Errors on errors - Estimating cosmological parameter covariance
  Current and forthcoming cosmological data analyses share the challenge of
huge datasets alongside increasingly tight requirements on the precision and
accuracy of extracted cosmological parameters. The community is becoming
increasingly aware that these requirements not only apply to the central values
of parameters but, equally important, also to the error bars. Due to non-linear
effects in the astrophysics, the instrument, and the analysis pipeline, data
covariance matrices are usually not well known a priori and need to be
estimated from the data itself, or from suites of large simulations. In either
case, the finite number of realisations available to determine data covariances
introduces significant biases and additional variance in the errors on
cosmological parameters in a standard likelihood analysis. Here, we review
recent work on quantifying these biases and additional variances and discuss
approaches to remedy these effects.
