Simulation of Highly Skewed Non-Gaussian Stochastic Processes
Author:
Affiliation:
1. Associate Member, ASCE
2. Assoc. Prof., Dept. of Civ. and Envir. Engrg., Princeton Univ., Princeton, NJ 08544.
3. Assoc., Risk Methodology Res., J. P. Morgan & Co. Inc., New York, NY 10005.
Publisher
American Society of Civil Engineers (ASCE)
Subject
Mechanical Engineering,Mechanics of Materials
Link
http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-9399%282001%29127%3A12%281284%29
Reference27 articles.
1. Cai G. Q. and Lin Y. K. ( 1996). “Generation of non-Gaussian stationary stochastic processes.” Physical Rev. 54(1) 299–303.
2. Deodatis G. ( 1997). “Simulation of stochastic processes and fields to model loading and material uncertainties.” Probabilistic methods for structural design C. G. Soares ed. Kluwer Dordrecht The Netherlands 261–288.
3. Deodatis G. Popescu R. and Prevost J.-H. ( 1995). “Simulation of stochastic processes and fields for Monte Carlo simulation applications: Some recent developments.” Proc. 1995 ASME Des. Engrg. Tech. Conf. Vol. 3 Part A ASME New York 955–965.
4. Crossings of Non‐Gaussian Translation Processes
5. Grigoriu M. ( 1995). Applied non-Gaussian processes Prentice-Hall Englewood Cliffs N.J.
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