I have two datasets in form of time-series: (Y_1(t), X_1(t)) and (Y_2(t), X_2(t)), which comes from measurements of the same object during two repetitions of the same experiment in two different structures(a dynamic driving cycle for the same IC engine).
Y is my response signal, measured CO2 level X contains information about environmental variables, such as humidity, pressure and temperature, and measurements of factors which affects Y, such as speed, momentum, humidity, flows, exhaust pressure&temperature, etc., for a total of 15 variables.
What is the most informative way to compare Y_1 and Y_2? I would like to be either be able to say that the Y_1 differs from Y_2 in a predictable way, due to a given change in a given variable contained in X or that the differences between Y_1 and Y_2 are not explainable by a change in X. Can creating a NARX/NARMAX model for either of them help me in any way?
Thanks in advance!