IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v15y1994i4p405-428.html
   My bibliography  Save this article

Semiparametric Time Series Regression

Author

Listed:
  • Young K. Truong
  • Charles J. Stone

Abstract

. Let (Xi, Yi), i= 0, pL 1,… denote a bivariate stationary time series with Xi being Rd‐valued and Yi being real‐valued. We consider the regression model Yi=θ(Xi) +Zi, where θ(·) is an unknown function and Zi is an autoregressive process. Given a realization of length n, we examine the problem of estimating the nonparametric function θ(·) and the parametric component Zi. Under appropriate regularity conditions, it is shown that both components can be optimally estimated.

Suggested Citation

  • Young K. Truong & Charles J. Stone, 1994. "Semiparametric Time Series Regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(4), pages 405-428, July.
    • Handle: RePEc:bla:jtsera:v:15:y:1994:i:4:p:405-428
    DOI: 10.1111/j.1467-9892.1994.tb00202.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.1994.tb00202.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.1994.tb00202.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    2. Dursun Aydın & Ersin Yılmaz, 2021. "Semiparametric modeling of the right-censored time-series based on different censorship solution techniques," Empirical Economics, Springer, vol. 61(4), pages 2143-2172, October.
    3. Shao, Zhen & Gao, Fei & Zhang, Qiang & Yang, Shan-Lin, 2015. "Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting i," Applied Energy, Elsevier, vol. 156(C), pages 502-518.
    4. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    5. Ip, Wai-Cheung & Wong, Heung & Li, Yuan & Xie, Zhongjie, 1999. "Threshold variable selection by wavelets in open-loop threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 42(4), pages 375-392, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jtsera:v:15:y:1994:i:4:p:405-428. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.