Repeated point-count abundance survey (synthetic)

A binomial N-mixture dataset (Royle 2004) of repeated counts at 100 sites over 3 visits, drawn from a known generative model. Latent abundance increases with shrub cover and decreases with elevation; per-visit detection increases with survey effort. Synthetic, not field data; the generative coefficients and the realised latent abundances are in truth.

Usage

foray_counts

Format

A list with components:

y

100 x 3 integer matrix of counts.

occ.covs

Data frame of site covariates: elevation, shrub (both standardised).

det.covs

Named list with one 100 x 3 visit covariate matrix, effort (standardised).

truth

List of generative quantities: beta_lambda, beta_p, the realised latent abundance N, and per-site lambda.

See also

abun(), tobs(), simulate_abun()

Examples

data(foray_counts)
summary(as.vector(foray_counts$y))
# \donttest{
fit <- tobs(~ elevation + shrub, data = foray_counts$occ.covs,
            family = abun(), detection = ~ effort,
            y = foray_counts$y, visits = foray_counts$det.covs)
coef(fit)
# }