| Routine Name |
Mark of Introduction |
Purpose |
| G02AAF
Example Text Example Data |
22 | nagf_correg_corrmat_nearest Computes the nearest correlation matrix to a real square matrix, using the method of Qi and Sun |
| G02ABF
Example Text Example Data |
23 | nagf_correg_corrmat_nearest_bounded Computes the nearest correlation matrix to a real square matrix, augmented G02AAF to incorporate weights and bounds |
| G02AEF
Example Text Example Data |
23 | nagf_correg_corrmat_nearest_kfactor Computes the nearest correlation matrix with -factor structure to a real square matrix |
| G02AJF
Example Text Example Data |
24 | nagf_nearest_correlation_h_weight Computes the nearest correlation matrix to a real square matrix, using element-wise weighting |
| G02ANF
Example Text Example Data |
25 | nagf_nearest_correlation_shrinking Computes a correlation matrix from an approximate matrix with fixed submatrix |
| G02BAF
Example Text Example Data |
4 | nagf_correg_coeffs_pearson Pearson product-moment correlation coefficients, all variables, no missing values |
| G02BBF
Example Text Example Data |
4 | nagf_correg_coeffs_pearson_miss_case Pearson product-moment correlation coefficients, all variables, casewise treatment of missing values |
| G02BCF
Example Text Example Data |
4 | nagf_correg_coeffs_pearson_miss_pair Pearson product-moment correlation coefficients, all variables, pairwise treatment of missing values |
| G02BDF
Example Text Example Data |
4 | nagf_correg_coeffs_zero Correlation-like coefficients (about zero), all variables, no missing values |
| G02BEF
Example Text Example Data |
4 | nagf_correg_coeffs_zero_miss_case Correlation-like coefficients (about zero), all variables, casewise treatment of missing values |
| G02BFF
Example Text Example Data |
4 | nagf_correg_coeffs_zero_miss_pair Correlation-like coefficients (about zero), all variables, pairwise treatment of missing values |
| G02BGF
Example Text Example Data |
4 | nagf_correg_coeffs_pearson_subset Pearson product-moment correlation coefficients, subset of variables, no missing values |
| G02BHF
Example Text Example Data |
4 | nagf_correg_coeffs_pearson_subset_miss_case Pearson product-moment correlation coefficients, subset of variables, casewise treatment of missing values |
| G02BJF
Example Text Example Data |
4 | nagf_correg_coeffs_pearson_subset_miss_pair Pearson product-moment correlation coefficients, subset of variables, pairwise treatment of missing values |
| G02BKF
Example Text Example Data |
4 | nagf_correg_coeffs_zero_subset Correlation-like coefficients (about zero), subset of variables, no missing values |
| G02BLF
Example Text Example Data |
4 | nagf_correg_coeffs_zero_subset_miss_case Correlation-like coefficients (about zero), subset of variables, casewise treatment of missing values |
| G02BMF
Example Text Example Data |
4 | nagf_correg_coeffs_zero_subset_miss_pair Correlation-like coefficients (about zero), subset of variables, pairwise treatment of missing values |
| G02BNF
Example Text Example Data |
4 | nagf_correg_coeffs_kspearman_overwrite Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data |
| G02BPF
Example Text Example Data |
4 | nagf_correg_coeffs_kspearman_miss_case_overwrite Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, overwriting input data |
| G02BQF
Example Text Example Data |
4 | nagf_correg_coeffs_kspearman Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data |
| G02BRF
Example Text Example Data |
4 | nagf_correg_coeffs_kspearman_miss_case Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, preserving input data |
| G02BSF
Example Text Example Data |
4 | nagf_correg_coeffs_kspearman_miss_pair Kendall/Spearman non-parametric rank correlation coefficients, pairwise treatment of missing values |
| G02BTF
Example Text Example Data |
14 | nagf_correg_ssqmat_update Update a weighted sum of squares matrix with a new observation |
| G02BUF
Example Text Example Data |
14 | nagf_correg_ssqmat Computes a weighted sum of squares matrix |
| G02BWF
Example Text Example Data |
