rust: ratio-of-uniforms simulation with transformation

What does rust do?

The rust package implements the multivariate generalized ratio-of-uniforms method of simulating random variates from a d-dimensional continuous distribution. The user specifies (the log of) a positive target function f that is proportional to the density function of the distribution.

A simple example

we use the main function ru is used to simulate a sample of size 1000 from a two-dimensional standard normal distribution with strong positive correlation between the components. Of course, this particular example is purely illustrative: there are better ways to simulate from a multivariate normal distribution.

rho <- 0.9
covmat <- matrix(c(1, rho, rho, 1), 2, 2)
log_dmvnorm <- function(x, mean = rep(0, d), sigma = diag(d)) {
  x <- matrix(x, ncol = length(x))
  d <- ncol(x)
  - 0.5 * (x - mean) %*% solve(sigma) %*% t(x - mean)
}
x <- ru(logf = log_dmvnorm, sigma = covmat, d = 2, n = 1000, init = c(0, 0))

Installation

To get the current released version from CRAN:

install.packages("rust")

Vignette

See vignette("rust-vignette", package = "rust") for an overview of the package.