Statistics for High-Dimensional Data pdf epub mobi txt 电子书下载 2025

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出版者:Springer

作者:Peter Bühlmann

出品人:

页数:558

译者:

出版时间:2011-6-14

价格:USD 79.11

装帧:Hardcover

isbn号码:9783642201912

丛书系列:Springer Series in Statistics

图书标签:

机器学习
统计
Statistics
数学
统计学
high-dimension
统计理论
statistics
统计学
高维数据
机器学习
数据分析
统计建模
降维
特征选择
正则化
理论统计
应用统计

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具体描述

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.