Routine |
Mark of Introduction |
Purpose |
|---|---|---|
| g02aaf | 22 | nagf_correg_corrmat_nearest Computes the nearest correlation matrix to a real square matrix, using the method of Qi and Sun |
| g02abf | 23 | nagf_correg_corrmat_nearest_bounded Computes the nearest correlation matrix to a real square matrix, augmenting g02aaf to incorporate weights and bounds |
| g02aef | 23 | nagf_correg_corrmat_nearest_kfactor Computes the nearest correlation matrix with -factor structure to a real square matrix |
| g02ajf | 24 | nagf_correg_corrmat_h_weight Computes the nearest correlation matrix to a real square matrix, using element-wise weighting |
| g02akf | 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 | 25 | nagf_correg_corrmat_shrinking Computes a correlation matrix from an approximate matrix with fixed submatrix |
| g02apf | 26 | nagf_correg_corrmat_target Computes a correlation matrix from an approximate one using a specified target matrix |
| g02asf | 27 | nagf_correg_corrmat_fixed Computes the nearest correlation matrix to a real square matrix, with fixed elements |
| g02baf | 4 | nagf_correg_coeffs_pearson Pearson product-moment correlation coefficients, all variables, no missing values |
| g02bbf | 4 | nagf_correg_coeffs_pearson_miss_case Pearson product-moment correlation coefficients, all variables, casewise treatment of missing values |
| g02bcf | 4 | nagf_correg_coeffs_pearson_miss_pair Pearson product-moment correlation coefficients, all variables, pairwise treatment of missing values |
| g02bdf | 4 | nagf_correg_coeffs_zero Correlation-like coefficients (about zero), all variables, no missing values |
| g02bef | 4 | nagf_correg_coeffs_zero_miss_case Correlation-like coefficients (about zero), all variables, casewise treatment of missing values |
| g02bff | 4 | nagf_correg_coeffs_zero_miss_pair Correlation-like coefficients (about zero), all variables, pairwise treatment of missing values |
| g02bgf | 4 | nagf_correg_coeffs_pearson_subset Pearson product-moment correlation coefficients, subset of variables, no missing values |
| g02bhf | 4 | nagf_correg_coeffs_pearson_subset_miss_case Pearson product-moment correlation coefficients, subset of variables, casewise treatment of missing values |
| g02bjf | 4 | nagf_correg_coeffs_pearson_subset_miss_pair Pearson product-moment correlation coefficients, subset of variables, pairwise treatment of missing values |
| g02bkf | 4 | nagf_correg_coeffs_zero_subset Correlation-like coefficients (about zero), subset of variables, no missing values |
| g02blf | 4 | nagf_correg_coeffs_zero_subset_miss_case Correlation-like coefficients (about zero), subset of variables, casewise treatment of missing values |
| g02bmf | 4 | nagf_correg_coeffs_zero_subset_miss_pair Correlation-like coefficients (about zero), subset of variables, pairwise treatment of missing values |
| g02bnf | 4 | nagf_correg_coeffs_kspearman_overwrite Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data |
| g02bpf | 4 | nagf_correg_coeffs_kspearman_miss_case_overwrite Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, overwriting input data |
| g02bqf | 4 | nagf_correg_coeffs_kspearman Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data |
| g02brf | 4 | nagf_correg_coeffs_kspearman_miss_case Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, preserving input data |
| g02bsf | 4 | nagf_correg_coeffs_kspearman_miss_pair Kendall/Spearman non-parametric rank correlation coefficients, pairwise treatment of missing values |
| g02btf | 14 | nagf_correg_ssqmat_update Update a weighted sum of squares matrix with a new observation |
| g02buf | 14 | nagf_correg_ssqmat Computes a weighted sum of squares matrix |
| g02bwf | 14 | nagf_correg_ssqmat_to_corrmat Computes a correlation matrix from a sum of squares matrix |
| g02bxf | 14 | nagf_correg_corrmat Computes (optionally weighted) correlation and covariance matrices |
| g02byf | 17 | nagf_correg_corrmat_partial Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by g02bxf |
| g02bzf | 24 | nagf_correg_ssqmat_combine Combines two sums of squares matrices, for use after g02buf |
| g02caf | 4 | nagf_correg_linregs_const Simple linear regression with constant term, no missing values |
| g02cbf | 4 | nagf_correg_linregs_noconst Simple linear regression without constant term, no missing values |
| g02ccf | 4 | nagf_correg_linregs_const_miss Simple linear regression with constant term, missing values |
| g02cdf | 4 | nagf_correg_linregs_noconst_miss Simple linear regression without constant term, missing values |
| g02cef | 4 | nagf_correg_linregm_service_select Service routine for multiple linear regression, select elements from vectors and matrices |
| g02cff | 4 | nagf_correg_linregm_service_reorder Service routine for multiple linear regression, reorder elements of vectors and matrices |
| g02cgf | 4 | nagf_correg_linregm_coeffs_const Multiple linear regression, from correlation coefficients, with constant term |
| g02chf | 4 | nagf_correg_linregm_coeffs_noconst Multiple linear regression, from correlation-like coefficients, without constant term |
