Normal distribution methods for SWoodburyMatrix objects

Draw samples and compute density functions for the multivariate normal distribution with an SWoodburyMatrix object as its covariance matrix.

dwnorm(x, mean, covariance, log = FALSE)

rwnorm(n, mean, covariance)

Arguments

x

A numeric vector or matrix.

mean

Optional mean vector; defaults to zero mean.

covariance

WoodburyMatrix object.

log

Logical indicating whether to return log of density.

n

Number of samples to return. If n = 1, returns a vector, otherwise returns an n by nrow(W) matrix.

Functions

• dwnorm: Compute the density of the distribution

• rwnorm: Draw samples from the distribution

See also

WoodburyMatrix

Examples

library(Matrix)
# Trivial example with diagonal covariance matrices
W <- WoodburyMatrix(Diagonal(10), Diagonal(10))
x <- rwnorm(10, covariance = W)
print(dwnorm(x, covariance = W, log = TRUE))
#>  [1] -14.04641 -15.26103 -18.91791 -16.18885 -15.12880 -17.57357 -16.69482
#>  [8] -23.39031 -22.60567 -18.80693