Prediction error alone may misalign with causal estimator performance across models; study compares OLS, GAMs, XGBoost, and DML-XGBoost in a partially linear model using simulations
Read the original at arxiv.org→arXiv:2609.00071v1 Announce Type: new Abstract: Prediction error is widely used to evaluate nuisance-function estimators in causal inference, but its relationship with causal estimator performance may differ across...
Original headline: "When Prediction Error Is Not Enough: Evaluating Nuisance-Function Prediction for Causal Estimation"
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- Sep 2, 04:00 UTC arXiv cs.AI lead source When Prediction Error Is Not Enough: Evaluating Nuisance-Function Prediction for Causal Estimation