By Barry C. Arnold

The concept that of conditional specification of distributions isn't new yet, other than in basic households, it has now not been good built within the literature. Computational problems certainly hindered or discouraged advancements during this path. notwithstanding, such roadblocks are of dimished significance this present day. Questions of compatibility of conditional and marginal standards of distributions are of basic significance in modeling eventualities. types with conditionals in exponential households are fairly tractable and supply priceless versions in a huge number of settings.

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It too can be viewed as a cone generated by some finite set of vectors in IR m . In any cone π, there may be some vectors u such that −u ∈ π and some / π. Consequently, a cone can be represented as vectors u such that −u ∈ the sum of a linear space and a cone. 24) where L(V ) is the linear space generated by the columns of an (m × k1 )dimensional matrix V and π(W ) is the cone generated by the columns of an (m × k2 )-dimensional matrix W . 24) are called the generators of the dual cone Ω(π(A)).

44) where ∗ ∗ qij1 + qij2 = 1, i = 1, 2, . . , I, j = 1, 2, . . , J, and indeed ∗ qijk ∈ [0, 1], ∀i, j, k. 4 Minimal Incompatibility in Terms of Kullback-Leibler Pseudo-Distance 33 In addition, the following relations hold I I p∗1|2 (i|j) = 1= j = 1, 2, . . 46) ∗ dij qij2 , i = 1, 2, . . , I. 47). 45) by stack normalizations. 5 and iteratively apply such row, column, and stack normalizations we are guaranteed convergence to a unique Q∗ since we are simply using a variation of the Darroch-Ratcliff (1972) iterative scaling algorithm.

We will mention alternatives to the Kullback-Leibler measure but, in many ways, it seems the most attractive choice. 4 Minimal Incompatibility in Terms of Kullback-Leibler Pseudo-Distance Suppose that A and B, two families of conditional distributions, are not compatible and perhaps do not even have identical incidence sets. We seek a probability matrix P with nonnegative entries summing to 1, which has conditionals as close as possible to those given by A and B. j ≈ aij , ∀i, j, pij /pi. ≈ bij , ∀i, j.