rinvWishart: Generate data with the inverse Wishart distribution

In SimDesign: Structure for Organizing Monte Carlo Simulation Designs

Generate data with the inverse Wishart distribution

Description

Function generates data in the form of symmetric matrices from the inverse Wishart distribution given a covariance matrix and degrees of freedom.

Usage

rinvWishart(n = 1, df, sigma)

Arguments

n	number of matrix observations to generate. By default n = 1, which returns a single symmetric matrix. If n > 1 then a list of n symmetric matrices are returned instead
df	degrees of freedom
sigma	positive definite covariance matrix

Value

a numeric matrix with columns equal to ncol(sigma) when n = 1, or a list of n matrices with the same properties

Author(s)

Phil Chalmers [e-mail]

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. \Sexpr[results=rd]{tools:::Rd_expr_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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10691898.2016.1246953")}

See Also

runSimulation

Examples

# random inverse Wishart matrix given variances [3,6], covariance 2, and df=15
sigma <- matrix(c(3,2,2,6), 2, 2)
x <- rinvWishart(sigma = sigma, df = 15)
x

# list of matrices
x <- rinvWishart(20, sigma = sigma, df = 15)
x

SimDesign documentation built on Sept. 11, 2024, 8 p.m.