Quasi-medians are robust and relatively efficient estimators of a common mean given multivariate normality
AbstractIn this note we examine the efficiency of averaging marginal quasi-medians as compared to averaging marginal sample means when estimating a common location parameter given multivariate normal data. It is shown that the efficiency of certain quasi-medians approach that of the sample mean as the dimension of the problem grows larger. Modest gains in efficiency may be had even when the dimension of the problem is extended from the univariate setting to the bivariate setting.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 57 (2002)
Issue (Month): 4 (May)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Babu, G. Jogesh & Rao, C. Radhakrishna, 1988. "Joint asymptotic distribution of marginal quantiles and quantile functions in samples from a multivariate population," Journal of Multivariate Analysis, Elsevier, vol. 27(1), pages 15-23, October.
- Maritz, J. S., 1991. "Estimating the covariance matrix of bivariate medians," Statistics & Probability Letters, Elsevier, vol. 12(4), pages 305-309, October.
- Withers, Christopher S. & Nadarajah, Saralees, 2011. "Estimates of low bias for the multivariate normal," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1635-1647, November.
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