Bayesian Modeling of Spatio-Temporal Data with R / (Record no. 13398)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03121 a2200301 4500 |
| 001 - CONTROL NUMBER | |
| control field | 005588 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | IIMU |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240220175544.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240220b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780367277987 (hbk.) |
| Terms of availability | £89.99 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | IIMU |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Edition number | 23 |
| Classification number | 519.542 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Sahu, Sujit K. |
| 245 ## - TITLE STATEMENT | |
| Title | Bayesian Modeling of Spatio-Temporal Data with R / |
| Statement of responsibility, etc. | by Sujit K. Sahu. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Name of publisher, distributor, etc. | Chapman & Hall, |
| Date of publication, distribution, etc. | 2022. |
| Place of publication, distribution, etc. | London : |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xv,411 p.; |
| Dimensions | 24 cm. |
| 365 ## - TRADE PRICE | |
| Source of price type code | GOC |
| Price type code | £ |
| Price amount | £89.99 |
| Currency code | ₹ |
| Unit of pricing | 1 GBP = 110.20 INR |
| 490 ## - SERIES STATEMENT | |
| Series statement | Chapman & Hall / CRC Interdisciplinary Statistics Series |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 1. Examples of spatio-temporal data 2. Jargon of spatial and spatio-temporal modeling 3. Exploratory data analysis methods 4. Bayesian inference methods 5. Bayesian computation methods 6. Bayesian modeling for point referenced spatial data 7. Bayesian modeling for point referenced spatio-temporal data 8. Practical examples of point referenced data modeling 9. Bayesian forecasting for point referenced data 10. Bayesian modeling for areal unit data 11. Further examples of areal data modeling 12. Gaussian processes for data science and other applications Appendix A. Statistical densities used in the book Appendix B. Answers to selected exercises |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. This book is designed to make spatio-temporal modeling and analysis accessible and understandable to a wide audience of students and researchers, from mathematicians and statisticians to practitioners in the applied sciences. It presents most of the modeling with the help of R commands written in a purposefully developed R package to facilitate spatio-temporal modeling. It does not compromise on rigour, as it presents the underlying theories of Bayesian inference and computation in standalone chapters, which would be appeal those interested in the theoretical details. By avoiding hard core mathematics and calculus, this book aims to be a bridge that removes the statistical knowledge gap from among the applied scientists. |
| Expansion of summary note | Taken from the publisher site. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Bayesian Model. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Sampling (Statistics) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Spatial analysis (Statistics) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computer program with R. |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Publisher Description and content page |
| Uniform Resource Identifier | https://www.routledge.com/Bayesian-Modeling-of-Spatio-Temporal-Data-with-R/Sahu/p/book/9780367277987 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Monograph |
| Item part | 005588 |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Materials specified (bound volume or other part) | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Inventory number | Total Checkouts | Full call number | Barcode | Checked out | Date last seen | Date last checked out | Copy number | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| hbk. | Indian Institute of Management Udaipur | Indian Institute of Management Udaipur | B2/3 | 2024-02-19 | 23 | 7438.00 | 67576 - 13/02/2024 | 1 | 519.542 | 005588 | 2024-09-08 | 2024-03-12 | 2024-03-12 | 1 | 9709.92 | 2024-02-19 | Monograph |