I have a time series of different physical measurements. One of these, lets call it X, is determined by the others, $Y_1$...$Y_n$, through various physical processes (which are complex and not fully known). There is no influence of X on Y. The Y parameters are all caused by the same source, so they are correlated to various degrees. Some of these correlations are close to 1 or -1.
I am looking for a statistical method to analyze the impact of the different parameters on X.
PCA was suggested, but I have not used it before and from what I read it seems not well suited to the problem because of the correlation between the input parameters.
It might be possible to reduce the Ys to a combined parameter for each physical process (where correlation is lowest between them) and then use PCA, but I would be interested if there is a statistical method better suited to my problem, where I can use all parameters. Maybe someone here has an idea?