Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data

The Multiple-try Metropolis (MTM) algorithm is the new alternatives in the field of Bayesian extremes for summarizing the posterior distribution. MTM produce efficient estimation scheme for modelling extreme data in term of the convergence and small burn-in periods. The main objective is to explore...

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Main Authors: Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma
Format: Conference or Workshop Item
Language:English
Published: AIP Publishing LLC 2013
Online Access:http://psasir.upm.edu.my/id/eprint/35055/
http://psasir.upm.edu.my/id/eprint/35055/1/Prior%20selection%20for%20Gumbel%20distribution%20parameters%20using%20multiple-try%20metropolis%20algorithm%20for%20monthly%20maxima%20PM10%20data.pdf
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author Mohd Amin, Nor Azrita
Adam, Mohd Bakri
Ibrahim, Noor Akma
author_facet Mohd Amin, Nor Azrita
Adam, Mohd Bakri
Ibrahim, Noor Akma
author_sort Mohd Amin, Nor Azrita
building UPM Institutional Repository
collection Online Access
description The Multiple-try Metropolis (MTM) algorithm is the new alternatives in the field of Bayesian extremes for summarizing the posterior distribution. MTM produce efficient estimation scheme for modelling extreme data in term of the convergence and small burn-in periods. The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. Focus is on modelling the extreme data based on block maxima approach using Gumbel distribution. The comparative study between MTM and MLE is shown by the numerical problems. Several goodness of fit tests are compute for selecting the best model. The application is on the monthly maxima PM10 data for Johor state.
first_indexed 2025-11-15T09:26:42Z
format Conference or Workshop Item
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institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T09:26:42Z
publishDate 2013
publisher AIP Publishing LLC
recordtype eprints
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spelling upm-350552016-10-11T02:21:39Z http://psasir.upm.edu.my/id/eprint/35055/ Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data Mohd Amin, Nor Azrita Adam, Mohd Bakri Ibrahim, Noor Akma The Multiple-try Metropolis (MTM) algorithm is the new alternatives in the field of Bayesian extremes for summarizing the posterior distribution. MTM produce efficient estimation scheme for modelling extreme data in term of the convergence and small burn-in periods. The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. Focus is on modelling the extreme data based on block maxima approach using Gumbel distribution. The comparative study between MTM and MLE is shown by the numerical problems. Several goodness of fit tests are compute for selecting the best model. The application is on the monthly maxima PM10 data for Johor state. AIP Publishing LLC 2013 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/35055/1/Prior%20selection%20for%20Gumbel%20distribution%20parameters%20using%20multiple-try%20metropolis%20algorithm%20for%20monthly%20maxima%20PM10%20data.pdf Mohd Amin, Nor Azrita and Adam, Mohd Bakri and Ibrahim, Noor Akma (2013) Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data. In: Statistics and Operational Research International Conference (SORIC 2013), 3–5 Dec. 2013, Sarawak, Malaysia. (pp. 317-324). 10.1063/1.4894356
spellingShingle Mohd Amin, Nor Azrita
Adam, Mohd Bakri
Ibrahim, Noor Akma
Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
title Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
title_full Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
title_fullStr Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
title_full_unstemmed Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
title_short Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
title_sort prior selection for gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima pm10 data
url http://psasir.upm.edu.my/id/eprint/35055/
http://psasir.upm.edu.my/id/eprint/35055/
http://psasir.upm.edu.my/id/eprint/35055/1/Prior%20selection%20for%20Gumbel%20distribution%20parameters%20using%20multiple-try%20metropolis%20algorithm%20for%20monthly%20maxima%20PM10%20data.pdf