Measuring HighOrder Moments of the Galaxy Distribution from Counts in Cells: The Edgeworth Approximation
Abstract
To probe the weakly nonlinear regime, past the point where simple linear theory is sufficient to describe the statistics of the density distribution, we measure the skewness (S_{3}) and kurtosis (S_{4}) of the count probability distribution function (CPDF) of the IRAS 1.2 Jy sample obtained from counts in cells. These quantities are free parameters in a maximum likelihood fit of an Edgeworth expansion convolved with a Poissonian to the observed CPDF. This method, applicable on scales >~5 h^{1} Mpc, is appreciably less sensitive to the tail of the distribution than are measurements of S_{3} and S_{4} from moments of the CPDF. We measure S_{3} and S_{4} to l ~ 50 h^{1} Mpc; the data are consistent with scale invariance, yielding averages of <S_{3}> = 2.83 +/ 0.09 and <S_{4}> = 6.89 +/ 0.68. These values are higher than those found by Bouchet et al. in 1993 (<S_{3}> = 1.5 +/ 0.5 and <S_{4}> = 4.4 +/ 3.7) using the moments method on the same data set, owing to lack of correction for finitevolume effects in the latter work. Unlike the moments method, our results are quite robust to the fact that IRAS galaxies are underrepresented in cluster cores. We use Nbody simulations to show that our method yields unbiased results.
 Publication:

The Astrophysical Journal
 Pub Date:
 January 1998
 DOI:
 10.1086/305095
 Bibcode:
 1998ApJ...493...39K
 Keywords:

 GALAXIES: CLUSTERS: GENERAL;
 GALAXIES: STATISTICS;
 INFRARED: GALAXIES;
 COSMOLOGY: LARGESCALE STRUCTURE OF UNIVERSE;
 METHODS: NUMERICAL;
 Galaxies: Clusters: General;
 Galaxies: Statistics;
 Infrared: Galaxies;
 Cosmology: LargeScale Structure of Universe;
 Methods: Numerical