A smoothed Q-learning algorithm for estimating optimal dynamic treatment regime

A smoothed Q-learning algorithm for estimating optimal dynamic treatment regime

In this paper we propose a smoothed Q-learning algorithm for estimating optimal dynamic treatment regimes. In contrast to the Q-learning algorithm in which non-regular inference is involved, we show that under assumptions adopted in this paper, the proposed smoothed Q-learning estimator is asymptoti...

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Bibliographic Details
Main Authors: FAN, Yanqin, HE, Ming, SU, Liangjun, ZHOU, Xiao-Hua
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
Subjects:
Asymptotic normality
Exceptional law
Optimal smoothing parameter
Sequential randomization
Wald-type inference
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/2044
https://ink.library.smu.edu.sg/context/soe_research/article/3043/viewcontent/Smoothed_Q_learning_algorithm_for_estimating_optimal_2016_pp.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/soe_research/2044
https://ink.library.smu.edu.sg/context/soe_research/article/3043/viewcontent/Smoothed_Q_learning_algorithm_for_estimating_optimal_2016_pp.pdf

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