Double k-Class Estimators in Regression Models with Non-spherical Disturbances
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Cited by:
- 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.
- 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.
- 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.
- Shalabh, & Garg, G. & Heumann, C., 2012. "Performance of double k-class estimators for coefficients in linear regression models with non-spherical disturbances under asymmetric losses," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 35-47.
- 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.
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Keywords
bias dominance large sample asymptotic quadratic loss mean squared error Monte-Carlo simulation risk;Statistics
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