Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy-tailed distributions.We show that the recently proposed methods by Xia et al.(2002) can be made robust in such a way that preserves all advantages of the original...

The Half-Half (HH) plot is a new graphical method to investigate qualitatively the shape of a regression curve. The empirical HH-plot counts observations in the lower and upper quarter of a strip that moves horizontally over the scatter plot. The plot displays jumps clearly and reveals further...

Consider the nonparametric regression model Y = m(X)+e, where the function m is smooth, but unknown.We construct tests for the independence of e and X, based on n independent copies of (X; Y ).The testing procedures are based on differences of neighboring Y 's.We establish asymptotic results for...

AMS classifications: 62G08, 62G10, 62G20, 62G30; 60F17.

The Nadaraya-Watson nonparametric estimator of regression is known to be highly sensitive to the presence of outliers in data.This sensitivity can be reduced, for example, by using local L-estimates of regression.Whereas the local L-estimation is traditionally done using an empirical conditional...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

To accommodate the inhomogenous character of financial time series over longer time periods, standard parametric models can be extended by allow- ing their coeffcients to vary over time. Focusing on conditional heteroscedas- ticity models, we discuss various strategies to identify and estimate...

The question whether exchange rate risk a¤ects trade has received considerable attention in the literature. However, the conclusions are still mixed. This paper analyzes why it is so difficult to obtain a clear answer from time series analyses. We use data on bilateral aggregate US exports to...

AMS classifications: 62G08, 62G10, 62G20, 62G30; 60F17.

Abstract: Data depth measures the centrality of a point with respect to a given distribution or data cloud. It provides a natural center-outward ordering of multivariate data points and yields a systematic nonparametric multivariate analysis scheme. In particular, the halfspace depth is shown to...