R: Density of multivariate Gaussian distribution

dmvnorm {mclust} | R Documentation

## 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

    # 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)

[Package mclust version 5.4.8 Index]