Asymptotic properties of an estimator of the drift coefficients of multidimensional Ornstein-Uhlenbeck processes that are not necessarily stable

DOI10.1214/08-EJS290zbMath1320.62192arXiv0805.4535MaRDI QIDQ1951803

Philip Lee, Gopal Krishna Basak

Publication date: 24 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0805.4535

zbMATH Keywords

estimationconsistencyasymptotic efficiencystable processOrnstein-Uhlenbeck processesdrift coefficient matrix

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Markov processes: estimation; hidden Markov models (62M05) Strong limit theorems (60F15) Diffusion processes (60J60)

Related Items

Likelihood theory for the graph Ornstein-Uhlenbeck process, Deviation inequalities for quadratic Wiener functionals and moderate deviations for parameter estimators, Second-order continuous-time non-stationary Gaussian autoregression, On maximum likelihood estimation of the drift matrix of a degenerated O-U process, Asymptotic Properties of the LS-estimator of a Gaussian Autoregressive Process by an Averaging Method

Cites Work

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• Linear stochastic systems with constant coefficients. A statistical approach
• On the strong law of large numbers for multivariate martingales
• A class of limit theorems for singular diffusions
• Stability in distribution for a class of singular diffusions
• Estimation for diffusion processes from discrete observation
• On the estimation of parameters for linear stochastic differential equations
• Sequential parameter estimation with guaranteed mean-square accuracy for unstable linear stochastic systems
• On minimum uniform metric estimate of parameters of diffusion-type processes
• Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters
• Estimation of parameters of linear homogeneous stochastic differential equations
• Hypoelliptic second order differential equations
• Maximum likelihood estimation for continuous-time stochastic processes
• Parameter estimation for some non-recurrent solutions of SDE
• A Review of Some Aspects of Asymptotic Likelihood Theory for Stochastic Processes
• On the Statistical Treatment of Linear Stochastic Difference Equations