summaryRank

<p>matrix to be ranked by row and summarized</p>

<p>This function allows getting out the choice (of column stock) from four
rows of numbers quantifying the four orders of exact stochastic dominance comparisons.
If the choice row has 1 then that column is to be chosen with the largest
(portfolio) weight. If the original matrix row names exist, same are repeated
for the extra rows representing the ranks.  The row name for sum of ranks is
sumRanks and the ranking of the sumRanks providing the choice is named choice
along the bottom row of the output matrix called "out."</p>

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 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. See five vignettes of the package for theory
and usage tips. See Vinod (2019) \doi{10.1080/03610918.2015.1122048}.

Hrishikesh Vinod

summaryRank: Compute ranks of rows of matrix and summarize them into a choice suggestion.

Description

Usage

Arguments

Value