A New Class of Generalized Modified Weibull Distribution with Applications

Oluyede, Broderick O.; Huang, Shujiao; Yang, Tiantian

doi:10.17713/ajs.v44i3.36

Cited by 10 publications

(9 citation statements)

References 48 publications

(47 reference statements)

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“…Last but not least, Oluyede et al. (2014) evaluated the 5‐parameter generalized Dagum distribution positively against 3–4 parameter alternatives on US baseball players’ salaries.…”

Section: Discussionmentioning

confidence: 99%

Parametric representation of the top of income distributions: Options, historical evidence, and model selection

Hlásny

2021

Journal of Economic Surveys

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Empirical distributions of top incomes suffer from statistical problems affecting the measurement of inequality and its trend. Researchers and practitioners have been increasingly noting parametric regularities across income distributions and turning to parametric functions to approximate or supplement the observed distributions, both for descriptive purposes and for correcting distributional statistics derived from data. The proliferation of distinct branches of modeling literature has highlighted the need to compare the alternative modeling options, and develop systematic tools to discriminate between them. This paper reviews the state of methodological and empirical knowledge regarding the adoptable parametric functions, and lists references and statistical programs allowing practitioners to apply these models to microdata in household surveys and administrative registers, or grouped‐records data from national accounts statistics. Implications for modeling the distributions of other economic outcomes including consumption and wealth, and incomes below the topmost tail, are drawn. For incomes, a handful of distribution functions hold promise for modeling the top tails based on theoretical and empirical properties—namely the extreme values distributions, the generalized Pareto, the Singh–Maddala and the generalized beta type 2. Understanding these functions in relation to other commonly invoked alternatives is a contribution of this review.

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“…Last but not least, Oluyede et al. (2014) evaluated the 5‐parameter generalized Dagum distribution positively against 3–4 parameter alternatives on US baseball players’ salaries.…”

Section: Discussionmentioning

confidence: 99%

Parametric representation of the top of income distributions: Options, historical evidence, and model selection

Hlásny

2021

Journal of Economic Surveys

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“…This section demonstrates the applicability of the proposed GOBPW distribution using four practical data sets involving cancer-related diseases, including bladder, acute bone, neck and head, as well as blood cancers. The performance of the GOBPW distribution is evaluated and compared with the other competing models also based the Weibull distribution with five parameters, including the beta modified Weibull (BMW) distribution by [102], Kumaraswamy modified Weibull (KumMW) distribution by [103], gamma generalized modified Weibull (GGMW) distribution by [104], gamma log-logistic Weibull (GLLoGW) distribution by [105], and beta log-logistic Weibull (BLLoGW) distribution by [106].…”

Section: Applications To Cancer Disease Data Setsmentioning

confidence: 99%

A New Statistical Model Based on the Novel Generalized Odd Beta Prime Family of Continuous Probability Distributions with Applications to Cancer Disease Data Sets

Suleiman¹,

Othman²,

Ishaq³

et al. 2022

Preprint

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Statistical modeling of lifetime data plays an essential role in a wide range of practical fields, such as health and engineering. There have been a lot of studies done to develop statistical models that can better describe health data than traditional models. For the first time, we pioneer a novel family of continuous probability distributions called the generalized odd beta prime generalized (GOBP-G) family of distributions. The cumulative distribution and probability density functions of the new family are presented. A new generalization of the Weibull distribution called "generalized odd beta prime-Weibull" (GOBPW) is proposed using the pioneered GOBP-G family. The mixture representations of the new distribution are defined and derived. Some formal statistical properties of the GOBPW distribution, such as the moments, moment generating function, incomplete moments, information generating function, entropies, stress-strength function, quantile function, and order statistics, are derived. The estimation of the parameters of the proposed distribution is evaluated using the maximum likelihood estimation approach. Different cancer disease data sets, such as the bladder, head and neck, acute bone, and blood cancers, are used to illustrate the applicability and usefulness of the new model and were compared using several statistical accuracy measures with that of well-established extended Weibull distributions, which are the beta modified Weibull distribution, Kumaraswamy modified Weibull distribution, gamma generalized modified Weibull distribution, gamma log-logistic Weibull distribution, and beta log-logistic Weibull distribution. The results show that the proposed model gives better results than the competitive models. This study could guide the relevant stakeholders in choosing a suitable statistical model for the health data instead of relying on traditional models to enhance decision-making.

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“…We also compared the GWW and GWU distributions with the gamma generalized modified Weibull (GGMW) (Oluyede, Huang, and Yang (2015)) and gamma modified Weibull (GMW) distributions, respectively. The pdf of the GGMW distribution (Oluyede et al 2015) is given by…”

Section: Applicationsmentioning

confidence: 99%

The Gamma-Weibull-G Family of Distributions with Applications

Oluyede

2018

AJS

Self Cite

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Weibull distribution and its extended families has been widely studied in lifetime applications. Based on the Weibull-G family of distributions and the exponentiated Weibull distribution, we study in detail this new class of distributions, namely, Gamma-Weibull-G (GWG) family of distributions. Some special models in the new class are discussed. Statistical properties of the family of distributions, such as expansion of density function, hazard and reverse hazard functions, quantile function, moments, incomplete moments, generating functions, mean deviations, Bonferroni and Lorenz curves and order statistics are presented. We also present Rényi entropy, estimation of parameters by using method of maximum likelihood, asymptotic confidence intervals and applications using real data sets.

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A New Class of Generalized Modified Weibull Distribution with Applications

Cited by 10 publications

References 48 publications

Parametric representation of the top of income distributions: Options, historical evidence, and model selection

Parametric representation of the top of income distributions: Options, historical evidence, and model selection

A New Statistical Model Based on the Novel Generalized Odd Beta Prime Family of Continuous Probability Distributions with Applications to Cancer Disease Data Sets

The Gamma-Weibull-G Family of Distributions with Applications

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