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The Resource Bayesian Data Analysis for Animal Scientists : The Basics, by Agustín Blasco, (electronic resource)

Bayesian Data Analysis for Animal Scientists : The Basics, by Agustín Blasco, (electronic resource)

Label
Bayesian Data Analysis for Animal Scientists : The Basics
Title
Bayesian Data Analysis for Animal Scientists
Title remainder
The Basics
Statement of responsibility
by Agustín Blasco
Creator
Contributor
Author
Subject
Language
eng
Summary
In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters. The biologist or the agricultural researcher does not normally have a background in Bayesian statistics, having difficulties in following the technical books introducing Bayesian techniques. The difficulties arise from the way of making inferences, which is completely different in the Bayesian school, and from the difficulties in understanding complicated matters such as the MCMC numerical methods. We compare both schools, classic and Bayesian, underlying the advantages of Bayesian solutions, and proposing inferences based in relevant differences, guaranteed values, probabilities of similitude or the use of ratios. We also give a scope of complex problems that can be solved using Bayesian statistics, and we end the book explaining the difficulties associated to model choice and the use of small samples. The book has a practical orientation and uses simple models to introduce the reader in this increasingly popular school of inference
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0
Literary form
non fiction
Bayesian Data Analysis for Animal Scientists : The Basics, by Agustín Blasco, (electronic resource)
Label
Bayesian Data Analysis for Animal Scientists : The Basics, by Agustín Blasco, (electronic resource)
Link
http://libproxy.rpi.edu/login?url=http://dx.doi.org/10.1007/978-3-319-54274-4
Publication
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Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Foreword -- Notation -- 1. Do we understand classical statistics? -- 2. The Bayesian choice -- 3. Posterior distributions -- 4. MCMC -- 5. The 2baby3 model -- 6. The linear model. I. The 2fixed3 effects model -- 7. The linear model. II. The 2mixed3 model -- 8. A scope of the possibilities of Bayesian inference + MCMC -- 9. Prior information -- 10. Model choice -- Appendix -- References
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9783319542744&userID=ebsco-test&password=ebsco-test
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unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4380015'}
Extent
XVIII, 275 p. 62 illus., 57 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783319542744
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote

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