I'm trying to create a model which is of the form y = (a0 + a1l)[b0+MΣm=1 bmcos(mx-αm)] [c0 + NΣn=1 cn cos(nz-βn)] In the above system, l,x and z are independent variables and y is the dependent variable. The a, b and c terms are the unknowns. To solve for these unknowns, I have two separate data sets that I can use. Using data set 1 creates an overdetermined system providing me with more observations than unknowns, while data set 2 creates an underdetermined system with less observations than unknowns. In such a case, which approach would be better - underdetermined or overdetermined? and Why?