Local influence assessment in heteroscedastic measurement error models

Authors:
Mário de Castro;Manuel Galea-Rojas;Heleno Bolfarine
Affiliations:
Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, Caixa Postal 668, 13560-970, São Carlos-SP, Brazil;Universidad de Valparaíso, Casilla 5030, Valparaíso, Chile;Instituto de Matemática e Estatística, Universidade de São Paulo, Caixa Postal 66281, Ag. Cidade de São Paulo, 05311-970, São Paulo-SP, Brazil
Venue:
Computational Statistics & Data Analysis
Year:
2007

Citing 1
Cited 2

The element-wise weighted total least-squares problem

Computational Statistics & Data Analysis

Editorial: Total Least Squares and Errors-in-variables Modeling

Computational Statistics & Data Analysis
Influence measures on corrected score estimators in functional heteroscedastic measurement error models

Journal of Multivariate Analysis

Quantified Score

Hi-index	0.03

Visualization

Abstract

Functional heteroscedastic measurement error models are investigated aiming to assess the effects of perturbations of data on some inferential procedures. This goal is accomplished by resorting to methods of local influence. The techniques provide to the practitioner a valuable tool that enables to identify potential influential elements and to quantify the effects of perturbations in these elements on results of interest. An illustrative example with a real data set is also reported.