Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
arXiv:2008.03288v119 citations
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This is an incremental rejoinder to discussions on a statistical methodology paper.
The paper addresses the problem of testing confidence interval coverage for causal parameters estimated by machine learning, responding to discussions on a previously published work.
This is the rejoinder to the discussion by Kennedy, Balakrishnan and Wasserman on the paper "On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning" published in Statistical Science.