Maximum likelihood estimator for hidden Markov models in continuous time
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Publication:625302
DOI10.1007/s11203-008-9025-4zbMath1205.62120arXiv0707.0271OpenAlexW3102595170MaRDI QIDQ625302
Publication date: 15 February 2011
Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0707.0271
Asymptotic properties of parametric estimators (62F12) Markov processes: estimation; hidden Markov models (62M05)
Related Items (8)
Parameter estimation for continuous time hidden Markov processes ⋮ Asymptotic properties of MLE for partially observed fractional diffusion system ⋮ On parameter estimation of the hidden Gaussian process in perturbed SDE ⋮ On parameter estimation of the hidden Ornstein-Uhlenbeck process ⋮ On parameter estimation of hidden ergodic Ornstein-Uhlenbeck process ⋮ On localization of source by hidden Gaussian processes with small noise ⋮ The stability of conditional Markov processes and Markov chains in random environments ⋮ Asymptotic properties of MLE for partially observed fractional diffusion system with dependent noises
Cites Work
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- Model robustness of finite state nonlinear filtering over the infinite time horizon
- Leroux's method for general hidden Markov models
- Parameter estimation and asymptotic stability in stochastic filtering
- Uniform coupling of non-homogeneous Markov chains
- Asymptotic Stability of the Wonham Filter: Ergodic and Nonergodic Signals
- Hidden Markov processes
- Almost Global Stochastic Stability
- Some Applications of Stochastic Differential Equations to Optimal Nonlinear Filtering
- Statistical Inference for Probabilistic Functions of Finite State Markov Chains
- Probabilistic Functions of Finite State Markov Chains
- Asymptotics of the maximum likelihood estimator for general hidden Markov models
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