General results for the transmuted Family of distributions and new models

• Autor(a) principal: Bourguignon, Marcelo
• Data de Publicação: 2016
• Outros Autores: Ghosh, Indranil, Cordeiro, Gauss M.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/handle/123456789/49678; http://dx.doi.org/10.1155/2016/7208425
• topic: Transmuted Family; Information Theory; Maximum Likelihood Estimation

The transmuted family of distributions has been receiving increased attention over the last few years. For a baseline G distribution, we derive a simple representation for the transmuted-G family density function as a linear mixture of the G and exponentiated-G densities. We investigate the asymptotes and shapes and obtain explicit expressions for the ordinary and incomplete moments, quantile and generating functions, mean deviations, R´enyi and Shannon entropies, and order statistics and their moments. We estimate the model parameters of the family by the method of maximum likelihood. We prove empirically the flexibility of the proposed model by means of an application to a real data set.