On the Gumbel-Burr XII Distribution: Regression and Application

Al-Aqtash, Raid; Mallick, Avishek; Hamedani, G. G.; Aldeni, Mahmoud

doi:10.5539/ijsp.v10n6p31

Cited by 5 publications

(3 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results from LMOW-W model are compared with some alternative regression models, namely; the log-Weibull (LW) in [ 45 ], the log-gamma-Weibull (LGW) in [ 46 ], the Kumaraswamy-log-logistic (KumL) [ 47 ], the log-modified Weibull (LMW) in [ 48 ], the log-generalized modified Weibull (LGMW) in [ 49 ] and the log-Pareto Weibull generalized lambda (LPWGL) in [ 50 ].…”

Section: Regression Modelingmentioning

confidence: 99%

A new generalized family of distributions based on combining Marshal-Olkin transformation with T-X family

Klakattawi¹,

Alsulami²,

Elaal³

et al. 2022

PLoS ONE

View full text Add to dashboard Cite

Data analysis in real life often relies mainly on statistical probability distributions. However, data arising from different fields such as environmental, financial, biomedical sciences and other areas may not fit the classical distributions. Therefore, the need arises for developing new distributions that would capture high degree of skewness and kurtosis and enhance the goodness-of-fit in empirical distribution. In this paper, we introduce a novel family of distributions which can extend some popular classes of distributions to include different new versions of the baseline distributions. The proposed family of distributions is referred as the Marshall-Olkin Weibull generated family. The proposed family of distributions is a combination of Marshall-Olkin transformation and the Weibull generated family. Two special members of the proposed family are investigated. A variety of shapes for the densities and hazard rate are presented of the considered sub-models. Some of the main mathematical properties of this family are derived. The estimation for the parameters is obtained via the maximum likelihood method. Moreover, the performance of the estimators for the considered members is examined through simulation studies in terms of bias and root mean square error. Besides, based on the new generated family, the log Marshall-Olkin Weibull-Weibull regression model for censored data is proposed. Finally, COVID-19 data and three lifetime data sets are used to demonstrate the importance of the newly proposed family. Through such an applications, it is shown that this family of distributions provides a better fit when compared with other competitive distributions.

show abstract

Section: Regression Modelingmentioning

confidence: 99%

A new generalized family of distributions based on combining Marshal-Olkin transformation with T-X family

Klakattawi¹,

Alsulami²,

Elaal³

et al. 2022

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…bus.wisc.edu/jfrees/jfreesbooks/Regression20Modeling/ BookWebDec2010/data.html (accessed on 8 January 2023). Te competing models are the log-harmonic mixture Burr XII (LHMBXII) distribution [31] and the log-Gumbel Burr XII (LGBXII) distribution [38]. Te response variable y j is the total number of shares that were traded on an exchange during a specifc period (volume), while the covariate is the number of shares outstanding as of December 31, 1984, expressed in millions of shares (shares) (z j1 ).…”

Section: Application Of Modifed Alpha Power Transformed Burr XII Regr...mentioning

confidence: 99%

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

Anafo,

Ocloo,

Nasiru

2024

International Journal of Mathematics and Mathematical Sciences

View full text Add to dashboard Cite

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.

show abstract

“…The LHMBXII model was applied to a real data set used by [23] and compared to the log-Weibull Burr XII (LWBXII) distribution [6] and the log-Gumbel Burr XII (LGBXII) distribution [24]. The data set was retrieved from http://www.leg.ufpr.br/doku.php/publications: papercompanions:multquasibeta (accessed on 13 December, 2022).…”

Section: Application Of Log-harmonic Mixture Burr XII Regression Modelmentioning

confidence: 99%

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

Ocloo

Brew

NASIRU³

et al. 2023

Computational Journal of Mathematical and Statistical Sciences

View full text Add to dashboard Cite

In this paper, we introduce a new four-parameter mixture distribution called the Harmonic Mixture Burr XII distribution. The proposed model can be used to model data which exhibit bimodal shapes or are heavy-tailed. Specific properties like non-central and incomplete moments, quantile function, entropy, mean and median deviation, mean residual life, moment generating function, and stressstrength reliability are derived. Maximum likelihood estimation, ordinary least squares estimation, weighted least squares estimation, Cramér-von Mises estimation, and Anderson-Darling estimation methods were used to estimate the parameters of the distribution. Simulation studies was performed to assess the estimators and the maximum likelihood estimation was adjudged the best estimator. Using three sets of lifetime data, the empirical importance of the new distribution was determined. When compared to nine (9) extensions of the Burr XII distribution, it was clear that the proposed distribution fit the data better. Using the proposed model, a log-linear regression model called the log-harmonic mixture Burr XII is proposed.

show abstract

On the Gumbel-Burr XII Distribution: Regression and Application

Cited by 5 publications

References 29 publications

A new generalized family of distributions based on combining Marshal-Olkin transformation with T-X family

A new generalized family of distributions based on combining Marshal-Olkin transformation with T-X family

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

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

Contact Info

Product

Resources

About