Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data

• 第一著者: Rostami, Mohammad
• フォーマット: 学位論文
• 言語: English
• 出版事項: 2016
• 主題: Bayesian statistical decision theory; Algorithms
• オンライン･アクセス: http://psasir.upm.edu.my/id/eprint/69793/1/IPM%202016%2010%20-%20IR.pdf; http://psasir.upm.edu.my/id/eprint/69793/

Modelling the tails of distributions is important in many areas of research where the risk of unusually small or large events are of interest. In this research, application of extreme value theory within a Bayesian framework using the Metropolis Hastings algorithm and the slice sampler algorithm...