Detection of influential observations in functional errors-in-variables model
This paper presents several methods for detecting influential observations in a functional errors-in-variables (FEIV) model. Since the FEIV model is a regression-like model, similar approaches to those in regression model can be adopted. We focus on influence diagnostics based on leverage values, influence curve and case deletion approaches. Some numerical examples are given to illustrate the methods.