• closedAccess   Bootstrapping regression models with locally stationary disturbances 

      Ferreira, Guillermo; Mateu, Jorge; Vilar, Jose A.; Muñoz, Joel Springer (2020)
      A linear regression model with errors following a time-varying process is considered.In this class of models, the smoothness condition both in the trend function and inthe correlation structure of the error term ensures ...
    • closedAccess   Heteroskedastic geographically weighted regression model for functional data 

      Romano, Elvira; Mateu, Jorge; Butzbach, O. Elsevier (2020)
      A large number of approaches for modelling spatially dependent functional variables often assume that the functional regression coefficients are constant over the region of interest. However, in many occasions it is far ...
    • closedAccess   Mapping the intensity function of a non-stationary point process in unobserved areas 

      Gabriel, Edith; Rodríguez-Cortés, Francisco Javier; Coville, jerome; Mateu, Jorge; Chadoeuf, Joël Springer (2022)
      Seismic networks provide data that are used as basis both for public safety decisions and for scientific research. Their configuration affects the data completeness, which in turn, critically affects several seismological ...