Operational Variants of the Minimum Mean Squared Error Estimator in Linear Regression Models with Non-Spherical Disturbances
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DOI: 10.1023/A:1004169923370
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References listed on IDEAS
- Toutenburg, H. & Trenkler, G. & Liski, E., 1992. "Optimal estimation methods under weakened linear restrictions in regression," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 527-536, November.
- Ohtani, Kazuhiro, 1999. "MSE performance of a heterogeneous pre-test estimator," Statistics & Probability Letters, Elsevier, vol. 41(1), pages 65-71, January.
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Cited by:
- Pal, Amresh Bahadur & Dubey, Ashutosh Kumar & Chaturvedi, Anoop, 2016. "Shrinkage estimation in spatial autoregressive model," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 362-373.
- 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.
- Wan, Alan T. K. & Kurumai, Hiroko, 1999. "An iterative feasible minimum mean squared error estimator of the disturbance variance in linear regression under asymmetric loss," Statistics & Probability Letters, Elsevier, vol. 45(3), pages 253-259, November.
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Keywords
Asymptotic expansion; quadratic loss; minimum mean squared error; risk; Stein-rule;All these keywords.
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