dGaussian: Density function of Gaussian distribution

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

Description

Get the density of a set of samples from a (multivariate) Gaussian distribution. For a random vector x, the density function is defined as:

sqrt(2 pi^p |Sigma|)^{-1} exp(-1/2 (x-mu )^T Sigma^{-1} (x-mu))

where p is the dimension of x.

Usage

dGaussian(x, mu, Sigma = NULL, A = NULL, LOG = TRUE)

Arguments

x	matrix, when x is a numeric vector, it will be converted to a matrix with 1 column!
mu	numeric, mean vector.
Sigma	matrix, covariance matrix, one of Sigma and A should be non-NULL.
A	matrix, the Cholesky decomposition of Sigma, an upper triangular matrix, one of Sigma and A should be non-NULL.
LOG	logical, return log density of LOG=TRUE, default TRUE.

Value

A numeric vector.

See Also

rGaussian

Examples

plot(
   dGaussian(x=seq(-5,5,length.out = 1000),mu = 0,Sigma = 1,LOG = FALSE)
   ,type = "l"
)

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