Statistics for High-Dimensional Data
Springer series in statisticsPublished 1 January 2011
Peter Bühlmann, Sara van de Geer
Citations1,620
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Abstract
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, such as the Lasso and boosting methods. It also provides the mathematical theory behind them, proving their great potential in a large number of settings. Both the methods and theory are then illustrated with real data examples.
Keywords
Computer Science
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