An Innovative Method for Generating Distributions: Applied to Weibull Distribution

Lone, Murtiza Ali; Dar, Ishfaq Hassain; Jan, T. R.

doi:10.37398/jsr.2022.660336

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…This flexibility can be obtained in a straightforward manner by including additional parameters such as location, scale and shape. There are several generalized (or G) classes that have recently emerged in the literature, including the Weibull-G family proposed by Bourguignon et al 12 , Weighted Weibull-G family of distributions by Hassan et al 13 , Kumaraswamy-G family of distributions developed Cordeiro and de Castro 14 , two innovative methods for generating probability models with application to Weibull distribution were proposed by Lone et al 15 , 16 .…”

Section: Introductionmentioning

confidence: 99%

A novel extension of half-logistic distribution with statistical inference, estimation and applications

Bhat,

Ahmad,

Gemeay

et al. 2024

Sci Rep

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In the present study, we develop and investigate the odd Frechet Half-Logistic (OFHL) distribution that was developed by incorporating the half-logistic and odd Frechet-G family. The OFHL model has very adaptable probability functions: decreasing, increasing, bathtub and inverted U shapes are shown for the hazard rate functions, illustrating the model’s capacity for flexibility. A comprehensive account of the mathematical and statistical properties of the proposed model is presented. In estimation viewpoint, six distinct estimation methodologies are used to estimate the unknown parameters of the OFHL model. Furthermore, an extensive Monte Carlo simulation analysis is used to evaluate the effectiveness of these estimators. Finally, two applications to real data are used to demonstrate the versatility of the suggested method, and the comparison is made with the half-logistic and some of its well-known extensions. The actual implementation shows that the suggested model performs better than competing models.

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Section: Introductionmentioning

confidence: 99%

A novel extension of half-logistic distribution with statistical inference, estimation and applications

Bhat,

Ahmad,

Gemeay

et al. 2024

Sci Rep

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“…Similarly, Kumaraswamy (Kumaraswamy) introduced a novel methodology involving the addition of two shape parameters, further enriching the landscape of distributional possibilities. Additionally, Lone et al, Lone et al (2022Lone et al ( , 2024 introduced a new method and applied it to the Weibull distribution. Recenlty, Ahmad et al (2024) proposed another method based on trigonometric functions.…”

Section: Introductionmentioning

confidence: 99%

A new class of probability distributions with an application in engineering science

Hassan,

Dar,

Lone

2024

Pak.j.stat.oper.res.

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In this manuscript, we introduced a new class of probability distributions called new exponentiated transformation(NET) that adds more flexibility to any baseline distribution without adding the complexity of an extra parameter. NET is then specialised on exponentiated exponential distribution and a new exponentiated exponential( NEE) distribution is obtained. The NEE distribution has wider flexibility in terms of density function and also has increasing, decreasing and bathtub hazard rate function. Several mathematical properties of NEE distribution are also highlighted. For applicability of proposed distribution, two engineering data sets are considered and it is sensed that NEE leads to a better fit than all models taken under consideration

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Exponentiated Power Inverse Lomax Distribution with Applications

Rasool,

Ahmad

2024

Punjab Univ. j. math.

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The manuscript presents a novel distribution derived from the exponentiation technique called the Exponentiated Power Inverse Lomax Distribution (EPILD), which offers a generalized approach to the inverse Lomax distribution. To show the importance of the EPILD, we establish various mathematical properties including survival function, hazard rate, order statistics, entropy measures, r-th moment, and generating functions. To obtain the parameter estimates for the proposed model, we employed the maximum likelihood estimation(MLE) approach. The adaptability of the new model is evaluated by comparing it with well-known distributions using real-life data sets. In addition to real-life data sets, the flexibility of the model is also shown via a simulation study. We apply goodness of fit statistics, various model selection criteria, and graphical tools to examine the adequacy of the EPILD.

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An Innovative Method for Generating Distributions: Applied to Weibull Distribution

Cited by 3 publications

References 14 publications

A novel extension of half-logistic distribution with statistical inference, estimation and applications

A novel extension of half-logistic distribution with statistical inference, estimation and applications

A new class of probability distributions with an application in engineering science

Exponentiated Power Inverse Lomax Distribution with Applications

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