SFB 303 Discussion Paper No. A - 185
Author: Hart, Jeffrey D.
Title: Kernel Regression Estimation with Time Series Errors
Abstract: The problem of objectively choosing the bandwidth of a kernel estimate for a smooth function f is
addressed. It is shown both theoretically and by simulation that cross-validation produces extremely rough kernel
estimates when the data are sufficiently positively correlated. This makes it inadvisable to use residuals from a
cross-validated kernel estimate as a means of estimating the covariance function of the errors. Alternative
methods of estimating the covariance function are proposed. In a simulation study, incorporating these estimated
covariances into a risk estimation procedure leads to more efficient smoothing of positively correlated data.
Keywords: Bandwidth selection; Mean squared error; Mean average squared error; Autoregressive process;
Creation-Date: July 1988
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