Functional data analysis (FDA) is a statistical framework that allows for the analysis of
curves, images, or functions on higher dimensional domains. The goals of FDA, such as …

We investigate patterns of COVID-19 mortality across 20 Italian regions and their association
with mobility, positivity, and socio-demographic, infrastructural and environmental …

Emerging technologies generate data sets of increased size and complexity that require
new or updated statistical inferential methods and scalable, reproducible software. These …

Wearable data is a rich source of information that can provide a deeper understanding of
links between human behaviors and human health. Existing modelling approaches use …

We study additive function-on-function regression where the mean response at a particular
time point depends on the time point itself, as well as the entire covariate trajectory. We …

The exponential mechanism is a fundamental tool of Differential Privacy (DP) due to its
strong privacy guarantees and flexibility. We study its extension to settings with summaries …

In the automotive industry, quality assessment of resistance spot welding (RSW) joints of
metal sheets is typically based on costly and lengthy offline tests, which are unfeasible in the …

Increasingly, large, nationally representative health and behavioral surveys conducted
under a multistage stratified sampling scheme collect high dimensional data with correlation …

We propose a novel method for estimating population-level and subject-specific effects of
covariates on the variability of functional data. We extend the functional principal …

With advancements in technology and data storage, the availability of functional data whose
sample observations are recorded over a continuum, such as time, wavelength, space grids …