• Corpus ID: 219179547

Hyperparameter Selection for Subsampling Bootstraps

@article{Ma2020HyperparameterSF,
  title={Hyperparameter Selection for Subsampling Bootstraps},
  author={Yingying Ma and Hansheng Wang},
  journal={arXiv: Methodology},
  year={2020}
}
Massive data analysis becomes increasingly prevalent, subsampling methods like BLB (Bag of Little Bootstraps) serves as powerful tools for assessing the quality of estimators for massive data. However, the performance of the subsampling methods are highly influenced by the selection of tuning parameters ( e.g., the subset size, number of resamples per subset ). In this article we develop a hyperparameter selection methodology, which can be used to select tuning parameters for subsampling… 

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