Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Prior Books Ltd, Cheltenham, Reino Unido
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EUR 54,45
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Añadir al carritoHardcover. Condición: Like New. First Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs; hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price.
Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 80,29
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 90,44
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 102,71
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 101,49
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 90,42
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: HPB-Red, Dallas, TX, Estados Unidos de America
EUR 108,01
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Añadir al carritohardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Publicado por Cambridge University Press CUP, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 107,83
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Añadir al carritoCondición: New. pp. 656.
Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 113,92
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Majestic Books, Hounslow, Reino Unido
EUR 107,77
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 98,33
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Publicado por Cambridge University Press, Cambridge, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Grand Eagle Retail, Fairfield, OH, Estados Unidos de America
EUR 122,76
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Añadir al carritoHardcover. Condición: new. Hardcover. Explosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding practical use in numerous subject areas. Written by leading researchers, this authoritative text draws on theoretical advances of the past twenty years to synthesize all aspects of Bayesian nonparametrics, from prior construction to computation and large sample behavior of posteriors. Because understanding the behavior of posteriors is critical to selecting priors that work, the large sample theory is developed systematically, illustrated by various examples of model and prior combinations. Precise sufficient conditions are given, with complete proofs, that ensure desirable posterior properties and behavior. Each chapter ends with historical notes and numerous exercises to deepen and consolidate the reader's understanding, making the book valuable for both graduate students and researchers in statistics and machine learning, as well as in application areas such as econometrics and biostatistics. Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 111,19
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Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Russell Books, Victoria, BC, Canada
Original o primera edición
EUR 127,82
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Añadir al carritoHardcover. Condición: New. 1st Edition. Special order direct from the distributor.
Publicado por Cambridge University Press, Cambridge, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: CitiRetail, Stevenage, Reino Unido
EUR 96,18
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Añadir al carritoHardcover. Condición: new. Hardcover. Explosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding practical use in numerous subject areas. Written by leading researchers, this authoritative text draws on theoretical advances of the past twenty years to synthesize all aspects of Bayesian nonparametrics, from prior construction to computation and large sample behavior of posteriors. Because understanding the behavior of posteriors is critical to selecting priors that work, the large sample theory is developed systematically, illustrated by various examples of model and prior combinations. Precise sufficient conditions are given, with complete proofs, that ensure desirable posterior properties and behavior. Each chapter ends with historical notes and numerous exercises to deepen and consolidate the reader's understanding, making the book valuable for both graduate students and researchers in statistics and machine learning, as well as in application areas such as econometrics and biostatistics. Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 119,97
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.
EUR 159,34
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Añadir al carritoHardcover. Condición: Brand New. 646 pages. 10.00x7.25x1.75 inches. In Stock.
Publicado por Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 159,72
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Añadir al carritoHardcover. Condición: New. New. book.
Publicado por Cambridge University Press, Cambridge, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 166,65
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Añadir al carritoHardcover. Condición: new. Hardcover. Explosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding practical use in numerous subject areas. Written by leading researchers, this authoritative text draws on theoretical advances of the past twenty years to synthesize all aspects of Bayesian nonparametrics, from prior construction to computation and large sample behavior of posteriors. Because understanding the behavior of posteriors is critical to selecting priors that work, the large sample theory is developed systematically, illustrated by various examples of model and prior combinations. Precise sufficient conditions are given, with complete proofs, that ensure desirable posterior properties and behavior. Each chapter ends with historical notes and numerous exercises to deepen and consolidate the reader's understanding, making the book valuable for both graduate students and researchers in statistics and machine learning, as well as in application areas such as econometrics and biostatistics. Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 111,81
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Añadir al carritoHardcover. Condición: Brand New. 646 pages. 10.00x7.25x1.75 inches. In Stock. This item is printed on demand.
Publicado por Cambridge University Press, 2019
ISBN 10: 0521878268 ISBN 13: 9780521878265
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 97,73
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and .