Title: Simulated switched Z-estimation for accurate finite sample inference
Authors: Samuel Orso - University of Geneva (Switzerland) [presenting]
Maria-Pia Victoria-Feser - University of Geneva (Switzerland)
Stephane Guerrier - University of Geneva (Switzerland)
Mucyo Karemera - University of Geneva (Switzerland)
Abstract: Constructing tests or confidence regions that control over the error rates in the long-run is probably one of the most important problem in statistics. Yet, the theoretical justification for most methods in statistics is asymptotic. The bootstrap for example, despite its simplicity and its widespread usage, is an asymptotic method. There is, in general, no claim about the exactness of inferential procedures in finite sample. We propose an alternative to the parametric bootstrap. We set up general conditions to demonstrate theoretically that accurate inference can be claimed in finite sample.