Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing
Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing
复制标题
情境动态定价中需求预测的不确定性量化
DOI：
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复制
发表时间：
2020
影响因子：
5
通讯作者：
Yining Wang
中科院分区：
文献类型：
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作者：
Xi Chen;Yining Wang
数据驱动的序贯决策在现代运营管理中有着广泛的应用，如动态定价、库存控制和分类优化。大多数现有的数据驱动的顺序决策研究集中在设计一个在线策略，以最大限度地提高收入。然而，对底层真实模型函数（例如，需求函数），这是从业人员的一个关键问题，尚未得到很好的探讨。本研究以动态定价中的需求函数预测问题为例，研究了需求函数精确置信区间的构造问题。主要的挑战是，顺序收集的数据导致显着的分布偏差的最大似然估计或经验风险最小化估计，使经典的统计方法，如沃尔德检验不再有效。我们通过开发一种去偏方法来解决这一挑战，并提供了去偏估计的渐近正态性保证。基于这个去偏估计，我们提供了需求函数的逐点和一致置信区间。
Data‐driven sequential decision has found a wide range of applications in modern operations management, such as dynamic pricing, inventory control, and assortment optimization. Most existing research on data‐driven sequential decision focuses on designing an online policy to maximize revenue. However, the research on uncertainty quantification on the underlying true model function (e.g., demand function), a critical problem for practitioners, has not been well explored. In this study, using the problem of demand function prediction in dynamic pricing as the motivating example, we study the problem of constructing accurate confidence intervals for the demand function. The main challenge is that sequentially collected data lead to significant distributional bias in the maximum likelihood estimator or the empirical risk minimization estimate, making classical statistical approaches such as the Wald’s test no longer valid. We address this challenge by developing a debiased approach and provide the asymptotic normality guarantee of the debiased estimator. Based this the debiased estimator, we provide both point‐wise and uniform confidence intervals of the demand function.
DOI：
10.2139/ssrn.2579462
发表时间：
2015-03
期刊：
Revenue & Yield Management eJournal
影响因子：
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作者：
Xi Chen;Zachary Owen;Clark Pixton;D. Simchi-Levi
通讯作者：
Xi Chen;Zachary Owen;Clark Pixton;D. Simchi-Levi
DOI：
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发表时间：
2018-10
期刊：
J. Mach. Learn. Res.
影响因子：
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作者：
Xi Chen;Yining Wang;Yuanshuo Zhou
通讯作者：
Xi Chen;Yining Wang;Yuanshuo Zhou
DOI：
10.1080/01621459.2021.1979011
发表时间：
2019-11
影响因子：
3.7
作者：
Y. Deshpande;Adel Javanmard;M. Mehrabi
通讯作者：
Y. Deshpande;Adel Javanmard;M. Mehrabi