IDENTIFICATION OF UNOBSERVED COMPONENTS MODELS

Luiz Hotta

Journal of Time Series Analysis, 1989, vol. 10, issue 3, 259-270

Abstract: Abstract. Unobserved components ARIMA models are common in time series applications. However, fitting models of this type leads to problems of model identification. In this paper we derive a methodology to check whether a proposed model is identifiable. We show that this kind of identification can be checked using the autocovariance generating function and/or the (pseudo‐)spectral generating function.

Date: 1989
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