Relatore
Elvezio Ronchetti
Research Center for Statistics
and Geneva School of Economics and Management University of Geneva, Switzerland
Elvezio.Ronchetti@unige.ch
http://www.unige.ch/ses/metri/ronchetti/
Abstract
Robust statistics deals with deviations from ideal models and develops statistical procedures which are still reliable and reasonably efficient in a small neighborhood of the model.
We first review some fundamental ideas developed in robust statistics which can be used to construct robust statistical procedures in fairly general settings.
We then adapt these ideas to filtering methods, which are powerful tools to estimate the hidden state of a state-space model, by defining a concept of robustness for a filter and by proposing robust filters which provide accurate state and parameter inference in the presence of model misspecifications.
Joint work with L. Calvet and V. Czellar.
Organizzatori
Giuseppe Cavaliere
Alessandra Luati