Check the degree of multicollinearity present in the dataset
Degree of multicollinearity present in the dataset can be determined by using two type of indicators, called VIF and Condition Number.
checkm(formula, data, na.action, ...)
in this section interested model should be given. This should be given as a
an optional data frame, list or environment containing the variables in the model. If not found in
data, the variables are taken from
environment(formula), typically the environment from which the function is called.
if the dataset contain
na.actionindicate what should happen to those
- currently disregarded.
If all the values of VIF > 10 implies that multicollinearity present. If condition number < 10 ; There is not multicollinearity. 30 < condition number < 100 ; There is a multicollinearity. condition number >100 ; Severe multicollinearity.
checkmreturns the values of two multicllinearity indicators VIF and Condition Number.
## Portland cement data set is used. data(pcd) checkm(Y~X1+X2+X3+X4,data=pcd)