Multivariate Separation of Cosmic Components

Details Multivariate Separation of Cosmic Components Multivariate Separation of Cosmic Components

Jan 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003cokon.103....5b&link_type=abstract

Communications of the Konkoly Observatory, Hungary Proceedings of the conference: 'The interaction of stars with their environme

Statistics

Scientific paper

Observing and storing the photons of the incoming radiation from the Cosmos typically give a data cube defined by (α, δ, λ). It is easy to translate this data structure into the formalism of multivariate statistics. A common problem in the multivariate statistics is whether the stochastic variables described by observed properties are statistically independent or can be described by a less number of hidden variables. This is the task of factor analysis. Forming groups from cases having similar properties according to the measures of similarities or the distances is the task of cluster analysis. We demonstrated in three cases how these technics can be used for separating physically independent cosmic components projected onto the same celestial area by chance.

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