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Post-Selection Inference
Annual Review of Statistics and Its Application ( IF 7.4 ) Pub Date : 2022-03-07 , DOI: 10.1146/annurev-statistics-100421-044639 Arun K. Kuchibhotla 1 , John E. Kolassa 2 , Todd A. Kuffner 3
中文翻译：
选择后推理
更新日期：2022-03-07
Annual Review of Statistics and Its Application ( IF 7.4 ) Pub Date : 2022-03-07 , DOI: 10.1146/annurev-statistics-100421-044639 Arun K. Kuchibhotla 1 , John E. Kolassa 2 , Todd A. Kuffner 3
Affiliation
We discuss inference after data exploration, with a particular focus on inference after model or variable selection. We review three popular approaches to this problem: sample splitting, simultaneous inference, and conditional selective inference. We explain how each approach works and highlight its advantages and disadvantages. We also provide an illustration of these post-selection inference approaches.
中文翻译：
选择后推理
我们讨论数据探索后的推理，特别关注模型或变量选择后的推理。我们回顾了解决这个问题的三种流行方法：样本分割、同时推理和条件选择性推理。我们解释了每种方法的工作原理，并强调了它的优缺点。我们还提供了这些选择后推理方法的说明。
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