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(230419)Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits
작성일
2023.04.11
작성자
경제연구소
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경제연구소에서는 다음과 같은 주제로 특강 및 세미나를 개최합니다.



발표자: Jack R. Porter(University of Wisconsin-Madison)


주제: Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits


Abstract

We develop asymptotic approximation results that can be applied to sequential
estimation and inference problems, adaptive randomized controlled trials, and other
statistical decision problems that involve multiple decision nodes with structured and
possibly endogenous information sets. Our results extend the classic asymptotic
representation theorem used extensively in efficiency bound theory and local power
analysis. In adaptive settings where the decision at one stage can affect the observation of
variables in later stages, we show that a limiting data environment characterizes all limit
distributions attainable through a joint choice of an adaptive design rule and statistics
applied to the adaptively generated data, under local alternatives. We illustrate how the
theory can be applied to study the choice of adaptive rules and end-of-sample statistical
inference in batched (groupwise) sequential adaptive experiments.


장소: 대우관 본관 3층 323호


날짜: 4월 19일(수) 오전 10시


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