Title of the talk: Bivariate distribution with singular component

Date & Time: 15 April 2026 at 12 PM on Meeting room, Dept. of Mathematics

Abstract: Real-life data sets with ties arise quite commonly in reliability and survival analysis. We attempt to model such types of data sets using bivariate distributions with singular components. For this purpose, we consider mainly two types of approaches, namely the "minimization approach” and the "maximization approach." Using the minimization approach, the bivariate modified Weibull (BMW) distribution is derived. The BMW is more general distribution, and it reduces to the Marshall-Olkin bivariate exponential (MOBE) and Marshall-Olkin bivariate Weibull (MOBW) distributions under certain parameter restrictions. Some properties of BMW will be discussed. Finally, we will discuss the maximum likelihood estimation of parameters of the BMW distribution via the EM algorithm. We will give some numerical results and comparisons.

About the speaker: Dr Sanjay is currently a FARE fellow at Dept. of Mathematics and Statistics, IIT Kanpur. He completed his PhD from IIT Kanpur during 2019–2025 under the supervision of Prof. Debasis Kundu and Prof. Sharmishtha Mitra. His doctoral thesis, titled “Robust Inference of Bivariate Distributions,” focuses on developing computationally and asymptotically efficient estimators for parameters of bivariate lifetime models, with an emphasis on robust and efficient estimation techniques.