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 characte...(展开全部)

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 characte...(展开全部)

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 characte...(展开全部)

The book covers new mathematical and computational principles for high-dimensional data analysis (statistics and geometry), scalable optimization methods (convex and nonconvex), and important applications such as scientific imaging, wideband communications, face recognition, 3D vision, and deep networks. This book is to be used as an introductory graduate textbook for the areas...(展开全部)

The book covers new mathematical and computational principles for high-dimensional data analysis (statistics and geometry), scalable optimization methods (convex and nonconvex), and important applications such as scientific imaging, wideband communications, face recognition, 3D vision, and deep networks. This book is to be used as an introductory graduate textbook for the areas...(展开全部)

High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the f...(展开全部)

This book is intended for those developers who are willing to enter the field of data science and are looking for concise information of statistics with the help of insightful programs and simple explanation. Some basic hands on R will be useful.

<span>"This is a first-class book dealing with one of the most important areas of current research in applied statistics&#8230;the methods described are widely applicable&#8230;the standard of exposition is extremely high." <br />--Short Book Reviews from the International Statistical Institute</span></p> <span>"The new chapters (10-14) improve an already excellent resou...(展开全部)

<span>"This is a first-class book dealing with one of the most important areas of current research in applied statistics&#8230;the methods described are widely applicable&#8230;the standard of exposition is extremely high." <br />--Short Book Reviews from the International Statistical Institute</span></p> <span>"The new chapters (10-14) improve an already excellent resou...(展开全部)

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnos...(展开全部)