Double k-Class Estimators in Regression Models with Non-spherical Disturbances
In this paper, we consider a family of feasible generalised double k-class estimators in a linear regression model with non-spherical disturbances. We derive the large sample asymptotic distribution of the proposed family of estimators and compare its performance with the feasible generalized least squares and Stein-rule estimators using the mean squared error matrix and risk under quadratic loss criteria. A Monte-Carlo experiment investigates the finite sample behaviour of the proposed family of estimators.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 79 (2001)
Issue (Month): 2 (November)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hill, R.Carter & Judge, George G, 1990. "Improved estimation under collinearity and squared error loss," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 296-312, February.
- Carter, R. A. L., 1981. "Improved Stein-rule estimator for regression problems," Journal of Econometrics, Elsevier, vol. 17(1), pages 113-123, September.
- Carter Hill, R. & Judge, George, 1987. "Improved prediction in the presence of multicollinearity," Journal of Econometrics, Elsevier, vol. 35(1), pages 83-100, May.
- Vinod, H. D., 1980.
"Improved stein-rule estimator for regression problems,"
Journal of Econometrics,
Elsevier, vol. 12(2), pages 143-150, February.
- Vinod, H. D., 1981. "Improved Stein-rule estimator for regression problems," Journal of Econometrics, Elsevier, vol. 17(1), pages 125-125, September.
- Rothenberg, Thomas J, 1984. "Approximate Normality of Generalized Least Squares Estimates," Econometrica, Econometric Society, vol. 52(4), pages 811-25, July.
- Carter, R. A. L. & Srivastava, V. K. & Chaturvedi, A., 1993. "Selecting a double k-class estimator for regression coefficients," Statistics & Probability Letters, Elsevier, vol. 18(5), pages 363-371, December.
- Menjoge, Shailendra S., 1984. "On double k-class estimators of coefficients in linear regression," Economics Letters, Elsevier, vol. 15(3-4), pages 295-300.
- Srivastava, V. K. & Chaturvedi, A., 1986. "A necessary and sufficient condition for the dominance of an improved family of estimators in linear regression models," Economics Letters, Elsevier, vol. 20(4), pages 345-349.
- Judge, G.G. & Bock, M.E., 1983. "Biased estimation," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 10, pages 599-649 Elsevier.
- Ullah, Aman & Ullah, Shobha, 1978. "Double k-Class Estimators of Coefficients in Linear Regression," Econometrica, Econometric Society, vol. 46(3), pages 705-22, May.
When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:79:y:2001:i:2:p:226-250. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.