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Asymptotic properties of Bayes estimators for Gaussian Itô-processes with noisy observations

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  • Deck, T.

Abstract

The estimation of a real parameter [theta] in a linear stochastic differential equation of the simple type is investigated, based on noisy, time continuous observations of Xt. Sufficient conditions on the continuous functions [beta] and [sigma] are given such that the (conditionally normal) Bayes estimators of [theta] satisfy certain error bounds and are strongly consistent.

Suggested Citation

  • Deck, T., 2006. "Asymptotic properties of Bayes estimators for Gaussian Itô-processes with noisy observations," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 563-573, February.
    • Handle: RePEc:eee:jmvana:v:97:y:2006:i:2:p:563-573
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    References listed on IDEAS

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    1. Kunita, Hiroshi, 1971. "Asymptotic behavior of the nonlinear filtering errors of Markov processes," Journal of Multivariate Analysis, Elsevier, vol. 1(4), pages 365-393, December.
    2. Kallianpur, G. & Selukar, R. S., 1991. "Parameter estimation in linear filtering," Journal of Multivariate Analysis, Elsevier, vol. 39(2), pages 284-304, November.
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