gMCP (version 0.8-17)

rqmvnorm: Random sample from the multivariate normal distribution

Description

Draw a quasi or pseudo random sample from the MVN distribution. For details on the implemented lattice rule for quasi-random numbers see Cools et al. (2006).

Usage

rqmvnorm(
  n,
  mean = rep(0, nrow(sigma)),
  sigma = diag(length(mean)),
  type = c("quasirandom", "pseudorandom")
)

Value

Matrix of simulated values

Arguments

n

Number of samples, when type = "quasirandom" is used this number is rounded up to the next power of 2 (e.g. 1000 to 1024=2^10) and at least 1024.

mean

Mean vector

sigma

Covariance matrix

type

What type of random numbers to use. quasirandom uses a randomized Lattice rule, and should be more efficient than pseudorandom that uses ordinary (pseudo) random numbers.

Author

We thank Dr. Frances Kuo for the permission to use the generating vectors (order 2 lattice rule) obtained from her website https://web.maths.unsw.edu.au/~fkuo/lattice/.

References

Cools, R., Kuo, F. Y., and Nuyens, D. (2006) Constructing embedded lattice rules for multivariate integration. SIAM Journal of Scientific Computing, 28, 2162-2188.

Examples

sims <- rqmvnorm(100, mean = 1:2, sigma = diag(2))
plot(sims)