Robust testing for superiority between two regression curves

Graciela Boente and Juan Carlos Pardo-Fernández

Computational Statistics & Data Analysis, 2016, vol. 97, issue C, 151-168

Abstract: 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.

Keywords: Hypothesis testing; Nonparametric regression models; Robust inference; Smoothing techniques (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:97:y:2016:i:c:p:151-168

DOI: 10.1016/j.csda.2015.12.002

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