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BETA EXPONENTIATED INVERSE RAYLEIGH DISTRIBUTION: STATISTICAL PROPERTIES, BAYESIAN, AND NON-BAYESIAN ESTIMATION WITH APPLICATION
Advances and Applications in Statistics • 2021
Publication Information
Authors
Nasr I. Rashwan, Zohdy M. Nofal, Yehia M. El Gebaly and
Gehad M. Awad
Keywords
hazard rate function, moment generating function, Renyi entropy, beta
distribution, beta exponentiated inverse Rayleigh, maximum likelihood, Bayesian estimation
Journal
Advances and Applications in Statistics
Publisher
Advances and Applications in Statistics © 2021 Pushpa Publishing House, Prayagraj, India
Volume
Volume 69
Issue
Number 1, 2021
Pages
Pages 85-114
publication.type
International
Paper Link
Not Available
Supplementary Materials
Not Available
Abstract
In this paper, a new distribution is proposed called beta exponentiated
inverse Rayleigh (BEIR). Some of its statistical properties such as
quantile function, order statistics, moments, inverse moments, moment
generating function and Renyi entropy are derived and discussed.
Maximum likelihood and Bayesian methods are used to estimate the
model parameters. Monte-Carlo simulation study is carried out to
examine the bias and mean square error of maximum likelihood and
Bayesian estimators. Finally, real data sets are used to illustrate the
importance of the new distribution.
inverse Rayleigh (BEIR). Some of its statistical properties such as
quantile function, order statistics, moments, inverse moments, moment
generating function and Renyi entropy are derived and discussed.
Maximum likelihood and Bayesian methods are used to estimate the
model parameters. Monte-Carlo simulation study is carried out to
examine the bias and mean square error of maximum likelihood and
Bayesian estimators. Finally, real data sets are used to illustrate the
importance of the new distribution.