Measuring Uncertainty about Long-Run Predictions

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NEARLY OPTIMAL TESTS WHEN A NUISANCE PARAMETER IS PRESENT UNDER THE NULL HYPOTHESIS (2015, methodology): “For example, the testing problem of Müller and Watson (2013b) involves hypotheses about the covariance matrix of a mean zero multivariate normal, which under the null hypothesis is a function of a high dimensional nuisance parameter δ ∈ D.”