Nearest neighbor inverse regression
Hsing, Tailen
Ann. Statist., Tome 27 (1999) no. 4, p. 697-731 / Harvested from Project Euclid
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Sliced inverse regression (SIR), formally introduced by Li, is a very general procedure for performing dimension reduction in nonparametric regression. This paper considers a version of SIR in which the “slices” are determined by nearest neighbors and the response variable takes value possibly in a multidimensional space. It is shown, under general conditions, that the “effective dimension reduction space” can be estimated with rate $n^{-1/2}$ where $n$ is the sample size.
Publié le : 1999-04-14
Classification:  Central limit theorem,  dimension reduction,  nonparametric regression,  sliced inverse regression.,  62G05,  62F05 
@article{1018031213,
     author = {Hsing, Tailen},
     title = {Nearest neighbor inverse regression},
     journal = {Ann. Statist.},
     volume = {27},
     number = {4},
     year = {1999},
     pages = { 697-731},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1018031213}
}

Hsing, Tailen. Nearest neighbor inverse regression. Ann. Statist., Tome 27 (1999) no. 4, pp.  697-731. http://gdmltest.u-ga.fr/item/1018031213/