dc.creatorBalakrishnan, N.
dc.creatorSaulo, Helton
dc.creatorBourguignon, Marcelo
dc.creatorZhu, Xiaojun
dc.date2022-11-08T18:46:52Z
dc.date2022-11-08T18:46:52Z
dc.date2017
dc.date.accessioned2023-09-04T13:34:35Z
dc.date.available2023-09-04T13:34:35Z
dc.identifierBALAKRISHNAN, N.; et al. On moment-type estimators for a class of log-symmetric distributions. Computacional Statistics, v. 32, p. 1339-1355, 2017. Disponível em: https://link.springer.com/article/10.1007%2Fs00180-017-0722-6. Acesso em: 07 dez. 2017.
dc.identifierhttps://repositorio.ufrn.br/handle/123456789/49679
dc.identifier10.1007/s00180-017-0722-6
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8602498
dc.descriptionIn 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 themaximum likelihood estimators through MonteCarlo simulations. Finally, some illustrative examples are presented to illustrate the methods of estimation developed here.
dc.languageen
dc.publisherComputacional Statistics
dc.rightsAcesso Aberto
dc.subjectAsymptotic normality
dc.subjectHodges–Lehmann estimator
dc.subjectLog-symmetric distributions
dc.subjectMaximum likelihood estimator
dc.subjectMoment estimator
dc.subjectModified moment estimator
dc.titleOn moment-type estimators for a class of log-symmetric distributions
dc.typearticle


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