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Bayes quadratic unbiased estimator of spatial covariance parameters
This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes ...
On the analysis of path-dependent functionals of stochastic PDEs
Weak approximation methods for stochastic partial differential equations (SPDEs) are concerned with approximating the probability distribution of the solution process rather than the realizations of the solution process itself. In this thesis, we provide new results and methods concerning the weak error analysis of numerical approximations of path-dependent functionals of solution processes of SPDEs. Two separate approaches to analyzing weak approximation errors are considered: the Itô calculus approach and the ...