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...
| Main Authors: | Bühlmann, Peter (Author), van de Geer, Sara (Author) |
|---|---|
| Corporate Author: | SpringerLink (Online service) |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2011.
|
| Series: | Springer Series in Statistics,
|
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Similar Items
-
Estimation and Testing Under Sparsity École d'Été de Probabilités de Saint-Flour XLV – 2015 /
by: van de Geer, Sara
Published: (2016) -
A Course in Mathematical Statistics and Large Sample Theory
by: Bhattacharya, Rabi, et al.
Published: (2016) -
Basics of Modern Mathematical Statistics
by: Spokoiny, Vladimir, et al.
Published: (2015) -
Scan Statistics Methods and Applications /
Published: (2009) -
Mathematical Statistics Essays on History and Methodology /
by: Pfanzagl, Johann
Published: (2017)