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GMCM (version 1.1.1)

dmvnormal: Multivariate Gaussian probability density function and simulation

Description

Fast simulation and evalutation of multivariate Gaussian probability densities.

Usage

dmvnormal(x, mu, sigma)

rmvnormal(n, mu, sigma)

Arguments

x
A p times k matrix of quantiles. Each rows correspond to a realization from the density and each column corresponds to a dimension.
mu
The mean vector of dimension k.
sigma
The variance-covariance matrix of dimension k times k.
n
The number of observations to be simulated.

Value

  • dmvnormal returns a 1 by p matrix of the probability densities corresponding to each row of x. sigma. Each row corresponds to an observation.

    rmvnormal returns a p by k matrix of observations from a multivariate normal distribution with the given mean mu and covariance

Details

dmvnormal functions similarly to dmvnorm from the mvtnorm-package and likewise for rmvnormal and rmvnorm.

See Also

dmvnorm and rmvnorm in the mvtnorm-package.

Examples

Run this code
dmvnormal(x = matrix(rnorm(300), 100, 3),
          mu = 1:3,
          sigma = diag(3))
rmvnormal(n = 10, mu = 1:4, sigma = diag(4))

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