A weighted general family of distributions: Theory and practice

Bakouch, Hassan S.; Chesneau, Christophe; Enany, Mai G.

doi:10.1002/cmm4.1135

Cited by 9 publications

(7 citation statements)

References 23 publications

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“…Let 𝑥 = ∑ 𝑛 𝑖=1 (𝑥 𝑖 − 𝑥) 2 . By equating these values with the theoretical moments, we have the estimates of 𝛼 and 𝛿 as:…”

Section: Methods Of Momentsmentioning

confidence: 99%

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A weighted‐Weibull distribution: Properties and applications

Xavier,

Nadarajah

2023

Quality & Reliability Eng

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The paper describes a two parameter model and its relationship to the widely used Weibull model. Mathematical properties of the distribution like survival and hazard functions, moments, harmonic and geometric means, Shannon entropy and mean residual life are derived. Different methods of estimation are discussed and a simulation study is performed to verify the efficiency of estimation methods. Applications of our distribution in different scenarios observed in real life are illustrated.

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“…Let 𝑥 = ∑ 𝑛 𝑖=1 (𝑥 𝑖 − 𝑥) 2 . By equating these values with the theoretical moments, we have the estimates of 𝛼 and 𝛿 as:…”

Section: Methods Of Momentsmentioning

confidence: 99%

“…The reason being that the later has closed form expressions for the survival and hazard functions, whereas the former needs numerical integration. For details on the Weibull distribution, see Murthy et al 1 Bakouch et al 2 developed a weighted general family of distributions. We consider a density function of the following type:…”

Section: Introductionmentioning

confidence: 99%

A weighted‐Weibull distribution: Properties and applications

Xavier,

Nadarajah

2023

Quality & Reliability Eng

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“…In this section, we define the CDF and the PDF of ExRK distribution, respectively, by using the WD-G family of [10] and CDF in equation (1) as follows: 2 Complexity…”

Section: Formulation Of Exrk Distributionmentioning

confidence: 99%

“…Our motivation for developing a new flexible version of the RKD, which we refer to as the extended reduced Kies distribution (ExRKD), is to provide greater flexibility in fitting real-world data sets. Furthermore, the article's main objectives are as follows: e first objective is dedicated to the investigation of a novel version of the RKD based on the weighted-G (WD-G) family [10], which is referred to as the ExRKD.…”

Section: Introductionmentioning

confidence: 99%

A Flexible Extension of Reduced Kies Distribution: Properties, Inference, and Applications in Biology

et al. 2022

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The extended reduced Kies distribution (ExRKD), which is an asymmetric flexible extension of the reduced Kies distribution, is the subject of this research. Some of its most basic mathematical properties are deduced from its formal definitions. We computed the ExRKD parameters using eight well-known methods. A full simulation analysis was done that allows the study of these estimators’ asymptotic behavior. The efficiency and applicability of the ExRKD are investigated via the modeling of COVID-19 and milk data sets, which demonstrates that the ExRKD delivers a better match to the data sets when compared to competing models.

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“…In this section we define the formulation of the proposed model. Using the cumulative distribution function (CDF) of the WD-G [20], so we can define the CDF of the two-parameter WBHD as follows…”

Section: Formulation Of the Wbhdmentioning

confidence: 99%

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

Aldallal

Gemeay²,

Hussam³

et al. 2022

PLoS ONE

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The objective of this study is to construct a new distribution known as the weighted Burr–Hatke distribution (WBHD). The PDF and CDF of the WBHD are derived in a closed form. Moments, incomplete moments, and the quantile function of the proposed distribution are derived mathematically. Eleven estimate techniques for estimating the distribution parameters are discussed, and numerical simulations are utilised to evaluate the various approaches using partial and overall rankings. According to the findings of this study, it is recommended that the maximum product of spacing (MPSE) estimator of the WBHD is the best estimator according to overall rank table. The actuarial measurements were derived to the suggested distribution. By contrasting the WBHD with other competitive distributions using two different actual data sets collected from the COVID-19 mortality rates, we show the importance and flexibility of the WBHD.

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A weighted general family of distributions: Theory and practice

Cited by 9 publications

References 23 publications

A weighted‐Weibull distribution: Properties and applications

A weighted‐Weibull distribution: Properties and applications

A Flexible Extension of Reduced Kies Distribution: Properties, Inference, and Applications in Biology

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

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