Researchers have introduced a new statistical method called Targeted Highly Adaptive Lasso (Targeted HAL) for estimating non-pathwise differentiable functional parameters, such as dose-response curves. This method utilizes spline basis functions and a LASSO step to approximate the target function, aiming for improved accuracy and data-adaptive inference. Simulations indicate that Targeted HAL outperforms existing HAL plug-in estimators in terms of bias and mean squared error, offering a flexible approach without requiring parametric assumptions. AI
IMPACT Introduces a novel statistical technique that could enhance machine learning model accuracy and data-driven inference.
RANK_REASON The cluster contains two identical arXiv preprints detailing a new statistical methodology.
- Highly Adaptive Lasso (HAL)
- Hugging Face
- lasso
- maximum likelihood estimation
- Targeted HAL-MLE
- Targeted Highly Adaptive Lasso
- alphaXiv
- arXiv
- CatalyzeX Code Finder for Papers
- DagsHub
- Gotit.pub
- ScienceCast
- spline basis functions
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