Parameter Estimation for Controlled Semilinear Stochastic Systems: Identifiability and Consistency

We consider a controlled stochastic semilinear evolution equation with the drift depending on the unknown parameter. We show that the maximum likelihood estimator is strongly consistent for a class of bounded predictable controls.

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Veröffentlicht in:Journal of multivariate analysis 2002-02, Vol.80 (2), p.322-343
Hauptverfasser: Goldys, B., Maslowski, B.
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container_title Journal of multivariate analysis
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creator Goldys, B.
Maslowski, B.
description We consider a controlled stochastic semilinear evolution equation with the drift depending on the unknown parameter. We show that the maximum likelihood estimator is strongly consistent for a class of bounded predictable controls.
doi_str_mv 10.1006/jmva.2001.1989
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subjects Exact sciences and technology
identifiability
infinitesimal generator
invariant measure
Mathematics
maximum likelihood estimator
Probability and statistics
Probability theory and stochastic processes
Sciences and techniques of general use
semilinear stochastic evolution equation
semilinear stochastic evolution equation maximum likelihood estimator identifiability invariant measure strong law of large numbers transition semigroup infinitesimal generator
Stochastic analysis
strong law of large numbers
transition semigroup
title Parameter Estimation for Controlled Semilinear Stochastic Systems: Identifiability and Consistency
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