Stationary discrete autoregressive-moving average time series generated by mixtures

Abstract

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)