General results for the transmuted Family of distributions and new models

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 asymptot...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Principais autores: Bourguignon, Marcelo, Ghosh, Indranil, Cordeiro, Gauss M.
Formato: article
Idioma:English
Publicado em: Journal of Probability and Statistics
Assuntos:
Transmuted Family
Information Theory
Maximum Likelihood Estimation
Endereço do item:https://repositorio.ufrn.br/handle/123456789/49678
http://dx.doi.org/10.1155/2016/7208425
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
id ri-123456789-49678
record_format dspace
spelling ri-123456789-496782022-11-08T18:23:27Z General results for the transmuted Family of distributions and new models Bourguignon, Marcelo Ghosh, Indranil Cordeiro, Gauss M. 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. 2022-11-08T18:23:25Z 2022-11-08T18:23:25Z 2016 article BOURGUIGNON, Marcelo; GHOSH, Indranil; CORDEIRO, Gauss M. . General Results for the Transmuted Family of Distributions and New Models. Journal of Probability and Statistics, v. 2016, p. 1-12, 2016. Disponível em:https://www.hindawi.com/journals/jps/2016/7208425. Acesso em: 07 dez. 2017. https://repositorio.ufrn.br/handle/123456789/49678 http://dx.doi.org/10.1155/2016/7208425 en Acesso Aberto application/pdf Journal of Probability and Statistics
institution Repositório Institucional
collection RI - UFRN
language English
topic Transmuted Family
Information Theory
Maximum Likelihood Estimation
spellingShingle Transmuted Family
Information Theory
Maximum Likelihood Estimation
Bourguignon, Marcelo
Ghosh, Indranil
Cordeiro, Gauss M.
General results for the transmuted Family of distributions and new models
description 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.
format article
author Bourguignon, Marcelo
Ghosh, Indranil
Cordeiro, Gauss M.
author_facet Bourguignon, Marcelo
Ghosh, Indranil
Cordeiro, Gauss M.
author_sort Bourguignon, Marcelo
title General results for the transmuted Family of distributions and new models
title_short General results for the transmuted Family of distributions and new models
title_full General results for the transmuted Family of distributions and new models
title_fullStr General results for the transmuted Family of distributions and new models
title_full_unstemmed General results for the transmuted Family of distributions and new models
title_sort general results for the transmuted family of distributions and new models
publisher Journal of Probability and Statistics
publishDate 2022
url https://repositorio.ufrn.br/handle/123456789/49678
http://dx.doi.org/10.1155/2016/7208425
work_keys_str_mv AT bourguignonmarcelo generalresultsforthetransmutedfamilyofdistributionsandnewmodels
AT ghoshindranil generalresultsforthetransmutedfamilyofdistributionsandnewmodels
AT cordeirogaussm generalresultsforthetransmutedfamilyofdistributionsandnewmodels
_version_ 1773963692419842048

Registros relacionados