Bayesian data analysis in ecology using linear models with R, BUGS, and Stan / (Record no. 613438)

MARC details
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 161221s2015 ne a ob 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780128016787
Qualifying information electronic bk.
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0128016787
Qualifying information electronic bk.
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780128013700
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0128013702
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780128013700
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OCLC library identifier NLGGC
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OCLC library identifier NZ1
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OCLC library identifier CHDSB
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OCLC library identifier CHBIS
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OCLC library identifier DEBSZ
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OCLC library identifier GBVCP
System control number 823581543
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OCLC library identifier DEBBG
System control number BV043619938
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)906699032
Canceled/invalid control number (OCoLC)908100768
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)ocn906699032
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
y 12-21-2016
z hafiz
w metacoll.MYUKM.updates.D20160920.T210208.sdallbooks.1 (perolehan)hafizupload21122016.mrc
x 134
040 ## - CATALOGING SOURCE
Original cataloging agency NST
Language of cataloging eng
Description conventions rda
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Transcribing agency NST
Modifying agency NST
-- IDEBK
-- OPELS
-- E7B
-- YDXCP
-- COO
-- CDX
-- CHVBK
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049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QH541.15.S72
072 #7 - SUBJECT CATEGORY CODE
Subject category code NAT
Subject category code subdivision 010000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code NAT
Subject category code subdivision 045040
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code SCI
Subject category code subdivision 026000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code SCI
Subject category code subdivision 020000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 577.01/5195
Edition information 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Korner-Nievergelt, Franzi,
Relator term author.
245 10 - TITLE STATEMENT
Title Bayesian data analysis in ecology using linear models with R, BUGS, and Stan /
Statement of responsibility, etc. Fr衮zi Korner-Nievergelt [and five others].
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Amsterdam ;
-- Boston :
Name of producer, publisher, distributor, manufacturer Academic Press, an imprint of Elsevier,
Date of production, publication, distribution, manufacture, or copyright notice [2015]
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource :
Other physical details illustrations
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 0# - FORMATTED CONTENTS NOTE
Formatted contents note Front Cover; Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan; Copyright; Contents; Digital Assets; Acknowledgments; Chapter 1 -- Why do we Need Statistical Models and What is this Book About?; 1.1 WHY WE NEED STATISTICAL MODELS; 1.2 WHAT THIS BOOK IS ABOUT; FURTHER READING; Chapter 2 -- Prerequisites and Vocabulary; 2.1 SOFTWARE; 2.2 IMPORTANT STATISTICAL TERMS AND HOW TO HANDLE THEM IN R; FURTHER READING; Chapter 3 -- The Bayesian and the Frequentist Ways of Analyzing Data; 3.1 SHORT HISTORICAL OVERVIEW; 3.2 THE BAYESIAN WAY; 3.3 THE FREQUENTIST WAY
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3.4 COMPARISON OF THE BAYESIAN AND THE FREQUENTIST WAYSFURTHER READING; Chapter 4 -- Normal Linear Models; 4.1 LINEAR REGRESSION; 4.2 REGRESSION VARIANTS: ANOVA, ANCOVA, AND MULTIPLE REGRESSION; FURTHER READING; Chapter 5 -- Likelihood; 5.1 THEORY; 5.2 THE MAXIMUM LIKELIHOOD METHOD; 5.3 THE LOG POINTWISE PREDICTIVE DENSITY; FURTHER READING; Chapter 6 -- Assessing Model Assumptions: Residual Analysis; 6.1 MODEL ASSUMPTIONS; 6.2 INDEPENDENT AND IDENTICALLY DISTRIBUTED; 6.3 THE QQ PLOT; 6.4 TEMPORAL AUTOCORRELATION; 6.5 SPATIAL AUTOCORRELATION; 6.6 HETEROSCEDASTICITY; FURTHER READING
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 7 -- Linear Mixed Effects Models7.1 BACKGROUND; 7.2 FITTING A LINEAR MIXED MODEL IN R; 7.3 RESTRICTED MAXIMUM LIKELIHOOD ESTIMATION; 7.4 ASSESSING MODEL ASSUMPTIONS; 7.5 DRAWING CONCLUSIONS; 7.6 FREQUENTIST RESULTS; 7.7 RANDOM INTERCEPT AND RANDOM SLOPE; 7.8 NESTED AND CROSSED RANDOM EFFECTS; 7.9 MODEL SELECTION IN MIXED MODELS; FURTHER READING; Chapter 8 -- Generalized Linear Models; 8.1 BACKGROUND; 8.2 BINOMIAL MODEL; 8.3 FITTING A BINARY LOGISTIC REGRESSION IN R; 8.4 POISSON MODEL; FURTHER READING; Chapter 9 -- Generalized Linear Mixed Models; 9.1 BINOMIAL MIXED MODEL
