Statistics for High-Dimensional Data: Methods, Theory and Applications (2011) (Springer Series in Statistics)
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- Synopsis
- 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.
- Copyright:
- 2011
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783642201929
- Related ISBNs:
- 9783642201912
- Publisher:
- Springer Berlin Heidelberg
- Date of Addition:
- 07/13/22
- Copyrighted By:
- N/A
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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