| 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 R2 and CP values from residual sums of squares |
| G04DAF | Computes sum of squares for contrast between means |