A Bayesian estimation of the Gini index and the Bonferroni index for the Dagum distribution with the application of different priors

Abstract Bayesian estimators and highest posterior density credible intervals are obtained for two popular inequality measures, viz. the Gini index Bonferroni in case of Dagum distribution. The study considers informative non-informative priors, i.e. Mukherjee-Islam prior extension Jeffrey’s prior, respectively, under presumption Linear Exponential (LINEX) loss function. A Monte Carlo simulation is carried out order to obtain relative efficiency both indices while taking into consideration different priors functions. estimated proves lower when using comparison LINEX function outperforms squared error (SELF) terms loss. Highest also these measures. used real-life data sets illustration purposes.