Ricerc@Sapienza

When functional data are observed over a domain that is subject-specific, most of the techniques for functional data analysis are invalidated. Recently, new methods able to handle this situation were developed and in particular we focus on well-known functional PCA. With the aim of classifying the Aneurisk65 dataset, we apply a few possible methods and we show that carrying out the analysis over the full domain, where at least one of the functional data is observed, may not be the optimal choice.

Functional data are usually assumed to be observed on a common domain. However, it is often the case that some portion of the functional data is missing for some statistical unit, invalidating most of the existing techniques for functional data analysis. The development of methods able to handle partially observed or incomplete functional data is currently attracting increasing interest. We here briefly review this literature.