Un Modelo Bayesiano No Paramétrico Multinivel

This work presents the development of a multilevel Bayesian nonparametric model that allows for the estimation of linear relationships in heterogeneous data sets, while simultaneously identifying clusters without the need to specify the number of groups in advance. The study includes the mathematical development of the model using the Chinese Restaurant Process and the implementation of algorithms for its fitting. The results obtained from real data show that the model performs well in both clustering data and characterizing linear relationships, achieving results comparable and even better to those obtained by traditional parametric methods.