IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v37y2010i6p923-943.html
   My bibliography  Save this article

Multiple linear regression model with stochastic design variables

Author

Listed:
  • M. Qamarul Islam
  • Moti Tiku

Abstract

In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.

Suggested Citation

  • M. Qamarul Islam & Moti Tiku, 2010. "Multiple linear regression model with stochastic design variables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 923-943.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:6:p:923-943
    DOI: 10.1080/02664760902939612
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664760902939612
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760902939612?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.

    References listed on IDEAS

    as
    1. Tiku, Moti L. & Islam, M. Qamarul & Sazak, Hakan S., 2008. "Estimation in bivariate nonnormal distributions with stochastic variance functions," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1728-1745, January.
    2. Ayşen Akkaya & Moti Tiku, 2005. "Robust estimation and hypothesis testing under short-tailedness and inliers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 129-150, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. GUORUI BIAN & MICHAEL McALEER & WING-KEUNG WONG, 2013. "Robust Estimation And Forecasting Of The Capital Asset Pricing Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-18.
    2. A. Asrat Atsedeweyn & K. Srinivasa Rao, 2014. "Linear regression model with new symmetric distributed errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 364-381, February.
    3. Khaleghei Ghosheh Balagh, Akram & Naderkhani, Farnoosh & Makis, Viliam, 2014. "Highway Accident Modeling and Forecasting in Winter," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 384-396.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ayşen Akkaya & Moti Tiku, 2008. "Short-tailed distributions and inliers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 282-296, August.
    2. Tiku, Moti L. & Senoglu, Birdal, 2009. "Estimation and hypothesis testing in BIB design and robustness," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3439-3451, July.
    3. Ping Chen & Jinde Wang, 2010. "Application in stochastic volatility models of nonlinear regression with stochastic design," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(2), pages 142-156, March.
    4. Tiku, Moti L. & Sürücü, Baris, 2009. "MMLEs are as good as M-estimators or better," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 984-989, April.
    5. Pelin Kasap & Birdal Senoglu & Olcay Arslan, 2016. "Stochastic analysis of covariance when the error distribution is long-tailed symmetric," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 1977-1997, August.
    6. M. Qamarul Islam & Fetih Yildirim & Mehmet Yazici, 2014. "Inference in multivariate linear regression models with elliptically distributed errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1746-1766, August.
    7. Sibel Balci & Aysen Dener Akkaya, 2015. "Robust pairwise multiple comparisons under short-tailed symmetric distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2293-2306, November.
    8. Tiku, Moti L. & Islam, M. Qamarul & Sazak, Hakan S., 2008. "Estimation in bivariate nonnormal distributions with stochastic variance functions," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1728-1745, January.

    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:37:y:2010:i:6:p:923-943. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.