




























The present paper establishes convolution theorems for regular estimators when the limit experiment is non-Gaussian or of infnite dimension with sparse parameter space. Applications are given for Gaussian shift experiments of infnite dimension, the Brownian motion signal plus noise model, Levy processes which are observed at discrete times and estimators of the endpoints of densities with jumps. The method of proof is also of interest for the classical convolution theorem of Hajek and Le Cam. As technical tool we present an elementary approach for the comparison of limit experiments on standard Borel spaces.
此内容由惯性聚合(RSS阅读器)自动聚合整理,仅供阅读参考。 原文来自 — 版权归原作者所有。