stan_colext function

Fit the MacKenzie et al. (2003) Dynamic Occupancy Model

This function fits the dynamic occupancy model of MacKenzie et al. (2003).

stan_colext(
  psiformula = ~1,
  gammaformula = ~1,
  epsilonformula = ~1,
  pformula = ~1,
  data,
  prior_intercept_psi = logistic(0, 1),
  prior_coef_psi = logistic(0, 1),
  prior_intercept_gamma = logistic(0, 1),
  prior_coef_gamma = logistic(0, 1),
  prior_intercept_eps = logistic(0, 1),
  prior_coef_eps = logistic(0, 1),
  prior_intercept_det = logistic(0, 1),
  prior_coef_det = logistic(0, 1),
  prior_sigma = gamma(1, 1),
  log_lik = TRUE,
  ...
)

Arguments

• psiformula: Right-hand sided formula for the initial probability of occupancy at each site
• gammaformula: Right-hand sided formula for colonization probability
• epsilonformula: Right-hand sided formula for extinction probability
• pformula: Right-hand sided formula for detection probability
• data: A unmarkedMultFrame object
• prior_intercept_psi: Prior distribution for the intercept of the psi (initial occupancy probability) model; see ?priors for options
• prior_coef_psi: Prior distribution for the regression coefficients of the psi model
• prior_intercept_gamma: Prior distribution on intercept for colonization probability
• prior_coef_gamma: Prior distribution on regression coefficients for colonization probability
• prior_intercept_eps: Prior distribution on intercept for extinction probability
• prior_coef_eps: Prior distribution on regression coefficients for extinction probability
• 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

Returns

ubmsFitColext object describing the model fit.

Examples

data(frogs)
umf <- formatMult(masspcru)
umf@y[umf@y > 1] <- 1 #convert counts to presence/absence
umf <- umf[1:100,] #Use only 100 sites

fit_frog <- stan_colext(~1, ~1, ~1, ~1, umf, chains=3, iter=300)

References

MacKenzie DI, Nicholas JD, Hines JE, Knutson MG, Franklin AB. 2003. Ecology 84: 2200-2207.

See Also

colext, unmarkedMultFrame