The Baby Model

  • Agustín Blasco


In this chapter we will obtain marginal posterior distributions of the unknowns using the simplest possible model, the one in which data are Normally distributed and we only have to estimate the mean and variance of the Normal distribution. In Chaps.  6,  7 and  8, we will see models that are more complex. We will find first analytical solutions to understand better the meaning of conditional and marginal distributions, and we will use Gibbs sampling later. We follow the humorous suggestion of Daniel Gianola and name the simplest model ‘Baby model’.


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  1. Bernardo JM, Smith FM (1994) Bayesian theory. Wiley, ChichesterCrossRefGoogle Scholar
  2. Blasco A (2001) The Bayesian controversy in animal breeding. J Anim Sci 79:2023–2046CrossRefGoogle Scholar
  3. Blasco A, Sorensen D, Bidanel JP (1998) A Bayesian analysis of genetic parameters and selection response for litter size components in pigs. Genetics 149:301–306PubMedPubMedCentralGoogle Scholar
  4. Box GEP, Draper NR (1987) Empirical model-building and response surfaces. Wiley, New YorkGoogle Scholar
  5. Fisher R (1922) On the mathematical foundations of theoretical statistics. Phil Trans A 222:309–368CrossRefGoogle Scholar

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© Springer International Publishing AG 2017

Authors and Affiliations

  • Agustín Blasco
    • 1
  1. 1.Institute of Animal Science and TechnologyUniversitat Politècnica de ValènciaValènciaSpain

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