On truncated sequential estimation of the drifting parametermean in the first order autoregressive models

V. V. Konev, S. M. Pergamenschicov

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    This paper considers the problem of sequential point estimation of the drifting parameter mean in the first order autoregression process. The truncated sequential procedure proposed here is based on the least squares estimator and is shown to ensure the preassigned mean square accuracy of the estimates. The uniform in parameter asymptotic normality of the sequential estimator is established.

    Original languageEnglish
    Pages (from-to)193-216
    Number of pages24
    JournalSequential Analysis
    Volume9
    Issue number2
    DOIs
    Publication statusPublished - 1 Jan 1990

    Fingerprint

    Sequential Estimation
    Autoregressive Model
    First-order
    Sequential Procedure
    Point Estimation
    Autoregression
    Least Squares Estimator
    Asymptotic Normality
    Mean Square
    Estimator
    Estimate

    Keywords

    • autoregression process
    • drifting
    • parameter
    • truncated procedure

    ASJC Scopus subject areas

    • Modelling and Simulation
    • Statistics and Probability

    Cite this

    On truncated sequential estimation of the drifting parametermean in the first order autoregressive models. / Konev, V. V.; Pergamenschicov, S. M.

    In: Sequential Analysis, Vol. 9, No. 2, 01.01.1990, p. 193-216.

    Research output: Contribution to journalArticle

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