Test for Multicollinearity

Hello Talk Stats Forum!

I am working on building a Predictive Model using the binary logistic regression and LASSO logistic regression. In order to apply these models on some real data set I am using R software.

Before performing such a model I am testing for multicollinearity and will remove any highly correlated variables. In order to check if I have multicollinearity I will be looking at the VIF and Condition Index, then I will apply "spearman" correlation to remove any highly correlated variables, i.e. where the r value >0.5.

So far, I have coded the below:
Mat is my data

MatRed <- as.matrix((Mat[,c(9:11,14:27,31:46,53:65,70,75:80,92:101)])) #selecting the explanatory variables
MatRedDF <-data.frame(MatRed,row.names = NULL,check.rows = FALSE, check.names = TRUE,stringsAsFactors = FALSE) #changing the structure of my data
SpearmanCorr <- rcorr(MatRed,type="spearman") #running spearman correlation
VIF1 <- vif(MatRedDF) # checking for if i have multicollinearity

When I am trying to run the last code an error is being prompted which is:

Error in vcov.default(mod) :
there is no vcov() method for models of class data.frame

Anyone can help with this please?