• closedAccess   A penalized likelihood method for nonseparable space–time generalized additive models 

      Mosammam, Ali M.; Mateu, Jorge Springer Verlag (2018-07)
      In this paper, we study space-time generalized additive models. We apply the penalyzed likelihood method to fit generalized additive models (GAMs) for nonseparable spatio-temporal correlated data in order to improve the ...
    • closedAccess   Statistics for spatial functional data: some recent contributions 

      Delicado, Pedro; Giraldo, Ramón; Comas Rodríguez, Carlos; Mateu, Jorge John Wiley & Sons, Ltd. (2010)
      Functional data analysis (FDA) is a relatively new branch in statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional ...