probs.icar: OLM and ICAR model probabilities for areal data
In ref.ICAR: Objective Bayes Intrinsic Conditional Autoregressive Model for Areal Data

probs.icar

R Documentation

OLM and ICAR model probabilities for areal data

Performs simultaneous selection of covariates and spatial model structure for areal data.

probs.icar(
  Y,
  X,
  H,
  H.spectral = NULL,
  Sig_phi = NULL,
  b = 0.05,
  verbose = FALSE
)

`Y`	A vector of responses.
`X`	A matrix of covariates, which should include a column of 1's for models with a non-zero intercept
`H`	Neighborhood matrix for spatial subregions.
`H.spectral`	Spectral decomposition of neighborhood matrix, if user wants to pre-compute it to save time.
`Sig_phi`	Pseudo inverse of the neighborhood matrix, if user wants to pre-compute it to save time.
`b`	Training fraction for the fractional Bayes factor (FBF) approach.
`verbose`	If FALSE, marginal likelihood progress is not printed.

A list containing a data frame with all posterior model probabilities and other selection information.

`probs.mat`	Data frame containing posterior model probabilities for all candidate OLMs and ICAR models from the data.
`mod.prior`	Vector of model priors used to obtain the posterior model probabilities.
`logmargin.all`	Vector of all (log) fractional integrated likelihoods.
`base.model`	Maximum (log) fractional integrated likelihood among all candidate models. All fractional Bayes factors are obtained with respect to this model.
`BF.vec`	Vector of fractional Bayes factors for all candidate models.