BAYESIAN ANALYSIS OF DAGUM DISTRIBUTION

  • Saima Naqash Department of Statistics, University of Kashmir, Srinagar, India
  • S. P. Ahmad Department of Statistics, University of Kashmir, Srinagar, India
  • Aquil Ahmed Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh, India
Keywords: Dagum Distribution, Mixture Distribution, Predictive Distribution, xtension of Jeffreys Prior, Loss Functions, Risk Function, Efficiency

Abstract

The Dagum distribution is very useful to represent the distribution of income, actuarial, meteorological data as well for survival analysis. Moreover, it is considered to be the most suitable choice as compared to other three parameter distributions in several cases. It belongs to the generalized beta distribution and is generated from generalized beta-II by considering a shape parameter one and referred as inverse Burr distribution. In this paper, we obtain Bayesian estimation of the scale parameter of the Dagum distribution under informative and noninformative prior. Bayes estimators are derived using different loss functions. These estimators are compared using risk functions.

 

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Published
2017-06-12
Section
Articles