The aim of this talk is to highlight the usefulness of kernel methods in regression on functional variables. After reminding some asymptotic properties of the kernel estimator of the regression operator, we introduce a general framework to construct various innovative structural tests (no-effect, linearity, single-index,...). Various bootstrap procedures are implemented on datasets in order to emphasize the pertinence of such structural testing methods.
机构:
Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
Cent S Univ, Sch Math & Stat, Changsha, Hunan, Peoples R ChinaUniv Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
Chen, Ziqi
Gao, Qibing
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Nanjing Normal Univ, Sch Math Sci, Nanjing, Jiangsu, Peoples R ChinaUniv Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
Gao, Qibing
Fu, Bo
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Fudan Univ, Sch Data Sci, Shanghai, Peoples R ChinaUniv Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
Fu, Bo
Zhu, Hongtu
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Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
Univ North Carolina Chapel Hill, Chapel Hill, NC 27599 USAUniv Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
机构:
Univ Lille 3, Univ Lille Nord France, Lab EQUIPPE EA 4018, Villeneuve Dascq, FranceUniv Lille 3, Univ Lille Nord France, Lab EQUIPPE EA 4018, Villeneuve Dascq, France
Amiri, Aboubacar
Crambes, Christophe
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Univ Montpellier 2, Inst Math & Modelisat Montpellier, F-34090 Montpellier, FranceUniv Lille 3, Univ Lille Nord France, Lab EQUIPPE EA 4018, Villeneuve Dascq, France
Crambes, Christophe
Thiam, Baba
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Univ Lille 3, Univ Lille Nord France, Lab EQUIPPE EA 4018, Villeneuve Dascq, FranceUniv Lille 3, Univ Lille Nord France, Lab EQUIPPE EA 4018, Villeneuve Dascq, France