2005 Fiscal Year Final Research Report Summary
Statistical modelling to treat data with missing value
| Project/Area Number |
15500187
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | NAGASAKI UNIVERSITY |
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Principal Investigator |
KIKUCHI Yasuki Nagasaki University, Graduate School of Biomedical Sciences, Associate Professor, 大学院・医歯薬学総合研究科, 助教授 (10124140)
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| Co-Investigator(Kenkyū-buntansha) |
MARUYAMA Yukihiro Nagasaki University, Faculty of Economics, Professor, 経済学部, 教授 (30229629)
NOMAKUCHI Kentaro Kochi University, Faculty of Science, Professor, 理学部, 教授 (60124806)
ANRAKU Kazuo Seinan Gakuin University, Department of Human Sciences, Professor, 人間科学部, 教授 (90184332)
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| Project Period (FY) |
2003 – 2005
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| Keywords | incompelete information / EM-algorithm / normal mixture model / hidden Markov normal model / estimation of survival function / Gamma-Weibull distribution / observed information matrix / Bootstrap method |
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| Research Abstract |
The purpose of this research was to construct the effective statistical models and to develop the effective method of estimation about the error of the estimates in statistical inference based on incomplete information such as data containing the missing value.
We compared the estimates of the variance obtained by the observed information matrix and Bootstrap method for the estimates obtained by EM-algorithm for Poisson mixture model. Kikuchi and Nomakuchi presented this result at the 17th meeting of Japanese Society of Computational Statistics (2003.05).
We studied about the estimation of the parameters for normal mixture model and hidden Markov normal model by EM-algorithm and the variance of the estimates by the observed information matrix. Kikuchi and Nomakuchi will present this result at the 20th meeting of Japanese Society of Computational Statistics (2006.06).
Kikuchi became the research partaker of the research project of Ministry of Health, Labour and Welfare since 2003. We added a new theme relevant to the application of EM-algorithm to the clinical trial. We developed the method of the estimation of the survival function assuming the Gamma-Weibull distribution and the generalized Gamma distribution. Kikuchi and Nomakuchi presented this result at the 18th meeting of Japanese Society of Computational Statistics (2004.05), and Kikuchi, Nomakuchi and Anraku presented a paper about this result entitled "Estimation of the survival function by EM-algorithm (in Japanese)" on the collected papers of the above research project.
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Research Products
(24 results)
