Claudia Di Caterina

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fotoCDC, August 26, 2024
Position
Associate Professor
Academic sector
STAT-01/A - Statistics
Research sector (ERC-2024)
PE1_15 - Generic statistical methodology and modelling

PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Office
Polo Santa Marta,  Floor 1,  Room 1.22
Telephone
0458028247
E-mail
claudia|dicaterina*univr|it <== Replace | with . and * with @ to have the right email address.
Personal web page
https://claudiadicaterina.weebly.com

Office Hours

Office hours available by appointment on Zoom or in presence.

Curriculum

Associate professor in Statistics since March 2025, she arrived at the University of Verona as temporary assistant professor in October 2021. She was awarded a PhD in Statistical Sciences from the University of Padova and visited for research periods the statistical departments of University College London and University of Toronto. In the area of methodological statistics, she is particularly interested in likelihood asymptotics, pseudo-likelihoods, anytime-valid inference and bias reduction techniques.

Di seguito sono elencati gli eventi e gli insegnamenti di Terza Missione collegati al docente:

  • Eventi di Terza Missione: eventi di Public Engagement e Formazione Continua.
  • Insegnamenti di Terza Missione: insegnamenti che fanno parte di Corsi di Studio come Corsi di formazione continua, Corsi di perfezionamento e aggiornamento professionale, Corsi di perfezionamento, Master e Scuole di specializzazione.
Research interests
Topic Description Research area
MSC 62F05 - Asymptotic properties of parametric tests Study of the behaviour (size and power) in large samples of parametric tests based on the likelihood function or on pseudo-likelihoods, including settings with many nuisance parameters and/or other irregularity conditions. Quantitative Methods for Economics
Parametric inference
MSC 62F12 - Asymptotic properties of estimators Study of the behaviour (consistency, bias, efficiency) in large samples of parametric estimators based on the likelihood function or on pseudo-likelihoods, including settings with many nuisance parameters and/or other irregularity conditions. Quantitative Methods for Economics
Parametric inference
MSC 62F25 - Tolerance and confidence regions This research area includes the development of so-called anytime-valid confidence sequences for unknown parameters in particular modelling frameworks, as opposed to the usual confidence regions valid only for a fixed sample size. Such confidence sequences guarantee a high coverage probability for the true parameter value even under optional stopping of the experiment and arbitrary enlargement of the sample. Quantitative Methods for Economics
Parametric inference
MSC 62H12 - Estimation Estimation and hypotesis testing procedures based on the likelihood function or on pseudo-likelihoods in the presence of high-dimensional data having a potentially complex distribution. Quantitative Methods for Economics
Multivariate analysis


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