UNCERTAINTY QUANTIFICATION WITH alpha-STABLE-PROCESS MODELS
Tuo, Rui
刊名STATISTICA SINICA
2018-04-01
卷号28期号:2页码:553-576
关键词Computer experiments kriging Levy processes stable distributions
ISSN号1017-0405
英文摘要In this article we consider using a class of alpha-stable processes, which can be regarded as generalizations of the Gaussian processes, as the surrogate models for uncertainty quantification. We introduce a class of alpha-stable processes, whose finite-dimensional distributions can be represented using independent stable random variables. This representation allows for Bayesian inference for the proposed statistical model. We can obtain the posterior distributions for the untried points as well as the model parameters through an MCMC algorithm. The computation for the representation requires some geometrical information given by the design points. We propose an efficient algorithm to solve this computational geometry problem. Two examples are given to illustrate the proposed method and its potential advantages.
资助项目NSFC[11501551] ; NSFC[11271355] ; NSFC[11671386] ; National Center for Mathematics and Interdisciplinary Sciences, CAS ; NSF[DMS 1007574]
WOS研究方向Mathematics
语种英语
出版者STATISTICA SINICA
WOS记录号WOS:000450211500002
内容类型期刊论文
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/31742]  
专题系统科学研究所
通讯作者Tuo, Rui
作者单位Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Tuo, Rui. UNCERTAINTY QUANTIFICATION WITH alpha-STABLE-PROCESS MODELS[J]. STATISTICA SINICA,2018,28(2):553-576.
APA Tuo, Rui.(2018).UNCERTAINTY QUANTIFICATION WITH alpha-STABLE-PROCESS MODELS.STATISTICA SINICA,28(2),553-576.
MLA Tuo, Rui."UNCERTAINTY QUANTIFICATION WITH alpha-STABLE-PROCESS MODELS".STATISTICA SINICA 28.2(2018):553-576.
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