rmvnorm: Generate data with the multivariate normal (i.e., Gaussian)...

Description Usage Arguments Value Author(s) References See Also Examples

Description

Function generates data from the multivariate normal distribution given some mean vector and/or covariance matrix.

Usage

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Arguments

n

number of observations to generate

mean

mean vector, default is rep(0, length = ncol(sigma))

sigma

positive definite covariance matrix, default is diag(length(mean))

Value

a numeric matrix with columns equal to length(mean)

Author(s)

Phil Chalmers rphilip.chalmers@gmail.com

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. doi: 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. doi: 10.1080/10691898.2016.1246953

See Also

runSimulation

Examples

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# random normal values with mean [5, 10] and variances [3,6], and covariance 2
sigma <- matrix(c(3,2,2,6), 2, 2)
mu <- c(5,10)
x <- rmvnorm(1000, mean = mu, sigma = sigma)
head(x)
summary(x)
plot(x[,1], x[,2])

SimDesign documentation built on Sept. 5, 2021, 5:23 p.m.