checkm
From lrmest v3.0
by Ajith Dissanayake
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.
Usage
checkm(formula, data, na.action, ...)
Arguments
 formula

in this section interested model should be given. This should be given as a
formula
.  data

an optional data frame, list or environment containing the variables in the model. If not found in
data
, the variables are taken fromenvironment(formula)
, typically the environment from which the function is called.  na.action

if the dataset contain
NA
values, thenna.action
indicate what should happen to thoseNA
values.  ...
 currently disregarded.
Details
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.
Value
checkm
returns the values of two multicllinearity indicators VIF and Condition Number.
Examples
## Portland cement data set is used.
data(pcd)
checkm(Y~X1+X2+X3+X4,data=pcd)
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