A bivariate densities can be represented as a density level set containing a fixed amount of probability (0.75, for instance). Then a functional dataset where the observations are bivariate density functions can be analyzed ...

The paper under discussion is a very well-written and interesting piece of work by Secchi et al. (2015) dealing with spatio-temporal data on mobile phone use in the area of Milan. I congratulate the authors for such a ...

The problem of nonparametrically predicting a scalar response variable from a functional predictor is considered. A sample of pairs (functional predictor and response) is observed. When predicting the response for a new ...

Wildfires have become one of the biggest natural hazards for environments worldwide. The effects of wildfires are heterogeneous, meaning that the magnitude of their effects depends on many factors such as geographical ...

We present a methodology to perform spatial prediction when measured data are curves. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization ...