Function |
Mark of Introduction |
Purpose |
|---|---|---|
| g02aac
Example Text Example Data |
9 | nag_correg_corrmat_nearest Computes the nearest correlation matrix to a real square matrix, using the method of Qi and Sun |
| g02abc
Example Text Example Data |
23 | nag_correg_corrmat_nearest_bounded Computes the nearest correlation matrix to a real square matrix, augmenting g02aac to incorporate weights and bounds |
| g02aec
Example Text Example Data |
23 | nag_correg_corrmat_nearest_kfactor Computes the nearest correlation matrix with -factor structure to a real square matrix |
| g02ajc
Example Text Example Data |
24 | nag_correg_corrmat_h_weight Computes the nearest correlation matrix to a real square matrix, using element-wise weighting |
| g02akc
Example Text Example Data |
27 | nag_correg_corrmat_nearest_rank Computes the rank-constrained nearest correlation matrix to a real square matrix, using the method of Qi and Sun |
| g02anc
Example Text Example Data |
25 | nag_correg_corrmat_shrinking Computes a correlation matrix from an approximate matrix with fixed submatrix |
| g02apc
Example Text Example Data |
26 | nag_correg_corrmat_target Computes a correlation matrix from an approximate one using a specified target matrix |
| g02asc
Example Text Example Data |
27 | nag_correg_corrmat_fixed Computes the nearest correlation matrix to a real square matrix, with fixed elements |
| g02brc
Example Text Example Data |
3 | nag_correg_coeffs_kspearman_miss_case Kendall and/or Spearman non-parametric rank correlation coefficients, allows variables and observations to be selectively disregarded |
| g02btc
Example Text Example Data |
7 | nag_correg_ssqmat_update Update a weighted sum of squares matrix with a new observation |
| g02buc
Example Text Example Data |
7 | nag_correg_ssqmat Computes a weighted sum of squares matrix |
| g02bwc
Example Text Example Data |
7 | nag_correg_ssqmat_to_corrmat Computes a correlation matrix from a sum of squares matrix |
| g02bxc
Example Text Example Data |
3 | nag_correg_corrmat Product-moment correlation, unweighted/weighted correlation and covariance matrix, allows variables to be disregarded |
| g02byc
Example Text Example Data |
6 | nag_correg_corrmat_partial Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by g02bxc |
| g02bzc
Example Text Example Data |
24 | nag_correg_ssqmat_combine Combines two sums of squares matrices, for use after g02buc |
| g02cac
Example Text Example Data |
3 | nag_correg_linregs_const Simple linear regression with or without a constant term, data may be weighted |
| g02cbc
Example Text Example Data |
3 | nag_correg_linregs_noconst Simple linear regression confidence intervals for the regression line and individual points |
| g02dac
Example Text Example Data |
1 | nag_correg_linregm_fit Fits a general (multiple) linear regression model |
| g02dcc
Example Text Example Data |
2 | nag_correg_linregm_obs_edit Add/delete an observation to/from a general linear regression model |
| g02ddc
Example Text Example Data |
2 | nag_correg_linregm_update Estimates of regression parameters from an updated model |
| g02dec
Example Text Example Data |
2 | nag_correg_linregm_var_add Add a new independent variable to a general linear regression model |
| g02dfc
Example Text Example Data |
2 | nag_correg_linregm_var_del Delete an independent variable from a general linear regression model |
| g02dgc
Example Text Example Data |
1 | nag_correg_linregm_fit_newvar Fits a general linear regression model to new dependent variable |
| g02dkc
Example Text Example Data |
2 | nag_correg_linregm_constrain Estimates of parameters of a general linear regression model for given constraints |
| g02dnc
Example Text Example Data |
2 | nag_correg_linregm_estfunc Estimate of an estimable function for a general linear regression model |
| g02eac
Example Text Example Data |
7 | nag_correg_linregm_rssq Computes residual sums of squares for all possible linear regressions for a set of independent variables |
| g02ecc
Example Text Example Data |
7 | nag_correg_linregm_rssq_stat Calculates and values from residual sums of squares |
| g02eec
Example Text Example Data |
7 | nag_correg_linregm_fit_onestep Fits a linear regression model by forward selection |
| g02efc
Example Text Example Data |
8 | nag_correg_linregm_fit_stepwise Stepwise linear regression |
| g02fac
Example Text Example Data |
1 | nag_correg_linregm_stat_resinf Calculates standardized residuals and influence statistics |
| g02fcc
Example Text Example Data |
7 | nag_correg_linregm_stat_durbwat Computes Durbin–Watson test statistic |
| g02gac
Example Text Example Data |
4 | nag_correg_glm_normal Fits a generalized linear model with Normal errors |
| g02gbc
Example Text Example Data |
4 | nag_correg_glm_binomial Fits a generalized linear model with binomial errors |
