A Projection-based Conditional Dependence Measure with Applications to High-dimensional Undirected Graphical Models.
A Projection-based Conditional Dependence Measure with Applications to High-dimensional Undirected Graphical Models.
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DOI：
10.1016/j.jeconom.2019.12.016
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发表时间：
2020-09
影响因子：
6.3
通讯作者：
Xia L
中科院分区：
文献类型：
--
作者：
Fan J;Feng Y;Xia L
测量条件依赖性是计量经济学中的一个重要课题，具有广泛的应用，包括图形模型。在因子模型设置下，提出了一种新的基于投影的条件依赖测度。提出了相应的条件独立检验，揭示了因子数量可能是高维的渐近零分布。结果表明，新的检验方法可以有效地控制渐近I型误差，并能有效地进行计算。阐述了一种利用新的检验方法构建不含高斯假设的依赖图的通用方法。通过仿真和实际数据研究，我们证明了新方法在R包图形中实现的优越性。
Measuring conditional dependence is an important topic in econometrics with broad applications including graphical models. Under a factor model setting, a new conditional dependence measure based on projection is proposed. The corresponding conditional independence test is developed with the asymptotic null distribution unveiled where the number of factors could be high-dimensional. It is also shown that the new test has control over the asymptotic type I error and can be calculated efficiently. A generic method for building dependency graphs without Gaussian assumption using the new test is elaborated. We show the superiority of the new method, implemented in the R package pgraph, through simulation and real data studies.
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影响因子：
3.7
作者：
Fan J;Feng Y;Song R
通讯作者：
Song R
影响因子：
1.8
作者：
Fan, Jianqing;Feng, Yang;Wu, Yichao
通讯作者：
Wu, Yichao
影响因子：
1.5
作者：
Belloni, Alexandre;Chernozhukov, Victor
通讯作者：
Chernozhukov, Victor
影响因子：
--
作者：
HOEFFDING, W
通讯作者：
HOEFFDING, W
影响因子：
--
作者：
BLUM, JR;KIEFER, J;ROSENBLATT, M
通讯作者：
ROSENBLATT, M