A computational approach to first-passage-time problems for Gauss-Markov processes
The authors propose a new computationally simple, speedy and accurate method for the construction of first-passage-time probability density functions for Gauss-Markov processes through time-dependent boundaries, both for fixed and random initial states. Furthermore, some applications to Brownian motion and to the Brownian bridge are also provided along with a comparison with some computational results for Durbin and Daniels. Finally, certain results on classes of boundaries are also obtained.
scientific article; zbMATH DE number 1663789