dHabitatMask | R Documentation |
The dHabitatMask distribution checks and ensures that the proposed activity center location (s) falls within the suitable habitat (defined in the binary matrix habitatMask).
dHabitatMask(x, s, xmax, xmin, ymax, ymin, habitatMask, log = 0) rHabitatMask(n, s, xmax, xmin, ymax, ymin, habitatMask)
x |
Ones trick data. |
s |
Bivariate activity center coordinates. |
xmax |
Maximum of trap location x-coordinates. |
xmin |
Minimum of trap location x-coordinates. |
ymax |
Maximum of trap location y-coordinates. |
ymin |
Minimum of trap location y-coordinates. |
habitatMask |
A binary matrix object indicating which cells are considered as suitable habitat. |
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. |
The rHabitatMask function returns the value of the habitat mask cell (0 or 1) where the proposed activity center falls. See also M. Meredith: SECR in BUGS/JAGS with patchy habitat.
The log-likelihood value associated with the bivariate activity center location s being in the suitable habitat (i.e. 0 if it falls within the habitat mask and -Inf otherwise).
Daniel Turek
## define model code code <- nimbleCode({ for(i in 1:N) { s[i, 1] ~ dunif(0, 100) s[i, 2] ~ dunif(0, 100) OK[i] ~ dHabitatMask( s = s[i,1:2], xmax = 100, xmin = 0, ymax = 100, ymin = 0, habitatMask = habitatMask[1:100,1:100]) } }) N <- 20 habitatMask <- matrix(rbinom(10000,1,0.75), nrow = 100) constants <- list(N = N, habitatMask = habitatMask) data <- list(OK = rep(1, N)) inits <- list(s = array(runif(2*N, 0, 100), c(N,2))) ## create NIMBLE model object Rmodel <- nimbleModel(code, constants, data, inits) ## use model object for MCMC, etc.
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