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|Title:||On the sparsity of signals in a random sample||Authors:||Jiang, B.
|Keywords:||Large covariance matrix
Method of moments
|Issue Date:||Dec-2012||Citation:||Jiang, B., Loh, W.-L. (2012-12). On the sparsity of signals in a random sample. Biometrika 99 (4) : 915-928. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/ass039||Abstract:||This article proposes a method of moments technique for estimating the sparsity of signals in a random sample. This involves estimating the largest eigenvalue of a large Hermitian trigonometric matrix under mild conditions. As illustration, the method is applied to two well-known problems. The first focuses on the sparsity of a large covariance matrix and the second investigates the sparsity of a sequence of signals observed with stationary, weakly dependent noise. Simulation shows that the proposed estimators can have significantly smaller mean absolute errors than their main competitors. © 2012 Biometrika Trust.||Source Title:||Biometrika||URI:||http://scholarbank.nus.edu.sg/handle/10635/105281||ISSN:||00063444||DOI:||10.1093/biomet/ass039|
|Appears in Collections:||Staff Publications|
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