Estimation of Pareto Parameters Using a Fuzzy Least-Squares Method and Other Known Techniques with a Comparison
Hegazy M. Zaher
Institute of Statistical Studies and Research, Cairo University, Egypt.
Ahmed A. El-Sheik
Institute of Statistical Studies and Research, Cairo University, Egypt.
Noura A. T. Abu El-Magd *
Faculty of Business and Economics, Misr University for Science and Technology, Egypt.
*Author to whom correspondence should be addressed.
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.
Keywords: Pareto distribution, fuzzy least-squares, TL-moments, L-moments, LQ-moments, maximum likelihood, simulations