The article discusses using copula functions to model relationships between different sets of data. Copulas are a useful tool because they allow for flexible modeling of how variables are related to each other, beyond simple linear correlations. By incorporating covariates, researchers can create highly flexible models that accurately capture complex dependence structures. The study compares different copula families to determine which ones are most suitable for modeling real-world data, considering factors like concordance and tail dependence.