Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/66265 
Year of Publication: 
1997
Series/Report no.: 
SFB 373 Discussion Paper No. 1997,99
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
Optimal bandwidths for local polynomial regression usually involve functionals of the derivatives of the unknown regression function. In the multivariate case, estimates of these functionals are not readily available, primarily because estimating multivariate derivatives is complicated. In this paper, an estimator of multivariate second derivative is obtained via local quadratic regression with cross terms left out. This estimator has the optimal rate of convergence but is simpler and uses a lot less computing time than the full local quadratic estimator. Using this as a pilot estimator, an estimator of the integrated squared Laplacian of a multivariate regression function is obtained which leads to a plug-in formula of the optimal bandwidth for multivariate local linear regression. This bandwidth has good theoretical properties as well as satisfactory performance in our simulation study. It is also recommended for variable selection methods.
Subjects: 
Bandwidth selection
Asymptotic optimality
Functional estimation
Laplacian
Local quadratic regression
Second derivatives
Within bias trade off
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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