Technical note: Sufficient operational statistics
研究了数据驱动决策中何时可将高维决策函数简化为统计量的单维函数，提出了充分操作统计量的概念，推导了识别该统计量的因子分解定理，并给出了基于该统计量的求解过程及其有限样本性能界。
The decision in a data‐driven decision‐making problem is generally a high‐dimensional function of data. When can the decision be reduced to a single‐dimensional function of a statistic? This study addresses this question based on the operational statistics literature. The study introduces the notion of sufficient operational statistics and derives the factorization theorem for identifying such statistics. Further, the study proposes a solution procedure based on the statistics and derives the finite‐sample performance bound of the proposed solution.