The problem of aliasing in identifying finite parameter continuous time stochastic models

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    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.

    Original languageEnglish
    Pages (from-to)9-16
    Number of pages8
    JournalActa Applicandae Mathematicae
    Volume79
    Issue number79
    Publication statusPublished - Oct 2003

    Keywords

    • continuous time stochastic process
    • vector autoregressive model
    • aliasing
    • identification problem
    • likelihood function
    • time series analysis
    • MULTIVARIABLE SYSTEMS
    • REPRESENTATION
    • MATRIX

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