This package can find the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a MF (P=1), a mass-size distribution (P=2) or the mass-spin-morphology distribution (P=3). Unlike most common fitting approaches, this method accurately accounts for measurement is uncertainties and complex selection functions. A full description of the algorithm can be found in Obreschkow et al. (2017).
|Maintainer||Danail Obreschkow <[email protected]>|
|Package repository||View on GitHub|
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