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Michael Jähnisch, Michael Nussbaum

Asymptotic equivalence for a model of independent non identically distributed observations

It is shown that a nonparametric model of independent non identically distributed observations on the unit interval can be approximated, in the sense of Le Cam´s Δ-distance, by a bivariate Gaussian white noise model. The parameter space is a smoothness class of conditional densities uniformly bounded away from zero on the unit square. The proof is based on coupling of likelihood processes via a functional Hungarian construction of the sequential empirical process and the Kiefer–Müller process.

Statistics & Decisions, Oldenbourg Wissenschaftsverlag

Print ISSN: 0721-2631
Volume: 21, 03/2003
Pages: 197

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