Occ.OD: Analyzes Occupancy data using the Occupancy/Detection model

In dereksonderegger/OccupancyModels: Functions for analyzing occupancy models using Bayesian methods.

Description

Uses Mackenzie's Occupancy/Detection model.

Usage

Occ.OD(Y, Covariate.data = NULL, Occupancy.formula = ~1,
  Detection.formula = ~1, n.chains = 4, n.adapt = 1000, n.iter = 1000,
  num.cores = 1, fit = NULL, inits = NULL)

Arguments

Y	A data frame with 5 columns - Species, Site, Observer, Effort, NumDetections
Covariate.data	Data frame with the same number of rows as Y
Occupancy.formula	Model formula specifying the relationship between Occupancy and the covariates
Detection.formula	Model formula specifying the relationship between Detection probability and the covariates
n.chains	How many MCMC chains to fit.
n.adapt	How long should the burn-in phase be.
n.iter	How many samples to take after the burn-in.
num.cores	How many computer cores to use.
inits	Initial values for the model chains.
N.limit	Maximum conceivable number of individuals at a site. Making this too large slows down the model fitting, though.

dereksonderegger/OccupancyModels documentation built on May 15, 2019, 3:58 a.m.