Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/40344
Título: A new count model generated from mixed Poisson transmuted exponential family with an application to health care data
Autores/as: Bhati, Deepesh
Kumawat, Pooja
Gómez–Déniz, E. 
Clasificación UNESCO: 1202 Análisis y análisis funcional
Palabras clave: Count regression
Health care data
Mixed Poisson distribution
Over-dispersion
Transmuted exponential family
Fecha de publicación: 2017
Publicación seriada: Communications in Statistics - Theory and Methods 
Resumen: In this article, a new mixed Poisson distribution is introduced. This new distribution is obtained by utilizing mixing process, with Poisson distribution as mixed distribution and Transmuted Exponential as mixing distribution. Distributional properties like unimodality, moments, overdispersion, infinite divisibility are studied. Three methods viz. Method of moment, Method of moment and proportion, and Maximum-likelihood method are used for parameter estimation. Further, an actuarial application in context of aggregate claim distribution is presented. Finally, to showthe applicability and superiority of proposed model, we discuss count data and count regression modeling and compare with somewell established models.
URI: http://hdl.handle.net/10553/40344
ISSN: 0361-0926
DOI: 10.1080/03610926.2016.1257712
Fuente: Communications in Statistics - Theory and Methods[ISSN 0361-0926],v. 46, p. 11060-11076
Colección:Artículos
Vista completa

Citas SCOPUSTM   

25
actualizado el 24-mar-2024

Citas de WEB OF SCIENCETM
Citations

6
actualizado el 25-abr-2021

Visitas

20
actualizado el 16-sep-2023

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.