Using Eigen to solve a dense, constrained least squares fit

Viewed 2227

I need to solve a classic problem of the form Ax = b for a vector x that is of size 4. A is on the order of ~500 data points and thus is a dense 500x4 matrix.

Currently I can solve this using the normal equations described here and it works fine however I would like to constrain one of my parameters in x to never be above a certain value.

Is there a good way to do this programmatically with Eigen?

2 Answers
Related