Maximum Likelihood Estimation of Regression Parameters With Spatially Dependent Discrete Data.

The article presents a model which yields maximum likelihood (ML) estimates of regression parameters when the response is discrete and spatially dependent. This proposed model employs a spatial Gaussian copula, bringing the discrete distribution into the Gaussian geostatistical framework, where correlation completely describes dependence. It is used to estimate the relationship between Japanese beetle grub counts and soil organic matter.