Adaptive drift estimation for nonparametric diffusion model
By Vladimir Spokoiny. 2000
48 citations recorded by the source corpus.
Subfields: Finance, Modeling and Simulation, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/bee45932c2bb01f479c19f4ed1005f312670b5e9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Fabienne Comte
- Valentine Genon-Catalot
- Yves Rozenholc
- Arnak S. Dalalyan
- Christian M. Hafner
- Helmut Herwartz
- Christian Francq
- Jean-Michel Zakoian
In Modeling and Simulation
In Statistics and Probability
- Fabienne Comte
- Valentine Genon-Catalot
- Yves Rozenholc
- Arnak S. Dalalyan
- Alain Oliviero Durmus
- Jing Lei
- Christian M. Hafner
- Eric Moulines
Citations in the corpus
- Penalized nonparametric mean square estimation of the coefficients of diffusion processes (2007, result): “Asymptotic results were given for ergodic models as the length of the observation time interval tends to infinity: see, for instance, the reference paper by Banon [2], followed by more recent works by Prakasa Rao [30], Spokoiny [31], Kutoyants [28] or Dalalyan [18].”
- Sharp adaptive estimation of the drift function for ergodic diffusions (2005, methodology): “The adaptive estimation of the drift at a fixed point based on continuous-time observations has been studied by Spokoiny [34], who has applied the Lepskii method (see [28]) to the locally linear smoothers in order to construct an adaptive rateoptimal procedure.”