Title of article
Bayesian Inference using Multiple-try Metropolis Hastings Scheme for the Efficiency of Estimating Gumbel Distribution Parameters
Author/Authors
Amin, Nor Azrita Mohd Universiti Putra Malaysia - Institute of Mathematical Research, Malaysia , Amin, Nor Azrita Mohd Universiti Malaysia Perlis, Kampus Pauh Putra - Institute of Engineering Mathematics, Malaysia , Adam, Mohd Bakri Universiti Putra Malaysia - Institute of Mathematical Research, Malaysia , Ibrahim, Noor Akma Universiti Putra Malaysia - Institute of Mathematical Research, Malaysia
From page
25
To page
36
Abstract
This paper aims to explore the efficiency for estimating the parameters of Gumbel simulated data using Multiple-try Metropolis algorithm (MTM). Several goodness-of-fit tests are used to compare the performance of MTM and the former, Metropolis-Hastings algorithm (MH). Concerning for a fair comparison, this study uses the equivalent starting point, the similar number of iterations and also the same length of burn-in periods. The numerical studies show that the MTM method performs slightly better than MH method after 5000 iterations to meet the stationary distribution. More candidates in the proposals lead to a higher accuracy of MTM estimation.
Keywords
Markov chainMonte Carlo , Multiple , tryMetropolis algorithm , Metropolis , Hastings algorithm , goodness of fit , Gumbel distribution
Journal title
Matematika
Journal title
Matematika
Record number
2570196
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