Second-order properties of locally stationary processes

Kenichiro Tamaki

    研究成果: Article

    1 引用 (Scopus)

    抄録

    In this article, we investigate an optimal property of the maximum likelihood estimator of Gaussian locally stationary processes by the second-order approximation. In the case where the model is correctly specified, it is shown that appropriate modifications of the maximum likelihood estimator for Gaussian locally stationary processes is second-order asymptotically efficient. We also discuss second-order robustness properties.

    元の言語English
    ページ（範囲）145-166
    ページ数22
    ジャーナルJournal of Time Series Analysis
    巻30
    発行部数1
    DOI
    出版物ステータスPublished - 2009 1

    Fingerprint

    Locally Stationary Processes
    Maximum Likelihood Estimator
    Maximum likelihood
    Second-order Approximation
    Robustness
    Stationary process
    Maximum likelihood estimator
    Model

    ASJC Scopus subject areas

    • Applied Mathematics
    • Statistics and Probability
    • Statistics, Probability and Uncertainty

    これを引用

    Second-order properties of locally stationary processes. / Tamaki, Kenichiro.

    ：: Journal of Time Series Analysis, 巻 30, 番号 1, 01.2009, p. 145-166.

    研究成果: Article

    Tamaki, K 2009, 'Second-order properties of locally stationary processes', Journal of Time Series Analysis, 巻. 30, 番号 1, pp. 145-166. https://doi.org/10.1111/j.1467-9892.2008.00605.x
    Tamaki K. Second-order properties of locally stationary processes. Journal of Time Series Analysis. 2009 1;30(1):145-166. https://doi.org/10.1111/j.1467-9892.2008.00605.x
    Tamaki, Kenichiro. / Second-order properties of locally stationary processes. ：: Journal of Time Series Analysis. 2009 ; 巻 30, 番号 1. pp. 145-166.
    @article{b2914bb8626f4cd6879abd576f4236ae,
    title = "Second-order properties of locally stationary processes",
    abstract = "In this article, we investigate an optimal property of the maximum likelihood estimator of Gaussian locally stationary processes by the second-order approximation. In the case where the model is correctly specified, it is shown that appropriate modifications of the maximum likelihood estimator for Gaussian locally stationary processes is second-order asymptotically efficient. We also discuss second-order robustness properties.",
    keywords = "Gaussian locally stationary process, Maximum likelihood estimator, Second-order asymptotic efficiency",
    author = "Kenichiro Tamaki",
    year = "2009",
    month = "1",
    doi = "10.1111/j.1467-9892.2008.00605.x",
    language = "English",
    volume = "30",
    pages = "145--166",
    journal = "Journal of Time Series Analysis",
    issn = "0143-9782",
    publisher = "Wiley-Blackwell",
    number = "1",

    }

    TY - JOUR

    T1 - Second-order properties of locally stationary processes

    AU - Tamaki, Kenichiro

    PY - 2009/1

    Y1 - 2009/1

    N2 - In this article, we investigate an optimal property of the maximum likelihood estimator of Gaussian locally stationary processes by the second-order approximation. In the case where the model is correctly specified, it is shown that appropriate modifications of the maximum likelihood estimator for Gaussian locally stationary processes is second-order asymptotically efficient. We also discuss second-order robustness properties.

    AB - In this article, we investigate an optimal property of the maximum likelihood estimator of Gaussian locally stationary processes by the second-order approximation. In the case where the model is correctly specified, it is shown that appropriate modifications of the maximum likelihood estimator for Gaussian locally stationary processes is second-order asymptotically efficient. We also discuss second-order robustness properties.

    KW - Gaussian locally stationary process

    KW - Maximum likelihood estimator

    KW - Second-order asymptotic efficiency

    UR - http://www.scopus.com/inward/record.url?scp=58149141903&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=58149141903&partnerID=8YFLogxK

    U2 - 10.1111/j.1467-9892.2008.00605.x

    DO - 10.1111/j.1467-9892.2008.00605.x

    M3 - Article

    AN - SCOPUS:58149141903

    VL - 30

    SP - 145

    EP - 166

    JO - Journal of Time Series Analysis

    JF - Journal of Time Series Analysis

    SN - 0143-9782

    IS - 1

    ER -

    文献にアクセス