rmCauchy: Multivariate Cauchy Random Deviates

In heavy: Robust Estimation Using Heavy-Tailed Distributions

Description

Random number generation from the multivariate Cauchy distribution.

Usage

rmCauchy(n = 1, center = rep(0, nrow(Scatter)), Scatter = diag(length(center)))

Arguments

n	the number of samples requested
center	a vector giving the positions of each variable
Scatter	a positive-definite dispersion matrix

Details

The function rmCauchy is an interface to C routines, which make calls to subroutines from LAPACK. The matrix decomposition is internally done using the Cholesky decomposition. If Scatter is not non-negative definite then there will be a warning message.

Value

If n = 1 a vector of the same length as center, otherwise a matrix of n rows of random vectors.

References

Devroye, L. (1986). Non-Uniform Random Variate Generation. Springer-Verlag, New York.

See Also

rcauchy

Examples

# dispersion parameters
Scatter <- matrix(c(10,3,3,2), ncol = 2)
Scatter

# generate the sample
y <- rmCauchy(n = 1000, Scatter = Scatter)

# scatterplot of a random bivariate Cauchy sample with center
# vector zero and scale matrix 'Scatter'
par(pty = "s")
plot(y, xlab = "", ylab = "")
title("bivariate Cauchy sample", font.main = 1)

heavy documentation built on Oct. 30, 2019, 9:48 a.m.