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3189194 |
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20221013092600.0 |
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191215t20202020flua b 001 0 eng c |
| 097 |
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|3 Bib#:
|a 3189194
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| 020 |
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|a 9780367139919
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| 020 |
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|a 036713991X
|q (hardback)
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| 020 |
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|z 9780429029608
|q (ebook)
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| 020 |
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|z 0429029608
|q (ebook)
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| 024 |
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|a 16579613
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| 035 |
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|a on1130764237
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| 035 |
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|a (OCoLC)1130764237
|z (OCoLC)1202535386
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| 040 |
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|a YDX
|b eng
|e rda
|c YDX
|d OCLCQ
|d UZ0
|d OCLCF
|d CHVBK
|d OCLCO
|d EQO
|d CUV
|d AJB
|d INU
|d OCLCO
|d ORE
|
| 042 |
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|a pcc
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| 050 |
0 |
0 |
|a QA279.5
|b .M3975 2020
|
| 082 |
0 |
4 |
|a 519.542
|2 23
|
| 100 |
1 |
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|a McElreath, Richard,
|d 1973-
|e author.
|
| 245 |
1 |
0 |
|a Statistical rethinking :
|b a Bayesian course with examples in R and Stan /
|c Richard McElreath.
|
| 250 |
|
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|a Second edition
|
| 264 |
|
1 |
|a Boca Raton, FL :
|b CRC Press,
|c 2020.
|
| 264 |
|
4 |
|c r020
|
| 300 |
|
|
|a xvii, 593 pages :
|b illustrations ;
|c 26 cm.
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a unmediated
|b n
|2 rdamedia
|
| 338 |
|
|
|a volume
|2 rdacarrier
|
| 490 |
1 |
|
|a Chapman & Hall/CRC texts in statistical science series
|
| 500 |
|
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|a "A Chapman & Hall book."
|
| 500 |
|
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|a Revised edition of: Statistical rethinking : A Bayesian course with examples in R and Stan / Richard McElreath, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany. [2016].
|
| 504 |
|
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|a Includes bibliographical references (pages 557-583) and indexes.
|
| 505 |
0 |
|
|a The Golem of Prague -- Small worlds and large worlds -- Sampling the imaginary -- Geocentric models -- The many variables & the spurious waffles -- The haunted DAG & the causal terror -- Ulysses' compass -- Conditional manatees -- Markov chain Monte Carlo -- Big entropy and the generalized linear model -- God spiked the integers -- Monsters and mixtures -- Models with memory -- Adventures in covariance -- Missing data and other opportunities -- Generalized linear madness -- Horoscopes.
|
| 520 |
|
|
|a "Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding.The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It ends with an entirely new chapter that goes beyond generalized linear modeling, showing how domain-specific scientific models can be built into statistical analyses."--Back cover.
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| 650 |
|
0 |
|a Bayesian statistical decision theory.
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| 650 |
|
0 |
|a R (Computer program language)
|
| 650 |
|
0 |
|a Computer software.
|
| 650 |
|
0 |
|a Computer programs.
|
| 830 |
|
0 |
|a Texts in statistical science.
|
| 943 |
|
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|a YBP GobiExport Record
|
| 991 |
|
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|a 2022-10-13
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| 992 |
|
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|a Created by fiwi, 13/10/2022. Updated by , .
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| 999 |
f |
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|i f2b63b29-f59d-5e1d-af01-184789218fce
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|t 0
|
| 952 |
f |
f |
|p For loan
|a University Of Canterbury
|b UC Libraries
|c EPS Library
|d EPS Library, Level 2
|t 0
|e QA 279.5 .M141 2020
|h Library of Congress classification
|i Book
|m AU20489927B
|