| g02gcc
Example Text Example Data |
4 | nag_correg_glm_poisson Fits a generalized linear model with Poisson errors |
| g02gdc
Example Text Example Data |
4 | nag_correg_glm_gamma Fits a generalized linear model with gamma errors |
| g02gkc
Example Text Example Data |
4 | nag_correg_glm_constrain Estimates and standard errors of parameters of a general linear model for given constraints |
| g02gnc
Example Text Example Data |
4 | nag_correg_glm_estfunc Estimable function and the standard error of a generalized linear model |
| g02gpc
Example Text Example Data |
9 | nag_correg_glm_predict Computes a predicted value and its associated standard error based on a previously fitted generalized linear model |
| g02hac
Example Text Example Data |
4 | nag_correg_robustm Robust regression, standard -estimates |
| g02hbc
Example Text Example Data |
7 | nag_correg_robustm_wts Robust regression, compute weights for use with g02hdc |
| g02hdc
Example Text Example Data |
7 | nag_correg_robustm_user Robust regression, compute regression with user-supplied functions and weights |
| g02hfc
Example Text Example Data |
7 | nag_correg_robustm_user_varmat Robust regression, variance-covariance matrix following g02hdc |
| g02hkc
Example Text Example Data |
4 | nag_correg_robustm_corr_huber Robust estimation of a covariance matrix, Huber's weight function |
| g02hlc
Example Text Example Data |
7 | nag_correg_robustm_corr_user_deriv Calculates a robust estimation of a covariance matrix, user-supplied weight function plus derivatives |
| g02hmc
Example Text Example Data |
7 | nag_correg_robustm_corr_user Calculates a robust estimation of a covariance matrix, user-supplied weight function |
| g02jac
Example Text Example Data |
8 (Deprecated) | nag_correg_mixeff_reml Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
| g02jbc
Example Text Example Data |
8 (Deprecated) | nag_correg_mixeff_ml Linear mixed effects regression using Maximum Likelihood (ML) |
| g02jcc | 9 (Deprecated) | nag_correg_mixeff_hier_init Hierarchical mixed effects regression, initialization function for g02jdc and g02jec |
| g02jdc
Example Text Example Data |
9 (Deprecated) | nag_correg_mixeff_hier_reml Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML) |
| g02jec
Example Text Example Data |
9 (Deprecated) | nag_correg_mixeff_hier_ml Hierarchical mixed effects regression using Maximum Likelihood (ML) |
| g02jfc
Example Text Example Data |
27 | nag_correg_lmm_init Linear mixed effects regression, initialization function for g02jhc |
| g02jgc
Example Text Example Data |
27 | nag_correg_lmm_init_combine Linear mixed effects regression, initialization function for g02jgc and g02jhc |
| g02jhc
Example Text Example Data |
27 | nag_correg_lmm_fit Linear mixed effects regression using either Restricted Maximum Likelihood (REML) or Maximum Likelihood (ML) |
| g02kac
Example Text Example Data |
9 | nag_correg_ridge_opt Ridge regression, optimizing a ridge regression parameter |
| g02kbc
Example Text Example Data |
9 | nag_correg_ridge Ridge regression using a number of supplied ridge regression parameters |
| g02lac
Example Text Example Data |
9 | nag_correg_pls_svd Partial least squares (PLS) regression using singular value decomposition |
| g02lbc
Example Text Example Data |
9 | nag_correg_pls_wold Partial least squares (PLS) regression using Wold's iterative method |
| g02lcc
Example Text Example Data |
9 | nag_correg_pls_fit PLS parameter estimates following partial least squares regression by g02lac or g02lbc |
| g02ldc
Example Text Example Data |
9 | nag_correg_pls_pred PLS predictions based on parameter estimates from g02lcc |
| g02mac
Example Text Example Data Example Plot |
25 | nag_correg_lars Least angle regression (LARS), least absolute shrinkage and selection operator (LASSO) and forward stagewise regression |
| g02mbc
Example Text Example Data Example Plot |
25 | nag_correg_lars_xtx Least Angle Regression (LARS), Least Absolute Shrinkage and Selection Operator (LASSO) and forward stagewise regression using the cross-products matrix |
| g02mcc
Example Text Example Data |
25 | nag_correg_lars_param Calculates additional parameter estimates following Least Angle Regression (LARS), Least Absolute Shrinkage and Selection Operator (LASSO) or forward stagewise regression |
| g02qfc
Example Text Example Data Example Plot |
23 | nag_correg_quantile_linreg_easy Linear quantile regression, simple interface, independent, identically distributed (IID) errors |
| g02qgc
Example Text Example Data Example Plot |
23 | nag_correg_quantile_linreg Linear quantile regression, comprehensive interface |
| g02zkc | 23 | nag_correg_optset Option setting function for g02qgc |
| g02zlc | 23 | nag_correg_optget Option getting function for g02qgc |