RegBest: Select variables in multiple linear regression

In FactoMineR: Multivariate Exploratory Data Analysis and Data Mining

Select variables in multiple linear regression

Description

Find an optimal submodel

Usage

RegBest(y,x, int = TRUE, wt=NULL, na.action = na.omit,
    method=c("r2","Cp", "adjr2"), nbest=1)

Arguments

y	A response vector
x	A matrix of predictors
int	Add an intercept to the model
wt	Optional weight vector
na.action	Handling missing values
method	Calculate R-squared, adjusted R-squared or Cp to select the model. By default a the F-test on the r-square is used
nbest	number of best models for each set of explained variables (by default 1)

Value

Returns the objects

all	gives all the nbest best models for a given number of variables
best	the best model

Author(s)

Francois Husson [e-mail]

See Also

lm

Examples

data(milk)
res = RegBest(y=milk[,6],x=milk[,-6])
res$best

FactoMineR documentation built on May 29, 2024, 3:36 a.m.