Mar 5, 2013 at 3:21 PM
Edited Mar 5, 2013 at 3:22 PM

Look. I'm not a mathematician or a statistician. I'm just a software developer with a job to do and most of the documentation I find regarding this project is Greek to me (no offense to the Greeks) so I'm hoping one of you more learned people wouldn't
mind taking a few minutes to guide me in the proper direction.
My task is to predict the price of a sale of an item at auction based on historical auction data. I have a List of Sale objects that have a SaleDate and SaleAmount where SaleDate is fairly random (as opposed to being in a more usable pattern such as every weekday
or once per week or once per month). Then, I need to show the overall curve/line graphically in a Silverlight/RT/WinPhone UI.
After some research, I thought that using a Weighted Least Squares might be a good fit (currently using nonWeighted Least Squares and it, after 4 years, is no longer doing the job well enough). I found this project and am quite impressed with how thorough
it appears to be. I would like to use it, if possible. But I don't know where to start....
So, would someone be kind enough to point me in the right direction?



I am assuming you know how to do a normal regression.
For a weighted regression, you would need to compute the correlation or covariance matrix in a weighted fashion and then do the regression .
I did this in Matlab a long time ago, but have not had a need to do so in MathNet Numerics. If the rest is Greek to you this could be too, but it really is just a bunch of weighted sums. There might be higher level statistical libraries that can do weighted
regression already.

