plotmtd {mstudentd}

Plot of the Bivariate t Density

Description

Plots the probability density of the multivariate t distribution with 2 variables with location parameter mu and scatter matrix Sigma.

Usage

plotmtd(nu, mu, Sigma, 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

nu

numeric. The degrees of freedom.

mu

length 2 numeric vector. The mean vector.

Sigma

symmetric, positive-definite square matrix of order 2. The correlation matrix.

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 dmtd.

...

Additional arguments to pass to plot3d.function.

Value

Returns invisibly the probability density function.

Author(s)

Pierre Santagostini, Nizar Bouhlel

References

S. Kotz and Saralees Nadarajah (2004), Multivariate t Distributions and Their Applications, Cambridge University Press.

See Also

dmtd: probability density of a multivariate t density

contourmtd: contour plot of a bivariate t density.

plot3d.function: plot a function of two variables.

Examples

nu <- 1
mu <- c(1, 4)
Sigma <- matrix(c(0.8, 0.2, 0.2, 0.2), nrow = 2)
plotmtd(nu, mu, Sigma)