Adaptive drift estimation for nonparametric diffusion model

Vladimir G. Spokoiny

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)815-836
Number of pages22
JournalAnnals of Statistics
Issue number3
Publication statusPublished - 2000
Externally publishedYes


  • Bandwidth selection
  • Drift and diffusion coefficients
  • Nonparametric estimation


Dive into the research topics of 'Adaptive drift estimation for nonparametric diffusion model'. Together they form a unique fingerprint.

Cite this