Preprint #96-8
Modeling Poisson Variables with Positive Spatial
Dependence
by
Mark S. Kaiser and Noel Cressie
Abstract
The Poisson auto-model is a natural vehicle for modeling data that consist of
small counts and may exhibit dependence, frequently spatial dependence.
Unfortunately, it is not possible to model positive dependence with a regular
Poisson auto-model. We develop a model that allows positive dependencies in
multivariate count data by specifying conditional distributions as
Winsorized Poisson probability mass functions. This Winsorized Poisson
auto-model may be used to model a set of random variables that individually
exhibit Poisson-like behavior, while incorporating either positive or
negative dependencies among the variables.
Copies of preprints are available from the author upon request. Use
the preprint number (located at the top of the page) and
make the request directly to the author, Iowa State
University,
Department of Statistics, Snedecor Hall, Ames, IA 50011-1210.