Learn R Programming

mclust (version 5.4.7)

dmvnorm: Density of multivariate Gaussian distribution

Description

Efficiently computes the density of observations for a generic multivariate Gaussian distribution.

Usage

dmvnorm(data, mean, sigma, log = FALSE)

Arguments

data

A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables.

mean

A vector of means for each variable.

sigma

A positive definite covariance matrix.

log

A logical value indicating whether or not the logarithm of the densities should be returned.

Value

A numeric vector whose ith element gives the density of the ith observation in data for the multivariate Gaussian distribution with parameters mean and sigma.

See Also

dnorm, dens

Examples

Run this code
# NOT RUN {
# univariate
ngrid <- 101
x <- seq(-5, 5, length = ngrid)
dens <- dmvnorm(x, mean = 1, sigma = 5)
plot(x, dens, type = "l")

# bivariate
ngrid <- 101
x1 <- x2 <- seq(-5, 5, length = ngrid)
mu <- c(1,0)
sigma <- matrix(c(1,0.5,0.5,2), 2, 2)
dens <- dmvnorm(as.matrix(expand.grid(x1, x2)), mu, sigma)
dens <- matrix(dens, ngrid, ngrid)
image(x1, x2, dens)
contour(x1, x2, dens, add = TRUE)
# }

Run the code above in your browser using DataLab