{"product_id":"9780387973678","title":"Springer Series in Statistics: With Implementation in S","description":"\u003ch1\u003eSpringer Series in Statistics: With Implementation in S\u003c\/h1\u003e \u003ch2\u003eHärdle, Wolfgang\u003c\/h2\u003e \u003cp\u003eThe author has attempted to present a book that provides a non-technical introduction into the area of non-parametric density and regression function estimation. The application of these methods is discussed in terms of the S computing environment. Smoothing in high dimensions faces the problem of data sparseness. A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points. Additive models provide a way out of this dilemma; but, for their interactiveness and recursiveness, they require highly effective algorithms. For this purpose, the method of WARPing (Weighted Averaging using Rounded Points) is described in great detail.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 1990-12-05\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9780387973678\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4612-4432-5\u003c\/p\u003e \u003cp\u003eDimensions: 234cm x156cm\u003c\/p\u003e \u003cp\u003ePages: 262\u003c\/p\u003e ","brand":"Springer New York","offers":[{"title":"Default Title","offer_id":46540616171660,"sku":"9780387973678","price":98.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780387973678.jpg?v=1775710778","url":"https:\/\/lateknightbooks.com\/products\/9780387973678","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}