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Statistics for high-dimensional data methods, theory and applications / Peter Bühlmann, Sara van de Geer.
| Author/creator | Bühlmann, Peter |
| Other author | Geer, S. A. van de (Sara A.) |
| Format | Electronic |
| Publication Info | Heidelberg ; New York : Springer, |
| Description | xvii, 556 p. : ill. (some col.) ; 24 cm. |
| Supplemental Content | Full text available from Springer Books |
| Supplemental Content | Full text available from Springer Nature - Springer Mathematics and Statistics eBooks 2011 English International |
| Subjects |
| Series | Springer series in statistics Springer series in statistics. ^A236188 |
| Contents | 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-regulation -- Stable solutions -- P-values for linear models and beyond -- Boosting and greedy algorithms -- Graphical modeling -- Probabililty and moment inequalities. |
| Bibliography note | Includes bibliographical references (p. 547-556) and indexes. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2011930793 |
| ISBN | 9783642201912 (hdbk. : acid-free paper) |
| ISBN | 3642201911 (hdbk. : acid-free paper) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | ✔ Available |