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Research Article Open access CC BY 3.0

Estimation of Pareto Parameters Using a Fuzzy Least-Squares Method and Other Known Techniques with a Comparison

Hegazy M. Zaher, Ahmed A. El-sheik, Noura A. T. Abu El-Magd

Journal of Advances in Mathematics and Computer Science · pp. 2067–2088 · Published 31 May 2014

10.9734/BJMCS/2014/10890

Abstract

The purpose of this paper is to obtain the fuzzy least-squares estimator for the two-parameter Pareto distribution and to compare the fuzzy estimator with different types of estimators. The trimmed linear moments (TL-moments), linear moments (L-moments) and linear quantile moments (LQ-moments) formulas will be obtained for the two-parameter Pareto distribution and the TL-moments estimator, L-moments estimator and LQ-moments estimator will be derived for the Pareto distribution. Numerical comparisons between the proposed method and the existing methods are implemented. According to these comparisons, it is suggested that the proposed fuzzy least-squares estimator is preferable all times.

Pareto distribution fuzzy least-squares TL-moments L-moments LQ-moments maximum likelihood simulations

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