Package: kpcalg
Date: 2017-01-19
Title: Kernel PC Algorithm for Causal Structure Detection
Description: 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
Author: Petras Verbyla, Nina Ines Bertille Desgranges, Lorenz Wernisch
Maintainer: Petras Verbyla <petras.verbyla@mrc-bsu.cam.ac.uk>
Imports: pcalg, energy, kernlab, parallel, mgcv, RSpectra, methods,
        graph, stats, utils
Suggests: Rgraphviz, knitr
VignetteBuilder: knitr
License: GPL (>= 2)
Depends: R (>= 3.0.2)
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-01-20 12:37:53 UTC; petras
Repository: CRAN
Date/Publication: 2017-01-22 12:38:35
Built: R 4.2.0; ; 2022-04-27 18:17:32 UTC; unix
