varSelec {MMIX}R Documentation

Variable selection

Description

Create a data frame from the original data set including a subset of variables.

Usage

varSelec(data,family,maxVar=10,trace=0)

Arguments

data a data frame including the response variable (first column) and the explanatory variables. All the variables must be numeric and the response variable value must be 0 or 1 for the logistic model.
family a description of the error distribution (gaussian("identity") or binomial("logit")).
maxVar maximum number of explanatory variables to include.
trace print information during the run if trace = 1. Larger values may give more information. If trace = 0 no information is printed.

Details

This function implements a stepwise regression for linear and logistic models, in the direction "forward" and with the criterion "aic". The procedure stops if the model includes more than maxVar factors. The returned data frame includes no more than maxVar explanatory variables.

Value

varSelec returns a data frame including the response variable and the selected explanatory variables.

Author(s)

Marie Morfin and David Makowski

See Also

bmaBic, mixAic, arms

Examples

##Data 
#Explanatory variables 
X1<-c(-0.2,-2.4,-0.7,1.2,0.0,-1.1,-2.1,-0.3,2.0,-1.7,1.4,-1.3,-3.4,0.4,-1.3,
-4.8)
X2<- c(-3,  2,  1, -2, -2, -4,  0,  1,  1, -1, -1, -4,  0,  2,  0, -4)
X3<-c(2,1,0,-2,1,-2, 0, -1, -4, 1, -3, -3, -3, -1, 0, 2)

#Linear model
Y1<- c(8.7, 6, 9.1, 10.4, 7.6 ,10.4,  7.9, 11.9, 18, 10.5, 16.5, 8.8, 7.7,
 13.5, 8.2, 0.8)
data1<-data.frame(Y1,X1,X2,X3)
#Logistic model
Y2<-c(1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1)
data2<-data.frame(Y2,X1,X2,X3)

##varSelec
data1bis<-varSelec(data=data1,family=gaussian("identity"),maxVar=2)
data2bis<-varSelec(data=data2,family=binomial("logit"),maxVar=2)


[Package MMIX version 1.1 Index]