Moments of Dual Generalized Order Statistics and Characterization for Transmuted Exponential Model

Sobhi, Mashail AL

doi:10.21608/cjmss.2022.272548

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…The [ 27 ], also known as Pareto II, distribution has been frequently used in a variety of situations. [ 28 ] discussed moments of dual generalized order statistics and characterization for the transmuted exponential model. [ 29 ] obtained order statistics of inverse Pareto distribution.…”

Section: Gull Alpha Power Lomax Distribution (Gapl)mentioning

confidence: 99%

The Gull Alpha Power Lomax distributions: Properties, simulation, and applications to modeling COVID-19 mortality rates

Tolba,

Muse,

Fayomi

et al. 2023

PLoS ONE

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The Gull Alpha Power Lomax distribution is a new extension of the Lomax distribution that we developed in this paper (GAPL). The proposed distribution’s appropriateness stems from its usefulness to model both monotonic and non-monotonic hazard rate functions, which are widely used in reliability engineering and survival analysis. In addition to their special cases, many statistical features were determined. The maximum likelihood method is used to estimate the model’s unknown parameters. Furthermore, the proposed distribution’s usefulness is demonstrated using two medical data sets dealing with COVID-19 patients’ mortality rates, as well as extensive simulated data applied to assess the performance of the estimators of the proposed distribution.

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Section: Gull Alpha Power Lomax Distribution (Gapl)mentioning

confidence: 99%

The Gull Alpha Power Lomax distributions: Properties, simulation, and applications to modeling COVID-19 mortality rates

Tolba,

Muse,

Fayomi

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Al-Kutubi et al [9] proposed a new extended two-parameter distribution's properties, estimate techniques, and geological and medical applications. Sobhi and Mashail [10] discussed moments of dual generalized order statistics and characterization for transmuted exponential model. Additionally, a thorough instructional overview of Markov chain Monte Carlo (MCMC) techniques was provided by Brooks [11], who also covered various implementation-related concerns.…”

Section: Introductionmentioning

confidence: 99%

Bayesian and Non-Bayesian Inference for The Generalized Power Akshaya Distribution with Application in Medical

Hamdy

Almetwally

2023

Computational Journal of Mathematical and Statistical Sciences

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Generalized power Akshaya distribution is a brand-new two-parameter distribution that builds on the Akshaya distribution first introduced by [1]. The lifetime data is intended to be modelled by this distribution. The generalised power Akshaya's parameters are estimated using both the non-Bayesian and Bayesian approaches in this work. The weighted least square estimation (WLSE), least square estimation (LSE), Cramer-von-Mises estimation (CVME), Anderson and Darling (AD) method of estimation, maximum product Space estimators (MPSE), and maximum likelihood estimation (MLE), six non-Bayesian estimation methods, are used to find the model parameters. The parameters of the suggested distribution were also determined using the squared error loss function and Bayesian estimating (BE) under independent gamma priors. The unknown parameters have been estimated using the Bayesian approach using Markov chain Monte Carlo (MCMC). Additionally, the parameters' average width of the confidence intervals and coverage probability are computed. Additionally, the reliable intervals for Bayesian estimates of the unknown parameters calculated.

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“…Nasiru [10] presented another weighted Weibull distribution (WWD) based on Azzalini's [5] family with statistical properties and MLE was used in parameters estimation. Sobhi and Mashail [11] discussed moments of dual generalized order statistics and characterization for transmuted exponential mode. Rezzoky and Nadhel [12] proposed a weighted generalized exponential distribution (WGED).They estimated its scale parameter by using MOM and MLE.…”

Section: Introductionmentioning

confidence: 99%

The Length-Biased Weighted Exponentiated Inverted Exponential Distribution: Properties and Estimation

El-Sherpieny

Abdel-Aziz

2023

Computational Journal of Mathematical and Statistical Sciences

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This paper introduces the length-biased weighted exponentiated inverted exponential distribution with sub models. The basic statistical properties are derived such as mean, mode, variance, reliability functions, moment generating function, characteristic function and order statistic distribution. Furthermore, maximum likelihood estimators of distribution parameters are obtained under censored Type I. Numerical study is applied. Variance-covariance matrix is obtained and Confidence intervals are calculated. Two real data sets are applied to compare performance of the proposed model with competitive distributions by using some criterions as measures of goodness fit.

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Moments of Dual Generalized Order Statistics and Characterization for Transmuted Exponential Model

Cited by 3 publications

References 14 publications

The Gull Alpha Power Lomax distributions: Properties, simulation, and applications to modeling COVID-19 mortality rates

The Gull Alpha Power Lomax distributions: Properties, simulation, and applications to modeling COVID-19 mortality rates

Bayesian and Non-Bayesian Inference for The Generalized Power Akshaya Distribution with Application in Medical

The Length-Biased Weighted Exponentiated Inverted Exponential Distribution: Properties and Estimation

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