| 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
|
