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Adaptive density estimator for galaxy surveys
Published online by Cambridge University Press: 12 October 2016
Abstract
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.
- 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