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

V. V. Konev, S. M. Pergamenschicov

    Research output: Contribution to journal › Article

    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 journal › Article

    Konev, VV & Pergamenschicov, SM 1990, 'On truncated sequential estimation of the drifting parametermean in the first order autoregressive models', Sequential Analysis, vol. 9, no. 2, pp. 193-216. https://doi.org/10.1080/07474949008836205
    Konev VV, Pergamenschicov SM. On truncated sequential estimation of the drifting parametermean in the first order autoregressive models. Sequential Analysis. 1990 Jan 1;9(2):193-216. https://doi.org/10.1080/07474949008836205
    Konev, V. V. ; Pergamenschicov, S. M. / On truncated sequential estimation of the drifting parametermean in the first order autoregressive models. In: Sequential Analysis. 1990 ; Vol. 9, No. 2. pp. 193-216.
    @article{82ad0e5f74fc46ada03ae0ce71405b89,
    title = "On truncated sequential estimation of the drifting parametermean in the first order autoregressive models",
    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.",
    keywords = "autoregression process, drifting, parameter, truncated procedure",
    author = "Konev, {V. V.} and Pergamenschicov, {S. M.}",
    year = "1990",
    month = "1",
    day = "1",
    doi = "10.1080/07474949008836205",
    language = "English",
    volume = "9",
    pages = "193--216",
    journal = "Sequential Analysis",
    issn = "0747-4946",
    publisher = "Taylor and Francis Ltd.",
    number = "2",

    }

    TY - JOUR

    T1 - On truncated sequential estimation of the drifting parametermean in the first order autoregressive models

    AU - Konev, V. V.

    AU - Pergamenschicov, S. M.

    PY - 1990/1/1

    Y1 - 1990/1/1

    N2 - 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.

    AB - 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.

    KW - autoregression process

    KW - drifting

    KW - parameter

    KW - truncated procedure

    UR - http://www.scopus.com/inward/record.url?scp=84972990216&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84972990216&partnerID=8YFLogxK

    U2 - 10.1080/07474949008836205

    DO - 10.1080/07474949008836205

    M3 - Article

    VL - 9

    SP - 193

    EP - 216

    JO - Sequential Analysis

    JF - Sequential Analysis

    SN - 0747-4946

    IS - 2

    ER -

    Access to Document