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Gradient-based smoothing parameter selection for nonparametric regression estimation

Journal of Econometrics, 84, 2015, 233-241

      我院李奇老师的文章发表在计量经济学国际一流期刊Journal of Econometrics上(Journal of Econometrics, 2015, 184, 233-241)。以下是论文的摘要。
      Estimating gradients is of crucial importance across a broad range of applied economic domains. Here we consider data-driven bandwidth selection based on the gradient of an unknown regression function. This is a difficult problem given that direct observation of the value of the gradient is typically not observed. The procedure developed here delivers bandwidths which behave asymptotically as though they were selected knowing the true gradient. Simulated examples showcase the finite sample attraction of this new mechanism and confirm the theoretical predictions.
(日期:2015-01-09 作者:D.J. Henderson, Qi Li, C. F. Parmeter, S. Yao 来源:)