Maximum Likelihood Estimation of ARMA Model with Error Processes for Replicated Observations

Wing-Keung Wong (), Robert B. Miller and Keshab Shrestha
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Robert B. Miller: University of Wisconsin-Madison
Keshab Shrestha: Concordia University

Departmental Working Papers from National University of Singapore, Department of Economics

Abstract: In this paper we analyse the repeated time series model where the fundamental component follows a ARMA process. In the model, the error variance as well as the number of repetition are allowed to change over time. It is shown that the model is identified. The maximum likelihood estimator is derived using the Kalman filter technique. The model considered in this paper can be considered as extension of the models considered by Anderson (1978), Azzalini (1981) and Wong and Miller (1990)

Keywords: ARMA model; Kalman filter; maximum likelihood estimation (search for similar items in EconPapers)
JEL-codes: C10 C13 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
Date: 2002
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Persistent link: http://EconPapers.repec.org/RePEc:nus:nusewp:wp0217

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