I'm working on a data mining topic. I have an attributed graph of inflation network of developing countries. My vertex attributes are such as Population, Exchange rate to US $, Price level of consumption(PC), Ratio of GNP to GDP(%),.... The covariation among vertex descriptors can tell me whether the vertex attributes are structurally correlated or not? Is there any possibility to predict the future speed of my graph after a given period? If yes, what do my vertices stand for?
Ok If I got you well I think that I will get a kind of correlation patterns sequences.
And every annual inflation is a function of its own history. So if I want to build a model that predict what comes at t+1 I feel lost for what stand for the time if I proceed that way
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