Simulation of random values from the ESAG distribution {Directional} | R Documentation |
Simulation of random values from the ESAG distribution
Description
Simulation of random values from the ESAG distribution.
Usage
resag(n, mu, gam)
rESAGd(n, mu, gam)
Arguments
n |
A number; how many vectors you want to generate. |
mu |
The mean vector the ESAG distribution. |
gam |
The |
Details
A random sample from the ESAG distribution is generated. In case the \gamma_s
are zero (or null for the rESAGd), the sample is drawn from the Independent Angular Gaussian (or projected normal). The resag() is designed for the sphere, whereas the rESAGd is designed for the sphere and hyper-sphere.
Value
An n \times d
matrix with the simulated unit vectors.
Author(s)
Michail Tsagris and Zehao Yu.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Zehao Yu zehaoy@email.sc.edu.
References
Zehao Yu and Xianzheng Huang (2024). A new parameterization for elliptically symmetric angular Gaussian distributions of arbitrary dimension. Electronic Journal of Statististics, 18(1): 301–334.
Paine P.J., Preston S.P., Tsagris M. and Wood A.T.A. (2018). An Elliptically Symmetric Angular Gaussian Distribution. Statistics and Computing, 28(3):689–697.
Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.
See Also
esag.mle, desag, spml.mle, acg.mle, circ.summary
Examples
m <- colMeans( as.matrix( iris[, 1:3] ) )
y <- resag(1000, m, c(1, 0.5) )
esag.mle(y)