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.
發表於2024-12-22
Statistics for High-Dimensional Data 2024 pdf epub mobi 電子書 下載
圖書標籤: 機器學習 統計 Statistics 數學 統計學 high-dimension 統計理論 statistics
哦哦哦,對的還有這本!
評分高維統計的入門書籍, 對高維的奠基性工作Lasso有比較詳細的介紹。主要著重在linear model上,也有作者實用上特彆是生物統計中的經驗。不錯的入門書籍
評分哦哦哦,對的還有這本!
評分peter課講得很好,這學期跟著他把這本書過瞭一遍。而且peter說快齣第二版瞭,加瞭一章講de-biased lasso:https://stat.ethz.ch/~buhlmann/teaching/desparsifiedLasso.pdf(可能還會有其他新內容?)
評分在讀
Statistics for High-Dimensional Data 2024 pdf epub mobi 電子書 下載