What I want to do is perform a linear regression on my data. The fit is great, but its intercept is not at the origin - it's slightly above it. For my analysis, however, it's important that the fit passes exactly through zero. (I'm well aware that in general, forcing a fit through zero is a bad idea, but it's essential for what I'm doing). I don't want to simply remove "b" from my linear fit (f = ax + b --> f= ax ) because that would reduce my correlation. Rather, I want to "re-fit" the data with (0,0) as a datapoint, *and* make sure that the fit passes through the origin (in other words, "b" would be zero, but the slope of my fit ("a") would be different from the slope of my original "non-forced" fit). Could anyone give me some hints as to what the correct way of doing this would be? I remember from undergrad courses that there was a "well-established", statistically acceptable way of doing this, but as I said above, my course notes are unavailable to me right now.

If it helps, I'm using Matlab for my statistical analysis. Thanks a lot in advance.