IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v45y2018i7p1303-1324.html
   My bibliography  Save this article

A flexible semiparametric regression model for bimodal, asymmetric and censored data

Author

Listed:
  • Thiago G. Ramires
  • Edwin M. M. Ortega
  • Niel Hens
  • Gauss M. Cordeiro
  • Gilberto A. Paula

Abstract

In this paper, we propose a new semiparametric heteroscedastic regression model allowing for positive and negative skewness and bimodal shapes using the B-spline basis for nonlinear effects. The proposed distribution is based on the generalized additive models for location, scale and shape framework in order to model any or all parameters of the distribution using parametric linear and/or nonparametric smooth functions of explanatory variables. We motivate the new model by means of Monte Carlo simulations, thus ignoring the skewness and bimodality of the random errors in semiparametric regression models, which may introduce biases on the parameter estimates and/or on the estimation of the associated variability measures. An iterative estimation process and some diagnostic methods are investigated. Applications to two real data sets are presented and the method is compared to the usual regression methods.

Suggested Citation

  • Thiago G. Ramires & Edwin M. M. Ortega & Niel Hens & Gauss M. Cordeiro & Gilberto A. Paula, 2018. "A flexible semiparametric regression model for bimodal, asymmetric and censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(7), pages 1303-1324, May.
    • Handle: RePEc:taf:japsta:v:45:y:2018:i:7:p:1303-1324
    DOI: 10.1080/02664763.2017.1369499
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2017.1369499
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2017.1369499?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:taf:japsta:v:45:y:2018:i:7:p:1303-1324. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.