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 variable to a general linear regression model |
G02DFF Example Text Example Data | 14 | Delete a 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 |
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 |