{"product_id":"9781071655740","title":"Sampling Algorithms with R","description":"\u003ch3\u003eSpringer Series in Statistics\u003c\/h3\u003e\u003ch1\u003eSampling Algorithms\u003c\/h1\u003e\u003ch2\u003ewith R\u003c\/h2\u003e\u003ch3\u003eYves Tillé\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Probability \u0026amp; Statistics \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"mso-ansi-language: EN-US;\"\u003eThis book provides a comprehensive overview of innovative sampling methods. Building on the foundations of general sampling theory, it offers a rigorous yet accessible framework for understanding and implementing modern sampling algorithms.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"mso-ansi-language: EN-US;\"\u003eSampling has undergone a profound transformation since the early 2000s. This new edition has been substantially expanded and offers a far more comprehensive treatment than the first, providing both broader scope and greater depth in modern sampling methodology. It places particular emphasis on state-of-the-art approaches, including systematic and quasi-systematic designs; maximum entropy sampling designs; balanced sampling and its variants; spatial and spread sampling that ensure geographic dispersion for autocorrelated variables; sample coordination for repeated surveys; and sampling from data streams for real-time signal analysis. Sampling enables big data reduction, illustrating how sampling theory can efficiently handle massive datasets.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"mso-ansi-language: EN-US;\"\u003eEach method is presented in detail with an emphasis on practical implementation. Numerous techniques are illustrated using the R programming language, and fully functional code is provided to facilitate immediate application.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"mso-ansi-language: EN-US;\"\u003eThis book is intended for master’s and doctoral students, as well as experienced statisticians and researchers who already have a good grasp of sampling theory and wish to enrich their toolbox with theory-based, ready-to-implement techniques.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"mso-ansi-language: EN-US;\"\u003eYves Tillé is a professor emeritus at the University of Neuchâtel, Switzerland.\u003c\/span\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e15 September 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer US\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781071655740\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e415\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer US","offers":[{"title":"Default Title","offer_id":50450012897420,"sku":"9781071655740","price":143.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781071655740.jpg?v=1780592764","url":"https:\/\/lateknightbooks.com\/products\/9781071655740","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}