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gMCP (version 0.8-5)

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"))

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.

Value

  • Matrix of simulated values

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

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

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