Fundamentals of nonparametric Bayesian inference / (Record no. 39178)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | nam a22 7a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 190312b2017 xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780521878265 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 519.542 GHO-S |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Ghosal, Subhashis |
| 245 ## - TITLE STATEMENT | |
| Title | Fundamentals of nonparametric Bayesian inference / |
| Statement of responsibility, etc. | Subhashis Ghosal and Aad van der Vaart |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | United Kingdom |
| Name of publisher, distributor, etc. | Cambridge University Press |
| Date of publication, distribution, etc. | 2017 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 646 p. |
| 365 ## - TRADE PRICE | |
| Price type code | GBP |
| Price amount | 64.00. |
| 500 ## - GENERAL NOTE | |
| General note | 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Nonparametric statistics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Bayesian statistical decision theory |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Vaart, Aad Van Der |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Cost, normal purchase price | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Total Renewals | Checked out | Date last checked out | Public note |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 510 | BITS Pilani Hyderabad | BITS Pilani Hyderabad | General Stack (For lending) | 12/03/2019 | 64.00 | 519.542 GHO-S | 37840 | 13/07/2024 | 12/03/2019 | Books | ||||||||
| Dewey Decimal Classification | 510 | BITS Pilani Hyderabad | BITS Pilani Hyderabad | General Stack (For lending) | 05/07/2022 | 1 | 519.542 GHO-S | 45938 | 21/07/2022 | 05/07/2022 | Books | 6 | 27/10/2025 | 21/07/2022 | Project Book : Dr. Sayan Ghosh. |