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Bayes and Sequential Estimation in Stochastic PDEs

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Part of the Lecture Notes in Mathematics book series (LNM,volume 1923)

In Chapters 2-4 we were concerned with the study of asymptotic properties of several estimators of real valued drift parameter in linear and nonlinear Itô stochastic differential equations (SDEs) whose solutions are real valued diffusions. In many cases the results can be generalized to multidimensional stochastic differential equations. Parameter estimation in finite dimensional stochastic differential equations (SDEs) has been paid a lot of attention during the last three decades. See e.g., Liptser and Shiryayev (1978), Basawa and Prakasa Rao (1980), Kutoyants (1984a, 1994a) and Prakasa Rao (1999).

Keywords

  • Maximum Likelihood Estimate
  • Maximum Likelihood Estimator
  • Asymptotic Normality
  • Sequential Estimation
  • Sequential Plan

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© 2008 Springer-Verlag Berlin Heidelberg

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(2008). Bayes and Sequential Estimation in Stochastic PDEs. In: Parameter Estimation in Stochastic Differential Equations. Lecture Notes in Mathematics, vol 1923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74448-1_5

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