Computer Science – Numerical Analysis
Scientific paper
May 1978
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1978a%26a....65..313s&link_type=abstract
Astronomy and Astrophysics, vol. 65, no. 3, May 1978, p. 313-321. Research supported by the Schweizerischer Nationalfonds zur F
Computer Science
Numerical Analysis
21
Numerical Analysis, Space Density, Star Distribution, Statistical Tests, Eddington Approximation, Galactic Structure, Least Squares Method, Matrices (Mathematics), Monte Carlo Method, Spiral Galaxies, Stellar Luminosity, Stellar Magnitude
Scientific paper
The problem of deriving stellar space densities for stars with a Gaussian luminosity function has put forth several numerical methods for solving the fundamental equation of stellar statistics. In this paper four different methods of deriving stellar space densities are statistically tested and compared by means of realistic computer generated space distributions. The major test results can be summarized as follows: (1) the methods which are tested here are not capable of giving correct density values of shortly extended relative maxima or minima of the density function (spiral arms), and (2) if the density function has a constant gradient, there is strong evidence that the Monte Carlo method (Gschwind, 1974) yields the best density values as well as the smallest mean errors.
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