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B1280
Title: Goodness-of-fit tests for Gaussian random processes Authors:  Daniel Hlubinka - Univerzita Karlova (Czech Republic) [presenting]
Zdenek Hlavka - Charles University (Czech Republic)
Abstract: Goodness-of-fit tests are introduced for families of Gaussian random processes parametrized by finite-dimensional parameters. The tests are based on the Cramer-von Mises distance of characteristic functionals. The main advantage of the characteristic functional approach is the sensitivity of the tests to violation of Gaussianity contrary to the classical tests based on covariance operators. We show several examples, including Ornstein-Uhlenbeck processes, fractional Brownian motion and Cox-Ingersoll-Ross processes.