Journal of Statistics Applications & Probability
In this article we study a new family of distributions in the real line. The proposed model can be seen as a suitable model for ﬁtting symmetric and kurtotic datasets. It arises as a mixture of the Laplace and bilateral gamma densities. We study some of its analytical properties and estimate the unknown parameters using maximum likelihood method. Algorithm of simulation and applications to the real dataset of monthly interest rate data are presented. An asymmetric generalization of the new model is discussed.
Digital Object Identifier (DOI)
K. U., Nitha and S. D., Krishnarani
"A New Family of Heavy Tailed Symmetric Distribution for Modeling Financial Data,"
Journal of Statistics Applications & Probability: Vol. 6:
3, Article 13.
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol6/iss3/13