Bayesian Normal and T-K Approximations for Shape Parameter of Type-I Dagum Distribution

Abstract

Dagum distribution is a statistical distribution used closely for fitting income and wealth distributions. This distribution has wide application in fields like reliability theory survival analysis, actuarial sciences, and meteorological data. In this article, we obtained Bayes estimators for the shape parameter of Dagum distribution using approximation techniques like normal and T-K approximations. Moreover different informative priors have been considered and a simulation study and three real data sets have been considered to study the efficiency of obtained results.

Estimating the Parameter of Weighted Ailamujia Distribution using Bayesian Approximation Techniques

“…If the resulting distribution is in closed form and difficult to characterize it, analytical or numerical approximation methods are often used for accuracy with less computational complicacy. Many authors have reviewed the approximation methods including Sultan and Ahmad [6,7] for Kumaraswamy distribution and generalized Power function distribution, Kawsar and Ahmad [8] for Inverse Exponential and Uzma and Ahmad [9,10] for Inverse Lomax and Dagum distributions.…”