g02 – Correlation and Regression Analysis

Routine Name	Mark of Introduction	Purpose
g02brc	3	nag_ken_spe_corr_coeff Kendall and/or Spearman non-parametric rank correlation coefficients, allows variables and observations to be selectively disregarded
g02btc	7	nag_sum_sqs_update Update a weighted sum of squares matrix with a new observation
g02buc	7	nag_sum_sqs Computes a weighted sum of squares matrix
g02bwc	7	nag_cov_to_corr Computes a correlation matrix from a sum of squares matrix
g02bxc	3	nag_corr_cov Product-moment correlation, unweighted/weighted correlation and covariance matrix, allows variables to be disregarded
g02byc	6	nag_partial_corr Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by g02bxc
g02cac	3	nag_simple_linear_regression Simple linear regression with or without a constant term, data may be weighted
g02cbc	3	nag_regress_confid_interval Simple linear regression confidence intervals for the regression line and individual points
g02dac	1	nag_regsn_mult_linear Fits a general (multiple) linear regression model
g02dcc	2	nag_regsn_mult_linear_addrem_obs Add/delete an observation to/from a general linear regression model
g02ddc	2	nag_regsn_mult_linear_upd_model Estimates of regression parameters from an updated model
g02dec	2	nag_regsn_mult_linear_add_var Add a new independent variable to a general linear regression model
g02dfc	2	nag_regsn_mult_linear_delete_var Delete an independent variable from a general linear regression model
g02dgc	1	nag_regsn_mult_linear_newyvar Fits a general linear regression model to new dependent variable
g02dkc	2	nag_regsn_mult_linear_tran_model Estimates of parameters of a general linear regression model for given constraints
g02dnc	2	nag_regsn_mult_linear_est_func Estimate of an estimable function for a general linear regression model
g02eac	7	nag_all_regsn Computes residual sums of squares for all possible linear regressions for a set of independent variables
g02ecc	7	nag_cp_stat Calculates R² and C_P values from residual sums of squares
g02eec	7	nag_step_regsn Fits a linear regression model by forward selection
g02fac	1	nag_regsn_std_resid_influence Calculates standardized residuals and influence statistics
g02fcc	7	nag_durbin_watson_stat Computes Durbin–Watson test statistic
g02gac	4	nag_glm_normal Fits a generalized linear model with Normal errors
g02gbc	4	nag_glm_binomial Fits a generalized linear model with binomial errors
g02gcc	4	nag_glm_poisson Fits a generalized linear model with Poisson errors
g02gdc	4	nag_glm_gamma Fits a generalized linear model with gamma errors
g02gkc	4	nag_glm_tran_model Estimates and standard errors of parameters of a general linear model for given constraints
g02gnc	4	nag_glm_est_func Estimable function and the standard error of a generalized linear model
g02hac	4	nag_robust_m_regsn_estim Robust regression, standard M-estimates
g02hbc	7	nag_robust_m_regsn_wts Robust regression, compute weights for use with g02hdc
g02hdc	7	nag_robust_m_regsn_user_fn Robust regression, compute regression with user-supplied functions and weights
g02hfc	7	nag_robust_m_regsn_param_var Robust regression, variance-covariance matrix following g02hdc
g02hkc	4	nag_robust_corr_estim Robust estimation of a correlation matrix, Huber's weight function
g02hlc	7	nag_robust_m_corr_user_fn Calculates a robust estimation of a correlation matrix, user-supplied weight function plus derivatives
g02hmc	7	nag_robust_m_corr_user_fn_no_derr Calculates a robust estimation of a correlation matrix, user-supplied weight function

NAG C Library