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《College Mathematics》 2018-04
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k-Nearest Neighbours Regression Estimation for Functional Time Series Data with Responses Missing at Random

MENG Shu-yu;LING Neng-xiang;School of Mathematics,Hefei University of Technology;  
We first investigate the k-nearest neighbours(kNN)estimation of nonparametric regression model for strongly mixing functional time series data with responses missing at random.We establish the uniform almost complete convergence rates of the kNN estimator under some regular conditions.Our research promotes the theoretical research of functional nonparametric regression model and provides theoretical support in functional data practical application field.
【Fund】: 国家社科基金重点项目(14ATJ005);; 国家统计局统计科学研究计划项目(2012LY080)
【CateGory Index】: O212.1
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