Click Here to Download: https://ouo.io/fpk6xk Introduction to High-Dimensional Statistics By: Christophe Giraud Publisher: Chapman and Hall/CRC Print ISBN: 9781482237948, 1482237946 eText ISBN: 9781482237955, 1482237954 Edition: 1st Copyright year: 2014 Format: PDF Available from $ 23.18 USD SKU 9781482237955R90 Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study. Additional ISBNs 9781482237955, 9781322629537, 1482237954, 1322629536
