  The study of compact binary in-spirals and mergers with gravitational wave
observatories amounts to optimizing a theoretical description of the data to
best reproduce the true detector output. While most of the research effort in
gravitational wave data modeling focuses on the gravitational wave- forms
themselves, here we will begin to improve our model of the instrument noise by
introducing parameters which allow us to determine the background instrumental
power spectrum while simul- taneously characterizing the astrophysical signal.
We use data from the fifth LIGO science run and simulated gravitational wave
signals to demonstrate how the introduction of noise parameters results in
resilience of the signal characterization to variations in an initial
estimation of the noise power spectral density. We find substantial improvement
in the consistency of Bayes factor calculations when we are able to marginalize
over uncertainty in the instrument noise level.
