A parallel algorithm is implemented to simulate sample paths of stationary normal processes possessing a Butterworth-type covariance, in order to investigate asymptotic properties of the first passage time probability densities for time-varying boundaries. After a self-contained outline of the simulation procedure, computational results are included to show that for large times and for large boundaries the first passage time probability density through an asymptotically periodic boundary is exponentially distributed to an excellent degree of approximation.
Computer-aided simulations of Gaussian processes and related asymptotic properties
NOBILE, Amelia Giuseppina;
2001
Abstract
A parallel algorithm is implemented to simulate sample paths of stationary normal processes possessing a Butterworth-type covariance, in order to investigate asymptotic properties of the first passage time probability densities for time-varying boundaries. After a self-contained outline of the simulation procedure, computational results are included to show that for large times and for large boundaries the first passage time probability density through an asymptotically periodic boundary is exponentially distributed to an excellent degree of approximation.File in questo prodotto:
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