{ "item_title" : "Statistics for High-Dimensional Data", "item_author" : [" Peter Bühlmann", "Sara Van de Geer "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/64/220/191/3642201911_b.jpg", "price_data" : { "retail_price" : "179.00", "online_price" : "179.00", "our_price" : "179.00", "club_price" : "179.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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