Some ARMA models for dependent sequences of poisson counts

作者: Ed Mckenzie

DOI: 10.2307/1427362

关键词: Autoregressive–moving-average modelBinomial distributionApplied mathematicsTime reversibilityMarginal distributionMathematicsCompound Poisson processJoint probability distributionStatisticsPoisson distributionAutoregressive model

摘要: A family of models for discrete-time processes with Poisson marginal distributions is developed and investigated. They have the same correlation structure as the linear ARMA processes. The joint distribution of n consecutive observations in such a process is derived and its properties discussed. In particular, time-reversibility and asymptotic behaviour are considered in detail. A vector autoregressive process is constructed and the behaviour of its components, which are Poisson ARMA processes, is considered. In particular, the two-dimensional case is discussed in detail.

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