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Fundamentals of nonparametric Bayesian inference (Record no. 36747)

MARC details
000 -LEADER
fixed length control field 02158 a2200265 4500
003 - CONTROL NUMBER IDENTIFIER
control field NISER
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260113114956.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260113b |||||||| |||| 00| 0 hin d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780521878265
Qualifying information Hardback
040 ## - CATALOGING SOURCE
Original cataloging agency NISER LIBRARY
Language of cataloging eng
Transcribing agency NISER LIBRARY
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.234
Item number GHO-F
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ghosal, Subhashis
245 10 - TITLE STATEMENT
Title Fundamentals of nonparametric Bayesian inference
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. New York :
Name of publisher, distributor, etc. Cambridge University Press,
Date of publication, distribution, etc. 2017.
300 ## - PHYSICAL DESCRIPTION
Extent xxiv, 646 pages ;
Dimensions 27 cm.
490 ## - SERIES STATEMENT
Series statement Cambridge series in statistical and probabilistic mathematics ;
Volume/sequential designation 44
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references (pages 623-637) and indexes.
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Nonparametric statistics
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Bayesian statistical decision theory
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Vaart, Aad van der
856 41 - ELECTRONIC LOCATION AND ACCESS
Materials specified Table of contents
Uniform Resource Identifier <a href="https://toc.library.ethz.ch/objects/pdf03/z01_978-0-521-87826-5_01.pdf">https://toc.library.ethz.ch/objects/pdf03/z01_978-0-521-87826-5_01.pdf</a>
856 41 - ELECTRONIC LOCATION AND ACCESS
Materials specified Reviews
Uniform Resource Identifier <a href="https://www.goodreads.com/book/show/35485670-fundamentals-of-nonparametric-bayesian-inference?ref=nav_sb_ss_1_13#CommunityReviews">https://www.goodreads.com/book/show/35485670-fundamentals-of-nonparametric-bayesian-inference?ref=nav_sb_ss_1_13#CommunityReviews</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Universal Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
    Universal Decimal Classification     NISER LIBRARY NISER LIBRARY 09/01/2026 20 7456.26   519.234 GHO-F 26347 12/01/2026 9941.68 09/01/2026 Book