Interpreting the distance correlation results for the COMBO-17 survey

• Verfasst von: Richards, Mercedes [VerfasserIn]
• Verfasst von: Richards, Donald [VerfasserIn]
• Verfasst von: Martínez-Gómez, Elizabeth [VerfasserIn]
• Titel: Interpreting the distance correlation results for the COMBO-17 survey
• Verf.angabe: Mercedes T. Richards, Donald St.P. Richards, and Elizabeth Martínez-Gómez
• E-Jahr: 2014
• Jahr: 2014 March 19
• Fussnoten: Gesehen am 08.09.2020
• Titel Quelle: Enthalten in: The astrophysical journal / 2
• Ort Quelle: London : Institute of Physics Publ., 1995
• Jahr Quelle: 2014
• Band/Heft Quelle: 784(2014,2) Artikel-Nummer L34, 5 Seiten
• ISSN Quelle: 2041-8213
• DOI: doi:10.1088/2041-8205/784/2/L34
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1729084265

Abstract

The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be enhanced through as new statistical measure of association and correlation, called the distance correlation coefficient, which has more statistical power to detect associations than does the classical Pearson measure of linear relationships between two variables. The distance correlation measure offers a more precise alternative to the classical measure since it is capable of detecting nonlinear relationships that may appear in astrophysical applications. We showed recently that the comparison between the distance and Pearson correlation coefficients can be used effectively to isolate potential outliers in various galaxy data sets, and this comparison has the ability to confirm the level of accuracy associated with the data. In this work, we elucidate the advantages of distance correlation when applied to large databases.