A Reduction Paradigm for Multivariate Laws

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4403 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4403 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4403 archive 351 disk0/00/00/52/76 2016-01-15 02:09:07 2021-08-27 17:16:08 2016-01-15 02:09:07 monograph show 2 Chiaromonte F. 1597 A Reduction Paradigm for Multivariate Laws pub iis_ecn iis_inn iis_mnt prog_ted A "reduction paradigm" is a theoretical framework which provides a definition of structures for multivariate laws, and allows to simplify their representation and statistical analysis. The main idea is to decompose a law as the superimposition of a "structural term" and a "noise," so that the latter can be neglected "without loss of information on the structure." When the lower structural term is supported by a lower-dimensional affine subspace, an "exhaustive dimension reduction" is achieved. We describe the reduction paradigm that results from selecting white noises, and convolution as superposition mechanism. 1997-03 published IR-97-015 IR-97-015 1185 public interim_report IIASA, Laxenburg, Austria 14 FALSE info:eu-repo/semantics/book