Efficient Method for Approximating the Joint Extreme Value Distribution of Multivariate Stationary Gaussian Processes-Reference-Cited by-同舟云学术

Efficient Method for Approximating the Joint Extreme Value Distribution of Multivariate Stationary Gaussian Processes

Published:2023-04 Issue:4 Volume:149 Page:
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Zhao Zhao¹,Low Ying Min²

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, National Univ. of Singapore, 1 Engineering Dr. 2, Singapore 117576.

2. Associate Professor, Dept. of Civil and Environmental Engineering, National Univ. of Singapore, 1 Engineering Dr. 2, Singapore 117576 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

https://ascelibrary.org/doi/pdf/10.1061/JENMDT.EMENG-6881

Reference31 articles.

1. Abramowitz, M., and I. E. Stegun. 1972. Handbook of mathematical functions. New York: Dover.

2. A saddlepoint approach to estimating joint extreme value distributions for vector non-stationary Gaussian processes

3. Barltrop, N. D. P., and A. J. Adams. 1991. Dynamics of fixed marine structures. London: Marine Technology Directorate Limited/Butterworth–Heinemann.

4. On the Number of Exits Across the Boundary of a Region by a Vector Stochastic Process

5. Clough, R. W., and J. Penzien. 2003. Dynamic of structures. New York: McGraw-Hill.

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