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Seminar on Probability and Statistics Wednesday June 9 2010 Tokyo Studio 3:00-4:10 pm
Weak convergence of Markov chain Monte Carlo method and its application to Yuima
鎌谷 研吾 / KAMATANI, Kengo 東京大学大学院数理科学研究科 / Graduate school of Mathematical Sciences, Univ. of Tokyo Abstract
We examine some asymptotic properties of Markov chain Monte Carlo methods
by the weak convergence framework of MCMC.
Our purpose is to compare this framework to
the Harris recurrence framework.
Numerical illustrations will be given via R.
The connection to the YUIMA package will also be discussed.
マルコフチェインモンテカルロ(MCMC)法の収束を MCMC法の弱収束の観点から論じる.とくに,MCMC法に対する マルコチェインのエルゴード性からのアプローチとの比較を行う. これらの収束理論の紹介とともに,幾つかの数値実験を統計ソフトフェアRを用いて考察する. また,MCMC法の弱収束とYuimaパッケージに実装されているadaBayes関数との関連を論じる. |
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