A Non-parametric ANOVA-type Test for Regression Curves Based on Characteristic Functions

Juan Carlos Pardo-Fernández, María Dolores Jiménez-Gamero and Anouar El Ghouch

Scandinavian Journal of Statistics, 2015, vol. 42, issue 1, 197-213

Abstract: type="main" xml:id="sjos12102-abs-0001">

This article studies a new procedure to test for the equality of k regression curves in a fully non-parametric context. The test is based on the comparison of empirical estimators of the characteristic functions of the regression residuals in each population. The asymptotic behaviour of the test statistic is studied in detail. It is shown that under the null hypothesis, the distribution of the test statistic converges to a finite combination of independent chi-squared random variables with one degree of freedom. The coefficients in this linear combination can be consistently estimated. The proposed test is able to detect contiguous alternatives converging to the null at the rate n-super- − 1 ∕ 2. The practical performance of the test based on the asymptotic null distribution is investigated by means of simulations.

Date: 2015
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