Doubly Robust Adaptive Conformal Inference for Causal Effects Under Temporal Dependence
arXiv:2606.305003.9
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Provides a practical solution for causal inference in time series data with temporal dependence, addressing a gap in existing conformal inference methods.
The paper proposes DR-ACI, a method for constructing prediction intervals for causal effects under temporal dependence, achieving valid coverage in non-stationary time series settings.
We propose doubly robust adaptive conformal inference (DR-ACI), which constructs prediction intervals for doubly robust pseudo-outcomes under temporal dependence.