Combinatorial Methods in Density Estimation

Language: English

Published by Springer, Springer Sep 2012, 2012

1461265274 / 9781461265276

Series: Book 53 of 160 - Springer Series in Statistics

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This item is printed on demand - Print on Demand Titel. 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 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 224 pp. Englisch.

Seller Inventory # 9781461265276

Title
Combinatorial Methods in Density Estimation
Author
Luc Devroye
Publisher
Springer, Springer Sep 2012
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1461265274
ISBN 13
9781461265276
Item weight
347 grams
Dimensions
235x155x13 mm
Series
Book 53 of 160: Springer Series in Statistics

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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