Open AccessThe quasi xgamma-geometric distribution with application in medicine
Author(s) -
Subhradev Sen,
Ahmed Z. Afify,
Hazem Al-Mofleh,
Mohammad Ahsanullah
Publication year - 2019
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil1916291s
Subject(s) - frequentist inference , mathematics , geometric distribution , reliability (semiconductor) , monte carlo method , hazard , distribution (mathematics) , statistics , probability distribution , hazard ratio , bayesian probability , mathematical analysis , bayesian inference , confidence interval , power (physics) , physics , chemistry , organic chemistry , quantum mechanics
In this paper, a new probability distribution, which is synthesized based on the quasi xgamma[26] and geometric distributions, is proposed and studied. The proposed distribution so synthesized is basically a family of positively skewed probability distributions and possesses increasing and decreasing hazard rate properties depending on the values of the unknown parameters. Different important distributional and survival and/or reliability properties are also studied. A unique characterization of the distribution is presented based on reversed hazard rate. Seven different frequentist methods of estimating unknown parameters are proposed and the methods are justified with Monte-Carlo simulation study. Flexible data generation algorithm eases the utility of the proposed model in survival and/or reliability application which is accomplished by real data analyses and by comparing with other competitive life distributions.