To check the multicollinearity, the method I know is to use `vif` in `car` library. To use `vif`, we first have to fit a model. However, the data is $p > n$. We cannot fit a linear regression model with OLS. Then we try to fit in LASSO but all coefficients are 0. Hence, I cannot check the multicollinearity.

Is there a way to check multicollinearity without a model? For example, correlation matrix. But what if $x1 = x2 + x3$? 

I have read this [post][1] . I am not clear how does PCA detect (rather than handling) multicollinearity.


  [1]: http://stats.stackexchange.com/questions/221231/check-multicollinearity-before-regression-in-r