The Burr III-Topp-Leone-G family of distributions with applications

Chipepa, Fastel; Oluyede, Broderick O.; Peter, Peter O.

doi:10.1016/j.heliyon.2021.e06534

Cited by 10 publications

(6 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, it allows for a deeper understanding of the distribution's behaviour and facilitates the analysis and interpretation of data. In particular, setting u = 0.25, 0.5, and 0.75 in Equation (13), we obtain the first (Q 1 ), second (median) (Q 2 ), and third (Q 3 ) quantiles. Moreover, based on the quantiles, Bowley's skewness (α 1 ) and Moor's kurtosis (α 2 ) are provided, respectively, by…”

Section: Quantile Functionmentioning

confidence: 99%

“…The CP is more than or equal 95.0% at γ = 0.05. 13. In almost all situations, using the MCMC under the non-IP, Sch.2 gives the lowest AL for η.…”

mentioning

confidence: 94%

“…The TL distribution and its extensions have received a lot of interest in the literature over the past few years. Among these extensions, there are the TL family of distributions introduced in [2][3][4], the transmuted TL-generated family proposed in [5], the Fréchet TL-generated family discussed in [6], the exponentiated generalized TL-generated family studied in [7], the new generalized TLgenerated family explored in [8], the type-II TL-generated family discussed in [9], the new power TL-generated family proposed in [10], the power TL distribution proposed in [11], the odd log-logistic TL-generated family explored in [12] and the Burr III-TL-generated family discussed in [13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A New Asymmetric Modified Topp–Leone Distribution: Classical and Bayesian Estimations under Progressive Type-II Censored Data with Applications

et al. 2023

View full text Add to dashboard Cite

In this article, a new modified asymmetric Topp–Leone distribution is created and developed from a theoretical and inferential point of view. It has the feature of extending the remarkable flexibility of a special one-shape-parameter lifetime distribution, known as the inverse Topp–Leone distribution, to the bounded interval [0, 1]. The probability density function of the proposed truncated distribution has the potential to be unimodal and right-skewed, with different levels of asymmetry. On the other hand, its hazard rate function can be increasingly shaped. Some important statistical properties are examined, including several different measures. In practice, the estimation of the model parameters under progressive type-II censoring is considered. To achieve this aim, the maximum likelihood, maximum product of spacings, and Bayesian approaches are used. The Markov chain Monte Carlo approach is employed to produce the Bayesian estimates under the squared error and linear exponential loss functions. Some simulation studies to evaluate these approaches are discussed. Two applications based on real-world datasets—one on the times of infection, and the second dataset is on trading economics credit rating—are considered. Thanks to its flexible asymmetric features, the new model is preferable to some known comparable models.

show abstract

Section: Quantile Functionmentioning

confidence: 99%

“…The CP is more than or equal 95.0% at γ = 0.05. 13. In almost all situations, using the MCMC under the non-IP, Sch.2 gives the lowest AL for η.…”

mentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Asymmetric Modified Topp–Leone Distribution: Classical and Bayesian Estimations under Progressive Type-II Censored Data with Applications

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The resulting distributions have found application in modeling data across various fields of study, such as environmental sciences, economics, and engineering. Some popular generators available in the literature include the exponentiated generated family by [2], the Marshall-Olkin-G by [3], the Kumaraswamy-G by [4], Beta-G by [5], Weibull-X by [6], Weibull-G by [7], the Lomax generator proposed by [8], the Topp-Leone generated family introduced by [9], the Lindley generator by [10], the Chen-G class by [11], the Burr III Topp-Leone-G by [12], the odd Burr-III family by [13], Marshall-Olkin Burr X family by [14], the Topp-Leone odd Lindley-G family by [15], and many others.…”

Section: Introductionmentioning

confidence: 99%

A New Generated Family of Distributions: Statistical Properties and Applications with Real-Life Data

Okutu,

Frempong,

Appiah

et al. 2023

Computational and Mathematical Methods

View full text Add to dashboard Cite

Several standard distributions can be used to model lifetime data. Nevertheless, a number of these datasets from diverse fields such as engineering, finance, the environment, biological sciences, and others may not fit the standard distributions. As a result, there is a need to develop new distributions that incorporate a high degree of skewness and kurtosis while improving the degree of goodness-of-fit in empirical distributions. In this study, by applying the T-X method, we proposed a new flexible generated family, the Ramos-Louzada Generator (RL-G) with some relevant statistical properties such as quantile function, raw moments, incomplete moments, measures of inequality, entropy, mean and median deviations, and the reliability parameter. The RL-G family has the ability to model “right,” “left,” and “symmetric” data as well as different shapes of the hazard function. The maximum likelihood estimation (MLE) method has been used to estimate the parameters of the RL-G. The asymptotic performance of the MLE is assessed by simulation analysis. Finally, the flexibility of the RL-G family is demonstrated through the application of three real complete datasets from rainfall, breaking stress of carbon fibers, and survival times of hypertension patients, and it is evident that the RL-Weibull, which is a special case of the RL-G family, outperformed its submodels and other distributions.

show abstract

“…ey have also discussed some special models of the OGHLW-G family to show the importance of the new models. Chipepa et al [8] also proposed the Burr III-Topp-Leone-G family of distributions for analyzing (i) carbon bres data, (ii) fracture toughness of silicon nitride data, and (iii) turbocharger failure times data.…”

Section: Introductionmentioning

confidence: 99%

A New Generalized- $X$ Family for Analyzing the COVID-19 Data Set: a Case Study

Yue

Zhou

Tekle³

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Nowadays, researchers in applied sectors are highly motivated to propose and study new generalizations of the existing distributions to provide the best fit to data. To provide a close fit to data in numerous sectors, a series of new distributions have been proposed. In this study, we propose a new family called the new generalized- X (for short, “NG- X ”) family of distributions. Based on the NG- X method, a novel modification of the Weibull model called the new generalized-Weibull (for short, “NG-Weibull”) distribution is studied. The heavy-tailed characteristics of the NG- X distributions are derived. The maximum likelihood estimators of the NG- X distributions are also obtained. Based on the special case (i.e., NG-Weibull) of the NG- X family, a simulation study is provided. The practical performance of the new NG-Weibull model is assessed by analyzing the COVID-19 data set. The fitting results of the NG-Weibull model are compared with three other competing models. Based on certain statistical measures, it is observed that the NG-Weibull model is the best competitive model.

show abstract

The Burr III-Topp-Leone-G family of distributions with applications

Cited by 10 publications

References 24 publications

A New Asymmetric Modified Topp–Leone Distribution: Classical and Bayesian Estimations under Progressive Type-II Censored Data with Applications

A New Asymmetric Modified Topp–Leone Distribution: Classical and Bayesian Estimations under Progressive Type-II Censored Data with Applications

A New Generated Family of Distributions: Statistical Properties and Applications with Real-Life Data

A New Generalized- $X$ Family for Analyzing the COVID-19 Data Set: a Case Study

Contact Info

Product

Resources

About

The Burr III-Topp-Leone-G family of distributions with applications

Cited by 10 publications

References 24 publications

A New Asymmetric Modified Topp–Leone Distribution: Classical and Bayesian Estimations under Progressive Type-II Censored Data with Applications

A New Asymmetric Modified Topp–Leone Distribution: Classical and Bayesian Estimations under Progressive Type-II Censored Data with Applications

A New Generated Family of Distributions: Statistical Properties and Applications with Real-Life Data

A New Generalized- X Family for Analyzing the COVID-19 Data Set: a Case Study

Contact Info

Product

Resources

About

A New Generalized- $X$ Family for Analyzing the COVID-19 Data Set: a Case Study