Adaptive drift estimation for nonparametric diffusion model
Spokoiny, Vladimir G.
Ann. Statist., Tome 28 (2000) no. 3, p. 815-836 / Harvested from Project Euclid
We consider a nonparametric diffusion process whose drift and diffusion coefficients are nonparametric functions of the state variable. The goal is to estimate the unknown drift coefficient.We apply a locally linear smoother with a data-driven bandwidth choice. The procedure is fully adaptive and nearly optimal up to a log log factor. The results about the quality of estimation are nonasymptotic and do not require any ergodic or mixing properties of the observed process.
Publié le : 2000-05-14
Classification:  Drift and diffusion coefficients,  nonparametric estimation,  bandwidth selection,  62G05,  62M99
@article{1015951999,
     author = {Spokoiny, Vladimir G.},
     title = {Adaptive drift estimation for nonparametric diffusion
			 model},
     journal = {Ann. Statist.},
     volume = {28},
     number = {3},
     year = {2000},
     pages = { 815-836},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1015951999}
}
Spokoiny, Vladimir G. Adaptive drift estimation for nonparametric diffusion
			 model. Ann. Statist., Tome 28 (2000) no. 3, pp.  815-836. http://gdmltest.u-ga.fr/item/1015951999/