Nonparametric analysis of covariance

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Two-sample tests in functional data analysis starting from discrete data (2007, background): “See, for example, Dette and Neumeyer (2001). Moreover, in such instances the data are passed from one statistician to another before processing, i.e., before smoothing. By way of contrast, functional datasets are usually exchanged by researchers in post-processed form, after the application of a smo”
An updated review of Goodness-of-Fit tests for regression models (2013, background): “Dette and Neumeyer (2001) discussed different procedures for testing the equality of a collection of regression curves.”
Semiparametric Time‐Varying Coefficients Regression Model for Longitudinal Data (2005, methodology): “Many tests have been developed for testing covariate effects in non-parametric regression models, varying-coefficient regression models and additive models, see e.g. Fan & Zhang (2000), Dette & Neumeyer (2001) and the references therein.”
Equivalence of Regression Curves (2018, methodology): “In the context of comparing curves, Dette and Neumeyer (2001) provided a nonparametric test for the null hypothesis that the L2-distance between two regression functions is large against the alternative that it is small.”