Bayesian inference in the social sciences / (Record no. 689279)

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005 - DATE AND TIME OF LATEST TRANSACTION
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 171212s2014 nju ob 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2014-014354
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118771129
Qualifying information (epub)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1118771125
Qualifying information (epub)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118771181
Qualifying information (pdf)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1118771184
Qualifying information (pdf)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118771051
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1118771052
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781118771211
Qualifying information (hardback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 1118771214
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC)
OCLC library identifier CHBIS
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OCLC library identifier DEBSZ
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OCLC library identifier DEBBG
System control number BV043396678
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OCLC library identifier CHNEW
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035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)876466907
Canceled/invalid control number (OCoLC)961540002
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035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)ocn876466907
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201902141409
Level of effort used to assign nonsubject heading access points murni
y 12-12-2017
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w MYUKM (1).mrc
x 594
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
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Transcribing agency DLC
Modifying agency OCLCF
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042 ## - AUTHENTICATION CODE
Authentication code pcc
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HA29
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT
Subject category code subdivision 003000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT
Subject category code subdivision 029000
Source bisacsh
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5/42
Edition information 23
245 00 - TITLE STATEMENT
Title Bayesian inference in the social sciences /
Statement of responsibility, etc. edited by Ivan Jeliazkov, Department of Economics, University of California, Irvine, California, USA, Xin-She Yang, School of Science and Technology, Middlesex University, London, United Kingdom.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Hoboken, New Jersey :
Name of producer, publisher, distributor, manufacturer John Wiley & Sons, Inc,
Date of production, publication, distribution, manufacture, or copyright notice 2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Machine generated contents note: List of Figures iii 1 Bayesian Analysis of Dynamic Network Regression with Joint Edge/Vertex Dynamics 1 Zack W. Almquist and Carter T. Butts 1.1 Introduction 2 1.2 Statistical Models for Social Network Data 2 1.3 Dynamic Network Logistic Regression with Vertex Dynamics 11 1.4 Empirical Examples and Simulation Analysis 14 1.5 Discussion 29 1.6 Conclusion 30 2 Ethnic Minority Rule and Civil War: A Bayesian Dynamic Multilevel Analysis 39 Xun Pang 2.1 Introduction: Ethnic Minority Rule and Civil War 40 2.2 EMR: Grievance and Opportunities of Rebellion 41 2.3 Bayesian GLMM-AR(p) Model 42 2.4 Variables, Model and Data 47 2.5 Empirical Results and Interpretation 49 2.6 Civil War: Prediction 54 2.7 Robustness Checking: Alternative Measures of EMR 59 2.8 Conclusion 60 References 62 3 Bayesian Analysis of Treatment Effect Models 67 Mingliang Li and Justin L. Tobias 3.1 Introduction 68 3.2 Linear Treatment Response Models Under Normality 69 3.3 Nonlinear Treatment Response Models 73 3.4 Other Issues and Extensions: Non-Normality, Model Selection and Instrument Imperfection 78 3.5 Illustrative Application 84 3.6 Conclusion 89 4 Bayesian Analysis of Sample Selection Models 95 Martijn van Hasselt 4.1 Introduction 95 4.2 Univariate Selection Models 97 4.3 Multivariate Selection Models 101 4.4 Semiparametric Models 111 4.5 Conclusion 114 References 114 5 Modern Bayesian Factor Analysis 117 Hedibert Freitas Lopes 5.1 Introduction 117 5.2 Normal linear factor analysis 119 5.3 Factor stochastic volatility 125 5.4 Spatial factor analysis 128 5.5 Additional developments 133 5.6 Modern non-Bayesian factor analysis 136 5.7 Final remarks 137 6 Estimation of stochastic volatility models with heavy tails and serial dependence 159 Joshua C.C. Chan and Cody Y.L. Hsiao 6.1 Introduction 159 6.2 Stochastic Volatility Model 160 6.3 Moving Average Stochastic Volatility Model 168 6.4 Stochastic Volatility Models with Heavy-Tailed Error Distributions 173 References 178 7 From the Great Depression to the Great Recession: A Modelbased Ranking of U.S. Recessions 