Technical note: Sufficient operational statistics

被引：1

作者：

Jia, Justin ^{[1
]}

Katok, Elena ^{[2
]}

机构：

[1] Univ Tennessee, Haslam Coll Business, Knoxville, TN 37996 USA

[2] Univ Texas Dallas, Naveen Jindal Sch Management, Richardson, TX 75083 USA

来源：

PRODUCTION AND OPERATIONS MANAGEMENT | 2022年 / 31卷 / 06期

关键词：

data-driven decision making; data reduction; operational statistics; sufficiency;

D O I：

10.1111/poms.13678

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页码：2429 / 2437

页数：9

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