Related papers: A Conditional Independence Test in the Presence of Discretization

A Conditional Independence Test in the Presence of Discretization

URL: http://arxiv.org/abs/2404.17644v3
Date: Wed, 02 Oct 2024 09:55:25 GMT
Title: A Conditional Independence Test in the Presence of Discretization
Authors: Boyang Sun, Yu Yao, Huangyuan Hao, Yumou Qiu, Kun Zhang,
Abstract summary: Existing test methods can't work when only discretized observations are available. We propose a conditional independence test specifically designed to accommodate the presence of such discretization.
Score: 14.917729593550199
License:
Abstract: Testing conditional independence has many applications, such as in Bayesian network learning and causal discovery. Different test methods have been proposed. However, existing methods generally can not work when only discretized observations are available. Specifically, consider $X_1$, $\tilde{X}_2$ and $X_3$ are observed variables, where $\tilde{X}_2$ is a discretization of latent variables $X_2$. Applying existing test methods to the observations of $X_1$, $\tilde{X}_2$ and $X_3$ can lead to a false conclusion about the underlying conditional independence of variables $X_1$, $X_2$ and $X_3$. Motivated by this, we propose a conditional independence test specifically designed to accommodate the presence of such discretization. To achieve this, we design the bridge equations to recover the parameter reflecting the statistical information of the underlying latent continuous variables. An appropriate test statistic and its asymptotic distribution under the null hypothesis of conditional independence have also been derived. Both theoretical results and empirical validation have been provided, demonstrating the effectiveness of our test methods.

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