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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Cici Saputri
Andalas University
Mathematics

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Bayesian inference for Pareto distribution with prior conjugate and prior non conjugate Ferra YANUAR; Cici Saputri
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v16i3.8019

Abstract

The purpose of this study is to determine the best estimator for estimating the shape   parameters of the Pareto distribution with the known  scale parameter. Estimation of these parameters is done by using the Gamma distribution as the prior distribution of the conjugate and the Uniform distribution as the non-conjugate prior distribution. A comparison of the two prior distributions is done through simulation studies with various sample sizes. The best estimator net is a method that produces the smallest posterior variance, absolute bias, and Bayes confidence interval. This study proves that the Bayes estimator by using the prior conjugate distribution produces all indicators of the goodness of the model with a smaller value than the non-conjugate prior distribution. Thus it can be concluded that the estimator with prior conjugate will produce a better predictive value than prior non-conjugate.
Co-Authors Yanuar, Ferra