rmvt: Generate data with the multivariate t distribution

Description

Function generates data from the multivariate t distribution given a covariance matrix, non-centrality parameter (or mode), and degrees of freedom.

Usage

rmvt(n, sigma, df, delta = rep(0, nrow(sigma)), Kshirsagar = FALSE)

Arguments

number of observations to generate

sigma

positive definite covariance matrix

degrees of freedom. df = 0 and df = Inf corresponds to the multivariate normal distribution

delta

the vector of non-centrality parameters of length n which specifies the either the modes (default) or non-centrality parameters

Kshirsagar

logical; triggers whether to generate data with non-centrality parameters or to adjust the simulated data to the mode of the distribution. The default uses the mode

Value

a numeric matrix with columns equal to ncol(sigma)

References

Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280. 10.20982/tqmp.16.4.p248

Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte Carlo simulation. Journal of Statistics Education, 24(3), 136-156. 10.1080/10691898.2016.1246953

Examples

Run this code

# NOT RUN {
# random t values given variances [3,6], covariance 2, and df = 15
sigma <- matrix(c(3,2,2,6), 2, 2)
x <- rmvt(1000, sigma = sigma, df = 15)
head(x)
summary(x)
plot(x[,1], x[,2])


# }