Provides classes which extend the basic mrpy.core.MRP class.

Adds methods for calculating the likelihood and its derivatives in special cases of interest. Specifically, the two main cases of interest are fitting the MRP to a sample of data (SampleLike) or fitting to a binned (or theoretical) curve.

At this point, the classes here only support the simplest possible cases, in which the effective volume is constant as a function of mass, down to some threshold truncation mass. Furthermore, only data without measurement error is supported at this point.

At this time, we don’t directly support fitting MRP extensions, such as a double-MRP.


expected_likelihood(theta, data_m, data_mf)


CurveLike(logm, data_dndm, logHs, alpha, …) A subclass of mrpy.core.MRP_PO_Likelihood which adds the likelihood (and derivatives) of a model given data in the form of a curve.
SampleLike(logm, logHs, alpha, beta, lnA[, …]) A subclass of mrpy.core.MRP which adds the likelihood (and derivatives) of a model given a sample of masses.
SampleLikeWeights(weights, *args, **kwargs) Compactified version of MRP_PO_Likelihood useful for simulated haloes.