Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/ass039
Title: On the sparsity of signals in a random sample
Authors: Jiang, B.
Loh, W.-L. 
Keywords: Large covariance matrix
Method of moments
Signal sequence
Sparsity
Trigonometric matrix
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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