Retrieve nimbleCode for spatial capture-recapture models

Creates model code using the nimbleCode function.

get_classic(
  dim_y,
  enc_dist = "binomial",
  sex_sigma = FALSE,
  hab_mask = FALSE,
  trapsClustered = FALSE
)

Arguments

dim_y

An integer of either 2 (the default) or that defines what dimensional format the encounter history data are in.

enc_dist

Either "binomial" or "poisson". Default is "binomial".

sex_sigma

A logical value indicating whether the scaling parameter ('sigma') is sex-specific

hab_mask

A logical value indicating whether a habitat mask will be used. Default is FALSE.

trapsClustered

A logical value indicating if traps are clustered in arrays across the sampling area.

Value

A nimbleCode object from the nimble package.

Details

This function provides templates that could be copied and easily modified to include further model complexity such as covariates explaining detection probability. The models include different encounter probability distributions, sex-specific scaling parameters, and habitat masking.

Author

Daniel Eacker

Examples

# get model for 2D encounter data, binomial encounter distribution, 
# non-sex-specific scaling parameter, and no habitat mask
scr_model = get_classic(dim_y = 2,enc_dist = "binomial",sex_sigma = FALSE,
                         hab_mask = FALSE,trapsClustered = FALSE)

# inspect model
scr_model
#> {
#>     p0 ~ dunif(0, 1)
#>     sigma ~ dunif(0, sigma_upper)
#>     psi ~ dunif(0, 1)
#>     for (i in 1:M) {
#>         z[i] ~ dbern(psi)
#>         s[i, 1] ~ dunif(x_lower, x_upper)
#>         s[i, 2] ~ dunif(y_lower, y_upper)
#>         dist[i, 1:J] <- sqrt((s[i, 1] - X[1:J, 1])^2 + (s[i, 
#>             2] - X[1:J, 2])^2)
#>         p[i, 1:J] <- p0 * exp(-dist[i, 1:J]^2/(2 * sigma^2))
#>     }
#>     for (i in 1:n0) {
#>         for (j in 1:J) {
#>             y[i, j] ~ dbin(p[i, j], K)
#>         }
#>     }
#>     for (i in (n0 + 1):M) {
#>         zeros[i] ~ dbern((1 - prod(1 - p[i, 1:J])^K) * z[i])
#>     }
#>     N <- sum(z[1:M])
#>     D <- N/A
#> }