Is there any way to determine VIF of some variable that is included in the dataset that has so many variables? I am new in statistics and need some help to determine the VIF value on all my variables/features in the dataset with a lot of variables. I have 98 variables with 76 observations and need to find VIF to do a variable/feature selection
I already know the formula for VIF is:
$VIF = 1/(1-R^2))$
..and $R^2$ is the coefficient of determination that always increases as long the terms are increased. Thus it leads me to an $R^2$ equal to 1 and consequently can't detect the p-value (it is NaN).

The first to the last column belong to feature, estimated coefficient, SE, tStat,  and pValue. I computed it with MATLAB. The p-value can be determined and $R^2$ is decreased if I was decreasing the variable on model fitting.
Is there any way to determine VIF of some variable that is included in the dataset that has many variables?

As shown in the formula below, each time when you calculate VIF for a feature, you are regressing it on the rest of the features. Note that this is applied to continuous variables. In case you would have categorical features, it needs to be generalized VIF. Both are available in R package.

