Artículos de revistas
Robust testing for superiority between two regression curves
Fecha
2016-05Registro en:
Boente Boente, Graciela Lina; Pardo Fernández, Juan Carlos; Robust testing for superiority between two regression curves; Elsevier Science; Computational Statistics And Data Analysis; 97; 5-2016; 151-168
0167-9473
CONICET Digital
CONICET
Autor
Boente Boente, Graciela Lina
Pardo Fernández, Juan Carlos
Resumen
The problem of testing the null hypothesis that the regression functions of two populations are equal versus one-sided alternatives under a general nonparametric homoscedastic regression model is considered. To protect against atypical observations, the test statistic is based on the residuals obtained by using a robust estimate for the regression function under the null hypothesis. The asymptotic distribution of the test statistic is studied under the null hypothesis and under root−n local alternatives. A Monte Carlo study is performed to compare the finite sample behaviour of the proposed tests with the classical one obtained using local averages. A sensitivity analysis is carried on a real data set.