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Mixing it up: A general framework for Markovian statistics
v1v2v3 (latest)

Mixing it up: A general framework for Markovian statistics

31 October 2020
Niklas Dexheimer
Claudia Strauch
Lukas Trottner
ArXiv (abs)PDFHTML

Papers citing "Mixing it up: A general framework for Markovian statistics"

7 / 7 papers shown
Title
Statistical algorithms for low-frequency diffusion data: A PDE approach
Statistical algorithms for low-frequency diffusion data: A PDE approach
Matteo Giordano
Sven Wang
74
4
0
02 May 2024
Data-driven rules for multidimensional reflection problems
Data-driven rules for multidimensional reflection problems
Soren Christensen
Asbjorn Holk Thomsen
Lukas Trottner
71
4
0
11 Nov 2023
Adaptive nonparametric drift estimation for multivariate jump diffusions
  under sup-norm risk
Adaptive nonparametric drift estimation for multivariate jump diffusions under sup-norm risk
Linqi Zhou
44
0
0
29 Sep 2023
Malliavin calculus for the optimal estimation of the invariant density
  of discretely observed diffusions in intermediate regime
Malliavin calculus for the optimal estimation of the invariant density of discretely observed diffusions in intermediate regime
Chiara Amorino
A. Gloter
66
2
0
05 Aug 2022
Estimating the characteristics of stochastic damping Hamiltonian systems
  from continuous observations
Estimating the characteristics of stochastic damping Hamiltonian systems from continuous observations
Niklas Dexheimer
Claudia Strauch
74
3
0
27 Sep 2021
Learning to reflect: A unifying approach for data-driven stochastic
  control strategies
Learning to reflect: A unifying approach for data-driven stochastic control strategies
Soren Christensen
Claudia Strauch
Lukas Trottner
57
10
0
23 Apr 2021
Optimal convergence rates for the invariant density estimation of
  jump-diffusion processes
Optimal convergence rates for the invariant density estimation of jump-diffusion processes
Chiara Amorino
Eulalia Nualart
47
8
0
21 Jan 2021
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