Twodimensional goodnessoffit testing in astronomy.
Abstract
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 twodimensional version of the KolmogorovSmirnov 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 distributionfree, and empirical formulae for the confidence levels are given. Secondly, the method of powerspectrum 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 objectiveprism plate of the Virgo Cluster.
 Publication:

Monthly Notices of the Royal Astronomical Society
 Pub Date:
 February 1983
 DOI:
 10.1093/mnras/202.3.615
 Bibcode:
 1983MNRAS.202..615P
 Keywords:

 Astronomy;
 Goodness Of Fit;
 Statistical Distributions;
 Monte Carlo Method;
 Power Spectra;
 Probability Distribution Functions;
 Quasars;
 Sampling;
 Significance;
 Virgo Galactic Cluster;
 Astronomy