CondIndTests: Nonlinear Conditional Independence Tests

Code for a variety of nonlinear conditional independence tests: Kernel conditional independence test (Zhang et al., UAI 2011, <arXiv:1202.3775>), Residual Prediction test (based on Shah and Buehlmann, <arXiv:1511.03334>), Invariant environment prediction, Invariant target prediction, Invariant residual distribution test, Invariant conditional quantile prediction (all from Heinze-Deml et al., <arXiv:1706.08576>).

Version: 0.1.1
Depends: R (≥ 3.1.0)
Imports: methods, randomForest, quantregForest, lawstat, RPtests, caTools, mgcv, MASS, kernlab
Published: 2017-06-29
Author: Christina Heinze-Deml, Jonas Peters
Maintainer: Christina Heinze-Deml <heinzedeml at stat.math.ethz.ch>
BugReports: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests
NeedsCompilation: no
Citation: CondIndTests citation info
CRAN checks: CondIndTests results

Downloads:

Reference manual: CondIndTests.pdf
Package source: CondIndTests_0.1.1.tar.gz
Windows binaries: r-devel: CondIndTests_0.1.1.zip, r-release: CondIndTests_0.1.1.zip, r-oldrel: CondIndTests_0.1.1.zip
OS X El Capitan binaries: r-release: CondIndTests_0.1.1.tgz
OS X Mavericks binaries: r-oldrel: CondIndTests_0.1.1.tgz

Reverse dependencies:

Reverse imports: nonlinearICP

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