Statistical modeling of joint probability distribution using copula: application to peak and residual displacement seismic demands

K Goda

Research output: Contribution to journalArticle (Academic Journal)

55 Citations (Scopus)

Abstract

Reliability analysis of structures requires statistical models of multi-variate random data that are nonlinearly interrelated. The current reliability methods that use the Nataf transformation and the linear correlation matrix may encounter difficulties in dealing with such situations. A copula approach can offer a general and flexible way of describing nonlinear dependence among multi-variate data in isolation from their marginal probability distributions, and serves as a powerful tool for modeling and simulating nonlinearly-interrelated data. In this study, an introduction as well as illustrative application of the copula theory is given in the context of structural reliability. The numerical example deals with the performance evaluation of existing structures subjected to earthquake loading in terms of both peak and residual displacement demands. The joint probability distribution modeling of peak and residual displacement seismic demands based on the copula theory is demonstrated, and the developed statistical models are used to examine the effects of nonlinear dependence on seismic reliability assessment.
Original languageEnglish
Pages (from-to)112 - 123
Number of pages12
JournalStructural Safety
Volume32(2)
DOIs
Publication statusPublished - Mar 2010

Fingerprint Dive into the research topics of 'Statistical modeling of joint probability distribution using copula: application to peak and residual displacement seismic demands'. Together they form a unique fingerprint.

  • Cite this