Keyword : Regression

F04YAF	Covariance matrix for linear least squares problems, $m$ real equations in $n$ unknowns
G02CAF	Simple linear regression with constant term, no missing values
G02CBF	Simple linear regression without constant term, no missing values
G02CCF	Simple linear regression with constant term, missing values
G02CDF	Simple linear regression without constant term, missing values
G02CEF	Service routine for multiple linear regression, select elements from vectors and matrices
G02CFF	Service routine for multiple linear regression, re-order elements of vectors and matrices
G02CGF	Multiple linear regression, from correlation coefficients, with constant term
G02CHF	Multiple linear regression, from correlation-like coefficients, without constant term
G02DAF	Fits a general (multiple) linear regression model
G02DCF	Add/delete an observation to/from a general linear regression model
G02DDF	Estimates of linear parameters and general linear regression model from updated model
G02DEF	Add a new independent variable to a general linear regression model
G02DFF	Delete an independent variable from a general linear regression model
G02DGF	Fits a general linear regression model to new dependent variable
G02DKF	Estimates and standard errors of parameters of a general linear regression model for given constraints
G02DNF	Computes estimable function of a general linear regression model and its standard error
G02EAF	Computes residual sums of squares for all possible linear regressions for a set of independent variables
G02EEF	Fits a linear regression model by forward selection
G02EFF	Stepwise linear regression
G02HAF	Robust regression, standard $M$ -estimates
G02HBF	Robust regression, compute weights for use with G02HDF
G02HDF	Robust regression, compute regression with user-supplied functions and weights
G02HFF	Robust regression, variance-covariance matrix following G02HDF
G02JAF	Linear mixed effects regression using Restricted Maximum Likelihood (REML)
G02JBF	Linear mixed effects regression using Maximum Likelihood (ML)
G02JCF	Hierarchical mixed effects regression, initialization routine for G02JDF and G02JEF
G02JDF	Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML)
G02JEF	Hierarchical mixed effects regression using Maximum Likelihood (ML)
G02KAF	Ridge regression, optimizing a ridge regression parameter
G02KBF	Ridge regression using a number of supplied ridge regression parameters
G02LAF	Partial least squares (PLS) regression using singular value decomposition
G02LBF	Partial least squares (PLS) regression using Wold's iterative method
G02LCF	PLS parameter estimates following partial least squares regression by G02LAF or G02LBF
G02LDF	PLS predictions based on parameter estimates from G02LCF
G02QFF	Linear quantile regression, simple interface, independent, identically distributed (IID) errors
G02QGF	Linear quantile regression, comprehensive interface
G08RAF	Regression using ranks, uncensored data
G08RBF	Regression using ranks, right-censored data

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Keyword Index for the NAG Library Manual

NAG Library Manual