R code to perform variable ranking with the Cox model in presence of highly correlated features

The R function ranking_cox_bw.R ranks the input features of a Cox model based on their predictive ability, suitably managing the presence of highly correlated numerical features. The function implements the method based on recursive feature elimination and Borda count presented in Vettoretti M. and Di Camillo B., A Variable Ranking Method for Machine Learning Models with Correlated Features: In-Silico Validation and Application for Diabetes Prediction. Appl. Sci. 2021, 11(16), 7740; https://doi.org/10.3390/app11167740

For the function documentation see the file ranking_cox_bw.Rd, while the R markdown file test_ranking_cox_bw_simulated_data.Rmd can be used to test the function with simulated data.