Thank you so much for taking time to answer to my post. Even relaxing the problem a little bit by assuming a fixed F value (e.g., F = 1). dp - C = x_1 - x_2 - x_0 now we have all the known (observed data) in the right hand and the unknown in the left. There is one equation and two unknown where I could define a prior on both unknowns, however I am still unclear how one would do an inference for this equation using the theory of P(C,dp| obs) = \frac {P(obs | C,dp) P(C,dp)} {P(obs)} in pymc without converting it to a regression problem, any code suggestion?
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