Parametric inference for hypoelliptic ergodic diffusions with full observations

DOI10.1007/s11203-020-09222-4zbMath1465.62047arXiv1802.02943OpenAlexW3042745567WikidataQ114223463 ScholiaQ114223463MaRDI QIDQ2023472

Anna Melnykova

Publication date: 3 May 2021

Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1802.02943

zbMATH Keywords

hypoelliptic diffusionsparametric inferencecontrast estimatorneuronal Fitzhugh-Nagumo model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric hypothesis testing (62F03) Markov processes: estimation; hidden Markov models (62M05) Diffusion processes (60J60)

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Cites Work

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• Estimation for stochastic damping Hamiltonian systems under partial observation. III: Diffusion term
• A contrast estimator for completely or partially observed hypoelliptic diffusion
• Convergence rate of weak local linearization schemes for stochastic differential equations with additive noise
• A stochastic version of the jansen and rit neural mass model: analysis and numerics
• Estimation for stochastic differential equations with a small diffusion coefficient
• On the estimation of the diffusion coefficient for multi-dimensional diffusion processes
• Local linearization method for the numerical solution of stochastic differential equations
• Hypoelliptic stochastic Fitzhugh-Nagumo neuronal model: mixing, up-crossing and estimation of the spike rate
• Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems.
• Parameter estimation for discretely observed stochastic volatility models
• Multi-class oscillating systems of interacting neurons
• Stochastic calculus of variations in mathematical finance.
• Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise.
• Time Series Modeling of Neuroscience Data
• The Malliavin Calculus and Related Topics
• Approximate discrete-time schemes for statistics of diffusion processes
• Parameter Estimation for Partially Observed Hypoelliptic Diffusions
• Sur les processus de diffusion de dimension 2
• Statistical Identification of Nonlinear Random Vibration Systems
• Estimation of an Ergodic Diffusion from Discrete Observations
• Consistency of a likelihood estimator for stochastic damping Hamiltonian systems. Totally observed data
• On unique ergodicity for degenerate diffusions
• Hypoelliptic Diffusions: Filtering and Inference from Complete and Partial Observations
• Stochastic volatility models as hidden Markov models and statistical applications
• Ergodicity for a stochastic Hodgkin-Huxley model driven by Ornstein-Uhlenbeck type input