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

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.

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Year of publication:	1996
Authors:	Pak, Ro Jin
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 26.1996, 3, p. 263-269
Publisher:	Elsevier
Keywords:	Asymptotic efficiency Hellinger distance Kernel density

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005254852