Since causal paths from data are important for all sciences, the package provides many sophisticated functions. causeSummBlk() gives easy-to-interpret causal paths. Let Z denote control variables and compare two flipped kernel regressions: X=f(Y, Z)+e1 and Y=g(X,Z)+e2. Our criterion Cr1 says that if |e1*Y|>|e2*X| then variation in X is more "exogenous or independent" than in Y and causal path is X to Y. Criterion Cr2 requires |e2|<|e1|. These inequalities between many absolute value are quantified by four orders of stochastic dominance. Our third criterion Cr3 for the causal path X to Y requires new generalized partial correlations to satisfy |r*(x|y,z)|< |r*(y|x,z)|. The function parcorBMany() reports generalized partials between the first variable and all others. The package provides additional R tools for causal assessment, "outlier detection," and for numerical integration by the trapezoidal rule, stochastic dominance, pillar 3D charts, etc. We also provide functions for bootstrap-based statistical inference for causal paths. causeSummary() and causeSummBlk() are easiest to use functions.

Version: | 1.1.5 |

Depends: | R (≥ 3.0.0), np (≥ 0.60), xtable (≥ 1.8), meboot (≥ 1.4), psych, lattice |

Suggests: | R.rsp |

Published: | 2019-10-30 |

Author: | Prof. H. D. Vinod, Fordham University, NY. |

Maintainer: | H. D. Vinod <vinod at fordham.edu> |

License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |

NeedsCompilation: | no |

Materials: | NEWS |

CRAN checks: | generalCorr results |

Reference manual: | generalCorr.pdf |

Vignettes: |
generalCorr-vignette generalCorr-vignette2 generalCorr-vignette3 generalCorr-vignette4 |

Package source: | generalCorr_1.1.5.tar.gz |

Windows binaries: | r-devel: generalCorr_1.1.5.zip, r-release: generalCorr_1.1.5.zip, r-oldrel: generalCorr_1.1.5.zip |

macOS binaries: | r-release: generalCorr_1.1.5.tgz, r-oldrel: generalCorr_1.1.5.tgz |

Old sources: | generalCorr archive |

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