# NAG CL InterfaceG02 (Correg)Correlation and Regression Analysis

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G02 (Correg) Chapter Introduction – A description of the Chapter and an overview of the algorithms available.

Function
Mark of
Introduction

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