Individual versus social optimization in statistical estimation

IF 0.9 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2025-04-11 DOI:10.1016/j.orl.2025.107284

Moshe Haviv

引用次数: 0

Abstract

A number of estimators participate in a non-cooperative game where the data they collect are reported to a central planner who takes decisions. She in her turn decides on the estimates to be imposed on the participants. Because they are aware of this, they may behave strategically and misreport. We exemplify this decision making process where the James-Stein's estimator is used by the central planner. In particular, we consider the resulting optimization or Nash equilibria reporting strategies in a number of variations of this game.

查看原文本刊更多论文

统计估计中的个人与社会优化

许多估计者参与一个非合作博弈，他们收集的数据被报告给一个中央计划者，后者负责决策。由她来决定对参与者施加的估计。因为他们意识到了这一点，他们可能会表现得很有策略，甚至会误报。我们举例说明了中央计划者使用詹姆斯-斯坦估计器的决策过程。特别地，我们考虑在这个博弈的许多变体中产生的最优化或纳什均衡报告策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.