ddirimix.grid1D: Univariate projection or marginalization of a Dirichlet mixture density on on `[0,1]`

Description

Plots a univariate Dirichlet mixture (in other words, a Beta mixture) angular density for extreme bi-variate data.

Usage

ddirimix.grid1D(
  par = get("dm.expar.D2k4"),
  wei = par$wei,
  Mu = par$Mu,
  lnu = par$lnu,
  npoints = 30,
  eps = 10^(-3),
  coord = c(1, 2),
  marginal = TRUE,
  invisible = TRUE,
  displ = TRUE,
  add = FALSE,
  ...
)

Value

The discretized density on [eps, 1-eps] (included in [0,1])

Arguments

par: The parameter list for the Dirichlet mixture model.
wei: Optional. If present, overrides the value of par$wei.
Mu: Optional. If present, overrides the value of par$Mu.
lnu: Optional. If present, overrides the value of par$lnu.
npoints: number of points on the 1D discretization grid.
eps: the minimum value ( = 1- the maximum value) of the grid points.
coord: A vector of size 2: the indices of the coordinates upon which the marginalization or projection is to be done if the dimension of the sample space is greater than two.
marginal: logical. If TRUE, the angular density corresponds to the marginal intensity measure of the extreme Poisson process, over coordinates coord. Otherwise, it is only the projection of the full dimensional angular measure (hence the moments constraints is not satisfied anymore).
invisible: Logical: should the result be returned as invisible ?
displ: Logical: should a plot be issued ?
add: Logical: should the density be added to the currently active plot ?
...: Additional arguments to be passed to plot