stan_occu {ubms}

Fit the MacKenzie et al. (2002) Occupancy Model

Description

This function fits the single season occupancy model of MacKenzie et al. (2002).

Usage

stan_occu(
  formula,
  data,
  prior_intercept_state = logistic(0, 1),
  prior_coef_state = logistic(0, 1),
  prior_intercept_det = logistic(0, 1),
  prior_coef_det = logistic(0, 1),
  prior_sigma = gamma(1, 1),
  log_lik = TRUE,
  ...
)

Arguments

formula

Double right-hand side formula describing covariates of detection and occupancy in that order

data

A unmarkedFrameOccu object

prior_intercept_state

Prior distribution for the intercept of the state (occupancy probability) model; see ?priors for options

prior_coef_state

Prior distribution for the regression coefficients of the state model

prior_intercept_det

Prior distribution for the intercept of the detection probability model

prior_coef_det

Prior distribution for the regression coefficients of the detection model

prior_sigma

Prior distribution on random effect standard deviations

log_lik

If TRUE, Stan will save pointwise log-likelihood values in the output. This can greatly increase the size of the model. If FALSE, the values are calculated post-hoc from the posteriors

...

Arguments passed to the stan call, such as number of chains chains or iterations iter

Value

ubmsFitOccu object describing the model fit.

References

MacKenzie DI, Nichols JD, Lachman GB, Droege S, Royle JA, Langtimm CA. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83: 2248-2255.

See Also

occu, unmarkedFrameOccu

Examples

data(frogs)
pferUMF <- unmarkedFrameOccu(pfer.bin)

#Add some covariates
siteCovs(pferUMF) <- data.frame(cov1=rnorm(numSites(pferUMF)))

#Fit model
(fm <- stan_occu(~1~cov1, pferUMF, chains=3, iter=300))