Detection of Covered Substructures in Multidimensional Parameter Space

An Application for the DENIS Survey
  • C. Kienel
  • S. Kimeswenger
Conference paper
Part of the Astrophysics and Space Science Library book series (ASSL, volume 210)

Abstract

Many algorithms concerning the separation or detection of components are based on two statistical methods: The Kernel Method (De Jager et al. 1986) or the Likelihood Statistic (Sutherland & Saunders 1992). All these standard methods have one or more restrictions (e.g. known number of groups or differentiability of the components). This paper presents a short introduction to a new algorithm, which works without any mathematical restriction concerning the dataset. An example with an artificial dataset has already been presented (Kienel & Kimeswenger 1995). In this paper we will present preliminary results worked out with colour-colour diagrams of IRAS sources.

References

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • C. Kienel
    • 1
  • S. Kimeswenger
    • 1
  1. 1.Institute of AstronomyUniversity of InnsbruckInnsbruckÖsterreich

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