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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
hardcover. Condition: 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!
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Seller: Prior Books Ltd, Cheltenham, United Kingdom
Association Member: ABA ILAB PBFA
Seller rating 5 out of 5 stars
First Edition
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Add to basketHardcover. Condition: 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.
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 109.73
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Condition: New. SUPER FAST SHIPPING.
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by Cambridge University Press CUP, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Condition: New. pp. 656.
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 111.36
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 109.76
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Condition: New.
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 124.53
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by Cambridge University Press, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 130.56
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, GB, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Hardback. Condition: New. 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.
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US$ 179.95
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Add to basketHardcover. Condition: Brand New. 646 pages. 10.00x7.25x1.75 inches. In Stock.
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, GB, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 168.79
Convert currencyUS$ 50.00 shipping within U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. 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.
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, GB, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
US$ 223.14
Convert currencyFree shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. 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.
-
Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, GB, 2017
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 215.66
Convert currencyUS$ 88.59 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. 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.
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US$ 129.71
Convert currencyUS$ 34.07 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: Brand New. 646 pages. 10.00x7.25x1.75 inches. In Stock. This item is printed on demand.
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Fundamentals of Nonparametric Bayesian Inference
Published by Cambridge University Press, 2019
ISBN 10: 0521878268 ISBN 13: 9780521878265
Language: English
US$ 134.40
Convert currencyUS$ 57.93 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketGebunden. Condition: 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 .
