Mathematical Sciences: Multivariate and Censored Data Analysis Methods for Astronomy

This project continues collaborative research between astronomers and statisticians with the objective of developing specifically useful statistical procedures for the analysis of multivariate data sets that arise in observational astronomy. It addresses the statistical problems of estimation of a bivariate distribution function under random censoring, censored regression, testing for multivariate normality under random censoring and a new analysis for statistical independence. Statistical analysis can elucidate astrophysical processes which are detectable only from data obtained from a sample of celestial objects. Using modern statistical theory and methodology, some of the obscuring distortions which are inevitable in such data can be 'removed' to make the most physically meaningful relations more apparent. For example, the relations between luminosity, size, rotation and metallicity in elliptical galaxies can be examined and described. This collaborative research focuses on the development of new methods that carry the potential for major advances in both statistics and astronomy.