Modeling Bivariate Data Using Linear Exponential and Weibull Distributions as Marginals
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Date
2023-08-04T00:00:00
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Publisher
De Gruyter Open Ltd
Abstract
Modeling bivariate data with different marginals is an important problem and have numerous applications in diverse disciplines. This paper introduces a new family of bivariate generalized linear exponential Weibull distribution having generalized linear and exponentiated Weibull distributions as marginals. Some important quantities like conditional distributions, conditional moments, product moments and bivariate quantile functions are derived. Concepts of reliability and measures of dependence are also discussed. The methods of maximum likelihood and Bayesian estimation are considered to estimate model parameters. Monte Carlo simulation experiments are performed to demonstrate the performance of the estimators. Finally, a real data application is also discussed to demonstrate the usefulness of the proposed distribution in real-life situations. � 2023 Mathematical Institute Slovak Academy of Sciences.
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Keywords
Bivariate generalized linear Weibull distribution, generalized linear exponential distribution, inference, MCMC, measures of association, Weibull distribution