The data analysis problem of coherently searching for unmodeled
gravitational-wave bursts in the data generated by a global network of
gravitational-wave observatories has been at the center of research for almost
two decades. As data from these detectors is starting to be analyzed, a renewed
interest in this problem has been sparked. A Bayesian approach to the problem
of coherently searching for gravitational wave bursts with a network of
ground-based interferometers is here presented. We demonstrate how to
systematically incorporate prior information on the burst signal and its source
into the analysis. This information may range from the very minimal, such as
best-guess durations, bandwidths, or polarization content, to complete prior
knowledge of the signal waveforms and the distribution of sources through
spacetime. We show that this comprehensive Bayesian formulation contains
several previously proposed detection statistics as special limiting cases, and
demonstrate that it outperforms them.Comment: 18 pages, 3 figures, revisions based on referee comment