rsespc: Simulation of random values from the SESPC distribution

In Directional: A Collection of Functions for Directional Data Analysis

Simulation of random values from the SESPC distribution

Description

Simulation of random values from the SESPC distribution

Usage

rsespc(n, mu, theta)

Arguments

n	A number; how many vectors you want to generate.
mu	The mean vector the SESPC distribution, a vector in R^3.
theta	The two \theta parameters of the SESPC distribution.

Details

A random sample from the SESPC distribution is generated. In case the \theta_s are zero, the sample is drawn from the SIPC (spherical independent projected Cauchy) distribution.

Value

An n \times 3 matrix with the simulated unit vectors.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Tsagris M. and Alzeley O. (2025). Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling. Australian & New Zealand Journal of Statistics, 67(1): 77–103. https://arxiv.org/pdf/2302.02468.pdf

Mardia K. V. and Jupp P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.

See Also

sespc.mle, dsespc

Examples

m <- colMeans( as.matrix( iris[,1:3] ) )
y <- rsespc(1000, m, c(1, 0.5) )
sespc.mle(y)

Directional documentation built on Nov. 5, 2025, 7 p.m.