SpatGC (version 0.1.0)

GClat: Fit ICAR Spatial Gamma-Count Model

Description

This function fits an ICAR spatial Gamma-Count (GC) model to a given dataset using the INLA package. It constructs the formula based on the provided covariate data and ID variables, and fits the model using the specified adjacency matrix (`W`) or a shapefile of the study region.

Usage

GClat(Y, ID, W = NULL, shapefile = NULL, covariate = NULL)

Value

An object of class "inla" representing the fitted ICAR spatial GC model. The object contains model estimates, diagnostics, and other results.

Arguments

Y

Vector of response variables (counts).

ID

Vector of indexes of regions (spatial units).

W

Optional adjacency matrix representing spatial connections between regions. If not provided, it can be generated from a shapefile using the `shapefile` argument.

shapefile

Optional shapefile representing the study region. If provided, the adjacency matrix (`W`) will be calculated from the shapefile.

covariate

Optional matrix of covariates. If not provided, the function assumes the model is intercept-only.

Examples

# \donttest{
  # Generate data from the GC spatial regression model with lattice spatial dependency
  W <- rAdj(500) # Generate a random adjacency matrix
  DDl <- rGClat(n = 500, alpha = 1, beta0 = 0.3, beta = c(-0.5, 0.5), W = W, V = 1)

  # Prepare the data
  Y <- DDl$y
  covariate <- DDl$covariate
  ID <- DDl$ID

  # Fit the spatial GC model
  ResultGC <- GClat(Y = Y, ID = ID, covariate = covariate, W = W)

  # Summary of the model fit
  summary(ResultGC)
# }