Titlebook: Conditionally Specified Distributions; Barry C. Arnold,Enrique Castillo,José-Mariá Sarabi Conference proceedings 1992 Springer-Verlag Berl

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Harrowing

Distributions with normal conditionals,l conditional densities are univariate normal. In addition, the regression functions are linear and the conditioned variances do not depend on the value of the conditioned variable. Moreover the contours of the joint density are ellipses. Individually none of the above properties is restrictive enou

包庇

Conditionals in Exponential Families,on in Chapter 2, it is natural to seek out more general results regarding distributions whose conditionals are posited to be members of quite general exponential families. Indeed the discussion leading up to Theorem 2.4, suggests that things should work well when conditionals are from exponential fa

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Other conditionally specified families,els not fitting into the exponential family paradigm. No general theorem analogous to Theorem 4.2.1 is available and results are obtained on a case by case basis. The key tools are, of course, Theorems 2.3 and 2.4 which permit us to solve the functional equations characterizing many conditionally sp

現(xiàn)實(shí)

Characterizations involving conditional moments, families. Two kinds of surprising results have been encountered. On the one hand, the class of conditionally specified joint densities might be surprisingly constrained. For example, exponential conditionals models turn out to be always negatively correlated. In some sense, then, specifying the for