Large-Scale Correlation Screening

DOI10.1198/jasa.2011.tm11015zbMath1234.62089arXiv1109.6846OpenAlexW1985260835MaRDI QIDQ3225816

Alfred O. III Hero, Bala Rajaratnam

Publication date: 22 March 2012

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1109.6846

zbMATH Keywords

phase transitionthresholdingvariable selectionsparsityhigh-dimensional inferenceRényi entropyfalse discoveryPoisson limitChen-Stein

Mathematics Subject Classification ID

Related Items (17)

Stable estimation of a covariance matrix guided by nuclear norm penalties ⋮ Matrix positivity preservers in fixed dimension. I ⋮ High-dimensional inference on covariance structures via the extended cross-data-matrix methodology ⋮ Statistical inference for high-dimension, low-sample-size data ⋮ Correlation tests for high-dimensional data using extended cross-data-matrix methodology ⋮ Graphical Markov models for infinitely many variables ⋮ Phase transition in limiting distributions of coherence of high-dimensional random matrices ⋮ Retaining positive definiteness in thresholded matrices ⋮ Critical exponents of graphs ⋮ Spectral Correlation Hub Screening of Multivariate Time Series ⋮ A panorama of positivity. II: Fixed dimension ⋮ Complete characterization of Hadamard powers preserving Loewner positivity, monotonicity, and convexity ⋮ Schur polynomials and matrix positivity preservers ⋮ Functions preserving positive definiteness for sparse matrices ⋮ Asymptotics of eigenstructure of sample correlation matrices for high-dimensional spiked models ⋮ Properties of eigenvalues and eigenvectors of large-dimensional sample correlation matrices ⋮ Preserving positivity for rank-constrained matrices

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