| Project/Area Number |
15300095
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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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 | Keio University |
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Principal Investigator |
SHIBATA Ritei Keio University, Faculty of Science and Technology, Professor, 理工学部, 教授 (60089828)
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| Co-Investigator(Kenkyū-buntansha) |
SHIMIZU Kunio Keio University. Department of Mathematics, Professor, 理工学部, 教授 (60110946)
JIMBO Masakazu Nagoya University, Graduate School of Information Science, Professor, 情報科学研究科, 教授 (50103049)
KATO Takeshi Keio University, Faculty of Science and Technology, Associate Professor, 理工学部, 専任講師 (40267399)
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| Project Period (FY) |
2003 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥10,300,000 (Direct Cost: ¥10,300,000)
Fiscal Year 2006: ¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 2005: ¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 2004: ¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 2003: ¥3,400,000 (Direct Cost: ¥3,400,000)
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| Keywords | Point Process / Modelling / Data / Textile Plot / Multiplicative Correlation / Hidden Markov Model / Neural Network / Maximum Likelihood Solution / 隠れ点過程 / 時系列 / 神経細胞 / 外国為替 / 最尤法 / クラスタ / 両側指数分布 |
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| Research Abstract |
Various Exploratory Data Analysis techniques have been developed particularly for time point data. The aim of this research is to provide a general way of building appropriate models for the given data. The models we have investigated are clustering marked point process, hidden Markov point process, hidden semi Markov point process, mixed point process, multiple point process and zero reset intensity model. We have developed not only mathematical theory but also algorithms of solving the maximum likelihood equation and a total environment for supporting the process of model building. The targeted phenomena are neural activation, hear beat, rain fall, earthquakes, customer visit to a beauty parlor, new bid price of foreign exchange. The environment is based on DandD and one of the features is a new data visualization technique called Textile plot.
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