Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-02T18:50:26.332Z Has data issue: false hasContentIssue false

Adaptive density estimator for galaxy surveys

Published online by Cambridge University Press:  12 October 2016

Enn Saar*
Affiliation:
Tartu Observatory, Tõravere, Tartumaa, Estonia email: [email protected] Estonian Academy of Sciences, Kohtu 4, Tallinn, Estonia
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

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
Copyright
Copyright © International Astronomical Union 2016 

References

Jasche, J. & Wandelt, B. D. 2012, Monthly Notices of the Royal Astronomical Society, 425, 1042 Google Scholar
Kitaura, F.-S., Erdoǧdu, P., Nuza, S. E., Khalatyan, A., Angulo, R. E., Hoffman, Y., & Gottlöber, S. 2012, Monthly Notices of the Royal Astronomical Society, 427, L35 Google Scholar
Silverman, B. W. 1986, Density Estimation for Statistics and Data Analysis. Chapman & Hall, London Google Scholar
Kopp, J. 2008, International Journal of Modern Physics C, 19, 523 Google Scholar
Tempel, E., Tago, E.,& Liivamägi, L. J. 2012, Astronomy and Astrophysics, 540, A106 Google Scholar