Adaptive non-asymptotic confidence balls in density estimation

It is widely recognized that an interdependent network of cytokines, including interleukin-1 (IL-1) and tumour necrosis factor alpha (TNF α), plays a primary role in mediating

The aim of this section is twofold: first, explain the basic ideas of our approach and second, in the ideal case where the variance σ 2 is known, build a confidence ball for f

for this purpose is particularly attractive, as it makes it possible to obtain exact, non- asymptotic confidence regions under relatively mild assumptions on the noise distribution..

Section 3 shows how interval analysis can be used to characterize the exact confidence regions provided by LSCR in a global and guaranteed way.. Examples are treated in Section 4,

D’après les résultats de la présente étude, la feuille de prescription (problèmes de lisibilité, paramètres de prescription non spécifiés, absence de

Various estimation proedures based on l 1 penalization (exemplied by the Dantzig proedure in [13℄ and the LASSO proedure in [28℄) have extensively been studied reently..

Keywords: Nonparametric estimation, model selection, relative density, two-sample problem.. AMS Subject Classification 2010: 62G05;

A note on the adaptive estimation of a bi-dimensional density in the case of knowledge of the copula density.. Ingo Bulla, Christophe Chesneau, Fabien Navarro,