\item{col}{The color to use for the plot. See \code{\link{plot3d.function}}.}
\item{tol}{tolerance (relative to largest variance) for numerical lack of positive-definiteness in Sigma, for the estimation of the density. see \code{\link{mvdggd}}.}
\item{tol}{tolerance (relative to largest variance) for numerical lack of positive-definiteness in Sigma, for the estimation of the density. see \code{\link{dmggd}}.}
\item{...}{Additional arguments to pass to \code{\link{plot3d.function}}.}
}
...
...
@@ -41,7 +41,7 @@ with mean vector \code{mu}, dispersion matrix \code{Sigma} and shape parameter \
mu <- c(1, 4)
Sigma <- matrix(c(0.8, 0.2, 0.2, 0.2), nrow = 2)
beta <- 0.74
plotmvggd(mu, Sigma, beta)
plotmggd(mu, Sigma, beta)
}
\references{
...
...
@@ -50,9 +50,9 @@ Commun. Statist. 1998, Theory Methods, col. 27, no. 23, p 589-600.
\doi{10.1080/03610929808832115}
}
\seealso{
\code{\link{contourmvggd}}: contour plot of a bivariate generalised Gaussian density.
\code{\link{contourmggd}}: contour plot of a bivariate generalised Gaussian density.
\code{\link{mvdggd}}: Probability density of a multivariate generalised Gaussian distribution.
\code{\link{dmggd}}: Probability density of a multivariate generalised Gaussian distribution.