Simulation of random values from the SESPC distribution {Directional} | R Documentation |
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 |
theta |
The two |
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 mtsagris@uoc.gr.
References
Tsagris M. and Alzeley O. (2024). Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling. Australian & New Zealand Journal of Statistics (accepted for publication). https://arxiv.org/pdf/2302.02468.pdf
Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.
See Also
Examples
m <- colMeans( as.matrix( iris[,1:3] ) )
y <- rsespc(1000, m, c(1, 0.5) )
sespc.mle(y)