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 .

Let's take a BBN with five nodes

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--1: How is the BBN simulated? It is easy to get to page 136 half way (point 4). However, how is the vine formed from this? Why does the book say that the sampling order MUST be D4=(4,3,2,1) but D5=D(5,4,2,3,1)? --Jouni 11:25, 1 June 2009 (EEST)

--2: What does the Figure 6.10 actually mean at page 171? --Jouni 11:25, 1 June 2009 (EEST)

--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.) --Jouni 11:25, 1 June 2009 (EEST)

--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)

--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)