vif: Variance Inflation Factor

In MLRMPA: A package for Multilinear Regression Model Population Analysis

Description

VIF is to analysis the multicollinearity of the descriptors in feature set.

Usage

vif(y, x, lm)

Arguments

y	the activity values
x	the descriptors dataset
lm	a linear model between x and y

Details

The VIF of features below 5.0 is acceptable.

Value

VIF.value

a dataframe contains VIF values for each feature

References

M. Goodarzi, S. Deshpande, V. Murugesan, S. B. Katti, Y. S. Prabhakar, QSAR Comb. Sci. 2009, 28, 1487-1499.

See Also

lm lmcv

Examples

u <- c(5,10,15,20,30,40,60,80,100)
lot1 <- c(118,58,42,35,27,25,23,20,18)
lot2 <- c(69,35,26,21,18,16,13,12,6)
data <- data.frame(cbind(u,lot1,lot2))
lm <- lm(u~.,data=data)
y<-lm$model[,1]
x<-lm$model[,-1]
VIF<-vif(y,x,lm)
print(VIF)

MLRMPA documentation built on May 29, 2017, 10:17 a.m.