sketching - Sketching of Data via Random Subspace Embeddings
Construct sketches of data via random subspace embeddings. For more details, see the following papers. Lee, S. and Ng, S. (2022). "Least Squares Estimation Using Sketched Data with Heteroskedastic Errors," Proceedings of the 39th International Conference on Machine Learning (ICML22), 162:12498-12520. Lee, S. and Ng, S. (2020). "An Econometric Perspective on Algorithmic Subsampling," Annual Review of Economics, 12(1): 45–80.
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heteroskedasticityregressionsubspace-embeddingcpp
4.54 score 7 stars 8 scripts 237 downloadsATbounds - Bounding Treatment Effects by Limited Information Pooling
Estimation and inference methods for bounding average treatment effects (on the treated) that are valid under an unconfoundedness assumption. The bounds are designed to be robust in challenging situations, for example, when the conditioning variables take on a large number of different values in the observed sample, or when the overlap condition is violated. This robustness is achieved by only using limited "pooling" of information across observations. For more details, see the paper by Lee and Weidner, "Bounding Treatment Effects by Pooling Limited Information across Observations," forthcoming at the Journal of Econometrics, <doi:10.48550/arXiv.2111.05243>.
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causal-inferencelack-of-overlaplimited-overlappartial-identificationtreatment-effectsunconfoundedness-assumption
4.22 score 3 stars 11 scripts 373 downloads