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Kernel PC (kPC) algorithm for causal structure learning and causal inference using graphical models. kPC is a version of PC algorithm that uses kernel based independence criteria in order to be able to deal with non-linear relationships and non-Gaussian noise. Includes pcalg: Functions for causal structure learning and causal inference using graphical models.
homepage: https://cran.r-project.org/package=kpcalg
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1.0.1 |
-R-3.5.1 |
foss/2018b |
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