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Given independent samples generated from the joint distribution $p(\mathbf{x},\mathbf{y},\mathbf{z})$, we study the problem of Conditional Independence (CI-Testing), i.e., whether the joint equals the CI distribution $p^{CI}(\mathbf{x},\mathbf{y},\mathbf{z})= p(\mathbf{z}) p(\mathbf{y}|\mathbf{z})p(\mathbf{x}|\mathbf{z})$ or not.
Partial association measures and an application to qualitative regression
J. J. DAUDIN · 1980
Earlier work this paper cites.
Sample estimate of the entropy of a random vector
LF Kozachenko and Nikolai N Leonenko · 1987
Earlier work this paper cites.
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P. Spirtes, C. Glymour, and R. Scheines · 2000
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Earlier work this paper cites.
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