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	Confidence intervals for sparse precision matrix estimation via Lasso penalized D-trace loss
	Huang Xudong1,2; Li Mengmeng2
刊名	COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
	2017
卷号	46期号:24页码:12299-12316
关键词	Confidence intervals D-trace loss High-dimensional Precision matrix Sparsity
ISSN号	0361-0926
DOI	10.1080/03610926.2017.1295074
英文摘要	This article aims at establishing the confidence intervals for individual parameters of high-dimensional sparse precision matrix. Benefit from a precision matrix estimator which is defined as the minimizer of the Lasso penalized D-trace loss under a positive-definiteness constraint, we modify the KKT condition of the optimization problem to obtain a de-sparsified estimator. We analyze the asymptotic properties of the estimator under some regularity conditions and establish the asymptotic normality and confidence intervals for the case of sub-Gaussian observations. Numerical results show the performance of the proposed method.
WOS研究方向	Mathematics
语种	英语
出版者	TAYLOR & FRANCIS INC
WOS记录号	WOS:000415803800023
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/1070]
专题	上海财经大学
通讯作者	Huang Xudong
作者单位	1.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China; 2.Anhui Normal Univ, Sch Math & Comp Sci, Wuhu 241002, Peoples R China
推荐引用方式 GB/T 7714	Huang Xudong,Li Mengmeng. Confidence intervals for sparse precision matrix estimation via Lasso penalized D-trace loss[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,2017,46(24):12299-12316.
APA	Huang Xudong,&Li Mengmeng.(2017).Confidence intervals for sparse precision matrix estimation via Lasso penalized D-trace loss.COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,46(24),12299-12316.
MLA	Huang Xudong,et al."Confidence intervals for sparse precision matrix estimation via Lasso penalized D-trace loss".COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 46.24(2017):12299-12316.

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