On Bivariate Inverse Lindley Distribution Derived From Copula


  • Mohammed Abulebda Department of Statistics, Central University of Rajasthan, Rajasthan, India
  • Arvind Pandey Department of Statistics, Central University of Rajasthan, Rajasthan, India
  • Shikhar Tyagi Department of Statistics, Central University of Rajasthan, Rajasthan, India


Bivariate inverse Lindley distribution, copula, Farlie-Gumbel-Morgenstern copula, maximum likelihood estimate


In the last few decades, copula distribution has become one of the most popular methods to construct bivariate distributions in literature. This paper introduces a new bivariate Inverse Lindley distribution based on the Farlie-Gumbel-Morgenstern (FGM) copula. We study essential mathematical properties and it’s application. We have been using the conditional copula distribution method to generate random numbers. Estimation of the parameters for bivariate Inverse Lindley distribution is obtained through maximum likelihood estimation. An example of a real data set is introduced to illustrate the proposed model.


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How to Cite

Abulebda, M. ., Pandey, A. ., & Tyagi, S. . (2023). On Bivariate Inverse Lindley Distribution Derived From Copula. Thailand Statistician, 21(2), 291–304. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/249002