A hacking day of Mathematics for Data Science at the Department of Mathematics

# Alessia Caponera

Department of Mathematics
University of Rome Tor Vergata
Bio My name is Alessia Caponera and I am currently a Postdoctoral Researcher at the Department of Mathematics, University of Rome Tor Vergata, in the research team of Prof. Domenico Marinucci. I received my Ph.D. in Statistics from the Department of Statistical Sciences, Sapienza University of Rome, in February 2020 I am also an elected member of the board (2018-2020) of the young group (y−SIS, youngsis.github.io) of the Italian Statistical Society. My main research interests are space-time spherical random fields and related topics, such as spectral representations, spherical wavelets and needlets, functional time-series analysis on the sphere.

## Syllabus

In recent years, time-varying spherical random fields are naturally becoming an important tool, especially for applications in Climate and Atmospheric Sciences, Cosmology and Astrophysics. Here, we focus on the class of spherical functional autoregressions, which can be interpreted as a functional extension to the sphere of the well-known real-valued autoregressive processes, and we discuss two estimation procedures for the corresponding autoregressive kernels. The former is based on a functional $L^2$-minimisation criterion, the latter on its penalised version, leading to a LASSO-type estimator. We present some asymptotic results and concentration bounds. Then, we compare their performances through simulations.

## References

• Caponera, A., Marinucci, D. (2020+) Asymptotics for spherical functional autoregressions. Annals of Statistics. In press. arXiv:1907.05802
• Caponera, A., Durastanti, C., Vidotto, A. (2019) LASSO estimation for spherical autoregressive processes. arXiv preprint. Submitted for publication. arXiv:1911.11470

## Schedule

• 26 June 2020, 10:00-12:00

## Details

• Poster: PDF
• The participation is free, however a notification by email to Prof. Claudio Agostinelli is mandatory