posterior.predictive3D: Posterior predictive density on the simplex, for...

Description Usage Arguments Details Value Note Author(s) See Also

Description

Computes an approximation of the predictive density based on a posterior parameters sample. Only allowed in the three-dimensional case.

Usage

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posterior.predictive3D(post.sample, densityGrid, from = post.sample$Nbin
  + 1, to = post.sample$Nsim, thin = 40, npoints = 40,
  eps = 10^(-3), equi = T, displ = T, ...)

Arguments

post.sample

A posterior sample as returned by posteriorMCMC

densityGrid

A function returning a npoints*npoints matrix, representing a discretized version of the spectral density on the two dimensional simplex. The function should be compatible with dgridplot. In particular, it must use discretize to produce the discretization grid. It must be of type
function(par, npoints, eps, equi, displ,invisible, ... ). See Details below.

from

Integer or NULL. If NULL, the default value is used. Otherwise, should be greater than post.sample$Nbin. Indicates the index where the averaging process should start. Default to post.sample$Nbin +1

to

Integer or NULL. If NULL, the default value is used. Otherwise, must be lower than Nsim+1. Indicates where the averaging process should stop. Default to post.sample$Nsim.

thin

Thinning interval.

npoints

The number of grid nodes on the squared grid containing the desired triangle.

eps

Positive number: minimum distance from any node inside the simplex to the simplex boundary

equi

logical. Is the simplex represented as an equilateral triangle (if TRUE) or a right triangle (if FALSE) ?

displ

logical. Should a plot be produced ?

...

Additional graphical parameters and arguments to be passed to contour and image.

Details

The posterior predictive density is approximated by averaging the densities produced by the function densityGrid(par, npoints, eps, equi, displ,invisible, ...) for par in a subset of the parameters sample stored in post.sample. The arguments of densityGrid must be

Only a sub-sample is used: one out of thin parameters is used (thinning). Further, only the parameters produced between time from and time to (included) are kept.

Value

A npoints*npoints matrix: the posterior predictive density.

Note

The computational burden may be high: it is proportional to npoints^2. Therefore, the function assigned to densityGridplot should be optimized, typically by calling .C with an internal, user defined C function.

Author(s)

Anne Sabourin

See Also

dgridplot, posteriorMCMC.


lbelzile/BMAmevt documentation built on June 13, 2019, 12:43 p.m.