Please use this identifier to cite or link to this item:
https://doi.org/10.1016/j.probengmech.2003.09.001
DC Field | Value | |
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dc.title | Simulation of non-Gaussian processes using fractile correlation | |
dc.contributor.author | Phoon, K.-K. | |
dc.contributor.author | Quek, S.-T. | |
dc.contributor.author | Huang, H. | |
dc.date.accessioned | 2014-06-17T08:25:06Z | |
dc.date.available | 2014-06-17T08:25:06Z | |
dc.date.issued | 2004-10 | |
dc.identifier.citation | Phoon, K.-K., Quek, S.-T., Huang, H. (2004-10). Simulation of non-Gaussian processes using fractile correlation. Probabilistic Engineering Mechanics 19 (4) : 287-292. ScholarBank@NUS Repository. https://doi.org/10.1016/j.probengmech.2003.09.001 | |
dc.identifier.issn | 02668920 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/66174 | |
dc.description.abstract | The difficulties of simulating non-Gaussian stochastic processes to follow arbitrary product-moment covariance models and arbitrary non-Gaussian marginal distributions are well known. This paper proposes to circumvent these difficulties by prescribing a fractile correlation function, rather than the usual product-moment covariance function. This fractile correlation can be related to the product-moment correlation of a Gaussian process analytically. A Gaussian process with the requisite product-moment correlation can be simulated using the Karhunen-Loeve (K-L) expansion and transformed to satisfy any arbitrary marginal distribution using the usual CDF mapping. The fractile correlation of the non-Gaussian process will be identical to that of the underlying Gaussian process because it is invariant to monotone transforms. This permits the K-L expansion to be extended in a very general way to any second-order non-Gaussian processes. The simplicity of the proposed approach is illustrated numerically using a stationary squared exponential and a non-stationary Brown-Bridge fractile correlation function in conjunction with a shifted lognormal and a shifted exponential marginal distribution. © 2003 Elsevier Ltd. All rights reserved. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.probengmech.2003.09.001 | |
dc.source | Scopus | |
dc.subject | CDF mapping | |
dc.subject | Fractile correlation | |
dc.subject | Karhunen-Loeve expansion | |
dc.subject | Non-Gaussian stochastic process | |
dc.subject | Non-stationary process | |
dc.subject | Product-moment correlation | |
dc.type | Article | |
dc.contributor.department | CIVIL ENGINEERING | |
dc.description.doi | 10.1016/j.probengmech.2003.09.001 | |
dc.description.sourcetitle | Probabilistic Engineering Mechanics | |
dc.description.volume | 19 | |
dc.description.issue | 4 | |
dc.description.page | 287-292 | |
dc.description.coden | PEMEE | |
dc.identifier.isiut | 000224497700001 | |
Appears in Collections: | Staff Publications |
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