rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Bayesian data analysis for animal scientists
    sub title: the basics
  name:
    name part: Blasco, Agustín
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: sz
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xviii, 275 pages : illustrations (some color) ; 24 cm
  abstract: 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.
  table of contents: Do we understand classic statistics? -- The Bayesian choice -- Posterior distributions -- MCMC -- The baby model -- The linear model : I. The 'fixed effects' model -- The linear model : II. The 'mixed' model -- A scope of the possibilities of Bayesian inference + MCMC -- Prior information -- Model selection.
  note: Agustín Blasco.
  note: Includes bibliographical references and index.
  subject:
    topic: Bayesian statistical decision theory
  subject:
    topic: Markov processes
  subject:
    topic: Animal industry
    topic: Statistical methods
  subject:
    topic: Bayes Theorem
  subject:
    topic: Markov Chains
  subject:
    topic: Statistics as Topic
  subject:
    topic: Animal Husbandry
    topic: statistics & numerical data
  classification: QA279.5 .B583 2017
  classification: QA 279.5 B644b 2017
  identifier: 9783319542737
  identifier: 3319542737
  identifier: 9783319542744
  identifier: 2017945825
  record info:
    record content source: YDX
    record creation date: 170202
    record change date: 20180108134349.0
    record identifier: in00004540297
    language of cataloging:
      language term: eng