Subhashis ghosal (38 risultati)

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hardcover. Condizione: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New. In English.

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Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

Hardback. Condizione: 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.…

Condizione: New. pp. 656.

Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardcover. Condizione: Brand New. 646 pages. 10.00x7.25x1.75 inches. In Stock.

Condizione: New.

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Condizione: New. Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 656 pages, 15 b/w illus. BIC Classification: PBT. Category: (U) Tertiary Education (US: College). Dimension: 253 x 177. . . 2017. Hardcover. . . . . Books ship from the US and Ireland. …

Taschenbuch. Condizione: Neu. Frontiers of Statistics and Data Science | Subhashis Ghosal (u. a.) | Taschenbuch | IISA Series on Statistics and Data Science | xviii | Englisch | 2026 | Springer | EAN 9789819607440 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Hardback. Condizione: 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.…

Condizione: New.

Condizione: New. Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 656 pages, 15 b/w illus. BIC Classification: PBT. Category: (U) Tertiary Education (US: College). Dimension: 253 x 177. . . 2017. Hardcover. . . . . …

Hardcover. Condizione: Brand New. 370 pages. 9.25x6.10x9.21 inches. In Stock.

Condizione: New. BRAND NEW. book.

Condizione: new. Questo è un articolo print on demand.

Hardcover. Condizione: 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condizione: 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 .…

Condizione: New. Print on Demand pp. 656.

Condizione: New. PRINT ON DEMAND pp. 656.

Buch. Condizione: Neu. Fundamentals of Nonparametric Bayesian Inference | Subhashis Ghosal (u. a.) | Buch | Gebunden | Englisch | 2019 | Cambridge University Press | EAN 9780521878265 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …