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Parameter estimation of Ornstein–Uhlenbeck process generating a stochastic graph

Article

Abstract

Given Y a graph process defined by an incomplete information observation of a multivariate Ornstein–Uhlenbeck process X, we investigate whether we can estimate the parameters of X. We define two statistics of Y. We prove convergence properties and show how these can be used for parameter inference. Finally, numerical tests illustrate our results and indicate possible extensions and applications.

Keywords

Stochastic graph process Inference for stochastic process Incomplete information Asymptotic properties of estimators 

Mathematics Subject Classification

62Mxx 05C80 62F12 

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.CMAP, Ecole Polytechnique and CNRSUniversité Paris SaclayPalaiseau CedexFrance

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