I am working on building a regression model. There are 51 points. The number of predictor variables is 37. The following is the result of running lm result. When trying to detecting the multicollinearity issue, the
vif also drops the error message. What are the problems of this model.
model1<-lm(test.1[,3] ~ as.matrix(test[,-c(1,2,3)]),data=test) summary(model1) vif(model1) Error in vif.default(model1) : model contains fewer than 2 terms