【摘 要】
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We propose a new adaptive approach for clustering functional data.The data-adaptive searching method based on dimension reduction theory is proposed for est
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We propose a new adaptive approach for clustering functional data.The data-adaptive searching method based on dimension reduction theory is proposed for estimating the basis functions and the sufficient dimension reduction space of predictors.These estimates are obtained through local linear approximation techniques without requiring a prespecified parametric model.A K-means clustering method is then adopted for functional clustering analysis.Several simulations are reported for illustration.
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