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Refitted cross-validation estimation for high-dimensional subsamples from low-dimension full data | Synapse
March 3, 2026
Refitted cross-validation estimation for high-dimensional subsamples from low-dimension full data
HZ
Haixiang Zhang
HW
HaiYing Wang
Puntos clave
Optimized estimation improves accuracy for high-dimensional datasets and subsamples, enhancing predictive modeling.
Key evidence includes a reduction in estimation error metrics, supporting the approach's effectiveness.
Cross-validation techniques refine estimation methods within high-dimensional spaces across various datasets.
Highlights the need for improved estimations, especially in high-dimensional statistical modeling.
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Zhang et al. (Tue,) studied this question.
synapsesocial.com/papers/69a75b67c6e9836116a22ac9
https://doi.org/https://doi.org/10.1007/s00180-025-01702-6
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