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• Data sharpening methods for bias reduction in nonparametric regression AI翻译
  作者：Choi, E; Hall, P; Rousson, V
  作者单位：Australian National University
  摘要：We consider methods for kernel regression when the explanatory and/or response variables are adjusted prior to substitution into a conventional estimator. This data-sharpening procedure is designed to preserve the advantages of relatively simple, low-order techniques, for example, their robustness against design sparsity problems, yet attain the sorts of bias reductions that are commonly associated only with high-order methods. We consider Nadaraya-Watson and local-linear methods in detail, al...