On moment-type estimators for a class of log-symmetric distributions

N. Balakrishnan, Helton Saulo, Marcelo Bourguignon () and Xiaojun Zhu
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N. Balakrishnan: McMaster University
Marcelo Bourguignon: Universidade Federal do Rio Grande do Norte
Xiaojun Zhu: Xi’an Jiaotong-Liverpool University

Computational Statistics, 2017, vol. 32, issue 4, No 6, 1339-1355

Abstract: Abstract In this paper, we propose three simple closed form estimators for a class of log-symmetric distributions on $${\mathbb {R}}^{+}$$ R + . The proposed methods make use of some key properties of this class of distributions. We derive the asymptotic distributions of these estimators. The performance of the proposed estimators are then compared with those of the maximum likelihood estimators through Monte Carlo simulations. Finally, some illustrative examples are presented to illustrate the methods of estimation developed here.

Keywords: Asymptotic normality; Hodges–Lehmann estimator; Log-symmetric distributions; Maximum likelihood estimator; Moment estimator; Modified moment estimator (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00180-017-0722-6

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