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Estimating the large mutation parameter of the Ewens sampling formula

Part of: Parametric inference Limit theorems

Published online by Cambridge University Press:  04 April 2017

Koji Tsukuda
Koji Tsukuda*
Affiliation:
Kurume University
*
* Current address: Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo, Japan. Email address: k.tsukuda@gmail.com
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Abstract

We derive some limit theorems associated with the Ewens sampling formula when its parameter is increasing together with a sample size. Moreover, the limit results are applied in order to investigate asymptotic properties of the maximum likelihood estimator.

Keywords

Asymptotic properties of estimatorsmaximum likelihood estimationEwens sampling formula

MSC classification

Primary: 62F12: Asymptotic properties of estimators
Secondary: 60F05: Central limit and other weak theorems
Type
Research Papers
Information
Journal of Applied Probability , Volume 54 , Issue 1 , March 2017 , pp. 42 - 54
Copyright
Copyright © Applied Probability Trust 2017 

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References

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