Generating random variates from PDF of Gauss-Markov processes with a reflecting boundary

Algorithms to generate random variates from probability density function of Gauss-Markov processes restricted by special lower reflecting boundary are formulated. They are essentially obtained by means of discretizations of stochastic equations or via acceptance-rejection methods. Particular attention is dedicated to restricted Wiener and Ornstein-Uhlenbeck processes.