Two-dimensional goodness-of-fit testing in astronomy

作者：John A. Peacock · 发表于：Monthly Notices of the Royal Astronomical Society · 年份：1983 · DOI：10.1093/mnras/202.3.615 · 被引用次数：681 · 研究领域：Statistical and numerical algorithms、Advanced Statistical Methods and Models、Diverse Scientific and Engineering Research

This paper deals with the techniques available to test for consistency between the empirical distribution of data points on a plane and a hypothetical density law. Two new statistical tests are developed. The first is a two-dimensional version of the Kolmogorov–Smirnov test, for which the distribution of the test statistic is investigated using a Monte Carlo method. This test is found in practice to be very nearly distribution-free, and empirical formulae for the confidence levels are given. Secondly, the method of power-spectrum analysis is extended to deal with cases in which the null hypothesis is not a uniform distribution. These methods are illustrated by application to the distribution of quasar candidates found on an objective-prism plate of the Virgo Cluster.