Parametric inference

People with expertise in this area
Research interests

Claudia Di Caterina: Associate Professor

Catia Scricciolo: Associate Professor

Research interests
Topic	People	Description
MSC 62F05 - Asymptotic properties of parametric tests	Claudia Di Caterina	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.
MSC 62F12 - Asymptotic properties of estimators	Claudia Di Caterina	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.
MSC 62F15 - Bayesian inference	Catia Scricciolo	Bayesian theory of function estimation in nonparametric statistical models, including the study of credible sets to provide a data-driven quantification of the uncertainty for point estimators. Analysis also covers inverse problems, such as deconvolution, wherein the object of interest has to be recovered from indirect noisy observations.
MSC 62F25 - Tolerance and confidence regions	Claudia Di Caterina	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.