> Perhaps the manual needs to be clearer about what is computed, which > is the unique least squares solution that has minimum norm solution > coefficients |c|^2 (this only comes into play if there's a null space > - otherwise there's only one solution anyway). The idea is to > minimise any spurious components of the solution. This is usually > what is needed when fitting data and pretty standard. > > When the rhs=0 and there is one singular value there is still an > infinite number of solutions, as the overall scale is > undetermined. The least squares choice is to return the minimum norm > solution, i.e. zero. > > In the help-gsl question, which was about fitting the equation for a > plane, the appropriate method is orthogonal regression rather than > linear regression, as there's no dependent variable.
Yes, after thinking about the problem some more I realized its a bit more complicated than I originally thought.
