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Título: Statistics For High-Dimensional Data. Methods, Theory An Applications | |
| Autor: Buhlmann, Peter; Van de Geer, Sara | Precio: $1584.00 | |
| Editorial: Springer-Verlag Berlin Heidelberg | Año: 2011 | |
| Tema: Estadistica | Edición: 1ª | |
| Sinopsis | ISBN: 9783642201912 | |
| 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, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections.
A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods' great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science. |
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