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Iain M. Johnstone
Researcher at Stanford University
Publications - 113
Citations - 31982
Iain M. Johnstone is an academic researcher from Stanford University. The author has contributed to research in topics: Minimax & Estimator. The author has an hindex of 54, co-authored 111 publications receiving 29434 citations. Previous affiliations of Iain M. Johnstone include University of Oxford & Australian National University.
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Least angle regression
Bradley Efron,Trevor Hastie,Iain M. Johnstone,Robert Tibshirani,Hemant Ishwaran,Keith Knight,Jean-Michel Loubes,Jean-Michel Loubes,Pascal Massart,Pascal Massart,David Madigan,David Madigan,Greg Ridgeway,Greg Ridgeway,Saharon Rosset,Saharon Rosset,Ji Zhu,Robert A. Stine,Berwin A. Turlach,Sanford Weisberg +19 more
TL;DR: A publicly available algorithm that requires only the same order of magnitude of computational effort as ordinary least squares applied to the full set of covariates is described.
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Adapting to Unknown Smoothness via Wavelet Shrinkage
TL;DR: In this article, the authors proposed a smoothness adaptive thresholding procedure, called SureShrink, which is adaptive to the Stein unbiased estimate of risk (sure) for threshold estimates and is near minimax simultaneously over a whole interval of the Besov scale; the size of this interval depends on the choice of mother wavelet.
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On the distribution of the largest eigenvalue in principal components analysis
TL;DR: In this article, the authors derived the Tracey-Widom law of order 1 for large p and n matrices, where p is the largest eigenvalue of a p-variate Wishart distribution on n degrees of freedom with identity covariance.
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Wavelet Shrinkage: Asymptopia?
TL;DR: A method for curve estimation based on n noisy data: translate the empirical wavelet coefficients towards the origin by an amount √(2 log n) /√n and draw loose parallels with near optimality in robustness and also with the broad near eigenfunction properties of wavelets themselves.
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Rejoinder to "least angle regression" by efron et al.
TL;DR: In this article, the authors re-joinder to ''Least angle regression'' by Efron et al. [math.ST/0406456] is presented.