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Double k-Class Estimators in Regression Models with Non-spherical Disturbances

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  • Wan, Alan T. K.
  • Chaturvedi, Anoop

Abstract

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.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 79 (2001)
Issue (Month): 2 (November)
Pages: 226-250

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Handle: RePEc:eee:jmvana:v:79:y:2001:i:2:p:226-250

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Related research

Keywords: bias dominance large sample asymptotic quadratic loss mean squared error Monte-Carlo simulation risk;

References

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  1. Rothenberg, Thomas J, 1984. "Approximate Normality of Generalized Least Squares Estimates," Econometrica, Econometric Society, vol. 52(4), pages 811-25, July.
  2. 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.
  3. 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.
  4. Vinod, H. D., 1981. "Improved Stein-rule estimator for regression problems," Journal of Econometrics, Elsevier, vol. 17(1), pages 125-125, September.
  5. Carter Hill, R. & Judge, George, 1987. "Improved prediction in the presence of multicollinearity," Journal of Econometrics, Elsevier, vol. 35(1), pages 83-100, May.
  6. 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.
  7. 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.
  8. Carter, R. A. L., 1981. "Improved Stein-rule estimator for regression problems," Journal of Econometrics, Elsevier, vol. 17(1), pages 113-123, September.
  9. Menjoge, Shailendra S., 1984. "On double k-class estimators of coefficients in linear regression," Economics Letters, Elsevier, vol. 15(3-4), pages 295-300.
  10. Ullah, Aman & Ullah, Shobha, 1978. "Double k-Class Estimators of Coefficients in Linear Regression," Econometrica, Econometric Society, vol. 46(3), pages 705-22, May.
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Cited by:
  1. Zhang, Xinyu & Chen, Ti & Wan, Alan T.K. & Zou, Guohua, 2009. "Robustness of Stein-type estimators under a non-scalar error covariance structure," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2376-2388, November.
  2. Chaturvedi, Anoop & Shalabh, 2004. "Risk and Pitman closeness properties of feasible generalized double k-class estimators in linear regression models with non-spherical disturbances under balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 90(2), pages 229-256, August.
  3. Chaturvedi, Anoop & Wan, Alan T. K. & Singh, Shri P., 2002. "Improved Multivariate Prediction in a General Linear Model with an Unknown Error Covariance Matrix," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 166-182, October.

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