Robust SiZer for Exploration of Regression Structures and Outlier Detection

Abstract

The SiZer methodology is a valuable tool for conducting exploratory data analysis. In this article a robust version of SiZer is developed for the regression setting. This robust SiZer is capable of producing SiZer maps with different degrees of robustness. By inspecting such SiZer maps, either as a series of plots or in the form of a movie, the structures hidden in a dataset can be more effectively revealed. It is also demonstrated that the robust SiZer can be used to help identify outliers. Results from both real data and simulated examples will be provided.

Key Words:

• Local linear regression
• M-Estimator
• Outlier identification
• Robust estimation