1. Departamento de Estatística , IMECC/UNICAMP , Brazil;2. Departamento de Ciências da Computa??o e Estatística , ICMC/USP-S?o Carlos , Brazil;3. Departamento de Estatística , IME/USP , S?o Paulo, SP, Brazil
Abstract:
In this paper we discuss the application of local influence in a measurement error regression model with null intercepts under a Student_t model with dependent populations. The Student_t distribution is a robust alternative to modelling data sets involving errors with longer than Normal tails. We derive the appropriate matrices for assessing the local influence for different perturbation schemes and use real data as an illustration of the usefulness of the application.