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stat.CO2023
Posterior Uncertainty Estimation via a Monte Carlo Procedure Specialized for Data Assimilation
Michael Stanley, Mikael Kuusela, Brendan Byrne +1
Through the Bayesian lens of data assimilation, uncertainty on model parameters is traditionally quantified through the posterior covariance matrix. However, in modern settings inv…
math.ST2023
Optimization-based frequentist confidence intervals for functionals in constrained inverse problems: Resolving the Burrus conjecture
Pau Batlle, Pratik Patil, Michael Stanley +2
We present an optimization-based framework to construct confidence intervals for functionals in constrained inverse problems, ensuring valid one-at-a-time frequentist coverage guar…