Open AccessOn the Comparison of the Methods of Parameter Estimation for Pareto Distribution
Author(s) -
Warsono,
Ega Jhea Gustavia,
Dian Kurniasari,
Amanto,
Yeftanus Antonio
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1338/1/012042
Subject(s) - pareto distribution , lomax distribution , maximum likelihood , consistency (knowledge bases) , pareto interpolation , estimation , pareto principle , mathematics , estimation theory , moment (physics) , statistics , distribution (mathematics) , variance (accounting) , generalized pareto distribution , computer science , extreme value theory , economics , mathematical analysis , geometry , management , physics , classical mechanics , accounting
The main purposes of this study is to asses on comparison of parameter estimation methods of the Pareto distribution. The estimation methods include moment, maximum likelihood estimation, probabilityweightedmoment, and generalizedmoment methods. Based on unbiasness, variance, and consistency properties, the results demonstrate that in estimating parameters of the Pareto distribution, the maximum likelihood method is the one of the best estimation methods.