Useful Generalization of the Inverse Lomax Distribution: Statistical Properties and Application to Lifetime Data

Maxwell, Obubu; Onyedikachi, Ibeakuzie Precious; Obi-Okpala, Chinelo Ijeoma; Kayode, Adeleke Akinrinade; Victor, Echebiri Udochukwu

doi:10.34297/ajbsr.2019.06.001040

Cited by 2 publications

(1 citation statement)

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“…Also, recent studies have proposed extensions of the IL distributions for further purposes. In this regard, let us cite Reference [ 24 ] for the inverse power Lomax (or power IL) distribution, Reference [ 25 ] for the Weibull IL distribution, Reference [ 26 ] for the alpha power transformed IL distribution, Reference [ 27 ] for the Marshall-Olkin IL distribution and Reference [ 28 ] for the odd generalized exponentiated IL distribution.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Entropy for Inverse Lomax Distribution under Multiple Censored Data

Bantan

Elgarhy

Chesneau

et al. 2020

Entropy

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The inverse Lomax distribution has been widely used in many applied fields such as reliability, geophysics, economics and engineering sciences. In this paper, an unexplored practical problem involving the inverse Lomax distribution is investigated: the estimation of its entropy when multiple censored data are observed. To reach this goal, the entropy is defined through the Rényi and q-entropies, and we estimate them by combining the maximum likelihood and plugin methods. Then, numerical results are provided to show the behavior of the estimates at various sample sizes, with the determination of the mean squared errors, two-sided approximate confidence intervals and the corresponding average lengths. Our numerical investigations show that, when the sample size increases, the values of the mean squared errors and average lengths decrease. Also, when the censoring level decreases, the considered of Rényi and q-entropies estimates approach the true value. The obtained results validate the usefulness and efficiency of the method. An application to two real life data sets is given.

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Section: Introductionmentioning

confidence: 99%

Estimation of Entropy for Inverse Lomax Distribution under Multiple Censored Data

Bantan

Elgarhy

Chesneau

et al. 2020

Entropy

View full text Add to dashboard Cite

show abstract

Inference of truncated inverse Rayleigh Odd Weibull exponential distribution with simulation and application to COVID-19 data

Al-Noor,

Sultan

2024

International Workshop on Machine Learning and Quantum Computing Applications in Medicine and Physics: Wmlq2022

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Useful Generalization of the Inverse Lomax Distribution: Statistical Properties and Application to Lifetime Data

Abstract: This work is licensed under Creative Commons Attribution 4.0 License AJBSR.MS.ID.001040.

Cited by 2 publications

References 7 publications

Estimation of Entropy for Inverse Lomax Distribution under Multiple Censored Data

Estimation of Entropy for Inverse Lomax Distribution under Multiple Censored Data

Inference of truncated inverse Rayleigh Odd Weibull exponential distribution with simulation and application to COVID-19 data

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