known. dPosterior() will return p(mu|m,S) See ?dPosterior.GaussianGaussian for details.

class(obj)="GaussianInvWishart"

Where

x \sim Gaussian(mu,Sigma)

Sigma \sim InvWishart(v,S)

mu is known. dPosterior() will return p(Sigma|v,S) See ?dPosterior.GaussianInvWishart for details.

class(obj)="GaussianNIW"

Where

x \sim Gaussian(mu,Sigma)

Sigma \sim InvWishart(v,S)

mu \sim Gaussian(m,Sigma/k)

dPosterior() will return p(mu,Sigma|m,k,v,S) See ?dPosterior.GaussianNIW for details.

class(obj)="GaussianNIG"

Where

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

sigma^2 \sim InvGamma(a,b)

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

X is a row vector, or a design matrix where each row is an obervation. dPosterior() will return p(beta,sigma^2|m,V,a,b) See ?dPosterior.GaussianNIG for details.

class(obj)="CatDirichlet"

Where

x \sim Categorical(pi)

pi \sim Dirichlet(alpha)

dPosterior() will return p(pi|alpha) See ?dPosterior.CatDirichlet for details.

Usage

1

Arguments

obj

A "BayesianBrick" object used to select a method.

...

further arguments passed to or from other methods.

Value

numeric, the density value

See Also

dPosterior.LinearGaussianGaussian for Linear Gaussian and Gaussian conjugate structure, dPosterior.GaussianGaussian for Gaussian-Gaussian conjugate structure, dPosterior.GaussianInvWishart for Gaussian-Inverse-Wishart conjugate structure, dPosterior.GaussianNIW for Gaussian-NIW conjugate structure, dPosterior.GaussianNIG for Gaussian-NIG conjugate structure, dPosterior.CatDirichlet for Categorical-Dirichlet conjugate structure ...


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