Zeger, Scott L. A regression model for time series of counts. (English) Zbl 0653.62064 Biometrika 75, No. 4, 621-629 (1988). Summary: 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. Cited in 10 ReviewsCited in 133 Documents MSC: 62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH) 62M09 Non-Markovian processes: estimation 62F10 Point estimation Keywords:dependence; quasilikelihood; iterative weighted least-squares algorithm; Poisson model; parameter-driven models; time series of counts; linear predictor; log linear model; estimating equation approach; filtered least-squares algorithm; Asymptotic properties; regression coefficients PDFBibTeX XMLCite \textit{S. L. Zeger}, Biometrika 75, No. 4, 621--629 (1988; Zbl 0653.62064) Full Text: DOI