A new numerical method for processing longitudinal data: clinical applications - Ilaria Stura; Emma Perracchione; Giuseppe Migliaretti; Franco Cavallo (Epidemiology, Biostatistics and Public Health)
Background: Processing longitudinal data is a computational issue that arises in many applications, such as in aircraft design, medicine, optimal control and weather forecasting. Given some longitudinal data, i.e. scattered measurements, the aim consists in approximating the parameters involved in the dynamics of the considered process. For this problem, a large variety of well-known methods have already been developed.