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.
Generating random variates from PDF of Gauss-Markov processes with a reflecting boundary / Buonocore, A.; Nobile, A. G.; Pirozzi, E.. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 118:(2018), pp. 40-53. [10.1016/j.csda.2017.08.008]
Generating random variates from PDF of Gauss-Markov processes with a reflecting boundary
Buonocore, A.;Pirozzi, E.
2018
Abstract
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.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
