The Use of Influence Functions for Outlier Detection and Data Editing

SYNOPTIC ABSTRACT

Hampel's influence function has been used in recent years for evaluating robust estimators, detecting outliers, computing asymptotic variances for estimators and for hypothesis testing. In this paper, the use of influence functions for various parameters is proposed not only as a tool for outlier detection but also as a method for replacing outliers and/or missing observations. This approach is illustrated on the estimation for the variance of a distribution and it is pointed out how the method can be applied in simple linear regression problems. This approach can be extended to more complex regression type applications such as the estimation of the orbit parameters of a satellite.

Key Words and Phrases:

• influence function
• outlier detection
• data validation
• data editing
• imputation