Minimum Hellinger distance estimation in simple linear regression models; distribution and efficiency

Ro Jin Pak

Statistics & Probability Letters, 1996, vol. 26, issue 3, 263-269

Abstract: The minimum Hellinger distance estimation in simple linear regression models is considered. It is shown that the estimators of the slope parameter and the intercept parameter are asymptotically fully efficient, and that the estimator of the scale parameter is asymptotically reasonably efficient. Also, the asymptotic normality of these estimators is shown.

Keywords: Asymptotic; efficiency; Hellinger; distance; Kernel; density (search for similar items in EconPapers)
Date: 1996
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Citations: View citations in EconPapers (3)

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