Journal Article10.1086/164359
Statistical methods for astronomical data with upper limits. II - Correlation and regression
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TL;DR: In this article, survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.
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Abstract: Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.
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Michele Cappellari,Nicholas Scott,Nicholas Scott,Katherine Alatalo,Leo Blitz,M. Bois,Frédéric Bournaud,Martin Bureau,Alison F. Crocker,Roger L. Davies,Timothy A. Davis,Timothy A. Davis,P. T. de Zeeuw,P. T. de Zeeuw,Pierre-Alain Duc,Eric Emsellem,Eric Emsellem,Eric Emsellem,Sadegh Khochfar,Davor Krajnović,Harald Kuntschner,Richard M. McDermid,Raffaella Morganti,Thorsten Naab,Tom Oosterloo,Marc Sarzi,Paolo Serra,Anne-Marie Weijmans,Lisa M. Young +28 more
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