  The advanced world-wide network of gravitational waves (GW) observatories is
scheduled to begin operations within the current decade. Thanks to their
improved sensitivity, they promise to yield a number of detections and thus to
open a new observational windows for astronomy and astrophysics. Among the
scientific goals that should be achieved, there is the independent measurement
of the value of the cosmological parameters, hence an independent test of the
current cosmological paradigm. Due to the importance of such task, a number of
studies have evaluated the capabilities of GW telescopes in this respect.
However, since GW do not yield information about the source redshift, different
groups have made different assumptions regarding the means through which the GW
redshift can be obtained. These different assumptions imply also different
methodologies to solve this inference problem. This work presents a formalism
based on Bayesian inference developed to facilitate the inclusion of all
assumptions and prior information about a GW source within a single data
analysis framework. This approach guarantees the minimisation of information
loss and the possibility of including naturally event-specific knowledge (such
as the sky position for a Gamma Ray Burst - GW coincident observation) in the
analysis. The workings of the method are applied to a specific example, loosely
designed along the lines of the method proposed by Schutz in 1986, in which one
uses information from wide-field galaxy surveys as prior information for the
location of a GW source. I show that combining the results from few tens of
observations from a network of advanced interferometers will constrain the
Hubble constant $H_0$ to an accuracy of $\sim 4 - 5$% at 95% confidence.