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 9.2 POISSON MIXED MODELFURTHER READING; Chapter 10 -- Posterior Predictive Model Checking and Proportion of Explained Variance; 10.1 POSTERIOR PREDICTIVE MODEL CHECKING; 10.2 MEASURES OF EXPLAINED VARIANCE; FURTHER READING; Chapter 11 -- Model Selection and Multimodel Inference; 11.1 WHEN AND WHY WE SELECT MODELS AND WHY THIS IS DIFFICULT; 11.2 METHODS FOR MODEL SELECTION AND MODEL COMPARISONS; 11.3 MULTIMODEL INFERENCE; 11.4 WHICH METHOD TO CHOOSE AND WHICH STRATEGY TO FOLLOW; FURTHER READING; Chapter 12 -- Markov Chain Monte Carlo Simulation; 12.1 BACKGROUND; 12.2 MCMC USING BUGS
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 12.3 MCMC USING STAN12.4 SIM, BUGS, AND STAN; FURTHER READING; Chapter 13 -- Modeling Spatial Data Using GLMM; 13.1 BACKGROUND; 13.2 MODELING ASSUMPTIONS; 13.3 EXPLICIT MODELING OF SPATIAL AUTOCORRELATION; FURTHER READING; Chapter 14 -- Advanced Ecological Models; 14.1 HIERARCHICAL MULTINOMIAL MODEL TO ANALYZE HABITAT SELECTION USING BUGS; 14.2 ZERO-INFLATED POISSON MIXED MODEL FOR ANALYZING BREEDING SUCCESS USING STAN; 14.3 OCCUPANCY MODEL TO MEASURE SPECIES DISTRIBUTION USING STAN; 14.4 TERRITORY OCCUPANCY MODEL TO ESTIMATE SURVIVAL USING BUGS
520 ## - SUMMARY, ETC.
Summary, etc. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions-including all R codes-that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types.
588 0# - SOURCE OF DESCRIPTION NOTE
Source of description note Online resource; title from PDF title page (Ebsco, viewed April 9, 2015).
590 ## - LOCAL NOTE (RLIN)
Local note Elsevier
Provenance (VM) [OBSOLETE] ScienceDirect All Books
630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title BUGS (Information storage and retrieval system)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Ecology
General subdivision Research
-- Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element R (Computer program language)
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element NATURE / Ecology
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element NATURE / Ecosystems & Habitats / Wilderness
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SCIENCE / Environmental Science
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SCIENCE / Life Sciences / Ecology
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element 菫ologie.
Authority record control number or standard number (DE-588)4043207-5
Source of heading or term gnd
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Datenverarbeitung.
Authority record control number or standard number (DE-588)4011152-0
Source of heading or term gnd
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayes-Verfahren.
Authority record control number or standard number (DE-588)4204326-8
Source of heading or term gnd
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Biostatistik.
Authority record control number or standard number (DE-588)4729990-3
Source of heading or term gnd
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element R.
Authority record control number or standard number (DE-588)4705956-4
Source of heading or term gnd
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Gibbs-sampling.
Authority record control number or standard number (DE-588)4352359-6
Source of heading or term gnd
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Ecology -- Research -- Statistical methods.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Ecology -- Study and teaching.
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
655 #0 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Title Bayesian data analysis in ecology using linear models with R, BUGS, and Stan.
Place, publisher, and date of publication Amsterdam, [Netherlands] : Academic Press, c2015
Physical description xii, 316 pages
International Standard Book Number 9780128013700
Record control number 2014957273
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://ezplib.ukm.my/login?url=http://www.sciencedirect.com/science/book/9780128013700">http://ezplib.ukm.my/login?url=http://www.sciencedirect.com/science/book/9780128013700</a>
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b16400525
b 2021-06-25
c 2019-11-12
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Suppress in OPAC No
914 ## - VTLS Number
VTLS Number vtls003614157
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Library
Operator's initials, OID (RLIN) 2016-08-12
Cataloger's initials, CIN (RLIN) m
Material Type (Sierra) E-Book
Language English
Country
-- 0
-- .b16400525

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