Package: generalCorr
Type: Package
Title: Generalized Correlations and Plausible Causal Paths
Version: 1.1.3
Date: 2019-10-07
Author: Prof. H. D. Vinod, Fordham University, NY.
Maintainer: H. D. Vinod <vinod@fordham.edu>
Encoding: UTF-8
Depends: R (>= 3.0.0), np (>= 0.60), xtable (>= 1.8), meboot (>= 1.4),
psych, lattice
Suggests: R.rsp
VignetteBuilder: R.rsp
Description: Since causal paths from data are important for all sciences, the
package provides many sophisticated functions. causeSummary()
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 parcorMany() 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.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-07 15:34:10 UTC; vinod
Repository: CRAN
Date/Publication: 2019-10-07 17:00:02 UTC

Package: generalCorr
Type: Package
Title: Generalized Correlations and Plausible Causal Paths
Version: 1.1.5
Date: 2019-10-30
Author: Prof. H. D. Vinod, Fordham University, NY.
Maintainer: H. D. Vinod <vinod@fordham.edu>
Encoding: UTF-8
Depends: R (>= 3.0.0), np (>= 0.60), xtable (>= 1.8), meboot (>= 1.4),
psych, lattice
Suggests: R.rsp
VignetteBuilder: R.rsp
Description: 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.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-30 20:26:19 UTC; vinod
Repository: CRAN
Date/Publication: 2019-10-30 20:50:02 UTC