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About this product
- DescriptionThis valuable compendium of statistical methods features a unique combination of methodology, theory, algorithms and applications. It covers recently developed approaches to handling large and complex data sets, including the Lasso and boosting methods.
- Author BiographyPeter Buhlmann is Professor of Statistics at ETH Zurich. His main research areas are high-dimensional statistical inference, machine learning, graphical modeling, nonparametric methods, and statistical modeling in the life sciences. He is currently editor of the Annals of Statistics. He was awarded a Medallion lecture by the Institute of Mathematical Statistics in 2009 and read a paper to the Royal Statistical Society in 2010.Sara van de Geer has been a full professor at the ETH in Zurich since 2005. Her main areas of research are empirical process theory, statistical learning theory, and nonparametric and high-dimensional statistics. She is an associate editor of Probability Theory and Related Fields, The Scandinavian Journal of Statistics and Statistical Surveys and a member of the Swiss National Science Foundation and correspondent of the Dutch Royal Academy of Sciences.She received the IMS medal in 2003 and the ISI award in 2005, and was an invited speaker at the International Conference of Mathematicians in 2010.
- Author(s)Peter Buhlmann,Sara van de Geer
- PublisherSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
- Date of Publication02/08/2013
- Series TitleSpringer Series in Statistics
- Place of PublicationBerlin
- Country of PublicationGermany
- ImprintSpringer-Verlag Berlin and Heidelberg GmbH & Co. K
- Content NoteXVIII, 558 p.
- Weight872 g
- Width155 mm
- Height235 mm
- Edition Statement2011 ed.
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