GClat {SpatGC}

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)

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.

Value

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

Examples

  # 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)