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Slice sampling technique in Bayesian extreme of gold price modelling


Citation

Rostami, Mohammad and Adam, Mohd Bakri and Ibrahim, Noor Akma and Yahya, Mohamed Hisham (2013) Slice sampling technique in Bayesian extreme of gold price modelling. In: International Conference on Mathematical Sciences and Statistics 2013 (ICMSS2013), 5-7 Feb. 2013, Kuala Lumpur, Malaysia. (pp. 473-477).

Abstract

In this paper, a simulation study of Bayesian extreme values by using Markov Chain Monte Carlo via slice sampling algorithm is implemented. We compared the accuracy of slice sampling with other methods for a Gumbel model. This study revealed that slice sampling algorithm offers more accurate and closer estimates with less RMSE than other methods. Finally we successfully employed this procedure to estimate the parameters of Malaysia extreme gold price from 2000 to 2011.


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Economics and Management
Institute for Mathematical Research
DOI Number: https://doi.org/10.1063/1.4823959
Publisher: AIP Publishing LLC
Keywords: Gumbel model; Malaysia gold price; MCMC; Simulation; Slice sampling
Depositing User: Nabilah Mustapa
Date Deposited: 08 Sep 2017 05:30
Last Modified: 08 Sep 2017 05:30
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1063/1.4823959
URI: http://psasir.upm.edu.my/id/eprint/57168
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