Routine |
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, augmenting 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_correg_corrmat_h_weight Computes the nearest correlation matrix to a real square matrix, using element-wise weighting |
| g02akf
Example Text Example Data |
27 | nagf_correg_corrmat_nearest_rank Computes the rank-constrained nearest correlation matrix to a real square matrix, using the method of Qi and Sun |
| g02anf
Example Text Example Data |
25 | nagf_correg_corrmat_shrinking Computes a correlation matrix from an approximate matrix with fixed submatrix |
| g02apf
Example Text Example Data |
26 | nagf_correg_corrmat_target Computes a correlation matrix from an approximate one using a specified target matrix |
| g02asf
Example Text Example Data |
27 | nagf_correg_corrmat_fixed Computes the nearest correlation matrix to a real square matrix, with fixed elements |
| 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 (Deprecated) | nagf_correg_mixeff_reml Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
| g02jbf
Example Text Example Data |
21 (Deprecated) | nagf_correg_mixeff_ml Linear mixed effects regression using Maximum Likelihood (ML) |
| g02jcf | 23 (Deprecated) | nagf_correg_mixeff_hier_init Hierarchical mixed effects regression, initialization routine for g02jdf and g02jef |
| g02jdf
Example Text Example Data |
23 (Deprecated) | nagf_correg_mixeff_hier_reml Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML) |
| g02jef
Example Text Example Data |
23 (Deprecated) | nagf_correg_mixeff_hier_ml Hierarchical mixed effects regression using Maximum Likelihood (ML) |
| g02jff
Example Text Example Data |
27 | nagf_correg_lmm_init Linear mixed effects regression, initialization routine for g02jhf |
| g02jgf
Example Text Example Data |
27 | nagf_correg_lmm_init_combine Linear mixed effects regression, initialization routine for g02jgf and g02jhf |
| g02jhf
Example Text Example Data |
27 | nagf_correg_lmm_fit Linear mixed effects regression using either Restricted Maximum Likelihood (REML) or 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 Calculates additional parameter estimates 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 |