  In this paper we present a frequentist-Bayesian hybrid method for estimating
covariances of unfolded distributions using pseudo-experiments. The method is
compared with other covariance estimation methods using the unbiased Rao-Cramer
bound (RCB) and frequentist pseudo-experiments. We show that the unbiased RCB
method diverges from the other two methods when regularization is introduced.
The new hybrid method agrees well with the frequentist pseudo-experiment method
for various amounts of regularization. However, the hybrid method has the added
advantage of not requiring a clear likelihood definition and can be used in
combination with any unfolding algorithm that uses a response matrix to model
the detector response.
