Mezclas de Procesos Gaussianos Jerárquicos Bayesianos para Análisis de Regresión

This paper essentially considers Gaussian process (GP) methods for regression analysis in longitudinal studies. The model is indeed a reasonable choice for description and prediction of phenomena involving repeated measurements in which there is evidence of heterogeneity among batches of measurements. First, we provide all the theoretical and practical details behind our modeling strategy. Then, we study the main properties of the model using simulated data. And finally, we apply analyze an AIDS clinical study developed by the AIDS Clinical Trials Group.