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We describe a novel method for determining the demographics of a populationof star clusters, for example distributions of cluster mass and age, fromunresolved photometry. This method has a number of desirable properties: itfully exploits all the information available in a data set without any binning,correctly accounts for both measurement error and sample incompleteness,naturally handles heterogenous data (for example fields that have been imagedwith different sets of filters or to different depths), marginalises overuncertain extinctions, and returns the full posterior distributions of theparameters describing star cluster demographics. We demonstrate the methodusing mock star cluster catalogs and show that our method is robust andaccurate, and that it can recover the demographics of star cluster populationssignificantly better than traditional fitting methods. For realistic samplesizes, our method is sufficiently powerful that its accuracy is ultimatelylimited by the accuracy of the underlying physical models for stellar evolutionand interstellar dust, rather than by statistical uncertainties. Our method isimplemented as part of the Stochastically Lighting Up Galaxies (SLUG) stellarpopulations code, and is freely available.

SLUG IV: A Novel Forward-Modelling Method to Derive the Demographics of Star Clusters