MARC details
| 000 -LEADER |
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| fixed length control field |
04081cam a22003858i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
7364 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
BD-DhEWU |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20140605020005.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
140205s2014 flu g b 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781439840955 (hardback) |
|
|---|
| International Standard Book Number |
1439840954 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)859253474 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| Description conventions |
rda |
| Modifying agency |
BD-DhEWU |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA279.5 |
| Item number |
.G45 2014 |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
519.542 |
| Item number |
BAY 2014 |
| 084 ## - OTHER CLASSIFICATION NUMBER |
|---|
| Classification number |
MAT029000 |
| Source of number |
bisacsh |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Gelman, Andrew, |
| 9 (RLIN) |
3494 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Bayesian data analysis / |
| Statement of responsibility, etc |
Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
Third edition. |
| 263 ## - PROJECTED PUBLICATION DATE |
|---|
| Projected publication date |
1111 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
pages cm. |
| 490 0# - SERIES STATEMENT |
|---|
| Series statement |
Chapman & Hall/CRC texts in statistical science |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and indexes. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Title |
TOC |
| Formatted contents note |
FUNDAMENTALS OF BAYESIAN INFERENCE Probability and Inference Single-Parameter Models Introduction to Multiparameter Models Asymptotics and Connections to Non-Bayesian Approaches Hierarchical Models FUNDAMENTALS OF BAYESIAN DATA ANALYSIS Model Checking Evaluating, Comparing, and Expanding Models Modeling Accounting for Data Collection Decision Analysis ADVANCED COMPUTATION Introduction to Bayesian Computation Basics of Markov Chain Simulation Computationally Efficient Markov Chain Simulation Modal and Distributional Approximations REGRESSION MODELS Introduction to Regression Models Hierarchical Linear Models Generalized Linear Models Models for Robust Inference Models for Missing Data NONLINEAR AND NONPARAMETRIC MODELS Parametric Nonlinear Models Basic Function Models Gaussian Process Models Finite Mixture Models Dirichlet Process Models APPENDICES A: Standard Probability Distributions B: Outline of Proofs of Asymptotic Theorems C: Computation in R and Stan Bibliographic Notes and Exercises appear at the end of each chapter. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
"Preface This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics. Although introductory in its early sections, the book is definitely not elementary in the sense of a first text in statistics. The mathematics used in our book is basic probability and statistics, elementary calculus, and linear algebra. A review of probability notation is given in Chapter 1 along with a more detailed list of topics assumed to have been studied. The practical orientation of the book means that the reader's previous experience in probability, statistics, and linear algebra should ideally have included strong computational components. To write an introductory text alone would leave many readers with only a taste of the conceptual elements but no guidance for venturing into genuine practical applications, beyond those where Bayesian methods agree essentially with standard non-Bayesian analyses. On the other hand, we feel it would be a mistake to present the advanced methods without first introducing the basic concepts from our data-analytic perspective. Furthermore, due to the nature of applied statistics, a text on current Bayesian methodology would be incomplete without a variety of worked examples drawn from real applications. To avoid cluttering the main narrative, there are bibliographic notes at the end of each chapter and references at the end of the book"-- |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
|---|
| Program name |
AS |
| 590 ## - LOCAL NOTE (RLIN) |
|---|
| Local note |
Tahur Ahmed |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Bayesian statistical decision theory. |
| 9 (RLIN) |
2787 |
|
|---|
| Topical term or geographic name as entry element |
MATHEMATICS / Probability & Statistics / General. |
| Source of heading or term |
bisacsh |
| 9 (RLIN) |
2343 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Cover image |
| Uniform Resource Identifier |
http://images.tandf.co.uk/common/jackets/websmall/978143984/9781439840955.jpg |
|
|---|
| Materials specified |
WorldCat Details |
| Uniform Resource Identifier |
http://www.worldcat.org/title/bayesian-data-analysis/oclc/859253474&referer=brief_results |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Text |
| Koha issues (borrowed), all copies |
1 |