Utilising D vines in a Bayesian belief network

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Scope

This method explains how to use D vines in creating rank correlations in a Bayesian belief network.

Definition

Kurowiecka and Cooke explain the method [1].

Let's take a BBN with five nodes

----1: . --Jouni 11:25, 1 June 2009 (EEST) {{{3}}} (type: truth; paradigms: science: comment)

----2: . What does the Figure 6.10 actually mean at page 171? --Jouni 11:25, 1 June 2009 (EEST) (type: truth; paradigms: science: comment)

----3:: . When we have the vine and the rank correlations that are required, how do we actually proceed? I can see why we need r21, r31, r43, r54, r52 4 based on the bbn, but I cannot see how to actually compute it? (Example 5.2 at page 137.) (type: truth; paradigms: science: comment)

----4:: . Do I understand correctly that the vine D4 is used to calculate r42, which is needed in D5 but that is not directly assessed? (Example 5.2 again?) --Jouni 11:25, 1 June 2009 (EEST) (type: truth; paradigms: science: comment)

----5:: . How critical is the choice of copula? What are the criteria for choosing a copula? Can you cause a large bias by choosing a wrong copula? --Jouni 11:25, 1 June 2009 (EEST) (type: truth; paradigms: science: comment)

  1. Kurowiecka and Cooka: Uncertainty analysis. John Wiley and sons, 2006.