On parameter estimation of the hidden Ornstein-Uhlenbeck process

DOI10.1016/J.JMVA.2018.09.008zbMath1408.62143OpenAlexW2893865449WikidataQ129184089 ScholiaQ129184089MaRDI QIDQ1755125

Yury A. Kutoyants

Publication date: 4 January 2019

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2018.09.008

zbMATH Keywords

parameter estimationhidden processsmall noise asymptoticspartially observed linear system

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Markov processes: estimation; hidden Markov models (62M05) Diffusion processes (60J60)

Related Items (7)

Parameter estimation for continuous time hidden Markov processes ⋮ Asymptotic properties for quadratic functionals of linear self-repelling diffusion process and applications ⋮ Parameter estimation for ergodic linear SDEs from partial and discrete observations ⋮ On parameter estimation of the hidden Gaussian process in perturbed SDE ⋮ On the Parameter Estimation in the Schwartz-Smith’s Two-Factor Model ⋮ On parameter estimation of hidden ergodic Ornstein-Uhlenbeck process ⋮ On localization of source by hidden Gaussian processes with small noise

Cites Work

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• On frequency estimation for a periodic ergodic diffusion process
• Maximum likelihood estimator for hidden Markov models in continuous time
• Linear stochastic systems with constant coefficients. A statistical approach
• Fisher's method of scoring in the problem of frequency estimation
• Statistical inference for ergodic diffusion processes.
• On parameter estimation of hidden telegraph process
• Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models
• On the multi-step MLE-process for ergodic diffusion
• Inference in hidden Markov models.
• Estimating a periodicity parameter in the drift of a time inhomogeneous diffusion
• Hidden Markov processes
• On Stochastic Processes Defined by Differential Equations with a Small Parameter

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