multiocc (version 0.2.3)

GibbsSampler: This function runs the MCMC.

Description

This function runs the MCMC.

Usage

GibbsSampler(
  M.iter,
  M.burn = NULL,
  M.thin = NULL,
  model.input,
  q = NULL,
  sv = FALSE,
  every = 1000,
  WAIC = FALSE,
  param2keep = c("alpha", "beta", "gamma", "rho", "sigma", "psi")
)

Value

A list with all standard MCMC output

Arguments

M.iter

The total number of iterations in MCMC

M.burn

The length of the burn in

M.thin

The number to thin the chain. Thinning by 10 only stores every 10th run.

model.input

A list of output created by running the create.data.R function

q

Desired number of Moran's I basis functions in the restricted spatial regression model

sv

A TRUE/FALSE on whether or not the MCMC output should be saved as 'MCMC.Rdata' and overwritten every 1000 iterations. Defaults to false.

every

A number to determine how frequently MCMC output is saved along the chain. Defaults to 1000.

WAIC

A TRUE/FALSE on whether or not the MCMC should compute and save WAIC. Defaults to false.

param2keep

A character vector that governs which outputs are saved. Permissible entries are "alpha", "beta", "gamma", "rho", "sigma", "psi", "z", "p", and "loglik"

Examples

head(detection)
head(occupancy)
head(coords)
DataNames = list("species"=colnames(detection)[4:9],
"detection"=c("duration"),"occupancy"=c("forest","elev"))
model.input = multioccbuild(detection, occupancy, coords, DataNames, threshold = 15000)
out = GibbsSampler(M.iter=3, M.burn=1, M.thin=1, model.input, q=10, sv=FALSE)