On moment-type estimators for a class of log-symmetric distributions
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 a...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Brasil |
| Institución: | Universidade Federal do Rio Grande do Norte (UFRN) |
| Repositorio: | Repositório Institucional da UFRN |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.ufrn.br:123456789/49679 |
| Acceso en línea: | https://repositorio.ufrn.br/handle/123456789/49679 |
| Access Level: | acceso abierto |
| Palabra clave: | Asymptotic normality Hodges–Lehmann estimator Log-symmetric distributions Maximum likelihood estimator Moment estimator Modified moment estimator |
| Sumario: | 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 themaximum likelihood estimators through MonteCarlo simulations. Finally, some illustrative examples are presented to illustrate the methods of estimation developed here. |
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