%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  generalCorr
%global packver   1.2.6
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          1.2.6
Release:          1%{?dist}%{?buildtag}
Summary:          Generalized Correlations, Causal Paths and Portfolio Selection

License:          GPL (>= 2)
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.0.0
Requires:         R-core >= 3.0.0
BuildArch:        noarch
BuildRequires:    R-CRAN-xtable >= 1.8
BuildRequires:    R-CRAN-meboot >= 1.4
BuildRequires:    R-CRAN-np >= 0.60
BuildRequires:    R-CRAN-psych 
BuildRequires:    R-CRAN-lattice 
Requires:         R-CRAN-xtable >= 1.8
Requires:         R-CRAN-meboot >= 1.4
Requires:         R-CRAN-np >= 0.60
Requires:         R-CRAN-psych 
Requires:         R-CRAN-lattice 

%description
Function gmcmtx0() computes a more reliable (general) correlation matrix.
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 the 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. Portfolio selection: decileVote(),
momentVote(), dif4mtx(), exactSdMtx() can rank several stocks. 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(). Panel data implementation is now included. See
eight vignettes of the package for theory, examples, and usage tips. See
Vinod (2019) doi{10.1080/03610918.2015.1122048}.

%prep
%setup -q -c -n %{packname}

# fix end of executable files
find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;
# prevent binary stripping
[ -d %{packname}/src ] && find %{packname}/src -type f -exec \
  sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true
[ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \
  sed -i 's@-g0@@g' {} \; || true
# don't allow local prefix in executable scripts
find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \;

%build

%install

mkdir -p %{buildroot}%{rlibdir}
%{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname}
test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so)
rm -f %{buildroot}%{rlibdir}/R.css
# remove buildroot from installed files
find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \;

%files
%{rlibdir}/%{packname}