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Stationary discrete autoregressive-moving average time series generated by mixtures

机译:混合物产生的平稳离散自回归运动平均时间序列

摘要

Two simple stationary processes of discrete random variables with arbitrarily chosen first-order marginal distributions, DARMA(p,N+1) and NDARMA(p,N), are given. The correlation structure of these processes mimics that of the usual linear ARMA(p,q) processes. The relationship of these processes to mover-stayer models, and to models for discrete time series given separately by Lindqvist and Pegram is discussed. Ad-hoc nonparametric estimators for the parameters in the DARMA(p,N+1) and NDARMA(p,N) are given. A simulation study shows them to be as good as maximum likelihood estimators for the first-order autoregressive case, and to be much simpler to compute than the maximum likelihood estimators. (Author)
机译:给出了具有任意选择的一阶边际分布的离散随机变量的两个简单平稳过程,即DARMA(p,N + 1)和NDARMA(p,N)。这些进程的相关结构模仿了通常的线性ARMA(p,q)进程。讨论了这些过程与动子模型以及Lindqvist和Pegram分别给出的离散时间序列模型之间的关系。给出了DARMA(p,N + 1)和NDARMA(p,N)中参数的临时非参数估计量。仿真研究表明,它们与一阶自回归案例的最大似然估计值一样好,并且比最大似然估计值更容易计算。 (作者)

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