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On the Extended Chen Distribution: Development, Properties, Characterizations and Applications

Bhatti, Fiaz Ahmad ; Hamedani, G. G. ; Najibi, Seyed Morteza LU orcid and Ahmad, Munir (2021) In Annals of Data Science 8(1). p.159-180
Abstract
In this paper, a flexible model called extended Chen (EC) distribution is derived from the generalized Burr-Hatke differential equation and nexus between the exponential and gamma variables. The EC distribution is also derived from compounding mixture of the generalized Chen and gamma distributions. The EC distribution is very flexible and its hazard rate function accommodates various shapes such as increasing, decreasing, decreasing–increasing, increasing–decreasing–increasing, bathtub and modified bathtub. The density function of the EC model is arc, J, reverse-J, left-skewed, right-skewed and symmetrical shaped. Some structural and mathematical properties such as descriptive measures on the basis of quantiles, stochastic orderings,... (More)
In this paper, a flexible model called extended Chen (EC) distribution is derived from the generalized Burr-Hatke differential equation and nexus between the exponential and gamma variables. The EC distribution is also derived from compounding mixture of the generalized Chen and gamma distributions. The EC distribution is very flexible and its hazard rate function accommodates various shapes such as increasing, decreasing, decreasing–increasing, increasing–decreasing–increasing, bathtub and modified bathtub. The density function of the EC model is arc, J, reverse-J, left-skewed, right-skewed and symmetrical shaped. Some structural and mathematical properties such as descriptive measures on the basis of quantiles, stochastic orderings, moments, order statistics and reliability measures are theoretically established. The EC distribution is characterized via various techniques. The maximum likelihood estimates for unknown parameters of the EC distribution are obtained. A simulation study is executed to assess the behavior of the maximum likelihood estimators. The EC distribution is applied to two real data sets to elucidate its potentiality and utility. The competence of the EC distribution is tested through various goodness of fit criteria. (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Characterizations, Compounding, Maximum likelihood estimation, Reliability, Stochastic ordering
in
Annals of Data Science
volume
8
issue
1
pages
22 pages
publisher
Springer
external identifiers
  • scopus:85094112802
ISSN
2198-5804
DOI
10.1007/s40745-019-00202-x
language
English
LU publication?
yes
id
ffd28f9a-40e8-4d1f-9e5a-8f7b57231331
date added to LUP
2021-03-18 13:25:23
date last changed
2022-04-27 00:53:51
@article{ffd28f9a-40e8-4d1f-9e5a-8f7b57231331,
  abstract     = {{In this paper, a flexible model called extended Chen (EC) distribution is derived from the generalized Burr-Hatke differential equation and nexus between the exponential and gamma variables. The EC distribution is also derived from compounding mixture of the generalized Chen and gamma distributions. The EC distribution is very flexible and its hazard rate function accommodates various shapes such as increasing, decreasing, decreasing–increasing, increasing–decreasing–increasing, bathtub and modified bathtub. The density function of the EC model is arc, J, reverse-J, left-skewed, right-skewed and symmetrical shaped. Some structural and mathematical properties such as descriptive measures on the basis of quantiles, stochastic orderings, moments, order statistics and reliability measures are theoretically established. The EC distribution is characterized via various techniques. The maximum likelihood estimates for unknown parameters of the EC distribution are obtained. A simulation study is executed to assess the behavior of the maximum likelihood estimators. The EC distribution is applied to two real data sets to elucidate its potentiality and utility. The competence of the EC distribution is tested through various goodness of fit criteria.}},
  author       = {{Bhatti, Fiaz Ahmad and Hamedani, G. G. and Najibi, Seyed Morteza and Ahmad, Munir}},
  issn         = {{2198-5804}},
  keywords     = {{Characterizations; Compounding; Maximum likelihood estimation; Reliability; Stochastic ordering}},
  language     = {{eng}},
  month        = {{03}},
  number       = {{1}},
  pages        = {{159--180}},
  publisher    = {{Springer}},
  series       = {{Annals of Data Science}},
  title        = {{On the Extended Chen Distribution: Development, Properties, Characterizations and Applications}},
  url          = {{http://dx.doi.org/10.1007/s40745-019-00202-x}},
  doi          = {{10.1007/s40745-019-00202-x}},
  volume       = {{8}},
  year         = {{2021}},
}