The geometry of least squares in the 21st century
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Publication:373539
DOI10.3150/12-BEJSP15zbMath1402.62157arXiv1309.7837MaRDI QIDQ373539
Publication date: 17 October 2013
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1309.7837
Ridge regression; shrinkage estimators (Lasso) (62J07) Gaussian processes (60G15) Linear regression; mixed models (62J05) History of mathematics in the 21st century (01A61) History of statistics (62-03)
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Inference in adaptive regression via the Kac-Rice formula, Recovering Structured Signals in Noise: Least-Squares Meets Compressed Sensing, Penalized least square in sparse setting with convex penalty and non Gaussian errors, Geometry and applied statistics
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