PS : François Bachoc (Univ. Toulouse) : Valid confidence intervals post-model-selection

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PS : François Bachoc (Univ. Toulouse) : Valid confidence intervals post-model-selection

3 mars 2020 / 11:30 - 12:30

In this talk, I will first introduce the post-model-selection inference setting, that has recently been subject to intensive investigation. In the case of Gaussian linear regression, I will review the post-model-selection confidence intervals suggested by Berk et al (2013). These intervals are meant to cover model-dependent regression coefficients, that depend on the selected set of variables. I will present some personal contributions on an adaptation of these confidence intervals to the case where the targets of inference are linear predictors. Then, I will present an extension of these confidence intervals to non-Gaussian and non-linear settings. The suggested more general intervals will be supported by asymptotic results and numerical comparisons with other intervals recently suggested in the literature.

PS : François Bachoc (Univ. Toulouse) : Valid confidence intervals post-model-selection

Détails

Date :
3 mars 2020
Heure :
11:30 - 12:30
Catégorie d’évènement:

Lieu

Bâtiment Fermat, salle 2107

Organisateurs

Julien Worms
Alexis Devulder