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 |
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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 |
format | Article |
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source | RePEc; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; ScienceDirect Journals (5 years ago - present) |
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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