Regression-type inference in nonparametric autoregression
Neumann, Michael H. ; Kreiss, Jens-Peter
Ann. Statist., Tome 26 (1998) no. 3, p. 1570-1613 / Harvested from Project Euclid
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We derive a strong approximation of a local polynomial estimator LPE in nonparametric autoregression by an (LPE) in a corresponding nonparametric regression model. This generally suggests the application of regression-typical tools for statistical inference in nonparametric autoregressive models. It provides an important simplification for the boot-strap method to be used: It is enough to mimic the structure of a nonparametric regression model rather than to imitate the more complicated process structure in the autoregressive case. As an example we consider a simple wild bootstrap, which is used for the construction of simultaneous confidence bands and nonparametric supremum-type tests.
Publié le : 1998-08-14
Classification:  Nonparametric autoregression,  nonparametric regression,  strong approximation,  bootstrap,  wild bootstrap,  confidence bands,  62G07,  62M05,  62G09,  62G15 
@article{1024691254,
     author = {Neumann, Michael H. and Kreiss, Jens-Peter},
     title = {Regression-type inference in nonparametric autoregression},
     journal = {Ann. Statist.},
     volume = {26},
     number = {3},
     year = {1998},
     pages = { 1570-1613},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1024691254}
}

Neumann, Michael H.; Kreiss, Jens-Peter. Regression-type inference in nonparametric autoregression. Ann. Statist., Tome 26 (1998) no. 3, pp.  1570-1613. http://gdmltest.u-ga.fr/item/1024691254/