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Comparison of different methods of parameters estimation for Pareto Model

Abstract

In this study, the scale and the shape parameters of the Pareto Distribution have been estimated using five different estimation techniques, namely Method of Moments, Maximum Likelihood Estimation, Fractional Moments, Probability Weighted Moments and Bayesian method. As a single choice of sample size and parameter point do not help to clarify performance of the methods, so different parameter points and different sample sizes are used. An extensive Monte Carlo simulation study has been conducted to investigate the performance of the estimators. The WinBUGS and R-Language are used to deal with numerical computations of estimates of parameters of Pareto distribution. The Bayesian method exhibits the minimum standard error with some exceptions.

Key words

Bayesian estimation; Fractional Moments; Maximum Likelihood Estimators; Method of Moments; Pareto Model; Weighted Moments

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