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November 2015 High-Dimensional Inference: Confidence Intervals, $p$-Values and R-Software hdi
Ruben Dezeure, Peter Bühlmann, Lukas Meier, Nicolai Meinshausen
Statist. Sci. 30(4): 533-558 (November 2015). DOI: 10.1214/15-STS527


We present a (selective) review of recent frequentist high-dimensional inference methods for constructing $p$-values and confidence intervals in linear and generalized linear models. We include a broad, comparative empirical study which complements the viewpoint from statistical methodology and theory. Furthermore, we introduce and illustrate the R-package hdi which easily allows the use of different methods and supports reproducibility.


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Ruben Dezeure. Peter Bühlmann. Lukas Meier. Nicolai Meinshausen. "High-Dimensional Inference: Confidence Intervals, $p$-Values and R-Software hdi." Statist. Sci. 30 (4) 533 - 558, November 2015.


Published: November 2015
First available in Project Euclid: 9 December 2015

zbMATH: 06946201
MathSciNet: MR3432840
Digital Object Identifier: 10.1214/15-STS527

Keywords: $p$-value , clustering , Confidence interval , generalized linear model , high-dimensional statistical inference , linear model , multiple testing , R-software

Rights: Copyright © 2015 Institute of Mathematical Statistics


Vol.30 • No. 4 • November 2015
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