\name{Density of a mixture of elliptically symmetric distributions}
\alias{dmixsespc}
\alias{dmixesag}
\title{
Density of a mixture of elliptically symmetric distributions
}

\description{
Density of a mixture of elliptically symmetric distributions.
}

\usage{
dmixsespc(y, probs, mu, theta, logden = FALSE)
dmixesag(y, probs, mu, gam, logden = FALSE)
}

\arguments{
\item{y}{
A matrix with unit vectors.
}
\item{probs}{
This is avector with the mixing probability of each group.
}
\item{mu}{
A matrix with the mean direction of each group.
}
\item{theta}{
A matrix with the \eqn{\theta} parameters of the SESPC distribution of each group.
}
\item{gam}{
A matrix with the \eqn{\gamma} parameters of the ESAG distribution of each group.
}
\item{logden}{
If you the logarithm of the density values set this to TRUE.
}
}

\details{
The function computes the density for a given mixture of SESPC or ESAG distributions.
}

\value{
A vector with the (log) density values of y.
}

\references{
Perdikis T., Alharbi N. and Tsagris M. (2026). Model--based clustering for spherical
and hyper--spherical data using elliptically symmetric distributions.

https://arxiv.org/abs/2605.27496
}

\author{
Michail Tsagris.

R implementation and documentation: Michail Tsagris \email{mtsagris@uoc.gr}.
}
%\note{
%%  ~~further notes~~
%}

\seealso{
\code{\link{mixsespc.mle}, \link{rmixsespc}
}
}

\examples{
probs <- c(0.5, 0.5)
mu <- matrix(rnorm(6, 10, 5), ncol = 3)
theta <- matrix(c(-2, 1, -2, 1), ncol = 2)
x <- rmixsespc(200, probs, mu, theta)$x
b <- dmixsespc(x, probs, mu, theta)
}
