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All Journal Variansi : Journal of Statistics and Its Application on Teaching and Research
A. Nurul Amalia
Prodi Statistika, FMIPA, Universitas Negeri Makassar
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Public Health

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PERBANDINGAN METODE MOMEN, MAXIMUM LIKELIHOOD DAN BAYES DALAM MENDUGA PARAMETER DISTRIBUSI PARETO A. Nurul Amalia; Muhammad Arif Tiro; Aswi Aswi
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 3 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm26374

Abstract

This study examines the estimation of Pareto distribution parameters using three different methods, namely the Moment, Maximum Likelihood, and Bayesian methods. The Pareto distribution is a continuous distribution with parameters k > 0 and α > 0. These two parameters are estimated by using three distinct parameter estimation methods. The goodness of fit measure used in choosing the best estimation method is the Mean Square Error (MSE) value. The smallest MSE is the best method. A simulation study is carried out as well as the case study of the data on the number of Gross National Income (GNI) per capita in Southeast Asian countries in 2019. The estimation and simulation results indicate that the best estimation method in estimating the parameters of the Pareto distribution is the Maximum Likelihood in terms of MSE value.Keywords: Pareto distribution, Moment Method, Maximum Likelihood IMethod, Bayesian Method
Co-Authors Aswi, Aswi Muhammad Arif Tiro