Slash-Weighted Lindley Distribution: Properties, Inference, and Applications-Reference-Cited by-同舟云学术

Slash-Weighted Lindley Distribution: Properties, Inference, and Applications

Published:2023-09-19 Issue:18 Volume:11 Page:3980
ISSN:2227-7390
Container-title:Mathematics
language:en
Short-container-title:Mathematics

Author:

Castillo Jaime S.¹^ORCID,Barranco-Chamorro Inmaculada²^ORCID,Venegas Osvaldo³^ORCID,Gómez Héctor W.¹^ORCID

Affiliation:

1. Departamento de Estadística y Ciencias de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile

2. Departamento de Estadística e Investigación Operativa, Facultad de Matemáticas, Universidad de Sevilla, 41012 Sevilla, Spain

3. Departamento de Ciencias Matemáticas y Físicas, Facultad de Ingeniería, Universidad Católica de Temuco, Temuco 4780000, Chile

Abstract

The slash-weighted Lindley model is introduced due to the need to obtain a model with more kurtosis than the weighted Lindley distribution. Several expressions for the pdf of this model are given. Its cumulative distribution function is expressed in terms of a generalized hypergeometric function and the incomplete gamma function. Moments and maximum likelihood estimation were studied. A simulation study was carried out to illustrate the good performance of the estimates. Finally, two real applications are included.

Funder

Semillero UA-2023

IOAP of University of Seville, Spain

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Link

https://www.mdpi.com/2227-7390/11/18/3980/pdf

Reference39 articles.

1. Fiducial distributions and Bayes’ theorem;Lindley;J. R. Stat. Soc. Ser. A,1958

2. Lindley distribution and its application;Ghitany;Math. Comput. Simul.,2008

3. Weighted distributions and size-biased sampling with applications to wildlife populations and human families;Patil;Biometrics,1978

4. A two-parameter weighted Lindley distribution and its applications to survival data;Ghitany;Math. Comput. Simul.,2011

5. Understanding some long-tailed symmetrical distributions;Rogers;Stat. Neerl.,1972