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

T. Deck

Journal of Multivariate Analysis, 2006, vol. 97, issue 2, 563-573

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.

Keywords: Parameter; estimation; Linear; filtering; theory (search for similar items in EconPapers)
Date: 2006
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