THERMAL SCIENCE

International Scientific Journal

Ahmed Jumanah Darwish

STATISTICAL PROPERTIES AND APPLICATIONS FOR EXPONENTIATED EXPONENTIAL RAYLEIGH DISTRIBUTION

ABSTRACT
Modelling in lifetime phenomena is a significant issue in many scientific areas. Sometimes many standard models lack superiority in modelling data set. Designing a new form of probability distribution by using different techniques has received a widely attention in statistical theory in the recent years. In this paper, we formulated exponentiated exponential Rayleigh (EER) distribution. We discussed the reliability and hazard rate functions of the EER distribution and computed the quantile, median, skewness and kurtosis. Moreover, the correlations between the parameters and the median, skewness, and kurtosis are investigated. Bayesian and non-Bayesian approaches are adopted to estimate the unknown parameters of EER distribution. In Bayesian approach, we are used Markov Chen Monte Carlo (MCMC) method to obtain the approximate Bayes point estimate. The proposed distribution is used to analyze, light-emitting diodes data, strength of glass fibers data and Wheaton River data. The estimation results of the EER distribution are compared with exponential Rayleigh, Rayleigh, and exponential distributions.
KEYWORDS
exponentiated and T-X family of distributions, Rayleigh distribution, MCMC technique, Bayes estimation, Maximum likelihood estimation
PAPER SUBMITTED: 2024-07-24
PAPER REVISED: 2024-10-10
PAPER ACCEPTED: 2024-10-25
PUBLISHED ONLINE: 2025-01-25
DOI REFERENCE: https://doi.org/10.2298/TSCI2406895D
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2024, VOLUME 28, ISSUE No. 6, PAGES [4895 - 4906]
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Statistical properties and applications for exponentiated exponential Rayleigh distribution

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