Hello,
I have a problem that has several dimensions and would like to get to know possible solutions/approaches to solving the problem. I have some experience in using SAS procedures but when it comes to macros, I am pretty much a amateur.
1. I have around 10 pairs of variables (each variable has ~30 datapoints) for which I need to compute non-linear correlation (likely quadratic or monotonic) for each pair.
2. In addition, I need to compute/assess if any non-linear cross-correlation exists for the pairs. The CROSSCORR functionality allows for, if my understanding is correct, computation of linear association with lags.
3. The variables/data being studied are temporal in nature. Any serial correlation is compensated for and the non-linear correlation is between the residuals (post serial correlation removal).
I am looking for a solution that:
1. computes cross-correlation to assess non-linear relationship, if such a thing even exists. Absent that, would regression work in such a scenario, with the R-squared being used in lieu of a correlation/cross-correlation measure?
2. is scalable (I have 30 entities for each of which I need to compute the cross-correlation for 10 pairs of 30 datapoints each).
I hope I have provided as much information as ipossible. If there's any more information required, I am happy to provide.
Thanks in advance.
Addendum: Have added sample data and the expected output. Hope that helps. The attached spreadsheet has 2 tabs: 1 for data and the other for the computed cross-correlation (based on linear association). The cross-correlation was computed using PROC ARIMA. The expectation now is to compute non-linear cross-correlation (monotonic/quadratic), if such a thing is possible.