| Routine Name |
Mark of Introduction |
Purpose |
| G02BAF Example Text Example Data |
4 | Pearson product-moment correlation coefficients, all variables, no missing values |
| G02BBF Example Text Example Data |
4 | Pearson product-moment correlation coefficients, all variables, casewise treatment of missing values |
| G02BCF Example Text Example Data |
4 | Pearson product-moment correlation coefficients, all variables, pairwise treatment of missing values |
| G02BDF Example Text Example Data |
4 | Correlation-like coefficients (about zero), all variables, no missing values |
| G02BEF Example Text Example Data |
4 | Correlation-like coefficients (about zero), all variables, casewise treatment of missing values |
| G02BFF Example Text Example Data |
4 | Correlation-like coefficients (about zero), all variables, pairwise treatment of missing values |
| G02BGF Example Text Example Data |
4 | Pearson product-moment correlation coefficients, subset of variables, no missing values |
| G02BHF Example Text Example Data |
4 | Pearson product-moment correlation coefficients, subset of variables, casewise treatment of missing values |
| G02BJF Example Text Example Data |
4 | Pearson product-moment correlation coefficients, subset of variables, pairwise treatment of missing values |
| G02BKF Example Text Example Data |
4 | Correlation-like coefficients (about zero), subset of variables, no missing values |
| G02BLF Example Text Example Data |
4 | Correlation-like coefficients (about zero), subset of variables, casewise treatment of missing values |
| G02BMF Example Text Example Data |
4 | Correlation-like coefficients (about zero), subset of variables, pairwise treatment of missing values |
| G02BNF Example Text Example Data |
4 | Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data |
| G02BPF Example Text Example Data |
4 | Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, overwriting input data |
| G02BQF Example Text Example Data |
4 | Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data |
| G02BRF Example Text Example Data |
4 | Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, preserving input data |
| G02BSF Example Text Example Data |
4 | Kendall/Spearman non-parametric rank correlation coefficients, pairwise treatment of missing values |
| G02BTF Example Text Example Data |
14 | Update a weighted sum of squares matrix with a new observation |
| G02BUF Example Text Example Data |
14 | Computes a weighted sum of squares matrix |
| G02BWF Example Text Example Data |
14 | Computes a correlation matrix from a sum of squares matrix |
| G02BXF Example Text Example Data |
14 | Computes (optionally weighted) correlation and covariance matrices |
| G02BYF Example Text Example Data |
17 | Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by G02BXF |
| G02CAF Example Text Example Data |
4 | Simple linear regression with constant term, no missing values |
| G02CBF Example Text Example Data |
4 | Simple linear regression without constant term, no missing values |
| G02CCF Example Text Example Data |
4 | Simple linear regression with constant term, missing values |
| G02CDF Example Text Example Data |
4 | Simple linear regression without constant term, missing values |
| G02CEF Example Text Example Data |
4 | Service routines for multiple linear regression, select elements from vectors and matrices |
| G02CFF Example Text Example Data |
4 | Service routines for multiple linear regression, re-order elements of vectors and matrices |
| G02CGF Example Text Example Data |
4 | Multiple linear regression, from correlation coefficients, with constant term |
| G02CHF Example Text Example Data |
4 | Multiple linear regression, from correlation-like coefficients, without constant term |
| G02DAF Example Text Example Data |
14 | Fits a general (multiple) linear regression model |
| G02DCF Example Text Example Data |
14 | Add/delete an observation to/from a general linear regression model |
| G02DDF Example Text Example Data |
14 | Estimates of linear parameters and general linear regression model from updated model |
| G02DEF Example Text Example Data |
14 | Add a new independent variable to a general linear regression model |
| G02DFF Example Text Example Data |
14 | Delete an independent variable from a general linear regression model |
| G02DGF Example Text Example Data |
14 | Fits a general linear regression model to new dependent variable |
| G02DKF Example Text Example Data |
14 | Estimates and standard errors of parameters of a general linear regression model for given constraints |
| G02DNF Example Text Example Data |
14 | Computes estimable function of a general linear regression model and its standard error |
| G02EAF Example Text Example Data |
14 | Computes residual sums of squares for all possible linear regressions for a set of independent variables |
| G02ECF Example Text Example Data |
14 | Calculates R2 and CP values from residual sums of squares |
| G02EEF Example Text Example Data |
14 | Fits a linear regression model by forward selection |
| G02EFF Example Text Example Data |
21 | Stepwise linear regression |
| G02FAF Example Text Example Data |
14 | Calculates standardized residuals and influence statistics |
| G02FCF Example Text Example Data |
15 | Computes Durbin–Watson test statistic |
| G02GAF Example Text Example Data |
14 | Fits a generalized linear model with Normal errors |
| G02GBF Example Text Example Data |
14 | Fits a generalized linear model with binomial errors |
| G02GCF Example Text Example Data |
14 | Fits a generalized linear model with Poisson errors |
| G02GDF Example Text Example Data |
14 | Fits a generalized linear model with gamma errors |
| G02GKF Example Text Example Data |
14 | Estimates and standard errors of parameters of a general linear model for given constraints |
| G02GNF Example Text Example Data |
14 | Computes estimable function of a generalized linear model and its standard error |
| G02HAF Example Text Example Data |
13 | Robust regression, standard M-estimates |
| G02HBF Example Text Example Data |
13 | Robust regression, compute weights for use with G02HDF |
| G02HDF Example Text Example Data |
13 | Robust regression, compute regression with user-supplied functions and weights |
| G02HFF Example Text Example Data |
13 | Robust regression, variance-covariance matrix following G02HDF |
| G02HKF Example Text Example Data |
14 | Calculates a robust estimation of a correlation matrix, Huber's weight function |
| G02HLF Example Text Example Data |
14 | Calculates a robust estimation of a correlation matrix, user-supplied weight function plus derivatives |
| G02HMF Example Text Example Data |
14 | Calculates a robust estimation of a correlation matrix, user-supplied weight function |
| G02JAF Example Text Example Data |
21 | Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
| G02JBF Example Text Example Data |
21 | Linear mixed effects regression using Maximum Likelihood (ML) |