Smoothing Serial Count Data Through a State-Space Model

Abstract

A method is proposed for smoothing serial Poisson count data through state-space modeling. Recursive formulas for evaluating the exact likelihood are given. The exact likelihood yields the likelihood ratio test for homogeneity of the Poisson means. The method is versatile enough to permit various extensions, including that for serial binomial data. The proposed method is applied to three sets of weekly disease incidence data.