Inference for the mean of large \(p\) small \(n\) data: a finite-sample high-dimensional generalization of Hotelling's theorem

DOI10.1214/13-EJS833zbMath1293.62126MaRDI QIDQ358893

Aymeric Stamm, Simone Vantini, Piercesare Secchi

Publication date: 9 August 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1375708877

zbMATH Keywords

high-dimensional dataMANOVAHotelling's theoreminference for the meanlarge \(p\) small \(n\) data

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Hypothesis testing in multivariate analysis (62H15)

Related Items (5)

Object Oriented Data Analysis: A few methodological challenges ⋮ High dimensional asymptotics for the naive Hotelling T² statistic in pattern recognition ⋮ Hotelling's \(T^2\) in separable Hilbert spaces ⋮ Hypothesis testing for high-dimensional time series via self-normalization ⋮ Inference for high-dimensional split-plot-designs: a unified approach for small to large numbers of factor levels

Uses Software

• R
• fda (R)

Cites Work

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• Testing the equality of several covariance matrices with fewer observations than the dimension
• The positive false discovery rate: A Bayesian interpretation and the \(q\)-value
• The control of the false discovery rate in multiple testing under dependency.
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Distances and inference for covariance operators
• Finite-sample consistency of combination-based permutation tests with application to repeated measures designs
• Multivariate Theory for Analyzing High Dimensional Data
• Testing Statistical Hypotheses

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