Editorial: Statistics for Functional Data
Computational Statistics & Data Analysis
Testing model assumptions in functional regression models
Journal of Multivariate Analysis
Computational Statistics & Data Analysis
Hi-index | 0.03 |
Modelling of changes in atmospheric radiation within the last decade is considered. First, vertical atmospheric radiation profiles are considered as a sample of functional variables and the dependence on time is estimated by a non-parametric regression (kernel smoothing). As a main result, parametric functional multiplicative regression models are provided. In particular, non-periodic models are motivated in a straightforward way by the observed data, while periodic proposals respect a hypothetical relation between atmospheric radiation and the 11-years solar cycle. Finally, some remarks on computational aspects and the choice of a suitable function space are given.