I have a hand full of daily economic data. I am currently using a brute force approach. Genetic optimization is only used when k is very large. This method is beautiful to me, but isn't valuable compared to OLS models.
So I have found a set of slides from a .edu source on bi-variate x parameters for estimating y for linear modeling. This is very nice and all but I have far more than two economic indicators in mind. The paper mention linear algebra as being a pre-requisite to much higher k values for "hyperplane" models.
Could anyone provide insight on how this could be done? I am thinking perhaps 10 or 15 x values and a single y value. It would be nice if there where a stupid simple explanation and a highly technical one. Despite a 120-130 IQ in mathematics, I suffer severe ADHD+ASD so learning is hard. :(
Re-stating the Question:
How to perform multi-variate linear regression for k explanatory variables. Where k is an integer element of [1,infinity)