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The Problem of Aliasing in Identifying Finite Parameter Continuous Time Stochastic Models
Authors:J. Roderick McCrorie
Affiliation:(1) Department of Economics, Queen Mary, University of London, Mile End Road, London, E1 4NS, U.K.
Abstract:This note exposits the problem of aliasing in identifying finite parameter continuous time stochastic models, including econometric models, on the basis of discrete data. The identification problem for continuous time vector autoregressive models is characterised as an inverse problem involving a certain block triangular matrix, facilitating the derivation of an improved sufficient condition for the restrictions the parameters must satisfy in order that they be identified on the basis of equispaced discrete data. Sufficient conditions already exist in the literature but these conditions are not sharp and rule out plausible time series behaviour.
Keywords:continuous time stochastic process  vector autoregressive model  aliasing  identification problem  likelihood function  time series analysis
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