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Article: Moment approach for singular values distribution of a large auto-covariance matrix
Title | Moment approach for singular values distribution of a large auto-covariance matrix |
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Authors | |
Keywords | Auto-covariance matrix Largest eigenvalue Limiting spectral distribution Moment method Singular values Stieltjes transform |
Issue Date | 2016 |
Publisher | Institute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aihp/default.htm |
Citation | Annales de l'Institut Henri Poincaré Probabilités et Statistiques, 2016, v. 52 n. 4, p. 1641-1666 How to Cite? |
Abstract | Let (εt)t>0(εt)t>0 be a sequence of independent real random vectors of pp-dimension and let XT=∑s+Tt=s+1εtε∗t−s/TXT=∑t=s+1s+Tεtεt−s∗/T be the lag-ss (ss is a fixed positive integer) auto-covariance matrix of εtεt. Since XTXT is not symmetric, we consider its singular values, which are the square roots of the eigenvalues of XTX∗TXTXT∗. Using the method of moments, we are able to investigate the limiting behaviors of the eigenvalues of XTX∗TXTXT∗ in two aspects. First, we show that the empirical spectral distribution of its eigenvalues converges to a nonrandom limit FF, which is a result previously developed in (J. Multivariate Anal. 137 (2015) 119–140) using the Stieltjes transform method. Second, we establish the convergence of its largest eigenvalue to the right edge of FF. |
Persistent Identifier | http://hdl.handle.net/10722/231312 |
ISSN | 2021 Impact Factor: 1.484 2020 SCImago Journal Rankings: 2.121 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wang, Q | - |
dc.contributor.author | Yao, JJ | - |
dc.date.accessioned | 2016-09-20T05:22:15Z | - |
dc.date.available | 2016-09-20T05:22:15Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Annales de l'Institut Henri Poincaré Probabilités et Statistiques, 2016, v. 52 n. 4, p. 1641-1666 | - |
dc.identifier.issn | 0246-0203 | - |
dc.identifier.uri | http://hdl.handle.net/10722/231312 | - |
dc.description.abstract | Let (εt)t>0(εt)t>0 be a sequence of independent real random vectors of pp-dimension and let XT=∑s+Tt=s+1εtε∗t−s/TXT=∑t=s+1s+Tεtεt−s∗/T be the lag-ss (ss is a fixed positive integer) auto-covariance matrix of εtεt. Since XTXT is not symmetric, we consider its singular values, which are the square roots of the eigenvalues of XTX∗TXTXT∗. Using the method of moments, we are able to investigate the limiting behaviors of the eigenvalues of XTX∗TXTXT∗ in two aspects. First, we show that the empirical spectral distribution of its eigenvalues converges to a nonrandom limit FF, which is a result previously developed in (J. Multivariate Anal. 137 (2015) 119–140) using the Stieltjes transform method. Second, we establish the convergence of its largest eigenvalue to the right edge of FF. | - |
dc.language | eng | - |
dc.publisher | Institute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aihp/default.htm | - |
dc.relation.ispartof | Annales de l'Institut Henri Poincaré Probabilités et Statistiques | - |
dc.subject | Auto-covariance matrix | - |
dc.subject | Largest eigenvalue | - |
dc.subject | Limiting spectral distribution | - |
dc.subject | Moment method | - |
dc.subject | Singular values | - |
dc.subject | Stieltjes transform | - |
dc.title | Moment approach for singular values distribution of a large auto-covariance matrix | - |
dc.type | Article | - |
dc.identifier.email | Yao, JJ: jeffyao@hku.hk | - |
dc.identifier.authority | Yao, JJ=rp01473 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1214/15-AIHP693 | - |
dc.identifier.scopus | eid_2-s2.0-84997171599 | - |
dc.identifier.hkuros | 263170 | - |
dc.identifier.volume | 52 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 1641 | - |
dc.identifier.epage | 1666 | - |
dc.identifier.isi | WOS:000389171800006 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0246-0203 | - |