Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/12690
Title: A Novel Bivariate Generalized Weibull Distribution with Properties and Applications
Authors: Arshad, Mohd.
Keywords: Bivariate distribution;copulas;exponential distribution;inference;Markov chain Monte Carlo;measures of association;Weibull distribution
Issue Date: 2023
Publisher: Taylor and Francis Ltd.
Citation: Pathak, A. K., Arshad, M., J. Azhad, Q., Khetan, M., & Pandey, A. (2023). A Novel Bivariate Generalized Weibull Distribution with Properties and Applications. American Journal of Mathematical and Management Sciences. Scopus. https://doi.org/10.1080/01966324.2023.2239963
Abstract: Univariate Weibull distribution is a well known lifetime distribution and has been widely used in reliability and survival analysis. In this paper, we introduce a new family of bivariate generalized Weibull (BGW) distributions, whose univariate marginals are exponentiated Weibull distribution. Different statistical quantiles like marginals, conditional distribution, conditional expectation, product moments, correlation and a measure component reliability are derived. Various measures of dependence and statistical properties along with aging properties are examined. Further, the copula associated with BGW distribution and its various important properties are also considered. The methods of maximum likelihood and Bayesian estimation are employed to estimate unknown parameters of the model. A Monte Carlo simulation and real data study are carried out to demonstrate the performance of the estimators and results have proven the effectiveness of the distribution in real-life situations. © 2023 Taylor & Francis Group, LLC.
URI: https://doi.org/10.1080/01966324.2023.2239963
https://dspace.iiti.ac.in/handle/123456789/12690
ISSN: 0196-6324
Type of Material: Journal Article
Appears in Collections:Department of Mathematics

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