A new approach to bivariate transmutation: construction of continuous bivariate distribution under negative dependency

Abstract

In this study, a new approach to transmutation theory is developed by using negativedependency basement. Once choosing a distribution that has negative dependency with thesame marginal, a new bivariate distribution is derived. In this study, we examined a newtransmutation technique in which a negative dependency offers a big success in modelingrather than most known and used statistical distributions. This approach clash with classicaltransmutation methods. In this study at the beginning, the classical transmutation is defined.Later, we introduce the new technique and obtain lower and upper bounds of distribution toshow that this approach gives us a distribution. Gaining new bivariate continuous distributionswith this technique may be more appropriate in theory, and modeling of some data sets interms of this approach may be more efficient.