A new class of distributions as a finite functional mixture using functional weights

Abstract In this paper, we introduce a new family of distributions whose probability density function is defined as a weighted sum of two probability density functions; one is defined as a warped version of the other. We focus our attention on a special case based on the exponential distribution wit...

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Main Authors: DALAL LALA BOUALI, CHRISTOPHE CHESNEAU, VIKAS KUMAR SHARMA, HASSAN S. BAKOUCH
Format: Article
Language:English
Published: Academia Brasileira de Ciências 2021-06-01
Series:Anais da Academia Brasileira de Ciências
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000300301&tlng=en
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author DALAL LALA BOUALI
CHRISTOPHE CHESNEAU
VIKAS KUMAR SHARMA
HASSAN S. BAKOUCH
author_facet DALAL LALA BOUALI
CHRISTOPHE CHESNEAU
VIKAS KUMAR SHARMA
HASSAN S. BAKOUCH
author_sort DALAL LALA BOUALI
collection DOAJ
description Abstract In this paper, we introduce a new family of distributions whose probability density function is defined as a weighted sum of two probability density functions; one is defined as a warped version of the other. We focus our attention on a special case based on the exponential distribution with three parameters, a dilation transformation and a weight with polynomial decay, leading to a new life-time distribution. The explicit expressions of the moments generating function, moments and quantile function of the proposed distribution are provided. For estimating the parameters, the method of maximum likelihood estimation is used. Two applications with practical data sets are given.
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spelling doaj.art-3519b1a01f3a4a04996453548ac328fa2022-12-22T04:16:12ZengAcademia Brasileira de CiênciasAnais da Academia Brasileira de Ciências1678-26902021-06-0193210.1590/0001-3765202120181019A new class of distributions as a finite functional mixture using functional weightsDALAL LALA BOUALIhttps://orcid.org/0000-0001-7496-9154CHRISTOPHE CHESNEAUhttps://orcid.org/0000-0002-1522-9292VIKAS KUMAR SHARMAhttps://orcid.org/0000-0003-0169-4094HASSAN S. BAKOUCHhttps://orcid.org/0000-0002-3189-0670Abstract In this paper, we introduce a new family of distributions whose probability density function is defined as a weighted sum of two probability density functions; one is defined as a warped version of the other. We focus our attention on a special case based on the exponential distribution with three parameters, a dilation transformation and a weight with polynomial decay, leading to a new life-time distribution. The explicit expressions of the moments generating function, moments and quantile function of the proposed distribution are provided. For estimating the parameters, the method of maximum likelihood estimation is used. Two applications with practical data sets are given.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000300301&tlng=enfinite mixtureweighted distributionexponential distributionmoment generating functionmaximum likelihood estimation
spellingShingle DALAL LALA BOUALI
CHRISTOPHE CHESNEAU
VIKAS KUMAR SHARMA
HASSAN S. BAKOUCH
A new class of distributions as a finite functional mixture using functional weights
Anais da Academia Brasileira de Ciências
finite mixture
weighted distribution
exponential distribution
moment generating function
maximum likelihood estimation
title A new class of distributions as a finite functional mixture using functional weights
title_full A new class of distributions as a finite functional mixture using functional weights
title_fullStr A new class of distributions as a finite functional mixture using functional weights
title_full_unstemmed A new class of distributions as a finite functional mixture using functional weights
title_short A new class of distributions as a finite functional mixture using functional weights
title_sort new class of distributions as a finite functional mixture using functional weights
topic finite mixture
weighted distribution
exponential distribution
moment generating function
maximum likelihood estimation
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000300301&tlng=en
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