Discrete Inverted Nadarajah-Haghighi Distribution: Properties and Classical Estimation with Application to Complete and Censored data

A novel discrete exponentiated Chen (DEC) distribution, which is a subset of the continuous exponentiated Chen distribution, is proposed. The offered model is more adaptable to analyzing a wide range of data than traditional and recently published models. Several important statistical and reliability characteristics of the DEC model are introduced. In the presence of Type-II censored data, the maximum likelihood and asymptotic confidence interval estimators of the model parameters are acquired. Two various bootstrapping estimators of the DEC parameters are also obtained. To examine the efficacy of the adopted methods, several simulations are implemented. To further clarify the offered model in the life scenario, the two applications, based on the number of vehicle fatalities in South Carolina in 2012 and the final exam marks in 2004 at the Indian Institute of Technology at Kanpur, are analyzed. The analysis findings showed that the DEC model is the most effective model for fitting the supplied data sets compared to eleven well-known models in literature, including: Poisson, geometric, negative binomial, discrete-Weibull, discrete Burr Type XII, discrete generalized exponential, discrete-gamma, discrete Burr Hatke, discrete Nadarajah-Haghighi, discrete modified-Weibull, and exponentiated discrete-Weibull models. Ultimately, the new model is recommended to be applied in many fields of real practice.

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“…A discrete equivalent of the Teissier distribution with application to data counting was recently studied by ref. [16].…”

Section: Introductionmentioning

confidence: 99%

The Discrete Exponentiated-Chen Model and Its Applications

et al. 2023

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On the discrete analogue of the Teissier distribution and its associated INAR(1) process

Irshad

Jodrá

Krishna

et al. 2023

Mathematics and Computers in Simulation

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A new (T-X$$^\theta$$) family of distributions: properties, discretization and estimation with applications

Mandouh,

Mahmoud,

Abdelatty

2024

Sci Rep

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In this paper, a new class of distributions called the T-X$$^\theta$$ θ family of distributions for bounded—(0,1)—and unbounded—$$(0,\infty )$$ ( 0 , ∞ ) —supported random variables is suggested. Some special sub-models of the proposed family are utilized. A new sub-model is selected to be studied in details. The statistical properties of the suggested family including quantile function, moments, moment generating function, order statistics and Rényi entropy are discussed. The maximum likelihood method is provided to estimate the parameters of the distribution and a Monte Carlo simulation study is used. The discretized T-X$$^\theta$$ θ family provided many sub-families and sub-models. In addition, eight real data sets are utilized to demonstrate the flexibility of the proposed continuous and discrete family’s multiple sub models.

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Discrete Inverted Nadarajah-Haghighi Distribution: Properties and Classical Estimation with Application to Complete and Censored data

Cited by 7 publications

References 26 publications

The Discrete Exponentiated-Chen Model and Its Applications

The Discrete Exponentiated-Chen Model and Its Applications

On the discrete analogue of the Teissier distribution and its associated INAR(1) process

A new (T-X$$^\theta$$) family of distributions: properties, discretization and estimation with applications

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