ICM 1998, Berlin, Aug. 18–27

Abstracts of Short Communications and Posters

Section:

12. Probability and Statistics

1991 MS Classification: 62 60H15 Huebner, Marianne, Michigan State University, U. S. A. Nonparametric estimation for stochastic partial differential equations Stochastic partial differential equations are used to describe complex physical systems. It may be necessary to estimate constant or nonconstant parameters in such systems. To estimate the nonconstant coefficients of the differential operators in the stochastic partial differential equations, an increasing sequence of finite dimensional subspaces of the parameter space (sieves) is constructed on whihc the likelhood function is maximized. The asymptotic properties of the resulting estimators are discussed.