14 | nagf_correg_ssqmat_to_corrmat Computes a correlation matrix from a sum of squares matrix |
| G02BXF
Example Text Example Data |
14 | nagf_correg_corrmat Computes (optionally weighted) correlation and covariance matrices |
| G02BYF
Example Text Example Data |
17 | nagf_correg_corrmat_partial Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by G02BXF |
| G02BZF
Example Text Example Data |
24 | nagf_correg_ssqmat_combine Combines two sums of squares matrices, for use after G02BUF |
| G02CAF
Example Text Example Data |
4 | nagf_correg_linregs_const Simple linear regression with constant term, no missing values |
| G02CBF
Example Text Example Data |
4 | nagf_correg_linregs_noconst Simple linear regression without constant term, no missing values |
| G02CCF
Example Text Example Data |
4 | nagf_correg_linregs_const_miss Simple linear regression with constant term, missing values |
| G02CDF
Example Text Example Data |
4 | nagf_correg_linregs_noconst_miss Simple linear regression without constant term, missing values |
| G02CEF
Example Text Example Data |
4 | nagf_correg_linregm_service_select Service routine for multiple linear regression, select elements from vectors and matrices |
| G02CFF
Example Text Example Data |
4 | nagf_correg_linregm_service_reorder Service routine for multiple linear regression, reorder elements of vectors and matrices |
| G02CGF
Example Text Example Data |
4 | nagf_correg_linregm_coeffs_const Multiple linear regression, from correlation coefficients, with constant term |
| G02CHF
Example Text Example Data |
4 | nagf_correg_linregm_coeffs_noconst Multiple linear regression, from correlation-like coefficients, without constant term |
| G02DAF
Example Text Example Data |
14 | nagf_correg_linregm_fit Fits a general (multiple) linear regression model |
| G02DCF
Example Text Example Data |
14 | nagf_correg_linregm_obs_edit Add/delete an observation to/from a general linear regression model |
| G02DDF
Example Text Example Data |
14 | nagf_correg_linregm_update Estimates of linear parameters and general linear regression model from updated model |
| G02DEF
Example Text Example Data |
14 | nagf_correg_linregm_var_add Add a new independent variable to a general linear regression model |
| G02DFF
Example Text Example Data |
14 | nagf_correg_linregm_var_del Delete an independent variable from a general linear regression model |
| G02DGF
Example Text Example Data |
14 | nagf_correg_linregm_fit_newvar Fits a general linear regression model to new dependent variable |
| G02DKF
Example Text Example Data |
14 | nagf_correg_linregm_constrain Estimates and standard errors of parameters of a general linear regression model for given constraints |
| G02DNF
Example Text Example Data |
14 | nagf_correg_linregm_estfunc Computes estimable function of a general linear regression model and its standard error |
| G02EAF
Example Text Example Data |
14 | nagf_correg_linregm_rssq Computes residual sums of squares for all possible linear regressions for a set of independent variables |
| G02ECF
Example Text Example Data |
14 | nagf_correg_linregm_rssq_stat Calculates and values from residual sums of squares |
| G02EEF
Example Text Example Data |
14 | nagf_correg_linregm_fit_onestep Fits a linear regression model by forward selection |
| G02EFF
Example Text Example Data |
21 | nagf_correg_linregm_fit_stepwise Stepwise linear regression |
| G02FAF
Example Text Example Data |
14 | nagf_correg_linregm_stat_resinf Calculates standardized residuals and influence statistics |
| G02FCF
Example Text Example Data |
15 | nagf_correg_linregm_stat_durbwat Computes Durbin–Watson test statistic |
| G02GAF
Example Text Example Data |
14 | nagf_correg_glm_normal Fits a generalized linear model with Normal errors |
| G02GBF
Example Text Example Data |
14 | nagf_correg_glm_binomial Fits a generalized linear model with binomial errors |
| G02GCF
Example Text Example Data |
14 | nagf_correg_glm_poisson Fits a generalized linear model with Poisson errors |
| G02GDF
Example Text Example Data |
14 | nagf_correg_glm_gamma Fits a generalized linear model with gamma errors |
