Chen, Ping; Feng, Yu Nonparametric estimation models of the drift vector and the diffusion matrix. (Chinese. English summary) Zbl 1248.62134 Chin. Ann. Math., Ser. A 32, No. 4, 497-506 (2011). Summary: The nonparametric estimation problem for multi-dimensional diffusion processes is considered. Using the properties of ItĂ´ diffusions, the samples of the drift vector and diffusion matrix are represented by a regression model with measurement error. The \(L^r\) upper bound of the stochastic error and the \(L^r\) convergence rate of the measurement error are given. The generic models for nonparametric estimation of the drift vector and diffusion matrix are established. Cited in 1 Document MSC: 62M05 Markov processes: estimation; hidden Markov models 62G08 Nonparametric regression and quantile regression 62G05 Nonparametric estimation Keywords:nonparametric regression; generic models PDFBibTeX XMLCite \textit{P. Chen} and \textit{Y. Feng}, Chin. Ann. Math., Ser. A 32, No. 4, 497--506 (2011; Zbl 1248.62134)