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The joint likelihood is a simple extension of the standard likelihoodformalism that enables the estimation of common parameters across disjointdatasets. Joining the likelihood, rather than the data itself, means nuisanceparameters can be dealt with independently. Application of this technique,particularly to Fermi-LAT dwarf spheroidal analyses, has already been met withgreat success. We present a description of the method's general implementationalong with a toy Monte-Carlo study of its properties and limitations.

Using Likelihood for Combined Data Set Analysis