2011 Fiscal Year Final Research Report
Asymptotic theory for iteration required Monte Carlo algorithms
| Project/Area Number |
22740055
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
General mathematics (including Probability theory/Statistical mathematics)
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| Research Institution | Osaka University (2011)
The University of Tokyo (2010) |
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Principal Investigator |
KAMATANI Kengo 大阪大学, 大学院・基礎工学研究科, 助教 (00569767)
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| Project Period (FY) |
2010 – 2011
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| Keywords | 統計数学 / モンテカルロ法 / 漸近展開 |
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| Research Abstract |
The aim of my research was to study the behaviors of Iteration Required Monte Carlo(ITRMC) algorithm, in particular, Markov chain Monte Carlo. I introduced the notion of degeneracy and weak consistency for those algorithms. I applied the result to mixture model and categorical data model and showed degeneracy of ITRMC algorithms for them. Taking advantage of our approach, I proposed efficient Monte Carlo methods which have better convergence property.
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Research Products
(9 results)
