Concentration of scalar ergodic diffusions and some statistical implications
From MaRDI portal
Publication:2077347
DOI10.1214/20-AIHP1144zbMath1483.60111arXiv1807.11331OpenAlexW3207204159WikidataQ114060529 ScholiaQ114060529MaRDI QIDQ2077347
Cathrine Aeckerle-Willems, Claudia Strauch
Publication date: 25 February 2022
Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1807.11331
Density estimation (62G07) Markov processes: estimation; hidden Markov models (62M05) Diffusion processes (60J60) Local time and additive functionals (60J55)
Related Items (3)
Estimation of the invariant density for discretely observed diffusion processes: impact of the sampling and of the asynchronicity ⋮ Nonparametric learning for impulse control problems -- exploration vs. exploitation ⋮ Sup-norm adaptive drift estimation for multivariate nonreversible diffusions
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Multivariate density estimation under sup-norm loss: oracle approach, adaptation and independence structure
- Upper functions for positive random functionals. I: General setting and Gaussian random functions
- Upper functions for positive random functionals. II. Application to the empirical processes theory. I
- Upper functions for positive random functionals. II: Application to the empirical processes theory, Part 2
- A Bernstein-type inequality for suprema of random processes with applications to model selection in non-Gaussian regression
- An exponential inequality for the distribution function of the kernel density estimator, with applications to adaptive estimation
- Statistical inference for ergodic diffusion processes.
- Concentration around the mean for maxima of empirical processes
- Semi-martingale inequalities via the Garsia-Rodemich-Rumsey lemma, and applications to local times
- Adaptive invariant density estimation for ergodic diffusions over anisotropic classes
- Adaptive estimation for bifurcating Markov chains
- Tail bounds via generic chaining
- Majorizing measures: The generic chaining
- Brownian Motion, Martingales, and Stochastic Calculus
- Central limit theorems for additive functionals of ergodic Markov diffusions processes
- Bernstein-type Concentration Inequalities for Symmetric Markov Processes
- Mathematical Foundations of Infinite-Dimensional Statistical Models
- Chernoff and Berry–Esséen inequalities for Markov processes
- Upper and Lower Bounds for Stochastic Processes
- Polynomial deviation bounds for recurrent Harris processes having general state space
- deviation bounds for additive functionals of markov processes
This page was built for publication: Concentration of scalar ergodic diffusions and some statistical implications