Detail

On conditional moments of high-dimensional random vectors given lower-dimensional projections

Author(s)
Lukas Steinberger, Hannes Leeb
Abstract

One of the most widely used properties of the multivariate Gaussian distribution, besides its tail behavior, is the fact that conditional means are linear and that conditional variances are constant. We here show that this property is also shared, in an approximate sense, by a large class of non-Gaussian distributions. We allow for several conditioning variables and we provide explicit non-asymptotic results, whereby we extend earlier findings of Hall and Li (Ann. Statist. 21 (1993) 867-889) and Leeb (Ann. Statist. 41 (2013) 464-483).

Organisation(s)
Department of Statistics and Operations Research, Research Network Data Science
Journal
Bernoulli: a journal of mathematical statistics and probability
Volume
24
Pages
565–591
No. of pages
27
ISSN
1350-7265
DOI
https://doi.org/10.3150/16-BEJ888
Publication date
02-2018
Peer reviewed
Yes
Austrian Fields of Science 2012
101018 Statistics
Keywords
ASJC Scopus subject areas
Statistics and Probability
Portal url
https://ucrisportal.univie.ac.at/en/publications/553a308c-256a-47eb-bd79-a12f77496d69