Parameter estimation for a bidimensional partially observed Ornstein-Uhlenbeck process with biological application. (English) Zbl 1224.62032
A bidimensional Ornstein-Uhlenbeck process is considered where the first component is observed only at discrete points with independent Gaussian errors. The aim is to estimate the process parameters. Exact likelihood, its gradient and Hessian are evaluated. Quasi-Newton and EM algorithms for the estimates and identifiability of the parameters are discussed. Results of simulations are presented.
Reviewer: R. E. Maiboroda (Kyïv)
MSC:
| 62M05 | Markov processes: estimation; hidden Markov models |
| 62F12 | Asymptotic properties of parametric estimators |
| 65C60 | Computational problems in statistics (MSC2010) |
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