  We present an alternative, Bayesian method for large-scale reconstruction
from observed peculiar velocity data. The method stresses a rigorous treatment
of the random errors and it allows extrapolation into poorly sampled regions in
real space or in k-space. A likelihood analysis is used to determine the
fluctuation power spectrum, followed by a Wiener Filter (WF) analysis to obtain
the minimum-variance mean fields of velocity and mass density. Constrained
Realizations (CR) are then used to sample the statistical scatter about the WF
mean field. The WF/CR method is applied as a demonstration to the Mark III data
with 1200 km/s, 900 km/s, and 500 km/s resolutions. The main reconstructed
structures are consistent with those extracted by the POTENT method. A
comparison with the structures in the distribution of IRAS 1.2Jy galaxies
yields a general agreement. The reconstructed velocity field is decomposed into
its divergent and tidal components relative to a cube of +/-8000 km/s centered
on the Local Group. The divergent component is very similar to the velocity
field predicted from the distribution of IRAS galaxies. The tidal component is
dominated by a bulk flow of 194 +/- 32 km/s towards the general direction of
the Shapley concentration, and it also indicates a significant quadrupole.
