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Adaptive density estimator for galaxy surveys

Published online by Cambridge University Press:  12 October 2016

Enn Saar
Enn Saar*
Affiliation:
Tartu Observatory, Tõravere, Tartumaa, Estonia email: [email protected] Estonian Academy of Sciences, Kohtu 4, Tallinn, Estonia
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Abstract

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Galaxy number or luminosity density serves as a basis for many structure classification algorithms. Several methods are used to estimate this density. Among them kernel methods have probably the best statistical properties and allow also to estimate the local sample errors of the estimate. We introduce a kernel density estimator with an adaptive data-driven anisotropic kernel, describe its properties and demonstrate the wealth of additional information it gives us about the local properties of the galaxy distribution.

Keywords

Cosmology: large-scale structure of universesurveysgalaxies: statistics
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 11 , Symposium S308: The Zeldovich Universe: Genesis and Growth of the Cosmic Web , June 2014 , pp. 242 - 247
Copyright
Copyright © International Astronomical Union 2016 

References

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