SOME DOUBLY STOCHASTIC TIME SERIES MODELS

Dag Tjøstheim

Journal of Time Series Analysis, 1986, vol. 7, issue 1, 51-72

Abstract: Abstract. We consider time series models obtained by replacing the parameters of autoregressive models by stochastic processes. Special attention is given to the problem of finding conditions for stationarity and to the problem of forecasting. For the first problem we are only able to obtain solutions in special cases, and the emphasis is on techniques rather than obtaining the most general results in each case. For the second problem more complete results are obtained by exploiting similarities with discrete time (nonlinear) filtering theory. The methods introduced are illustrated on two standard examples, one of state space type and one where the parameter process is a Markov chain.

Date: 1986
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https://doi.org/10.1111/j.1467-9892.1986.tb00485.x

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