University of Toronto - Lauréat du Prix CRM-SSC
15 janvier 2015 de 16 h 00 à 18 h 00 (heure de Montréal/HNE) Sur place
Functional data analysis (FDA) has received substantial attention, with applications arising from various disciplines, such as engineering, public health, finance etc. In general, the FDA approaches focus on nonparametric underlying models that assume the data are observed from realizations of stochastic processes satisfying some regularity conditions, e.g., smoothness constraints. The estimation and inference procedures usually do not depend on merely a finite number of parameters, which contrasts with parametric models, and exploit techniques, such as smoothing methods and dimension reduction, that allow data to speak for themselves. In this talk, I will give an overview of FDA methods and related topics developed in recent years.
AdresseCRM, UdeM, Pav. André-Aisenstadt, 2920, ch. de la Tour, salle 1360