Invariant density adaptive estimation for ergodic jump–diffusion processes over anisotropic classes

Type: Article

Publication Date: 2020-11-27

Citations: 12

DOI: https://doi.org/10.1016/j.jspi.2020.11.006

Locations

  • Journal of Statistical Planning and Inference - View - PDF
  • arXiv (Cornell University) - View - PDF
  • HAL (Le Centre pour la Communication Scientifique Directe) - View - PDF
  • DataCite API - View

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Works That Cite This (11)

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+ PDF Chat Minimax rate of estimation for invariant densities associated to continuous stochastic differential equations over anisotropic Hölder classes 2024 Chiara Amorino
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+ PDF Chat Rate of estimation for the stationary distribution of stochastic damping Hamiltonian systems with continuous observations 2022 Sylvain Delattre
Arnaud Gloter
Nakahiro Yoshida
+ PDF Chat On the nonparametric inference of coefficients of self-exciting jump-diffusion 2022 Chiara Amorino
Charlotte Dion‐Blanc
Arnaud Gloter
Sarah Lemler
+ PDF Chat Adaptive invariant density estimation for continuous-time mixing Markov processes under sup-norm risk 2022 Niklas Dexheimer
Claudia Strauch
Lukas Trottner
+ Estimation of the invariant density for discretely observed diffusion processes: impact of the sampling and of the asynchronicity 2023 Chiara Amorino
Arnaud Gloter
+ Parametric inference for ergodic McKean-Vlasov stochastic differential equations 2024 Valentine Genon‐Catalot
Catherine Larédo
+ PDF Chat On a projection least squares estimator for jump diffusion processes 2023 Hélène Halconruy
Nicolas Marie
+ PDF Chat Optimal convergence rates for the invariant density estimation of jump-diffusion processes 2022 Chiara Amorino
Eulàlia Nualart
+ PDF Chat Rate of estimation for the stationary distribution of jump-processes over anisotropic Holder classes 2021 Chiara Amorino
+ Mixing it up: A general framework for Markovian statistics 2020 Niklas Dexheimer
Claudia Strauch
Lukas Trottner