IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-7908-2349-3_8.html

Estimation of a General Parametric Location in Censored Regression

In: Exploring Research Frontiers in Contemporary Statistics and Econometrics

Author

Listed:
  • Cédric Heuchenne

    (HEC-Management School of University of Liége, QuantOM (Centre for Quantitative Methods and Operations Management)
    Université catholique de Louvain, Institut de statistique, biostatistique et sciences actuarielles)

  • Ingrid Van Keilegom

    (Université catholique de Louvain, Institut de statistique, biostatistique et sciences actuarielles)

Abstract

Consider the random vector (X, Y ), where Y represents a response variable and X an explanatory variable. The response Y is subject to random right censoring, whereas X is completely observed. Let m(x) be a conditional location function of Y given X = x. In this paper we assume that m( ⋅) belongs to some parametric class $$\mathcal{M} =\{ {m}_{\theta } : \theta \in \Theta \}$$ and we propose a new method for estimating the true unknown value θ0. The method is based on nonparametric imputation for the censored observations. The consistency and asymptotic normality of the proposed estimator are established.

Suggested Citation

  • Cédric Heuchenne & Ingrid Van Keilegom, 2011. "Estimation of a General Parametric Location in Censored Regression," Springer Books, in: Ingrid Van Keilegom & Paul W. Wilson (ed.), Exploring Research Frontiers in Contemporary Statistics and Econometrics, chapter 0, pages 177-187, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2349-3_8
    DOI: 10.1007/978-3-7908-2349-3_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-3-7908-2349-3_8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.