Local Polynomial Regression: Optimal Kernels and Asymptotic Minimax Efficiency

Jianqing Fan; Théo Gasser; Irène Gijbels; Michael Brockmann; Joachim Engel

doi:10.1023/a:1003162622169

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Local Polynomial Regression: Optimal Kernels and Asymptotic Minimax Efficiency

Jianqing Fan Théo Gasser Irène Gijbels Michael Brockmann Joachim Engel

Year: 1997 Journal: Annals of the Institute of Statistical Mathematics Vol: 49 (1)Pages: 79-99 Publisher: Springer Science+Business Media

DOI: 10.1023/a:1003162622169

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Keywords:

Mathematics Minimax Polynomial regression Estimator Applied mathematics Univariate Polynomial Linear regression Mathematical optimization Minimax estimator Regression analysis Boundary (topology) Statistics Multivariate statistics Minimum-variance unbiased estimator Mathematical analysis

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Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Control Systems and Identification

Physical Sciences → Engineering → Control and Systems Engineering

Local Polynomial Regression: Optimal Kernels and Asymptotic Minimax Efficiency

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