MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03200nam a2200349 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250930133612.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
120621s2011 enka b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780521196765 (hbk.) |
| Terms of availability |
RM268.60 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
0521196760 (hbk.) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
|---|
| Level of rules in bibliographic description |
201305171602 |
| Level of effort used to assign nonsubject heading access points |
zabidah |
| Level of effort used to assign subject headings |
201305131120 |
| Level of effort used to assign classification |
rasyilla |
| y |
06-21-2012 |
| z |
rasyilla |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Transcribing agency |
DLC |
| Modifying agency |
UKM |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
QA280.B397 |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
QA280 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) |
.B397 |
| 245 00 - TITLE STATEMENT |
|---|
| Title |
Bayesian time series models / |
| Statement of responsibility, etc. |
edited by David Barber, A. Taylan Cemgil, Silvia Chiappa. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Cambridge, UK : |
| Name of publisher, distributor, etc. |
Cambridge University Press, |
| Date of publication, distribution, etc. |
2011. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiii, 417 p. : |
| Other physical details |
ill. ; |
| Dimensions |
26 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
''What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they have to say. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Exploiting the unifying framework of probabilistic graphical models, the book covers approximation schemes, both Monte Carlo and deterministic, and introduces switching, multi-object, non-parametric and agent-based models in a variety of application environments. It demonstrates that the basic framework supports the rapid creation of models tailored to specific applications and gives insight into the computational complexity of their implementation. The authors span traditional disciplines such as statistics and engineering and the more recently established areas of machine learning and pattern recognition. Readers with a basic understanding of applied probability, but no experience with time series analysis, are guided from fundamental concepts to the state-of-the-art in research and practice'-- |
| Assigning source |
Provided by publisher. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
'Time series appear in a variety of disciplines, from finance to physics, computer science to biology. The origins of the subject and diverse applications in the engineering and physics literature at times obscure the commonalities in the underlying models and techniques. A central aim of this book is an attempt to make modern time series techniques accessible to a broad range of researchers, based on the unifying concept of probabilistic models. These techniques facilitate access to the modern time series literature, including financial time series prediction, video-tracking, music analysis, control and genetic sequence analysis. A particular feature of the book is that it brings together leading researchers that span the more traditional disciplines of statistics, control theory, engineering and signal processing,to the more recent area machine learning and pattern recognition'-- |
| Assigning source |
Provided by publisher. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Time-series analysis. |
| 9 (RLIN) |
61130 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Bayesian statistical decision theory. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Barber, David, |
| Dates associated with a name |
1963- |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Cemgil, Ali Taylan. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Chiappa, Silvia. |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) |
|---|
| a |
.b15409685 |
| b |
2019-11-12 |
| c |
2019-11-12 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
AM |
| Suppress in OPAC |
No |
| Call number prefix |
QA280.B397 |
| 914 ## - VTLS Number |
|---|
| VTLS Number |
vtls003505920 |
| 990 ## - EQUIVALENCES OR CROSS-REFERENCES [LOCAL, CANADA] |
|---|
| Link information for 9XX fields |
za |
| 991 ## - LOCAL NOTE (NAMA FAKULTI/INSTITUT/PUSAT) |
|---|
| a |
Fakulti Sains Sosial dan Kemanusiaan |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Library |
PERPUSTAKAAN TUN SERI LANANG |
| Operator's initials, OID (RLIN) |
2012-08-06 |
| Cataloger's initials, CIN (RLIN) |
m |
| Material Type (Sierra) |
Printed Books |
| Language |
English |
| Country |
|
| -- |
0 |
| -- |
.b15409685 |
