Multivariate functional data analysis for temporally and spatially dependent data and its application to life science
| Project/Area Number |
26730016
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Statistical science
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | クラスタリング / 関数データ / 次元縮小 / 関数データ解析 / 次元縮約 |
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| Outline of Final Research Achievements |
Due to the recent advances in data collection and storage, data sets for statistical analysis have become complex and enormous. In the analysis of repeated measures data, for example, the data are often considered as a certain function, and such an analysis is called functional data analysis. In this study, I developed a new clustering method that conducted clustering and dimension reduction of multivariate functional objects simultaneously. Related to the method, I developed another clustering method with dimension reduction for multivariate binary data. In addition, I developed a new clustering method that identified a cluster structure of outcome variables and predicted cluster memberships of future individuals based on explanatory variables.
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Report
(4 results)
Research Products
(31 results)
