We consider a regression model in which the mean function may have a discontinuity at an unknown point. We propose an estimate of the location of the discontinuity based on one-side nonparametric regression estimates of the mean function. The change point estimate is shown to converge in probability at rate $O(n^{-1})$ and to have the same asymptotic distribution as maximum likelihood estimates considered by other authors under parametric regression models. Confidence regions for the location and size of the change are also discussed.
Publié le : 1996-08-14
Classification:
Boundary crossing,
change point,
nonparametric regression,
62G07
@article{1032298290,
author = {Loader, Clive R.},
title = {Change point estimation using nonparametric regression},
journal = {Ann. Statist.},
volume = {24},
number = {6},
year = {1996},
pages = { 1667-1678},
language = {en},
url = {http://dml.mathdoc.fr/item/1032298290}
}
Loader, Clive R. Change point estimation using nonparametric regression. Ann. Statist., Tome 24 (1996) no. 6, pp. 1667-1678. http://gdmltest.u-ga.fr/item/1032298290/