Open AccessDiscretization of the method of generating an expanded family of distributions based upon truncated distributions
Author(s) -
Muhammad Farooq,
Muhammad Mohsin,
Muhammad Naeem,
Muhammad Farman,
Ali Akgül,
Muhammad Umar Saleem
Publication year - 2021
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci200605003f
Subject(s) - discretization , weibull distribution , generalization , quantile , mathematics , quantile function , computation , function (biology) , moment generating function , moment (physics) , generating function , computer science , method of moments (probability theory) , probability distribution , algorithm , statistics , discrete mathematics , mathematical analysis , physics , classical mechanics , evolutionary biology , estimator , biology
Discretization translates the continuous functions into discrete version making them more adaptable for numerical computation and application in applied mathematics and computer sciences. In this article, discrete analogues of a generalization method of generating a new family of distributions is provided. Several new discrete distributions are derived using the proposed methodology. A discrete Weibull-Geometric distribution is considered and various of its significant characteristics including moment, survival function, reliability function, quantile function, and order statistics are discussed. The method of maximum likelihood and the method of moments are used to estimate the model parameters. The performance of the proposed model is probed through a real data set. A comparison of our model with some existing models is also given to demonstrate its efficiency.