kpcalg: Kernel PC Algorithm for Causal Structure Detection (original) (raw)
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.
Version: | 1.0.1 |
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Depends: | R (≥ 3.0.2) |
Imports: | pcalg, energy, kernlab, parallel, mgcv, RSpectra, methods, graph, stats, utils |
Suggests: | Rgraphviz, knitr |
Published: | 2017-01-22 |
DOI: | 10.32614/CRAN.package.kpcalg |
Author: | Petras Verbyla, Nina Ines Bertille Desgranges, Lorenz Wernisch |
Maintainer: | Petras Verbyla <petras.verbyla at mrc-bsu.cam.ac.uk> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
CRAN checks: | kpcalg results |
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