Titlebook: Conditional Specification of Statistical Models; Barry C. Arnold,Enrique Castillo,José María Sarabi Book 1999 Springer Science+Business Me

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Bayesian Analysis Using Conditionally Specified Models,tc. Much early Bayesian work was focussed on so-called conjugate priors. Such priors are convenient but lack flexibility for modeling informed prior belief. The classical scenario, in which most of the issues are already clearly visible, involves a sample from a normal distribution with unknown mean and variance.

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https://doi.org/10.1007/b97592Statistica; Statistical Models; addition; boundary element method; development; distribution; equation; fun

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978-1-4757-7260-9Springer Science+Business Media New York 1999

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https://doi.org/10.1007/978-3-642-01004-0 discrepancy between incompatible conditionals. In addition, they suggests alternative ways in which most nearly compatible distributions can be defined in incompatible cases. A related concept of ∈-compatibility arises naturally in the discussion of incompatible cases.

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https://doi.org/10.1007/978-3-642-16007-3els not fitting into the exponential family paradigm. No general theorem analogous to Theorem 4.1 is available and results are obtained on a case by case basis. The key tools are of course Theorems 1.3 and 1.4 which permit us to solve the functional equations characterizing many conditionally specif

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