  We have implemented likelihood testing of the performance of an optimal
filter within the online analysis of AURIGA, a sub-Kelvin resonant-bar
gravitational wave detector. We demonstrate the effectiveness of this technique
in discriminating between impulsive mechanical excitations of the resonant-bar
and other spurious excitations. This technique also ensures the accuracy of the
estimated parameters such as the signal-to-noise ratio. The efficiency of the
technique to deal with non-stationary noise and its application to data from a
network of detectors are also discussed.
