E04FCF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (comprehensive) |

E04FYF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (easy-to-use) |

E04GBF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm using first derivatives (comprehensive) |

E04GDF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (comprehensive) |

E04GYF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm, using first derivatives (easy-to-use) |

E04GZF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (easy-to-use) |

E04HEF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (comprehensive) |

E04HYF | Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (easy-to-use) |

E04USF | Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive) |

E04YBF | Check user's routine for calculating Hessian of a sum of squares |

G02BTF | Update a weighted sum of squares matrix with a new observation |

G02BUF | Computes a weighted sum of squares matrix |

G02BWF | Computes a correlation matrix from a sum of squares matrix |

G02EAF | Computes residual sums of squares for all possible linear regressions for a set of independent variables |

G02ECF | Calculates R and ^{2}C values from residual sums of squares_{P} |

G04DAF | Computes sum of squares for contrast between means |

Library Contents

Keywords in Context Index

© The Numerical Algorithms Group Ltd, Oxford UK. 2001