Isbn: 9780387951171 - combinatorial methods in density estimation (springer series in statistics) (15 resultados)

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Hardcover. Condición: VG. No Jacket. used hardcover copy, lacking a dust jacket (as issued). light shelfwear, corners perhaps slightly bumped. pages and binding are clean, straight, and tight. there are no marks to the text or other serious flaws.

Condición: New. In English.

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Condición: New.

Condición: New.

Condición: New.

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Condición: New. pp. 224.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This text explores a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric. It is the first book on this topic. The text is intended for first-year graduate students in statistics and learning theory, and offers a host of opportunities for further research and thesis topics. Each chapter corresponds roughly to one lecture, and is supplemented with many classroom exercises. A one year course in probability theory at the level of Feller's Volume 1 should be more than adequate preparation. 224 pp. Englisch.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This text explores a new paradigm for the data-based or automatic selec.…

Condición: New. Print on Demand pp. 224 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book will be of interest to statistical researchers working in the area of nonparametric density estimation.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 224 pp. Englisch.

Condición: New. PRINT ON DEMAND pp. 224.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This text explores a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric. It is the first book on this topic. The text is intended for first-year graduate students in statistics and learning theory, and offers a host of opportunities for further research and thesis topics. Each chapter corresponds roughly to one lecture, and is supplemented with many classroom exercises. A one year course in probability theory at the level of Feller's Volume 1 should be more than adequate preparation. Gabor Lugosi is Professor at Universitat Pompeu Fabra in Barcelona, and Luc Debroye is Professor at McGill University in Montreal. In 1996, the authors, together with Lászlo Györfi, published the successful text, A Probabilistic Theory of Pattern Recognition with Springer-Verlag. Both authors have made many contributions in the area of nonparametric estimation.…