2010 Fiscal Year Final Research Report
New developments on local fitting semiparametric inference
| Project/Area Number |
20500257
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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 | Shimane University |
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Principal Investigator |
NAITO Kanta Shimane University, 総合理工学部, 准教授 (80304252)
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| Project Period (FY) |
2008 – 2010
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| Keywords | 機械学習 / 生物統計 / 平滑化 |
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| Research Abstract |
The research has contributed to the works to clarify theoretical properties of the local fitting semiparametric inferences and its application to biostatistics. The research has progressed according to the research plan previously submitted. The results of research include developing the asymptotic theory of semiparametric smoothing and the selection of smoothing parameters in the semiparametric generalized linear mixed model. As important results in the application to biostatistics, some distributional results of dilatation have been derived under linear and radial mapping models, which have been applied to the analysis of harmonized development of human fetuses.
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