%global __brp_check_rpaths %{nil}
%global packname  onlineCOV
%global packver   1.3
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          1.3
Release:          3%{?dist}%{?buildtag}
Summary:          Online Change Point Detection in High-Dimensional CovarianceStructure

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


BuildRequires:    R-devel
Requires:         R-core

%description
Implement a new stopping rule to detect anomaly in the covariance
structure of high-dimensional online data. The detection procedure can be
applied to Gaussian or non-Gaussian data with a large number of
components. Moreover, it allows both spatial and temporal dependence in
data. The dependence can be estimated by a data-driven procedure. The
level of threshold in the stopping rule can be determined at a
pre-selected average run length. More detail can be seen in Li, L. and Li,
J. (2020) "Online Change-Point Detection in High-Dimensional Covariance
Structure with Application to Dynamic Networks." <arXiv:1911.07762>.

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

find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;

%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

%files
%{rlibdir}/%{packname}