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Statistics for High-Dimensional Data Methods, Theory and Applications /
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 mo...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2011.
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| Edición: | 1st ed. 2011. |
| Colección: | Springer Series in Statistics,
|
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-3-642-20192-9 | ||
| 003 | DE-He213 | ||
| 005 | 20220118203701.0 | ||
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| 008 | 110719s2011 gw | s |||| 0|eng d | ||
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| 024 | 7 | |a 10.1007/978-3-642-20192-9 |2 doi | |
| 050 | 4 | |a QA276-280 | |
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| 082 | 0 | 4 | |a 519.5 |2 23 |
| 100 | 1 | |a Bühlmann, Peter. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Statistics for High-Dimensional Data |h [electronic resource] : |b Methods, Theory and Applications / |c by Peter Bühlmann, Sara van de Geer. |
| 250 | |a 1st ed. 2011. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2011. | |
| 300 | |a XVIII, 558 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Springer Series in Statistics, |x 2197-568X | |
| 505 | 0 | |a Introduction -- Lasso for linear models -- Generalized linear models and the Lasso -- The group Lasso -- Additive models and many smooth univariate functions -- Theory for the Lasso -- Variable selection with the Lasso -- Theory for l1/l2-penalty procedures -- Non-convex loss functions and l1-regularization -- Stable solutions -- P-values for linear models and beyond -- Boosting and greedy algorithms -- Graphical modeling -- Probability and moment inequalities -- Author Index -- Index -- References -- Problems at the end of each chapter. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Statistics . | |
| 650 | 0 | |a Computer science-Mathematics. | |
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 1 | 4 | |a Statistical Theory and Methods. |
| 650 | 2 | 4 | |a Probability and Statistics in Computer Science. |
| 700 | 1 | |a van de Geer, Sara. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783642268571 |
| 776 | 0 | 8 | |i Printed edition: |z 9783642201936 |
| 776 | 0 | 8 | |i Printed edition: |z 9783642201912 |
| 830 | 0 | |a Springer Series in Statistics, |x 2197-568X | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-642-20192-9 |z Texto Completo |
| 912 | |a ZDB-2-SMA | ||
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| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||