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 bootstrap 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.
CITATION STYLE
Neumann, M. H., & Kreiss, J. P. (1998). Regression-type inference in nonparametric autoregression. Annals of Statistics, 26(4), 1570–1613. https://doi.org/10.1214/aos/1024691254
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