IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v96y2001mseptemberp1097-1101.html
   My bibliography  Save this article

Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution

Author

Listed:
  • Foster A. M.
  • Tian L.
  • Wei L. J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Foster A. M. & Tian L. & Wei L. J., 2001. "Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1097-1101, September.
    • Handle: RePEc:bes:jnlasa:v:96:y:2001:m:september:p:1097-1101
    as

    Download full text from publisher

    File URL: http://www.ingentaconnect.com/content/asa/jasa/2001/00000096/00000455/art00027
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    2. Tianxi Cai & Lu Tian & L. J. Wei, 2004. "Semi-parametric Box-Cox Power Transformation Models for Censored Survival Observations," Harvard University Biostatistics Working Paper Series 1006, Berkeley Electronic Press.
    3. Daniel Becker & Alois Kneip & Valentin Patilea, 2021. "Semiparametric inference for partially linear regressions with Box-Cox transformation," Papers 2106.10723, arXiv.org.
    4. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2005. "Bootstrap prediction intervals for power-transformed time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 219-235.
    5. Atkinson, Anthony C. & Riani, Marco & Corbellini, Aldo, 2021. "The box-cox transformation: review and extensions," LSE Research Online Documents on Economics 103537, London School of Economics and Political Science, LSE Library.
    6. Komunjer, Ivana, 2009. "Global identification of the semiparametric Box-Cox model," Economics Letters, Elsevier, vol. 104(2), pages 53-56, August.
    7. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    8. Willard Manning, 2012. "Dealing with Skewed Data on Costs and Expenditures," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 44, Edward Elgar Publishing.
    9. Debashis Ghosh, 2004. "Semiparametic models and estimation procedures for binormal ROC curves with multiple biomarkers," The University of Michigan Department of Biostatistics Working Paper Series 1038, Berkeley Electronic Press.
    10. Marazzi, Alfio & Yohai, Victor J., 2006. "Robust Box-Cox transformations based on minimum residual autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2752-2768, June.
    11. Arkadiusz Szydlowski, 2017. "Testing a parametric transformation model versus a nonparametric alternative," Discussion Papers in Economics 17/15, Division of Economics, School of Business, University of Leicester.
    12. Debashis Ghosh, 2004. "Semiparametric methods for the binormal model with multiple biomarkers," The University of Michigan Department of Biostatistics Working Paper Series 1046, Berkeley Electronic Press.
    13. Yuanhua Feng & Wolfgang Karl Härdle, 2021. "Uni- and multivariate extensions of the sinh-arcsinh normal distribution applied to distributional regression," Working Papers CIE 142, Paderborn University, CIE Center for International Economics.

    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:bes:jnlasa:v:96:y:2001:m:september:p:1097-1101. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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.