Chapter Introduction | |
G02BAF | Pearson product-moment correlation coefficients, all variables, no missing values |
G02BBF | Pearson product-moment correlation coefficients, all variables, casewise treatment of missing values |
G02BCF | Pearson product-moment correlation coefficients, all variables, pairwise treatment of missing values |
G02BDF | Correlation-like coefficients (about zero), all variables, no missing values |
G02BEF | Correlation-like coefficients (about zero), all variables, casewise treatment of missing values |
G02BFF | Correlation-like coefficients (about zero), all variables, pairwise treatment of missing values |
G02BGF | Pearson product-moment correlation coefficients, subset of variables, no missing values |
G02BHF | Pearson product-moment correlation coefficients, subset of variables, casewise treatment of missing values |
G02BJF | Pearson product-moment correlation coefficients, subset of variables, pairwise treatment of missing values |
G02BKF | Correlation-like coefficients (about zero), subset of variables, no missing values |
G02BLF | Correlation-like coefficients (about zero), subset of variables, casewise treatment of missing values |
G02BMF | Correlation-like coefficients (about zero), subset of variables, pairwise treatment of missing values |
G02BNF | Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data |
G02BPF | Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, overwriting input data |
G02BQF | Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data |
G02BRF | Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, preserving input data |
G02BSF | Kendall/Spearman non-parametric rank correlation coefficients, pairwise treatment of missing values |
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 |
G02BXF | Computes (optionally weighted) correlation and covariance matrices |
G02BYF | Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by G02BXF |
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 routines for multiple linear regression, select elements from vectors and matrices |
G02CFF | Service routines 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 variable to a general linear regression model |
G02DFF | Delete a variable from a general linear regression model |
G02DGF | Fits a general linear regression model for 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 |
G02ECF | Calculates R2 and CP values from residual sums of squares |
G02EEF | Fits a linear regression model by forward selection |
G02FAF | Calculates standardized residuals and influence statistics |
G02FCF | Computes Durbin--Watson test statistic |
G02GAF | Fits a generalized linear model with Normal errors |
G02GBF | Fits a generalized linear model with binomial errors |
G02GCF | Fits a generalized linear model with Poisson errors |
G02GDF | Fits a generalized linear model with gamma errors |
G02GKF | Estimates and standard errors of parameters of a general linear model for given constraints |
G02GNF | Computes estimable function of a generalized linear model and its standard error |
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 |
G02HKF | Calculates a robust estimation of a correlation matrix, Huber's weight function |
G02HLF | Calculates a robust estimation of a correlation matrix, user-supplied weight function plus derivatives |
G02HMF | Calculates a robust estimation of a correlation matrix, user-supplied weight function |