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Suppose you know the model should be of the form y =f(x1)g(x2,x3), where f and g are the functions I'm trying to find. Essentially, x2, x3 collectively predict some hidden variable z, and the response variable y is z dampened by some function of x1. How would you encode this in a regression? Bayesian networks seem related, but don't seem as applicable to regression.

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  • $\begingroup$ What are f and g? $\endgroup$ – Tim Feb 6 '18 at 11:07

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