UNCERTAINTY QUANTIFICATION WITH alpha-STABLE-PROCESS MODELS

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	UNCERTAINTY QUANTIFICATION WITH alpha-STABLE-PROCESS MODELS
	Tuo, Rui
	2018-04-01
发表期刊	STATISTICA SINICA
ISSN	1017-0405
卷号	28 期号:2 页码:553-576
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.
关键词	Computer experiments kriging Levy processes stable distributions
语种	英语
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
WOS类目	Statistics & Probability
WOS记录号	WOS:000450211500002
出版者	STATISTICA SINICA
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/31743
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.