181 Rui Liu and Ivan Jeliazkov 7.1 Introduction 181 7.2 Methodology 183 7.3 Results 188 7.4 Conclusions 191 Appendix: Data 192 References 192 8 What Difference Fat Tails Make: A Bayesian MCMC Estimation of Empirical Asset Pricing Models 201 Paskalis Glabadanidis 8.1 Introduction 202 8.2 Methodology 204 8.3 Data 205 8.4 Empirical Results 206 8.5 Concluding Remarks 212 9 Stochastic Search For Price Insensitive Consumers 227 Eric Eisenstat 9.1 Introduction 228 9.2 Random utility models in marketing applications 230 9.3 The censored mixing distribution in detail 234 9.4 Reference price models with price thresholds 240 9.5 Conclusion 244 References 245 10 Hierarchical Modeling of Choice Concentration of US Households 249 Karsten T. Hansen, Romana Khan and Vishal Singh 10.1 Introduction 250 10.2 Data Description 252 10.3 Measures of Choice Concentration 252 10.4 Methodology 254 10.5 Results 256 10.6 Interpreting & theta; 260 10.7 Decomposing the effects of time, number of decisions and concentration preference 263 10.8 Conclusion 265 References 267 11 Approximate Bayesian inference in models defined through estimating equations 269 11.1 Introduction 269 11.2 Examples 271 11.3 Frequentist estimation 273 11.4 Bayesian estimation 276 11.5 Simulating from the posteriors 281 11.6 Asymptotic theory 283 11.7 Bayesian validity 285 11.8 Application 286 11.9 Conclusions 288 12 Reacting to Surprising Seemingly Inappropriate Results 295 Dale J. Poirier 12.1 Introduction 295 12.2 Statistical Framework 296 12.3 Empirical Illustration 300 12.4 Discussion 301 References 301 13 Identification and MCMC estimation of bivariate probit models w ith partial observability 303 Ashish Rajbhandari 13.1 Introduction 303 13.2 Bivariate Probit Model 305 13.3 Identification in a partially observable model 307 13.4 Monte Carlo Simulations 308 13.5 Bayesian Methodology 309 13.6 Application 312 13.7 Conclusion 315 Chapter Appendix 316 References 317 14 School Choice Effects in Tokyo Metropolitan Area: A Bayesian Spatial Quantile Regression Approach 321 Kazuhiko Kakamu and Hajime Wago 14.1 Introduction 321 14.2 The Model 323 14.3 Posterior Analysis 325 14.4 Empirical Analysis 326 14.5 Conclusions 330.
520 ## - SUMMARY, ETC.
Summary, etc. 'Bayesian Inference in the Social Sciences builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. Particular emphasis is placed on an interdisciplinary coverage, model checking, and modern computational tools such as Markov chain Monte Carlo. The book's broad interdisciplinary coverage provides exposure to recent and trending developments in a diverse, yet closely integrated, set of research topics in the social sciences. This approach facilitates the transmission of new ideas, developments, and methodology from one discipline to another, while at the same time maintaining manageability, coherence, and a clear focus'--
Assigning source Provided by publisher.
588 0# - SOURCE OF DESCRIPTION NOTE
Source of description note Print version record and CIP data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Social sciences
General subdivision Statistical methods.
9 (RLIN) 60875
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MATHEMATICS
General subdivision Probability & Statistics
-- Bayesian Analysis.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SOCIAL SCIENCE
General subdivision Statistics.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS
General subdivision Econometrics.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory.
Source of heading or term fast
Authority record control number or standard number (OCoLC)fst00829019
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Social sciences
General subdivision Statistical methods.
Source of heading or term fast
Authority record control number or standard number (OCoLC)fst01122983
9 (RLIN) 60875
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Jeliazkov, Ivan,
Dates associated with a name 1973-
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Yang, Xin-She.
9 (RLIN) 57771
773 0# - HOST ITEM ENTRY
Title Wiley e-books
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Title Bayesian inference in the social sciences.
Place, publisher, and date of publication Hoboken, New Jersey : Wiley, 2014
International Standard Book Number 9781118771211
Record control number (DLC) 2014011437
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://eresourcesptsl.ukm.remotexs.co/user/login?url=http://onlinelibrary.wiley.com/book/10.1002/9781118771051">https://eresourcesptsl.ukm.remotexs.co/user/login?url=http://onlinelibrary.wiley.com/book/10.1002/9781118771051</a>
Public note Wiley Online Library
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b16543361
b 2022-11-04
c 2019-11-12
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Suppress in OPAC No
914 ## - VTLS Number
VTLS Number vtls003629267
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Library
Operator's initials, OID (RLIN) 2017-12-12
Cataloger's initials, CIN (RLIN) m
Material Type (Sierra) E-Book
Language English
Country
-- 0
-- .b16543361

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