Artículo
Robust testing for superiority between two regression curves
Fecha de publicación:
05/2016
Editorial:
Elsevier Science
Revista:
Computational Statistics And Data Analysis
ISSN:
0167-9473
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
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.
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Articulos(IMAS)
Articulos de INSTITUTO DE INVESTIGACIONES MATEMATICAS "LUIS A. SANTALO"
Articulos de INSTITUTO DE INVESTIGACIONES MATEMATICAS "LUIS A. SANTALO"
Citación
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
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