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政大機構典藏 > 商學院 > 統計學系 > 期刊論文 > Item 140.119/18181

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/18181

Title:	Approximate confidence sets for a stationary AR process
Authors:	翁久幸;Michael Woodroofe
Keywords:	Asymptotic expansions;Asymptotic conﬁdence levels;Stationary autoregressive process;Very weak expansions
Date:	2004-05
Issue Date:	2008-12-19 14:53:27 (UTC+8)
Abstract:	Approximate conﬁdence intervals are derived for the autoregressive parameters of a stationary, Gaussian auto-regressive process of arbitrary order and shown to be asymptotically correct to order o(1/n), where n is the sample size. Simulation studies are included for small and moderate sample sizes for the case of two auto-regressive parameters, and these indicate excellent approximation for sample sizes as small as n = 10,20. The convergence is in the very weak sense, and the derivation differs from most existing work through its direct focus on Studentized estimation error and its use of Stein’s identity.
Relation:	Journal of Statistical Planning and Inference, 136, 2719-2745
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1016/j.jspi.2004.11.007
DOI:	10.1016/j.jspi.2004.11.007
Appears in Collections:	[統計學系] 期刊論文

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