On Neutrosophic Extension of the Maxwell Model: Properties and Applications

Abstract

This work presents the neutrosophic Maxwell distribution (NMD) as a novel probability distribution. The proposed model represents a generalized design of Maxwell distribution that provides more analytical flexibility for data, including all imprecise observations or some degree of vagueness within the dataset. Important reliability characteristics and distributional properties of NMD are developed under the notion of neutrosophy. The neutrosophic forms of some commonly used functions in applied statistics such as mean, variance, moment generating function, and shape coefficients are explored. In view of uncertainties involved in the processing data and indeterminacy in the defined parameters, an estimation framework using the maximum likelihood approach is established. Additionally, the quantile function is developed to validate the distributional properties of NMD. The efficiency of the neutrosophic estimate has been studied through a Monte Carlo simulation. Finally, real data on the incubation period of COVID-19 are considered for numerical illustration, and further extensions of the NMD for future research works are discussed.

A new one-parameter discrete probability distribution with its neutrosophic extension: mathematical properties and applications

“…The concept of neutrosophic probability as a function was originally presented by [ 32 ], where U is a neutrosophic sample space and defined the probability mapping to take the form where and . Furthermore, many scholars have studied various neutrosophic probability models such as Poisson, binomial, exponential, uniform, normal, Weibull, Kumaraswamy, generalized Pareto, Maxwell, Lognormal, and Gamma, see [ 2 , 9 , 11 , 23 – 25 , 29 , 31 ]. In many cases, researchers investigate goodness-of-fit tests, neutrosophic time series prediction, and modeling, such as neutrosophic logarithmic models, neutrosophic moving averages, and neutrosophic linear models, as shown in [ 3 , 10 , 13 ].…”

DUS-neutrosophic multivariate inverse Weibull distribution: properties and applications

“…Nayana et al [17] introduced DUS-transformation with neutrosophic Weibull distribution. More details about the applications of neutrosophic statistics can be seen [1,7,10,13,[20][21][22][23]. The idea for improving the quality aspect can be seen in Ghosh et al [9].…”

Retracted: On Neutrosophic Extension of the Maxwell Model: Properties and Applications

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”