The Peculiar Motions of Early-Type Galaxies in Two Distant Regions VI: The Maximum Likelihood Gaussian Algorithm

Abstract

The EFAR project is designed to measure the properties and peculiar motions of early-type galaxies in two distant regions. Here we describe the maximum likelihood algorithm we developed to investigate the correlations between the parameters of the EFAR database. One-, two-, and three-dimensional gaussian models are constructed to determine the mean value and intrinsic spread of the parameters, and the slopes and intrinsic parallel and orthogonal spread of the Mgb'-Mg2, Mg2-sigma, Mgb'-sigma relations, and the Fundamental Plane. In the latter case, the cluster peculiar velocities are also determined. We show that this method is superior to ``canonical'' approaches of least-squares type, which give biased slopes and biased peculiar velocities. We test the algorithm with Monte Carlo simulations of mock EFAR catalogues and derive the systematic and random errors on the estimated parameters. We find that random errors are always dominant. We estimate the influence of systematic errors due to the way clusters were selected and the hard limits and uncertainties in the selection function parameters for the galaxies. We explore the influence of uniform distributions in the Fundamental Plane parameters and the errors. We conclude that the mean peculiar motions of the EFAR clusters can be determined reliably. In particular, the placement of the two EFAR sample regions relative to the Lauer and Postman dipole allows us to strongly constrain the amplitude of the bulk motion in this direction.