Asymptotic inference for high-dimensional data

DOI10.1214/09-AOS718zbMath1184.62094arXiv1002.4554MaRDI QIDQ2380091

Anand N. Vidyashankar, James Kuelbs

Publication date: 24 March 2010

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1002.4554

zbMATH Keywords

high-dimensional datalaws of large numbersshrinkagestructured covariance matricesmicroarraysjoint inferencelarge \(p\) small \(n\)covariance matrix estimationfunctional genomicsinfinite-dimensional central limit theorem

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15) Central limit and other weak theorems (60F05)

Related Items (5)

Asymptotic inference for high-dimensional data ⋮ Joint regression analysis of mixed-type outcome data via efficient scores ⋮ Weak convergence results for multiple generations of a branching process ⋮ Near Optimal Prediction from Relevant Components ⋮ Test for a mean vector with fixed or divergent dimension

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