Package: generalCorr
Type: Package
Title: Generalized Correlations and Initial Causal Path
Version: 1.0.9
Date: 2017-10-03
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 (>= 1.5)
Suggests: R.rsp
VignetteBuilder: R.rsp
Description: Since causal paths from data are important for all sciences, the
package provides sophisticated functions. The idea is simply
that if X causes Y (path: X to Y) then non-deterministic variation in X
is more "original or independent" than similar variation in Y.  We compare
two flipped kernel regressions: X=f(Y, Z) and Y=g(X,Z), where Z are control
variables. Our first two criteria compare absolute gradients (Cr1) and
absolute residuals (Cr2), both quantified by stochastic dominance of four
orders (SD1 to SD4). Our third criterion (Cr3) expects X to be better able
to predict Y than the other way around using generalized partial correlation
If |r*(x|y)|> |r*(y|x)| it suggests that y is more likely
the "kernel cause" of x. The usual partial correlations are generalized for
the asymmetric matrix of r*'s developed here.
Partial correlations help asses effect of x on y after removing the effect of a
set of variables.
The package provides additional tools for causal assessment,
for printing the causal directions in a clear, comprehensive compact summary form,
for matrix algebra, for "outlier detection", and for numerical integration by the
trapezoidal rule, stochastic dominance, etc.
The package has functions for bootstrap-based statistical inference and one
for a heuristic t-test.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-03 22:33:44 UTC; hd
Repository: CRAN
Date/Publication: 2017-10-03 22:46:21 UTC

Package: generalCorr
Type: Package
Title: Generalized Correlations and Initial Causal Path
Version: 1.1.0
Date: 2018-01-04
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 (>= 1.5)
Suggests: R.rsp
VignetteBuilder: R.rsp
Description: Since causal paths from data are important for all sciences, the
package provides sophisticated functions. The idea is simply
that if X causes Y (path: X to Y) then non-deterministic variation in X
is more "original or independent" than similar variation in Y.  We compare
two flipped kernel regressions: X=f(Y, Z) and Y=g(X,Z), where Z are control
variables. Our first two criteria compare absolute cross products
of regressor values and residuals (Cr1) and
absolute residuals (Cr2), are both quantified by stochastic dominance of four
orders (SD1 to SD4). Our third criterion (Cr3) expects X to be better able
to predict Y than the other way around using generalized partial correlation
If |r*(x|y)|> |r*(y|x)| it suggests that y is more likely
the "kernel cause" of x. The usual partial correlations are generalized with
a new non-symmetric matrix developed here.
Partial correlations help asses effect of x on y after removing the effect of a
set of variables.
The package provides additional tools for causal assessment,
for printing the causal directions in a clear, comprehensive compact summary form,
for matrix algebra, for "outlier detection", and for numerical integration by the
trapezoidal rule, stochastic dominance, etc.
The package has functions for bootstrap-based statistical inference and one
for a heuristic t-test.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-01-05 04:20:38 UTC; hd
Repository: CRAN
Date/Publication: 2018-01-05 05:17:55 UTC