[Statlist] Next talk: Friday, November 18, 2011 with Davy Paindaveine, Universität Brüssel
Cecilia Rey
rey at stat.math.ethz.ch
Thu Nov 10 11:56:28 CET 2011
Hello Susan
An statlist at stat.math.ethz.ch senden am Montag
bitte mit einem cc auch noch an Torsten.Hothorn at stat.uni-muenchen.de.
Er ist zurzeit in Zürich.
Liebe Grüsse
Cecilia
ETH and University of Zurich
Proff. P. Buehlmann - L. Held - H.R. Kuensch -
M. Maathuis - S. van de Geer - M. Wolf
***********************************************************
We are glad to announce the following talk
Friday, November 18, 2011, 15.15h, HG G 19.1
********************************************************
by Davy Paindaveine, Universität Brüssel
Titel:
Semiparametrically Efficient Inference Based On Signed Ranks In
Symmetric Independent Component Models
Abstract:
We consider semiparametric location-scatter models for which the p-
variate observation is obtained as X = ÎZ + μ, where μ is a p-
vector, Πis a full-rank p à p matrix, and the (unobserved) random p-
vector Z has marginals that are centered and mutually independent but
are otherwise unspecified. As in blind source separation and
independent component analysis (ICA), the parameter of interest
throughout the paper is Î. On the basis of n i.i.d. copies of X, we
develop, under a symmetry assumption on Z, signed-rank one-sample
testing and estimation procedures for Î. We exploit the uniform local
and asymptotic normality (ULAN) of the model to define signed-rank
procedures that are semiparametrically efficient under correctly
specified densities. Yet, as usual in rank-based inference, the
proposed procedures remain valid (correct asymptotic size under the
null, for hypothesis testing, and root-n consistency, for point
estimation) under a very broad range of densities. We derive the
asymptotic properties of the proposed procedures and investigate
their finite-sample behavior through simulations.
The abstract is also to be found here: http://stat.ethz.ch/events/research_seminar
[[alternative HTML version deleted]]
More information about the Statlist
mailing list