nimbleSCR (version 0.2.1)

dDispersal_exp: Bivariate exponential dispersal distribution for activity centers

Description

This function is deprecated, and it will be removed from a future release.

Usage

dDispersal_exp(x, s, rate, log)
rDispersal_exp(n, s, rate)

Value

The log-probability value associated with the bivariate activity center location x, given the current activity center s, and the rate parameter of the exponential dispersal distance distribution.

Arguments

x

Bivariate activity center coordinates (at time t+1).

s

Current location of the bivariate activity center (at time t).

rate

Rate parameter of the exponential distribution for dispersal distance.

log

Logical argument, specifying whether to return the log-probability of the distribution.

n

Integer specifying the number of realisations to generate. Only n = 1 is supported.

Author

Daniel Turek

Details

The dDispersal_exp distribution is a bivariate distribution which can be used to model the latent bivariate activity centers (ACs) of individuals in a population. This distribution models the situation when individual AC dispersal is uniform in direction (that is, dispersal occurs in a direction theta, where theta is uniformly distributed on [-pi, pi]), and with an exponential distribution for the radial dispersal distance.

The dDispersal_exp distribution models the location of an AC at time (t+1), conditional on the previous AC location at time (t) and the rate parameter (rate) of the exponential distribution for dispersal distance.

Examples

if (FALSE) {

## define model code
code <- nimbleCode({
    lambda ~ dgamma(0.001, 0.001)
    for(i in 1:N) {
        AC[i, 1, 1] ~ dunif(0, 100)
        AC[i, 2, 1] ~ dunif(0, 100)
        for(t in 2:T) {
            AC[i, 1:2, t+1] ~ dDispersal_exp(s = AC[i, 1:2, t], rate = lambda)
        }
    }
})

constants <- list(N = 10, T = 6)

## create NIMBLE model object
Rmodel <- nimbleModel(code, constants)

## use model object for MCMC, etc.

}