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.
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lasso讲的很清楚
评分哦哦哦,对的还有这本!
评分高维统计的入门书籍, 对高维的奠基性工作Lasso有比较详细的介绍。主要着重在linear model上,也有作者实用上特别是生物统计中的经验。不错的入门书籍
评分peter课讲得很好,这学期跟着他把这本书过了一遍。而且peter说快出第二版了,加了一章讲de-biased lasso:https://stat.ethz.ch/~buhlmann/teaching/desparsifiedLasso.pdf(可能还会有其他新内容?)
评分哦哦哦,对的还有这本!
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