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

N. Balakrishnan, Helton Saulo, Marcelo Bourguignon*, Xiaojun Zhu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

In this paper, we propose three simple closed form estimators for a class of log-symmetric distributions on 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.

Original languageEnglish
Pages (from-to)1339-1355
Number of pages17
JournalComputational Statistics
Volume32
Issue number4
DOIs
Publication statusPublished - 1 Dec 2017

Keywords

  • Asymptotic normality
  • Hodges–Lehmann estimator
  • Log-symmetric distributions
  • Maximum likelihood estimator
  • Modified moment estimator
  • Moment estimator

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