# ddirimix.grid1D: Univariate projection or marginalization of a Dirichlet... In lbelzile/BMAmevt: Multivariate Extremes: Bayesian Estimation of the Spectral Measure

## Description

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

## Usage

 ```1 2 3 4 5``` ``` 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, ...) ```

## Arguments

 `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). `npoints` number of points on the 1D discretization grid. `eps` the minimum value ( = 1- the maximum value) of the grid points. `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` `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`.

## Value

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

lbelzile/BMAmevt documentation built on May 17, 2018, 12:16 p.m.