In this paper we study a marked empirical process based on residuals. Results on its large-sample behavior may be used to provide nonparametric full-model checks for regression. Their decomposition into principal components gives new insight into the question: which kind of departure from a hypothetical model may be well detected by residual-based goodness-of-fit methods? The work also contains a small simulation study on straight-line regression.
Publié le : 1997-04-14
Classification:
Marked empirical process,
residuals,
model check for regression,
principal components,
Cramér-von Mises,
smooth and directional tests,
62G05,
62G10,
62G30,
62J02
@article{1031833666,
author = {Stute, Winfried},
title = {Nonparametric model checks for regression},
journal = {Ann. Statist.},
volume = {25},
number = {6},
year = {1997},
pages = { 613-641},
language = {en},
url = {http://dml.mathdoc.fr/item/1031833666}
}
Stute, Winfried. Nonparametric model checks for regression. Ann. Statist., Tome 25 (1997) no. 6, pp. 613-641. http://gdmltest.u-ga.fr/item/1031833666/