D02JAF | Ordinary differential equations, boundary value problem, collocation and least squares, single $n$th-order linear equation |

D02JBF | Ordinary differential equations, boundary value problem, collocation and least squares, system of first-order linear equations |

D02TGF | $n$th-order linear ordinary differential equations, boundary value problem, collocation and least squares |

E02ADF | Least squares curve fit, by polynomials, arbitrary data points |

E02AFF | Least squares polynomial fit, special data points (including interpolation) |

E02AGF | Least squares polynomial fit, values and derivatives may be constrained, arbitrary data points |

E02BAF | Least squares curve cubic spline fit (including interpolation) |

E02BEF | Least squares cubic spline curve fit, automatic knot placement |

E02CAF | Least squares surface fit by polynomials, data on lines parallel to one independent coordinate axis |

E02DAF | Least squares surface fit, bicubic splines |

E02DCF | Least squares surface fit by bicubic splines with automatic knot placement, data on rectangular grid |

E02DDF | Least squares surface fit by bicubic splines with automatic knot placement, scattered data |

E02DHF | Evaluation of spline surface at mesh of points with derivatives |

E04NCF | Convex QP problem or linearly-constrained linear least squares problem (dense) |

E04PCF | Computes the least squares solution to a set of linear equations subject to fixed upper and lower bounds on the variables. An option is provided to return a minimal length solution if a solution is not unique |

E04YCF | Covariance matrix for nonlinear least squares problem (unconstrained) |

F04AMF | Least squares solution of $m$ real equations in $n$ unknowns, rank $\text{}=n$, $m\ge n$ using iterative refinement (Black Box) |

F04JGF | Least squares (if rank $\text{}=n$) or minimal least squares (if rank $\text{}<n$) solution of $m$ real equations in $n$ unknowns, $m\ge n$ |

F04QAF | Sparse linear least squares problem, $m$ real equations in $n$ unknowns |

F04YAF | Covariance matrix for linear least squares problems, $m$ real equations in $n$ unknowns |

F08BAF | Computes the minimum-norm solution to a real linear least squares problem |

F08BNF | Computes the minimum-norm solution to a complex linear least squares problem |

F08KAF | Computes the minimum-norm solution to a real linear least squares problem using singular value decomposition |

F08KCF | Computes the minimum-norm solution to a real linear least squares problem using singular value decomposition (divide-and-conquer) |

F08KNF | Computes the minimum-norm solution to a complex linear least squares problem using singular value decomposition |

F08KQF | Computes the minimum-norm solution to a complex linear least squares problem using singular value decomposition (divide-and-conquer) |

F08ZAF | Solves the real linear equality-constrained least squares (LSE) problem |

F08ZNF | Solves the complex linear equality-constrained least squares (LSE) problem |

© The Numerical Algorithms Group Ltd, Oxford UK. 2013