A weighted Topp-Leone G family of distributions: properties, applications for modelling reliability data and different method of estimation

Hashempour‎, Majid

doi:10.15672/hujms.795721

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…Generalizations of the TL distribution have been shown to be beneficial in a variety of disciplines. Many notable academics have made significant attempts to suggest new generalized and developed modifications of the TL model, for example, TL inverse Weibull distribution [2], Type I half-Logistic TL distribution [3], TL geometric distribution [4], truncated Cauchy power inverted TL distribution [5], TL Nadarajah-Haghighi distribution [6], power inverted TL distribution [7], TL linear exponential distribution [8], Kumaraswamy inverted TL distribution [9], new power TL family [10], alpha power inverted TL distribution [11], half-logistic inverted TL distribution [12], type II Power TL family [13], odd log-logistic TL family [14], TL odd Fréchet distribution [15], Burr III-TL family [16], inverse TL distribution [17], exponentiated generalized TL family [18], transmuted TL power function distribution [19], transmuted TL family [20], sine TL family [21], weighted TL family [22], TL inverse Lomax distribution [23], and new weighted TL family [24], among others.…”

Section: Introductionmentioning

confidence: 99%

Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications

Alotaibi

Al-Moisheer

Elbatal

et al. 2023

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In this article, we intend to introduce and study a new two-parameter distribution as a new extension of the power Topp–Leone (PTL) distribution called the Kavya–Manoharan PTL (KMPTL) distribution. Several mathematical and statistical features of the KMPTL distribution, such as the quantile function, moments, generating function, and incomplete moments, are calculated. Some measures of entropy are investigated. The cumulative residual Rényi entropy (CRRE) is calculated. To estimate the parameters of the KMPTL distribution, both maximum likelihood and Bayesian estimation methods are used under simple random sample (SRS) and ranked set sampling (RSS). The simulation study was performed to be able to verify the model parameters of the KMPTL distribution using SRS and RSS to demonstrate that RSS is more efficient than SRS. We demonstrated that the KMPTL distribution has more flexibility than the PTL distribution and the other nine competitive statistical distributions: PTL, unit-Gompertz, unit-Lindley, Topp–Leone, unit generalized log Burr XII, unit exponential Pareto, Kumaraswamy, beta, Marshall-Olkin Kumaraswamy distributions employing two real-world datasets.

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Section: Introductionmentioning

confidence: 99%

Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications

Alotaibi

Al-Moisheer

Elbatal

et al. 2023

Axioms

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On some mixtures of the Kies distribution

Zaevski,

Kyurkchiev

2024

Hacettepe Journal of Mathematics and Statistics

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The purpose of this paper is to explore some mixtures, discrete and continuous, based on the Kies distribution. Some conditions for convergence are established. We study the probabilistic properties of these mixtures. Special attention is taken to the so-called Hausdorff saturation. Several models are examined in detail – bimodal, multimodal, and mixtures based on binomial, geometric, exponential, gamma, and beta distributions. We provide some numerical experiments for real-life tasks – one for the Standard and Poor’s 500 financial index and another for unemployment insurance issues. In addition, we check the consistency of the proposed estimator using generated data of different sizes.

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A novel weighted family of probability distributions with applications to world natural gas, oil, and gold reserves

Hassan,

Alsadat,

Chesneau

et al. 2023

MBE

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<abstract><p>Recent innovations have focused on the creation of new families that extend well-known distributions while providing a huge amount of practical flexibility for data modeling. Weighted distributions offer an effective approach for addressing model building and data interpretation problems. The main objective of this work is to provide a novel family based on a weighted generator called the length-biased truncated Lomax-generated (LBTLo-G) family. Discussions are held about the characteristics of the LBTLo-G family, including expressions for the probability density function, moments, and incomplete moments. In addition, different measures of uncertainty are determined. We provide four new sub-distributions and investigated their functionalities. Subsequently, a statistical analysis is given. The LBTLo-G family's parameter estimation is carried out using the maximum likelihood technique on the basis of full and censored samples. Simulation research is conducted to determine the parameters of the LBTLo Weibull (LBTLoW) distribution. Four genuine data sets are considered to illustrate the fitting behavior of the LBTLoW distribution. In each case, the application outcomes demonstrate that the LBTLoW distribution can, in fact, fit the data more accurately than other rival distributions.</p></abstract>

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A weighted Topp-Leone G family of distributions: properties, applications for modelling reliability data and different method of estimation

Cited by 3 publications

References 33 publications

Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications

Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications

On some mixtures of the Kies distribution

A novel weighted family of probability distributions with applications to world natural gas, oil, and gold reserves

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