Slice sampling technique in Bayesian extreme of gold price modelling

• Main Authors: Rostami, Mohammad, Adam, Mohd Bakri, Ibrahim, Noor Akma, Yahya, Mohamed Hisham
• Format: Conference or Workshop Item
• Language: English
• Published: AIP Publishing LLC 2013
• Online Access: http://psasir.upm.edu.my/id/eprint/57168/1/Slice%20sampling%20technique%20in%20Bayesian%20extreme%20of%20gold%20price%20modelling.pdf; http://psasir.upm.edu.my/id/eprint/57168/; http://aip.scitation.org/doi/abs/10.1063/1.4823959
• Institution: Universiti Putra Malaysia

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.