On uniform asymptotic normality of sequential least squares estimators for the parameters in a stable AR(p)

L. Galtchouk, V. Konev

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    5 Citations (Scopus)


    For a stable autoregressive process of order p with unknown vector parameter θ, it is shown that under a sequential sampling scheme with the stopping time defined by the trace of the observed Fisher information matrix, the least-squares estimator of θ is asymptotically normally distributed uniformly in θ belonging to any compact set in the parameter region.

    Original languageEnglish
    Pages (from-to)119-142
    Number of pages24
    JournalJournal of Multivariate Analysis
    Issue number2
    Publication statusPublished - 1 Nov 2004



    • Autoregressive process
    • Least-squares estimator
    • Sequential estimation
    • Uniform asymptotic normality

    ASJC Scopus subject areas

    • Statistics and Probability
    • Numerical Analysis
    • Statistics, Probability and Uncertainty

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