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LeastSquares

LeastSquares[m, b]
finds an x which solves the linear least-squares problem for the matrix equation m.x

b.

MORE INFORMATION

LeastSquares[m, b] gives a vector x which 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.

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 "Direct" and "IterativeRefinement", and for sparse arrays "Direct" and "Krylov". The default setting of Automatic switches between these methods depending on the matrix given.

Basic Examples (1)

Solve a simple least-squares problem:

Generalizations & Extensions (1)

Applications (1)

Properties & Relations (3)

LinearSolve PseudoInverse Fit LinearModelFit SingularValueDecomposition QRDecomposition CoefficientArrays DesignMatrix FindFit NMinimize FindMinimum

Solving Linear Systems

Demonstrations with LeastSquares (Wolfram Demonstrations Project)

New in 6

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