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Biometrika 1988 75(4):621-629; doi:10.1093/biomet/75.4.621
© 1988 by Biometrika Trust
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A regression model for time series of counts

SCOTT L. ZEGER

Department of Biostatistics, Johns Hopkins University Baltimore, Maryland 21205, U.S.A.

This paper discusses a model for regression analysis with a time series of counts. Correlation is assumed to arise from an unobservable process added to the linear predictor in a log linear model. An estimating equation approach used for parameter estimation leads to an iterative weighted and filtered least-squares algorithm. Asymptotic properties for the regression coefficients are presented. We illustrate the technique with an analysis of trends in U.S. polio incidence since 1970.

Key Words: Dependence • Estimating equation • Log linear • Parameter driven • Poisson • Quasilikelihood • Regression


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