| G02GKF
Example Text Example Data |
14 | nagf_correg_glm_constrain Estimates and standard errors of parameters of a general linear model for given constraints |
| G02GNF
Example Text Example Data |
14 | nagf_correg_glm_estfunc Computes estimable function of a generalized linear model and its standard error |
| G02GPF
Example Text Example Data |
22 | nagf_correg_glm_predict Computes a predicted value and its associated standard error based on a previously fitted generalized linear model |
| G02HAF
Example Text Example Data |
13 | nagf_correg_robustm Robust regression, standard -estimates |
| G02HBF
Example Text Example Data |
13 | nagf_correg_robustm_wts Robust regression, compute weights for use with G02HDF |
| G02HDF
Example Text Example Data |
13 | nagf_correg_robustm_user Robust regression, compute regression with user-supplied functions and weights |
| G02HFF
Example Text Example Data |
13 | nagf_correg_robustm_user_varmat Robust regression, variance-covariance matrix following G02HDF |
| G02HKF
Example Text Example Data |
14 | nagf_correg_robustm_corr_huber Calculates a robust estimation of a covariance matrix, Huber's weight function |
| G02HLF
Example Text Example Data |
14 | nagf_correg_robustm_corr_user_deriv Calculates a robust estimation of a covariance matrix, user-supplied weight function plus derivatives |
| G02HMF
Example Text Example Data |
14 | nagf_correg_robustm_corr_user Calculates a robust estimation of a covariance matrix, user-supplied weight function |
| G02JAF
Example Text Example Data |
21 | nagf_correg_mixeff_reml Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
| G02JBF
Example Text Example Data |
21 | nagf_correg_mixeff_ml Linear mixed effects regression using Maximum Likelihood (ML) |
| G02JCF | 23 | nagf_correg_mixeff_hier_init Hierarchical mixed effects regression, initialization routine for G02JDF and G02JEF |
| G02JDF
Example Text Example Data |
23 | nagf_correg_mixeff_hier_reml Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML) |
| G02JEF
Example Text Example Data |
23 | nagf_correg_mixeff_hier_ml Hierarchical mixed effects regression using Maximum Likelihood (ML) |
| G02KAF
Example Text Example Data |
22 | nagf_correg_ridge_opt Ridge regression, optimizing a ridge regression parameter |
| G02KBF
Example Text Example Data |
22 | nagf_correg_ridge Ridge regression using a number of supplied ridge regression parameters |
| G02LAF
Example Text Example Data |
22 | nagf_correg_pls_svd Partial least squares (PLS) regression using singular value decomposition |
| G02LBF
Example Text Example Data |
22 | nagf_correg_pls_wold Partial least squares (PLS) regression using Wold's iterative method |
| G02LCF
Example Text Example Data |
22 | nagf_correg_pls_fit PLS parameter estimates following partial least squares regression by G02LAF or G02LBF |
| G02LDF
Example Text Example Data |
22 | nagf_correg_pls_pred PLS predictions based on parameter estimates from G02LCF |
| G02MAF
Example Text Example Data Example Plot |
25 | nagf_correg_lars Least angle regression (LARS), least absolute shrinkage and selection operator (LASSO) and forward stagewise regression |
| G02MBF
Example Text Example Data Example Plot |
25 | nagf_correg_lars_xtx Least Angle Regression (LARS), Least Absolute Shrinkage and Selection Operator (LASSO) and forward stagewise regression using the cross-products matrix |
| G02MCF
Example Text Example Data |
25 | nagf_correg_lars_param Additional parameter calculate following Least Angle Regression (LARS), Least Absolute Shrinkage and Selection Operator (LASSO) or forward stagewise regression |
| G02QFF
Example Text Example Data Example Plot |
23 | nagf_correg_quantile_linreg_easy Linear quantile regression, simple interface, independent, identically distributed (IID) errors |
| G02QGF
Example Text Example Data Example Plot |
23 | nagf_correg_quantile_linreg Linear quantile regression, comprehensive interface |
| G02ZKF | 23 | nagf_correg_optset Option setting routine for G02QGF |
| G02ZLF | 23 | nagf_correg_optget Option getting routine for G02QGF |