approx.propagate {FVDDPpkg}

Approximate the propagation of a Fleming-Viot latent signal

Description

Approximate the propagation of a Fleming-Viot latent signal

Usage

approx.propagate(fvddp, delta.t, N)

Arguments

fvddp

An instance of class generated via initialize(). In order to perform the propagation, the FVDDP has to be fed some data using update(), at least once.

delta.t

The time of the propagation.

N

The amount of samples to be drawn in order to perform the approximation.

Value

A object of class fvddp. Since this function is a Monte-Carlo based approximation of propagate(), the outputs are similar.

References

Ascolani F, Lijoi A, Ruggiero M (2021). “Predictive inference with Fleming–Viot-driven dependent Dirichlet processes.” Bayesian Analysis, 16(2), 371 – 395. doi:10.1214/20-BA1206.

See Also

approx.propagate() for a (slower) exact computation.

Examples

#a first example
FVDDP = initialize(theta = 1, sampling.f = function(x) rpois(x, 3),
                   density.f = function(x) dpois(x, 3), atomic = TRUE)
FVDDP = update(FVDDP, c(4,5))
approx.propagate(FVDDP, 0.2, 10000)

#another example; it does not matter wether P0 is atomic or not
FVDDP=initialize(theta = 3, function(x) rnorm(x, -1, 3),
                 function(x) dnorm(x, -1, 3), atomic = FALSE)
FVDDP = update(FVDDP, c(-1.145, 0.553, 0.553, 0.553))
approx.propagate(FVDDP, 0.6, 10000)