Descuento:
-5%Antes:
Despues:
118,75 €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.
Features
• Contains the fundamentals of the recent research in a very timely area
• Gives an overview of the area and adds many new insights
• There is a unique mix of methodology, theory, algorithms and applications
• The number of recent papers on the topic is huge
• Is a welcome consolidation
• Is an essential for the further development of theory and methods
-5%
-5%
-5%
-5%
-5%
-5%
-5%
