fit_BBS_model: Fit BBS-style hierarchical model for estimating trends in...

In pointblue/palo: Palo Program Data Analysis

Description

Fit BBS-style hierarchical model for estimating trends in point count survey data

Usage

fit_BBS_model(inputdata, n.adapt = 1000, n.burnin = 5000,
  n.sample = 10000, n.chains = 3, overdispersion = TRUE, ...)

Arguments

inputdata	Inputdata created by running setup_BBS_model
n.adapt	Number of iterations for adaptation, defaults to 1000
n.burnin	Number of iterations for burn-in, defaults to 5000
n.sample	Number of iterations for sampling, defauts to 10000
n.chains	Number of MCMC chains, defaults to 3
overdispersion	Defaults to TRUE, to include a term in the model for fitting overdispersion, as in BBS models
...	Additional arguments passed to jags.model, e.g. initial values.

Value

Returns a coda.samples object from rjags. Also displays summary statistics from MCMCsummary and prints trace plots from MCMCplot.

pointblue/palo documentation built on Nov. 5, 2019, 12:58 a.m.