Graphical tests assess whether a function of interest departs from an envelope of functions generated under a simulated null distribution. This approach originated in spatial statistics, but has recently gained some popularity in functional data …
Functional principal component analysis for sparse longitudinal data usually proceeds by first smoothing the covariance surface, and then obtaining an eigendecomposition of the associated covariance operator. Here we consider the use of penalized …
The functional autoregressive (FAR) model belongs to an important class of models for dependent functional data analysis (FDA) and has been investigated intensively in many applications, especially for modeling the autoregressive dynamics of …