PROBABILITY AND STATISTICS.
MINNESOTA UNIV MINNEAPOLIS DEPT OF STATISTICS
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Research on the derivation of stochastic differential equations in estimation and filtering problems in stochastic processes was completed. The system processes are continuous Markov processes with special emphasis on those which are solutions of a diffusion equation. The stochastic equation for the optimal filter is given not only in the form of an Ito differential equation but alternatively, as a differential equation of the Fisk-Stratonovich type. Other areas of research investigated under this grant are asymptotic properties of Bayes estimates for estimation problems with Markov process observations, distribution theory, ranking problems, prediction theory, stationary spectral measures and quasi-variant measures. References to papers completed in the above areas are included. Author
- Statistics and Probability