activity
20202025
most citedThe shapes of an epidemic: using Functional Data Analysis to characterize COVID-19 in Italy

46 citations · 77 across the 10 of their papers we have counts for

collaborators

10 papers

stat.ME2025

Towards Efficient Inference under Nonmonotone Missingness with General Imputation

Qi Xu, Lorenzo Testa, Jing Lei +1

Missing data are ubiquitous in classical survey and longitudinal studies as well as modern multi-modality data analysis. A longstanding challenge arises under nonmonotone missingne…

stat.ME2025

Rescuing double robustness: safe estimation under complete misspecification

Lorenzo Testa, Francesca Chiaromonte, Kathryn Roeder

Double robustness is a major selling point of semiparametric and missing data methodology. Its virtues lie in protection against partial nuisance misspecification and asymptotic se…

math.ST2025

Semiparametric semi-supervised learning for general targets under distribution shift and decaying overlap

Lorenzo Testa, Qi Xu, Jing Lei +1

In modern scientific applications, large volumes of covariate data are readily available, while outcome labels are costly, sparse, and often subject to distribution shift. This asy…

stat.ME2025★ 2 cited

Doubly-Robust Functional Average Treatment Effect Estimation

Lorenzo Testa, Tobia Boschi, Francesca Chiaromonte +2

Understanding causal relationships in the presence of complex, structured data remains a central challenge in modern statistics and science in general. While traditional causal inf…

econ.GN2023★ 17 cited

A unified repository for pre-processed climate data weighted by gridded economic activity

Marco Gortan, Lorenzo Testa, Giorgio Fagiolo +1

Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activi…

stat.AP2023

Contrasting pre-vaccine COVID-19 waves in Italy through Functional Data Analysis

Tobia Boschi, Jacopo Di Iorio, Lorenzo Testa +2

We use data from 107 Italian provinces to characterize and compare mortality patterns in the first two COVID-19 epidemic waves, which occurred prior to the introduction of vaccines…

stat.ME2023★ 6 cited

FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions

Tobia Boschi, Lorenzo Testa, Francesca Chiaromonte +1

Functional regression analysis is an established tool for many contemporary scientific applications. Regression problems involving large and complex data sets are ubiquitous, and f…

stat.AP2022★ 5 cited

Venture Capital investments through the lens of Network and Functional Data Analysis

Christian Esposito, Marco Gortan, Lorenzo Testa +4

In this paper we characterize the performance of venture capital-backed firms based on their ability to attract investment. The aim of the study is to identify relevant predictors…

cs.SI2021★ 1 cited

Can you always reap what you sow? Network and functional data analysis of VC investments in health-tech companies

Christian Esposito, Marco Gortan, Lorenzo Testa +4

"Success" of firms in venture capital markets is hard to define, and its determinants are still poorly understood. We build a bipartite network of investors and firms in the health…

stat.AP2020★ 46 cited

The shapes of an epidemic: using Functional Data Analysis to characterize COVID-19 in Italy

Tobia Boschi, Jacopo Di Iorio, Lorenzo Testa +2

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