  A test of a new Bayesian approach to solar flare prediction (Wheatland 2004a)
is presented. The approach uses the past history of flaring together with
phenomenological rules of flare statistics to make a prediction for the
probability of occurrence of a large flare within an interval of time, or to
refine an initial prediction (which may incorporate other information). The
test of the method is based on data from the Geostationary Observational
Environmental Satellites (GOES), and involves whole-Sun prediction of soft
X-ray flares for 1976-2003. The results show that the method somewhat
over-predicts the probability of all events above a moderate size, but performs
well in predicting large events.
