Second-order continuous-time non-stationary Gaussian autoregression

N. Lin () and S. Lototsky ()

Statistical Inference for Stochastic Processes, 2014, vol. 17, issue 1, 19-49

Abstract: The objective of the paper is to identify and investigate all possible types of asymptotic behavior for the maximum likelihood estimators of the unknown parameters in the second-order linear stochastic ordinary differential equation driven by Gaussian white noise. The emphasis is on the non-ergodic case, when the roots of the corresponding characteristic equation are not both in the left half-plane. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Lyapunov exponent; Maximum likelihood estimation; Asymptotic mixed normality; Non-normal limit distribution; Rate of convergence; Second-order stochastic equation; Primary 62F12; Secondary 62F03; 62M07; 62M09 (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sistpr:v:17:y:2014:i:1:p:19-49

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DOI: 10.1007/s11203-014-9090-9

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