plotmvggd: Plot of the Bivariate Generalised Gaussian Density

In mggd: Multivariate Generalised Gaussian Distribution; Kullback-Leibler Divergence

Plot of the Bivariate Generalised Gaussian Density

Description

Plots the probability density of the generalised Gaussian distribution with 2 variables with mean vector mu, dispersion matrix Sigma and shape parameter beta.

Usage

plotmvggd(mu, Sigma, beta, xlim = c(mu[1] + c(-10, 10)*Sigma[1, 1]),
                 ylim = c(mu[2] + c(-10, 10)*Sigma[2, 2]), n = 101,
                 xvals = NULL, yvals = NULL, xlab = "x", ylab = "y",
                 zlab = "f(x,y)", col = "gray", tol = 1e-6, ...)

Arguments

mu	length 2 numeric vector.
Sigma	symmetric, positive-definite square matrix of order 2. The dispersion matrix.
beta	positive real number. The shape of the first distribution.
xlim, ylim	x-and y- limits.
n	A one or two element vector giving the number of steps in the x and y grid, passed to plot3d.function.
xvals, yvals	The values at which to evaluate x and y. If used, xlim and/or ylim are ignored.
xlab, ylab, zlab	The axis labels.
col	The color to use for the plot. See plot3d.function.
tol	tolerance (relative to largest variance) for numerical lack of positive-definiteness in Sigma, for the estimation of the density. see mvdggd.
...	Additional arguments to pass to plot3d.function.

Value

Returns invisibly the probability density function.

Author(s)

Pierre Santagostini, Nizar Bouhlel

References

E. Gomez, M. Gomez-Villegas, H. Marin. A Multivariate Generalization of the Power Exponential Family of Distribution. Commun. Statist. 1998, Theory Methods, col. 27, no. 23, p 589-600. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/03610929808832115")}

See Also

contourmvggd: contour plot of a bivariate generalised Gaussian density.

mvdggd: Probability density of a multivariate generalised Gaussian distribution.

Examples

mu <- c(1, 4)
Sigma <- matrix(c(0.8, 0.2, 0.2, 0.2), nrow = 2)
beta <- 0.74
plotmvggd(mu, Sigma, beta)

mggd documentation built on March 31, 2023, 9:56 p.m.