Constraints on cosmological parameters are often distilled from sky surveys
by fitting templates to summary statistics of the data that are motivated by a
fiducial cosmological model. However, recent work has shown how to estimate the
distance scale using templates that are more generic: the basis functions used
are not explicitly tied to any one cosmological model. We describe a Bayesian
framework for (i) determining how many basis functions to use and (ii)
comparing one basis set with another. Our formulation provides intuition into
how (a) one's degree of belief in different basis sets, (b) the fact that the
choice of priors depends on basis set, and (c) the data set itself, together
determine the derived constraints. We illustrate our framework using
measurements in simulated datasets before applying it to real data.

Preprint

Comment: 9 pages, 7 figures, submitted to MNRAS

Subject: Astrophysics - Cosmology and Nongalactic Astrophysics