Department Of Mathematics And Statistics

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Author: search.filters.author.Pandey, Arvind

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    A Novel Bivariate Generalized Weibull Distribution with Properties and Applications
    (Taylor and Francis Ltd., 2023-09-09T00:00:00) Pathak, Ashok Kumar; Arshad, Mohd; J. Azhad, Qazi; Khetan, Mukti; Pandey, Arvind
    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.
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    ON A BIVARIATE XGAMMA DISTRIBUTION DERIVED FROM COPULA
    (University of Bologna, 2022-07-12T00:00:00) Abulebda, Mohammed; Pathak, Ashok Kumar; Pandey, Arvind; Tyagi, Shikhar
    In this paper, a new bivariate XGamma (BXG) distribution is presented using Farlie-Gumbel-Morgenstern (FGM) copula. We derive the expressions for conditional distribution, regression function and product moments for the BXG distribution. Concept of reliability and various measures of local dependence are also studied for the proposed model. Furthermore, estimation of the parameters of the BXG distribution is obtained through maximum likelihood estimation and inference function of margin estimation procedures. Finally, an application of the same is also demonstrated to a real data set. � 2022 University of Bologna. All rights reserved.