Frequentist-Bayes Hybrid Covariance Estimationfor Unfolding Problems

Pim Jordi Verschuuren

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arXiv · 2110.09382

Frequentist-Bayes Hybrid Covariance Estimationfor Unfolding Problems

Pim Jordi Verschuuren

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Abstract

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.

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Pim Jordi Verschuuren. 2021-10-15. Frequentist-Bayes Hybrid Covariance Estimationfor Unfolding Problems. https://arxiv.org/abs/2110.09382

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