Skewed Local Linear Smoothing near the Boundary
Date Issued
2007
Date
2007
Author(s)
Guo, Bo-Hung
Abstract
In this context, we consider the estimator proposed in Choi and Hall (1998), a linear combination of the skewed local linear estimators and a classic local linear estimator. It is used for reducing the bias order of the classic local linear estimator. Assume that the support of the real function is bounded. In the boundary region, the linear combination estimator doesn''t work because the shifted points of the skewed local linear estimators are not in the support of the real function. We propose a method to solve this problem. In partial regions near the boundaries, with the proper asymmetric shifted parameters, the bias of the estimator can be reduced by an order of magnitude, compared to the bias of the classic local linear estimator, and the order of magnitude of variance is not influenced.
Subjects
Boundary
Local linear smoothing
Skewing
Nonparametric regression
Bias reduction
Type
thesis
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