A Novel Bivariate Generalized Weibull Distribution with Properties and Applications

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Main Authors: Pathak, Ashok Kumar, Arshad, Mohd., Azhad, Qazi J., Khetan, Mukti, Pandey, Arvind
Format: Preprint
Published: 2021
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author Pathak, Ashok Kumar
Arshad, Mohd.
Azhad, Qazi J.
Khetan, Mukti
Pandey, Arvind
author_facet Pathak, Ashok Kumar
Arshad, Mohd.
Azhad, Qazi J.
Khetan, Mukti
Pandey, Arvind
contents 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 ageing 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
format Preprint
id arxiv_https___arxiv_org_abs_2107_11998
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle A Novel Bivariate Generalized Weibull Distribution with Properties and Applications
Pathak, Ashok Kumar
Arshad, Mohd.
Azhad, Qazi J.
Khetan, Mukti
Pandey, Arvind
Methodology
Statistics Theory
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 ageing 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
title A Novel Bivariate Generalized Weibull Distribution with Properties and Applications
topic Methodology
Statistics Theory
url https://arxiv.org/abs/2107.11998