| g02daf | 14 | nagf_correg_linregm_fit Fits a general (multiple) linear regression model |
| g02dcf | 14 | nagf_correg_linregm_obs_edit Add/delete an observation to/from a general linear regression model |
| g02ddf | 14 | nagf_correg_linregm_update Estimates of linear parameters and general linear regression model from updated model |
| g02def | 14 | nagf_correg_linregm_var_add Add a new independent variable to a general linear regression model |
| g02dff | 14 | nagf_correg_linregm_var_del Delete an independent variable from a general linear regression model |
| g02dgf | 14 | nagf_correg_linregm_fit_newvar Fits a general linear regression model to new dependent variable |
| g02dkf | 14 | nagf_correg_linregm_constrain Estimates and standard errors of parameters of a general linear regression model for given constraints |
| g02dnf | 14 | nagf_correg_linregm_estfunc Computes estimable function of a general linear regression model and its standard error |
| g02eaf | 14 | nagf_correg_linregm_rssq Computes residual sums of squares for all possible linear regressions for a set of independent variables |
| g02ecf | 14 | nagf_correg_linregm_rssq_stat Calculates and values from residual sums of squares |
| g02eef | 14 | nagf_correg_linregm_fit_onestep Fits a linear regression model by forward selection |
| g02eff | 21 | nagf_correg_linregm_fit_stepwise Stepwise linear regression |
| g02faf | 14 | nagf_correg_linregm_stat_resinf Calculates standardized residuals and influence statistics |
| g02fcf | 15 | nagf_correg_linregm_stat_durbwat Computes Durbin–Watson test statistic |
| g02gaf | 14 | nagf_correg_glm_normal Fits a generalized linear model with Normal errors |
| g02gbf | 14 | nagf_correg_glm_binomial Fits a generalized linear model with binomial errors |
| g02gcf | 14 | nagf_correg_glm_poisson Fits a generalized linear model with Poisson errors |
| g02gdf | 14 | nagf_correg_glm_gamma Fits a generalized linear model with gamma errors |
| g02gkf | 14 | nagf_correg_glm_constrain Estimates and standard errors of parameters of a general linear model for given constraints |
| g02gnf | 14 | nagf_correg_glm_estfunc Computes estimable function of a generalized linear model and its standard error |
| g02gpf | 22 | nagf_correg_glm_predict Computes a predicted value and its associated standard error based on a previously fitted generalized linear model |
| g02haf | 13 | nagf_correg_robustm Robust regression, standard -estimates |
| g02hbf | 13 | nagf_correg_robustm_wts Robust regression, compute weights for use with g02hdf |
| g02hdf | 13 | nagf_correg_robustm_user Robust regression, compute regression with user-supplied functions and weights |
| g02hff | 13 | nagf_correg_robustm_user_varmat Robust regression, variance-covariance matrix following g02hdf |
| g02hkf | 14 | nagf_correg_robustm_corr_huber Calculates a robust estimation of a covariance matrix, Huber's weight function |
| g02hlf | 14 | nagf_correg_robustm_corr_user_deriv Calculates a robust estimation of a covariance matrix, user-supplied weight function plus derivatives |
| g02hmf | 14 | nagf_correg_robustm_corr_user Calculates a robust estimation of a covariance matrix, user-supplied weight function |
| g02jff | 27 | nagf_correg_lmm_init Linear mixed effects regression, initialization routine for g02jhf |
| g02jgf | 27 | nagf_correg_lmm_init_combine Linear mixed effects regression, initialization routine for g02jgf and g02jhf |
| g02jhf | 27 | nagf_correg_lmm_fit Linear mixed effects regression using either Restricted Maximum Likelihood (REML) or Maximum Likelihood (ML) |
| g02kaf | 22 | nagf_correg_ridge_opt Ridge regression, optimizing a ridge regression parameter |
| g02kbf | 22 | nagf_correg_ridge Ridge regression using a number of supplied ridge regression parameters |
| g02laf | 22 | nagf_correg_pls_svd Partial least squares (PLS) regression using singular value decomposition |
| g02lbf | 22 | nagf_correg_pls_wold Partial least squares (PLS) regression using Wold's iterative method |
| g02lcf | 22 | nagf_correg_pls_fit PLS parameter estimates following partial least squares regression by g02laf or g02lbf |
| g02ldf | 22 | nagf_correg_pls_pred PLS predictions based on parameter estimates from g02lcf |
| g02maf | 25 | nagf_correg_lars Least angle regression (LARS), least absolute shrinkage and selection operator (LASSO) and forward stagewise regression |
| g02mbf | 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 | 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 | 23 | nagf_correg_quantile_linreg_easy Linear quantile regression, simple interface, independent, identically distributed (IID) errors |
| g02qgf | 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 |
| g02jaf | 21 (Deprecated) | nagf_correg_mixeff_reml Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
| g02jbf | 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 | 23 (Deprecated) | nagf_correg_mixeff_hier_reml Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML) |
| g02jef | 23 (Deprecated) | nagf_correg_mixeff_hier_ml Hierarchical mixed effects regression using Maximum Likelihood (ML) |