| G02CAF | Simple linear regression with constant term, no missing values |
| G02CBF | Simple linear regression without constant term, no missing values |
| G02CCF | Simple linear regression with constant term, missing values |
| G02CDF | Simple linear regression without constant term, missing values |
| G02CEF | Service routine for multiple linear regression, select elements from vectors and matrices |
| G02CFF | Service routine for multiple linear regression, re-order elements of vectors and matrices |
| G02CGF | Multiple linear regression, from correlation coefficients, with constant term |
| G02CHF | Multiple linear regression, from correlation-like coefficients, without constant term |
| G02DAF | Fits a general (multiple) linear regression model |
| G02DCF | Add/delete an observation to/from a general linear regression model |
| G02DDF | Estimates of linear parameters and general linear regression model from updated model |
| G02DEF | Add a new independent variable to a general linear regression model |
| G02DFF | Delete an independent variable from a general linear regression model |
| G02DGF | Fits a general linear regression model to new dependent variable |
| G02DKF | Estimates and standard errors of parameters of a general linear regression model for given constraints |
| G02DNF | Computes estimable function of a general linear regression model and its standard error |
| G02EAF | Computes residual sums of squares for all possible linear regressions for a set of independent variables |
| G02EEF | Fits a linear regression model by forward selection |
| G02EFF | Stepwise linear regression |
| G02HAF | Robust regression, standard M-estimates |
| G02HBF | Robust regression, compute weights for use with G02HDF |
| G02HDF | Robust regression, compute regression with user-supplied functions and weights |
| G02HFF | Robust regression, variance-covariance matrix following G02HDF |
| G02JAF | Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
| G02JBF | Linear mixed effects regression using Maximum Likelihood (ML) |
| G02JCF | Hierarchical mixed effects regression, initialization routine for G02JDF and G02JEF |
| G02JDF | Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML) |
| G02JEF | Hierarchical mixed effects regression using Maximum Likelihood (ML) |
| G02KAF | Ridge regression, optimizing a ridge regression parameter |
| G02KBF | Ridge regression using a number of supplied ridge regression parameters |
| G02LAF | Partial least squares (PLS) regression using singular value decomposition |
| G02LBF | Partial least squares (PLS) regression using Wold's iterative method |
| G02LCF | PLS parameter estimates following partial least squares regression by G02LAF or G02LBF |
| G02LDF | PLS predictions based on parameter estimates from G02LCF |
| G02QFF | Quantile linear regression, simple interface, independent, identically distributed (IID) errors |
| G02QGF | Quantile linear regression, comprehensive interface |
| G08RAF | Regression using ranks, uncensored data |
| G08RBF | Regression using ranks, right-censored data |