V. Peña

In this talk, we present differentially private methods for model averaging and selection for normal linear models. The methods are based on mixtures of g-priors. The procedures are asymptotically consistent and straightforward to implement with existing software.

Keywords: Variable selection, Differential Privacy, Bayesian Methods


GT11.BAYES1 Variable Selection
November 7, 2023  4:50 PM
CC1: Audience

Other papers in the same session

Model uncertainty quantification in the presence of missing data

S. Cabras, M. E. Castellanos Nueda, A. Forte Deltell, G. Garcia-Donato, A. Quirós Carretero

Cookie policy

We use cookies in order to be able to identify and authenticate you on the website. They are necessary for the correct functioning of it, and therefore they can not be disabled. If you continue browsing the website, you are agreeing with their acceptance, as well as our Privacy Policy.

Additionally, we use Google Analytics in order to analyze the website traffic. They also use cookies and you can accept or refuse them with the buttons below.

You can read more details about our Cookie Policy and our Privacy Policy.