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A comparison of some estimators of the mixture proportion of mixed normal distributions

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Pardo Llorente, María del Carmen (1997) A comparison of some estimators of the mixture proportion of mixed normal distributions. Journal of Computational and Applied Mathematics, 84 (2). pp. 207-217. ISSN 0377-0427

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Official URL: http://www.sciencedirect.com/science/article/pii/S0377042797001246


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Abstract

Fisher's method of maximum likelihood breaks down when applied to the problem of estimating the five parameters of a mixture of two normal densities from a continuous random sample of size n. Alternative methods based on minimum-distance estimation by grouping the underlying variable are proposed. Simulation results compare the efficiency as well as the robustness under symmetric departures from component normality of these estimators. Our results indicate that the estimator based on Rao's divergence is better than other classic ones.


Item Type:Article
Additional Information:

This work was supported by Grant DGICYT PB94-0308

Uncontrolled Keywords:Minimum-distance estimator; Simulation; Relative efficiency
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:17878
Deposited On:23 Jan 2013 11:12
Last Modified:26 Feb 2015 08:44

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