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	On the use of dimension reduction techniques in quasi-Monte Carlo methods
	Zhao, Y.Z.
	2010-10-12 ; 2010-10-12
关键词	Theoretical or Mathematical/ Monte Carlo methods principal component analysis random processes/ dimension reduction techniques quasi-Monte Carlo methods quasi-random sequences truncation variance ratio optimal Brownian bridge principal component analysis PCA OBB Latin hypercube sampling/ C1290 Applications of systems theory C1140G Monte Carlo methods
中文摘要	It is known that dimension reduction techniques may improve the efficiency of quasi-Monte Carlo (QMC) methods. Different dimension reduction techniques may lead to different efficiencies, even if the nominal dimensions are equal and the same quasi-random sequences are used. To explain this, the degree of additivity and the truncation variance ratio are studied in this paper. Three dimension reduction techniques are compared: Brownian bridge (BB), optimal Brownian bridge (OBB) and principal component analysis (PCA), in which OBB provides a new generating order so that it improves BB. Numerical experiments are performed to compare the efficiency of QMC and Latin hypercube sampling (LHS) combined with different dimension reduction techniques. The importance of the dimension reduction techniques in QMC and the usefulness of the degree of additivity and the truncation variance ratio in characterizing the performance of QMC are confirmed.[All rights reserved Elsevier].
语种	英语
出版者	Elsevier Science Ltd. ; UK
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/81179]
专题	清华大学
推荐引用方式 GB/T 7714	Zhao, Y.Z.. On the use of dimension reduction techniques in quasi-Monte Carlo methods[J],2010, 2010.
APA	Zhao, Y.Z..(2010).On the use of dimension reduction techniques in quasi-Monte Carlo methods..
MLA	Zhao, Y.Z.."On the use of dimension reduction techniques in quasi-Monte Carlo methods".(2010).

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