Kernel Smoothing of Data with Correlated Errors
相关误差数据的核平滑
Kernel smoothing is a common method of estimating the mean function in the nonparametric regression model y = f(x) + ε, where f(x) is a smooth deterministic mean function and ε is an error process with mean zero. In this article, the mean squared error of kernel estimators is computed for processes with correlated errors, and the estimators are shown to be consistent when the sequence of error processes converges to a mixing sequence. The standard techniques for bandwidth…