Bayesian hierarchical models : (Record no. 16373)

MARC details
000 -LEADER
fixed length control field 03227cam a2200457Mu 4500
001 - CONTROL NUMBER
control field 9780429113352
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220724194328.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu---unuuu
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190921s2019 xx o 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency OCoLC-P
Language of cataloging eng
Transcribing agency OCoLC-P
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781498785914
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1498785913
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780429113352
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0429113358
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780429532900
Qualifying information (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0429532903
Qualifying information (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780429547607
Qualifying information (electronic bk. : Mobipocket)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0429547609
Qualifying information (electronic bk. : Mobipocket)
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1120692089
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1120692089
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA279.5
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT
Subject category code subdivision 029000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.542
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Congdon, P.
240 10 - UNIFORM TITLE
Uniform title Applied Bayesian hierarchical methods
245 10 - TITLE STATEMENT
Title Bayesian hierarchical models :
Remainder of title with applications using R /
Statement of responsibility, etc. Peter D. Congdon.
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Milton :
Name of publisher, distributor, etc. CRC Press LLC,
Date of publication, distribution, etc. 2019.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (593 p.)
500 ## - GENERAL NOTE
General note Description based upon print version of record.
520 ## - SUMMARY, ETC.
Summary, etc. An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book's website
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note OCLC-licensed vendor bibliographic record.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MATHEMATICS / Probability & Statistics / General
Source of heading or term bisacsh
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory.
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Read Online
Uniform Resource Identifier <a href="https://www.taylorfrancis.com/books/9780429113352">https://www.taylorfrancis.com/books/9780429113352</a>
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified OCLC metadata license agreement
Uniform Resource Identifier <a href="http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf">http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type eBook

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