finds an x that solves the linear least-squares problem for the matrix equation .
- LeastSquares[m,b] gives a vector x that minimizes Norm[m.x-b].
- The vector x is uniquely determined by the minimization only if Length[x]==MatrixRank[m].
- The argument b can be a matrix, in which case the least-squares minimization is done independently for each column in b, which is the x that minimizes Norm[m.x-b,"Frobenius"].
- LeastSquares works on both numerical and symbolic matrices, as well as SparseArray objects.
- A Method option can also be given. Settings for arbitrary-precision numerical matrices include and , and for sparse arrays and . The default setting of Automatic switches between these methods, depending on the matrix given.
Introduced in 2007