The Exponential Modified Weibull Logistic Distribution (Emwl)

Nassar, Mohamed A.; Radwan, S.; Elmasry, A.

doi:10.53555/eijms.v4i1.14

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This section illustrates the performance of the new OBP-logistic model against several competitive models using data from gas fiber (GF), carbon fiber (CF) and magnesium concentrations (MC). The fitting flexibility of the OBP-logistic distribution is measured by comparing it to the gamma generalized logistic (GGL) distribution [74], new modified exponential logistic (NMEL) distribution [75], gamma-logistic (GL) distribution [45], exponential modified Weibull logistic (EMWL) distribution [76], exponentiated Weibull logistic (EWL) distribution [77], and transmuted Weibull logistic (TWL) distribution [78] using the statistical accuracy measures, such as the minimized (− l), the Akaike information criterion (AIC), Bayesian information criterion (BIC), Cramer-von Mises (CM), and Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) statistics. Given the competitive models, the suitable model is the one that provides the lowest values of the aforementioned measures [79,80].…”

Section: Applicationsmentioning

confidence: 99%

A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

et al. 2023

View full text Add to dashboard Cite

In parametric statistical modeling, it is important to construct new extensions of existing probability distributions (PDs) that can make modeling data more flexible and help stakeholders make better decisions. In the present study, a new family of probability distributions (FPDs) called the odd beta prime generalized (OBP-G) FPDs is proposed to improve the traditional PDs. A new PD called the odd beta prime-logistic (OBP-logistic) distribution has been developed based on the developed OBP-G FPDs. Some desirable mathematical properties of the proposed OBP-logistic distribution, including the moments, moment-generating function, information-generating function, quantile function, stress–strength, order statistics, and entropies, are studied and derived. The proposed OBP-logistic distribution’s parameters are determined by adopting the maximum likelihood estimation (MLE) method. The applicability of the new PD was demonstrated by employing three data sets and these were compared by the known extended logistic distributions, such as the gamma generalized logistic distribution, new modified exponential logistic distribution, gamma-logistic distribution, exponential modified Weibull logistic distribution, exponentiated Weibull logistic distribution, and transmuted Weibull logistic distribution. The findings reveal that the studied distribution provides better results than the competing PDs. The empirical results showed that the new OBP-logistic distribution performs better than the other PDs based on several statistical metrics. We hoped that the newly constructed OBP-logistic distribution would be an alternative to other well-known extended logistic distributions for the statistical modeling of symmetric and skewed data sets.

show abstract

Section: Applicationsmentioning

confidence: 99%

A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

et al. 2023

View full text Add to dashboard Cite

show abstract

A Better Approach to Generating Random Numbers

Nachandiya

Mamza

2019

Math. J. Interdiscip. Sci.

View full text Add to dashboard Cite

The term random number has been used by many scholars to explain the behaviour of a stochastic system. Many of such scholars with statistical or mathematical background view it as an organized set of numbers produced by a function in a numerical way in which the next number to be produced is unknown or unpredictable. This paper produced software that generates a sequence of random number and also compared the algorithm with the commonly used method of random number generator. The three most common methods selected were the Mid Square method, Fibonacci method and Linear Congruential Generator Method (LCG). The result shows that the LCG provides a more acceptable result in terms of speed, long cycle, uniformity and independenceApplications of this random numbers can be seen in Monte Carlo simulations, simulation or modelling, password generation, cryptography, and online games.

show abstract

The Exponential Modified Weibull Logistic Distribution (Emwl)

Cited by 2 publications

References 4 publications

A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

A Better Approach to Generating Random Numbers

Contact Info

Product

Resources

About