Calculate Line Of Best Fit Using Exponential Weighting? I know how to calculate a line of best fit with a set of data.
I want to be able to exponentially weight the data that is more recent so that the more recent data has a greater effect on the line.  
How can I do this?

Most linear least squares algorithms let you set the measurement error of each point.  Errors in point $i$ are then weighted by $\frac{1}{\sigma_i}$.  So assign a smaller measurement error to more recent points.  One algorithm is available for free in the obsolete version of Numerical Recipes, chapter 15.
