×


 x 

Shopping cart
Peter Bühlmann - Statistics for High-Dimensional Data: Methods, Theory and Applications - 9783642268571 - V9783642268571
Stock image for illustration purposes only - book cover, edition or condition may vary.

Statistics for High-Dimensional Data: Methods, Theory and Applications

€ 130.50
FREE Delivery in Ireland
Description for Statistics for High-Dimensional Data: Methods, Theory and Applications Paperback. This 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. Series: Springer Series in Statistics. Num Pages: 576 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 160 x 287 x 39. Weight in Grams: 842.

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 ... Read more

Show Less

Product Details

Format
Paperback
Publication date
2013
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
576
Condition
New
Series
Springer Series in Statistics
Number of Pages
558
Place of Publication
Berlin, Germany
ISBN
9783642268571
SKU
V9783642268571
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Peter Bühlmann
Peter Bühlmann is Professor of Statistics at ETH Zürich. 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 ... Read more

Reviews for Statistics for High-Dimensional Data: Methods, Theory and Applications
From the reviews: “This book is a complete study of ℓ1-penalization based statistical methods for high-dimensional data … . Definitely, this book is useful. … its strong level in mathematics makes it more suitable to researchers and graduate students who already have a strong background in statistics. … it gives the state-of-the-art of the theory, and therefore can be ... Read more

Goodreads reviews for Statistics for High-Dimensional Data: Methods, Theory and Applications


Subscribe to our newsletter

News on special offers, signed editions & more!