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

A. Buonocore, A.G. Nobile and E. Pirozzi

Computational Statistics & Data Analysis, 2018, vol. 118, issue C, 40-53

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.

Keywords: Acceptance–Rejection method; Inverse transform method; Restricted Wiener and Ornstein–Uhlenbeck processes (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:118:y:2018:i:c:p:40-53

DOI: 10.1016/j.csda.2017.08.008

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