On the Extension of the Burr XII Distribution: Applications and Regression

Ocloo, Selasi Kwaku; Brew, Lewis; NASIRU, SULEMAN; Odoi, Benjamin

doi:10.21608/cjmss.2023.181739.1000

Cited by 12 publications

(8 citation statements)

References 19 publications

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“…Te study of stressstrength reliability in light of the ranked set sampling (RSS) technique has recently captured the interest of multiple writers due to its application in a variety of felds. Terefore, in our upcoming work, we want to address the problem of stress-strength estimation for a certain distribution in the class using the RSS method [26][27][28], and also, for applications of lifetime data [29][30][31].…”

Section: Discussionmentioning

confidence: 99%

A Compound Class of Unit Burr XII Model: Theory, Estimation, Fuzzy, and Application

Zayed

Hassan

Almetwally

et al. 2023

Scientific Programming

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The current research offers an enhanced three-parameter lifetime model that combines the unit Burr XII distribution with a power series distribution. The novel class of distribution is named the unit Burr XII power series (UBXIIPS). This compounding technique allows for the production of flexible distributions with strong physical meanings in domains such as biology and engineering. The UBXIIPS class includes the unit Burr XII Poisson (UBXIIP) distribution, the unit Burr XII binomial distribution, the unit Burr XII geometric distribution, and the unit Burr XII negative binomial distribution. The statistical properties of the class include formulas for the density and cumulative distribution functions, and limiting behaviour, moments and incomplete moments, entropy measures, and quantile function are provided. For estimating population parameters and fuzzy reliability for the UBXIIP model, maximum likelihood and Bayesian approaches are studied by the Metropolis–Hastings algorithm. For maximum likelihood estimators, the length of asymptotic confidence intervals is specified, whereas, for Bayesian estimators, the length of credible confidence intervals is assigned. A simulation investigation of the UBXIIP model was established to evaluate the performance of suggested estimates. In addition, the UBXIIP distribution is explored using real-world data. The UBXIIP distribution appears to offer some benefits in understanding lifetime data when compared to unit Weibull, beta, Kumaraswamy, Kumaraswamy Kumaraswamy, Marshall-Olkin Kumaraswamy, and Topp–Leone Weibull Lomax distributions.

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Section: Discussionmentioning

confidence: 99%

A Compound Class of Unit Burr XII Model: Theory, Estimation, Fuzzy, and Application

Zayed

Hassan

Almetwally

et al. 2023

Scientific Programming

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“…Te precipitation (in inches) in the Minneapolis dataset was used in [30,31]. Te second dataset represents runof amounts at Jug Bridge, Maryland, and was used by Makubate et al [32].…”

Section: Applicationsmentioning

confidence: 99%

New Weighted Burr XII Distribution: Statistical Properties, Applications, and Regression

Anafo,

Ocloo,

Nasiru

2024

International Journal of Mathematics and Mathematical Sciences

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In this study, a three-parameter modification of the Burr XII distribution has been developed through the integration of the weighted version of the alpha power transformation family of distributions. This newly introduced model, termed the modified alpha power-transformed Burr XII distribution, exhibits the unique ability to effectively model decreasing, right-skewed, or unimodal densities. The paper systematically elucidates various statistical properties of the proposed distribution. The estimation of parameters was obtained using maximum likelihood estimation. The estimator has been evaluated for consistency through simulation studies. To gauge the practical applicability of the proposed distribution, two distinct datasets have been employed. Comparative analyses involving six alternative distributions unequivocally demonstrate that the modified alpha power-transformed Burr XII distribution provides a better fit. Additionally, a noteworthy extension is introduced in the form of a location-scale regression model known as the log-modified alpha power-transformed Burr XII model. This model is subsequently applied to a dataset related to stock market liquidity. The findings underscore the enhanced fitting capabilities of the proposed model in comparison to existing distributions, providing valuable insights for applications in financial modelling and analysis.

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“…The parameters of the CBHE distribution are estimated in this section using maximum likelihood, maximum product spacing, ordinary least squares, weighted least squares, Cramér-von Mises, percentile and Anderson-Darling estimation methods. Recently papers have been discussed the estimation methods for parameter of distribution modeling as [13,14,15].…”

Section: Parameter Estimationmentioning

confidence: 99%

Chen Burr-Hatke Exponential Distribution: Properties, Regressions and Biomedical Applications

Abubakari¹,

Anzagra

Nasiru³

2023

Computational Journal of Mathematical and Statistical Sciences

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Accurately modeling lifetime data is very important for appropriate decision making in health and biomedical fields. This usually requires the use of distributions. However, no single distribution can model all types of data. Hence, the development of distributions with appropriate usefulness is very important for modeling purposes. In this study, a new lifetime distribution, known as Chen Burr-Hatke exponential distribution is proposed. The objective of the study is to obtain a new lifetime distribution which can serve as an alternative distribution to modeling lifetime data. Also, such a distribution can be used to provide inferences via regression models. Plots of the density function of the new distribution show that the distribution can exhibit increasing, decreasing, right-skewed and left-skewed shapes. Also, plots of the hazard rate function show that the distribution can exhibit increasing, decreasing, and upside down bathtub shapes. Statistical properties, such as the quantile function, moments, order statistics and inequality measures, are derived. Several estimation methods are used to estimate the parameters of the distribution. Using Monte Carlo simulations, the estimators were all consistent. However, maximum likelihood estimation method was observed to better estimate the parameters of the distribution. Two regression models based on the distribution are established. The usefulness of the distribution and its regression models are demonstrated using real lifetime datasets. The results show that the models can provide a good fit to lifetime data, and hence can serve as alternative models to fitting such data.

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On the Extension of the Burr XII Distribution: Applications and Regression

Cited by 12 publications

References 19 publications

A Compound Class of Unit Burr XII Model: Theory, Estimation, Fuzzy, and Application

A Compound Class of Unit Burr XII Model: Theory, Estimation, Fuzzy, and Application

New Weighted Burr XII Distribution: Statistical Properties, Applications, and Regression

Chen Burr-Hatke Exponential Distribution: Properties, Regressions and Biomedical Applications

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