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rbbnp:A Bias Bound Approach to Non-Parametric Inference
A novel bias-bound approach for non-parametric inference is introduced, focusing on both density and conditional expectation estimation. It constructs valid confidence intervals that account for the presence of a non-negligible bias and thus make it possible to perform inference with optimal mean squared error minimizing bandwidths. This package is based on Schennach (2020) <doi:10.1093/restud/rdz065>.
Maintained by Xinyu DAI. Last updated 8 days ago.
1.70 score