Taschenbuch. Etat : 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. 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 L�szlo Gy�rfi, 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. 224 pp. Englisch. N� de r�f. du vendeur 9781461265276

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Combinatorial Methods in Density Estimation

Luc Devroye

Edit� par Springer-Verlag New York Inc., 2012

ISBN 10 : 1461265274 ISBN 13 : 9781461265276

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Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 379. N� de r�f. du vendeur C9781461265276

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Combinatorial Methods in Density Estimation

Gabor Lugosi

Edit� par Springer New York, Chapman And Hall/CRC, 2012

ISBN 10 : 1461265274 ISBN 13 : 9781461265276

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Taschenbuch. Etat : Neu. Druck auf Anfrage 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 L�szlo Gy�rfi, 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. N� de r�f. du vendeur 9781461265276

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Combinatorial Methods in Density Estimation (Springer Series in Statistics)

Devroye, Luc; Lugosi, Gabor

Edit� par Springer, 2012

ISBN 10 : 1461265274 ISBN 13 : 9781461265276

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Etat : New. N� de r�f. du vendeur ABLIING23Mar2716030028037

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Combinatorial Methods in Density Estimation

Luc Devroye|Gabor Lugosi

Edit� par Springer New York, 2012

ISBN 10 : 1461265274 ISBN 13 : 9781461265276

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Kartoniert / Broschiert. Etat : 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. N� de r�f. du vendeur 4189176

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