Package: generalCorr
Type: Package
Title: Generalized Correlations, Causal Paths and Portfolio Selection
Version: 1.2.2
Date: 2021-12-24
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() and causeSum2Blk()
    give 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 values 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 parcorVec() reports generalized partials between the first
    variable and all others.  The package provides several R functions including
    get0outliers() for outlier detection, bigfp() for numerical integration by the
    trapezoidal rule, stochdom2() for stochastic dominance, pillar3D() for 3D charts,
    canonRho() for generalized canonical correlations, depMeas() measures nonlinear
    dependence, and causeSummary(mtx) reports summary of causal paths among matrix columns
    is easiest to use. Portfolio selection: decileVote(), momentVote(), dif4mtx(), 
    exactSdMtx() can rank several stocks.  Several functions whose names begin with 'boot' provide bootstrap
    statistical inference including a new bootGcRsq() test for "Granger-causality" 
    allowing nonlinear relations. A new tool for evaluation of out-of-sample
    portfolio performance is outOFsamp(). See six vignettes of the package for theory
    and usage tips. See Vinod (2019) \doi{10.1080/03610918.2015.1122048}.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2022-01-03 16:48:48 UTC; vinod
Repository: CRAN
Date/Publication: 2022-01-03 17:10:02 UTC
Built: R 4.1.3; ; 2023-04-17 20:46:59 UTC; windows
