题目：Spatial Interference Detection in Treatment Effect Models

报告人：杨莹 研究员 （复旦大学）

地点：致远楼108室

时间：2024年11月21日 13:30-14:30

Abstract：

Modeling the interference effect is an important issue in the field of causal inference. Existing studies rely on explicit and often homogeneous assumptions regarding interference structures. In this paper, we introduce a low-rank and sparse treatment effect model that leverages data-driven techniques to identify the locations of interference effects. A profiling algorithm is proposed to estimate the model coefficients, and based on these estimates, global test and local detection methods are established to detect the existence of interference and the interference neighbor locations for each unit. We derive the non-asymptotic bound of the estimation error, and establish theoretical guarantees for the global test and the accuracy of the detection method in terms of Jaccard index. Simulations and real data examples are provided to demonstrate the usefulness of the proposed method.

报告人简介: 杨莹，现任复旦大学应用数学中心和数学科学学院双聘青年研究员，2022年毕业于北京大学统计科学中心，获得统计学博士学位，2024年在中国科学院数学与系统科学研究院完成博士后工作。研究方向为复杂数据的实时动态算法和基于因果推断的政策评估问题。入选中国科学技术协会青年人才托举工程，主持国家自然科学基金委青年基金。相关成果发表于JASA、JRSSB等期刊。

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