Internal Robustness of Growth Rate data
  We perform an Internal Robustness analysis (iR) to a compilation of the most
recent $f\sigma_8(z)$ data, using the framework of 1209.1897. The method
analyzes combinations of subsets in the data set in a Bayesian model comparison
way, potentially finding outliers, subsets of data affected by systematics or
new physics. In order to validate our analysis and assess its sensitivity we
performed several cross-checks, for example by removing some of the data or by
adding artificially contaminated points, while we also generated mock data sets
in order to estimate confidence regions of the iR. Applying this methodology,
we found no anomalous behavior in the $f\sigma_8(z)$ data set, thus validating
its internal robustness.
