IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v29y1996i3p191-199.html
   My bibliography  Save this article

Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model

Author

Listed:
  • Ohtani, Kazuhiro

Abstract

In this paper, we consider a linear regression model when relevant regressors are omitted in the specified model. We examine the MSE dominance of the pre-test Stein-rule estimator of regression coefficients using the Stein-variance estimator over the traditional Stein-rule estimator of regression coefficients.

Suggested Citation

  • Ohtani, Kazuhiro, 1996. "Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model," Statistics & Probability Letters, Elsevier, vol. 29(3), pages 191-199, September.
  • Handle: RePEc:eee:stapro:v:29:y:1996:i:3:p:191-199
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(95)00173-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Gelfand, Alan E. & Dey, Dipak K., 1988. "Improved estimation of the disturbance variance in a linear regression model," Journal of Econometrics, Elsevier, vol. 39(3), pages 387-395, November.
    2. Giles, Judith A., 1991. "Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances," Journal of Econometrics, Elsevier, vol. 50(3), pages 377-398, December.
    3. Ohtani, Kazuhiro, 1993. "A Comparison of the Stein-Rule and Positive-Part Stein-Rule Estimators in a Misspecified Linear Regression Model," Econometric Theory, Cambridge University Press, vol. 9(4), pages 668-679, August.
    4. Ohtani, Kazuhiro, 1988. "Optimal levels of significance of a pre-test in estimating the disturbance variance after the pre-test for a linear hypothesis on coefficients in a linear regression," Economics Letters, Elsevier, vol. 28(2), pages 151-156.
    5. Mittelhammer, R.C., 1984. "Restricted least squares, pre-test, ols and stein rule estimators: Risk comparisons under model misspecification," Journal of Econometrics, Elsevier, vol. 25(1-2), pages 151-164.
    6. Kubokawa, Tatsuya, 1991. "An approach to improving the James-Stein estimator," Journal of Multivariate Analysis, Elsevier, vol. 36(1), pages 121-126, January.
    7. Berry, J. Calvin, 1994. "Improving the James-Stein estimator using the Stein variance estimator," Statistics & Probability Letters, Elsevier, vol. 20(3), pages 241-245, 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. Kazuhiro Ohtani & Alan Wan, 2002. "ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 121-134.
    2. Hu, Guikai & Yu, Shenghua & Luo, Han, 2015. "Comparisons of variance estimators in a misspecified linear model with elliptically contoured errors," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 266-276.
    3. Akio Namba & Kazuhiro Ohtani, 2007. "Risk comparison of the Stein-rule estimator in a linear regression model with omitted relevant regressors and multivariatet errors under the Pitman nearness criterion," Statistical Papers, Springer, vol. 48(1), pages 151-162, January.
    4. Ohtani, Kazuhiro, 1998. "Inadmissibility of the Stein-rule estimator under the balanced loss function," Journal of Econometrics, Elsevier, vol. 88(1), pages 193-201, November.
    5. Akio Namba, 2003. "On the use of the Stein variance estimator in the double k-class estimator when each individual regression coefficient is estimated," Statistical Papers, Springer, vol. 44(1), pages 117-124, January.

    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. Kazuhiro Ohtani & Alan Wan, 2002. "ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 121-134.
    2. Wan, Alan T. K. & Zou, Guohua, 2003. "Optimal critical values of pre-tests when estimating the regression error variance: analytical findings under a general loss structure," Journal of Econometrics, Elsevier, vol. 114(1), pages 165-196, May.
    3. Akio Namba & Kazuhiro Ohtani, 2007. "Risk comparison of the Stein-rule estimator in a linear regression model with omitted relevant regressors and multivariatet errors under the Pitman nearness criterion," Statistical Papers, Springer, vol. 48(1), pages 151-162, January.
    4. A. Saleh & B. Golam Kibria, 2011. "On some ridge regression estimators: a nonparametric approach," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 819-851.
    5. Kazuhiro Ohtani, 1998. "An MSE comparison of the restricted Stein-rule and minimum mean squared error estimators in regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 7(2), pages 361-376, December.
    6. Ohtani, Kazuhiro, 2002. "Exact distribution of a pre-test estimator for regression error variance when there are omitted variables," Statistics & Probability Letters, Elsevier, vol. 60(2), pages 129-140, November.
    7. Namba, Akio & Ohtani, Kazuhiro, 2006. "PMSE performance of the Stein-rule and positive-part Stein-rule estimators in a regression model with or without proxy variables," Statistics & Probability Letters, Elsevier, vol. 76(9), pages 898-906, May.
    8. Akio Namba, 2003. "On the use of the Stein variance estimator in the double k-class estimator when each individual regression coefficient is estimated," Statistical Papers, Springer, vol. 44(1), pages 117-124, January.
    9. Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Other publications TiSEM f131c709-4db4-468d-9ae8-9, Tilburg University, School of Economics and Management.
    10. Qin, Huaizhen & Ouyang, Weiwei, 2016. "Asymmetric risk of the Stein variance estimator under a misspecified linear regression model," Statistics & Probability Letters, Elsevier, vol. 116(C), pages 94-100.
    11. Chaturvedi Anoop & Mishra Sandeep, 2019. "Generalized Bayes Estimation Of Spatial Autoregressive Models," Statistics in Transition New Series, Statistics Poland, vol. 20(2), pages 15-32, June.
    12. Akio Namba, 2001. "MSE performance of the 2SHI estimator in a regression model with multivariate t error terms," Statistical Papers, Springer, vol. 42(1), pages 81-96, January.
    13. Ohtani, Kazuhiro, 1998. "Inadmissibility of the Stein-rule estimator under the balanced loss function," Journal of Econometrics, Elsevier, vol. 88(1), pages 193-201, November.
    14. Zhu, Rong & Zhou, Sherry Z.F., 2011. "Estimating the error variance after a pre-test for an interval restriction on the coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2312-2323, July.
    15. Lee C. Adkins, 2013. "The Restricted Least Squares Stein-Rule in gretl," Economics Working Paper Series 1305, Oklahoma State University, Department of Economics and Legal Studies in Business.
    16. David E. A. Giles, 2000. "Preliminary-Test and Bayes Estimation of a Location Parameter Under 'Reflected Normal' Loss," Econometrics Working Papers 0004, Department of Economics, University of Victoria.
    17. Danilov, Dmitry & Magnus, J.R.Jan R., 2004. "On the harm that ignoring pretesting can cause," Journal of Econometrics, Elsevier, vol. 122(1), pages 27-46, September.
    18. Ohtani, Kazuhiro & Kozumi, Hideo, 1996. "The exact general formulae for the moments and the MSE dominance of the Stein-rule and positive-part Stein-rule estimators," Journal of Econometrics, Elsevier, vol. 74(2), pages 273-287, October.
    19. Irene Vrbik & Paul McNicholas, 2015. "Fractionally-Supervised Classification," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 359-381, October.
    20. Maruyama Yuzo, 2003. "A robust generalized Bayes estimator improving on the James-Stein estimator for spherically symmetric distributions," Statistics & Risk Modeling, De Gruyter, vol. 21(1), pages 69-78, 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:eee:stapro:v:29:y:1996:i:3:p:191-199. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.