E-Bayesian and hierarchical estimation of Maxwell-Boltzman distribution

Abstract EN

his paper is devoted to compare the E-Bayesian and hierarchical Bayesian estimation of the shape parameter corresponding to the Burr Type ?? distribution.

The E-Bayesian and hierarchical Bayesian estimation are obtained under the squared error loss function (SELF), LINEX loss function, general entropy loss function (GELF), and precautionary loss function (PLF).

Properties of the E-Bayesian and hierarchical Bayesian estimation are investigated.

Comparisons among all estimates are performed in terms of mean square error (MSE) via Monte Carlo simulation.

Numerical computations showed that E-Bayesian estimates are more efficient than the hierarchical Bayesian estimates.

Real data is used to represent these estimates