Da: Phatpocket Limited, Waltham Abbey, HERTS, Regno Unito
EUR 31,12
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Aggiungi al carrelloCondizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 111,30
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Editore: Springer-Verlag New York Inc., 2012
ISBN 10: 1461265274 ISBN 13: 9781461265276
Lingua: Inglese
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 144,84
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Aggiungi al carrelloCondizione: New. Series: Springer Series in Statistics. Num Pages: 221 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 12. Weight in Grams: 349. . 2012. Softcover reprint of the original 1st ed. 2001. Paperback. . . . .
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 146,77
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EUR 144,13
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EUR 144,13
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EUR 146,76
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Da: Best Price, Torrance, CA, U.S.A.
EUR 138,58
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Da: Best Price, Torrance, CA, U.S.A.
EUR 138,58
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Da: California Books, Miami, FL, U.S.A.
EUR 165,81
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Aggiungi al carrelloCondizione: New.
Editore: Springer-Verlag New York Inc., 2012
ISBN 10: 1461265274 ISBN 13: 9781461265276
Lingua: Inglese
Da: Kennys Bookstore, Olney, MD, U.S.A.
EUR 180,23
Convertire valutaQuantità: 15 disponibili
Aggiungi al carrelloCondizione: New. Series: Springer Series in Statistics. Num Pages: 221 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 12. Weight in Grams: 349. . 2012. Softcover reprint of the original 1st ed. 2001. Paperback. . . . . Books ship from the US and Ireland.
EUR 165,43
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EUR 166,72
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EUR 171,88
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EUR 189,75
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Aggiungi al carrelloCondizione: New. pp. 224.
EUR 196,19
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Aggiungi al carrelloCondizione: New. pp. 224.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 146,29
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 146,62
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Editore: Springer-Verlag New York Inc., New York, NY, 2001
ISBN 10: 0387951172 ISBN 13: 9780387951171
Lingua: Inglese
Da: Grand Eagle Retail, Mason, OH, U.S.A.
EUR 150,11
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. 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 Laszlo Gyoerfi, 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. This book will be of interest to statistical researchers working in the area of nonparametric density estimation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Editore: Springer-Verlag New York Inc., 2001
ISBN 10: 0387951172 ISBN 13: 9780387951171
Lingua: Inglese
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 212,74
Convertire valutaQuantità: 15 disponibili
Aggiungi al carrelloCondizione: New. A book aimed at statistical researchers working in the area of nonparametric density estimation. Series: Springer Series in Statistics. Num Pages: 221 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 14. Weight in Grams: 1090. . 2001. Hardback. . . . .
Da: Revaluation Books, Exeter, Regno Unito
EUR 215,53
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Aggiungi al carrelloPaperback. Condizione: Brand New. 221 pages. 9.25x6.10x0.51 inches. In Stock.
Editore: Springer-Verlag New York Inc., New York, NY, 2012
ISBN 10: 1461265274 ISBN 13: 9781461265276
Lingua: Inglese
Da: Grand Eagle Retail, Mason, OH, U.S.A.
EUR 167,11
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. 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 Laszlo Gyoerfi, 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Editore: Springer-Verlag New York Inc., 2001
ISBN 10: 0387951172 ISBN 13: 9780387951171
Lingua: Inglese
Da: Kennys Bookstore, Olney, MD, U.S.A.
EUR 265,30
Convertire valutaQuantità: 15 disponibili
Aggiungi al carrelloCondizione: New. A book aimed at statistical researchers working in the area of nonparametric density estimation. Series: Springer Series in Statistics. Num Pages: 221 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 14. Weight in Grams: 1090. . 2001. Hardback. . . . . Books ship from the US and Ireland.
Editore: Springer-Verlag New York Inc., New York, NY, 2001
ISBN 10: 0387951172 ISBN 13: 9780387951171
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 263,73
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. 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 Laszlo Gyoerfi, 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. This book will be of interest to statistical researchers working in the area of nonparametric density estimation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: Springer-Verlag New York Inc., New York, NY, 2012
ISBN 10: 1461265274 ISBN 13: 9781461265276
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 265,14
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. 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 Laszlo Gyoerfi, 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: moluna, Greven, Germania
EUR 110,02
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Aggiungi al carrelloCondizione: 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.
Da: moluna, Greven, Germania
EUR 127,40
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Aggiungi al carrelloGebunden. Condizione: 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.
Editore: Springer-Verlag New York Inc., 2012
ISBN 10: 1461265274 ISBN 13: 9781461265276
Lingua: Inglese
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 135,59
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Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 379.
Da: Majestic Books, Hounslow, Regno Unito
EUR 200,42
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 224 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
Da: Majestic Books, Hounslow, Regno Unito
EUR 205,05
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Aggiungi al carrelloCondizione: 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.