%global __brp_check_rpaths %{nil} %global packname VARshrink %global packver 0.3.1 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.3.1 Release: 3%{?dist}%{?buildtag} Summary: Shrinkage Estimation Methods for Vector Autoregressive Models License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.5.0 Requires: R-core >= 3.5.0 BuildArch: noarch BuildRequires: R-CRAN-corpcor >= 1.6.9 BuildRequires: R-CRAN-vars >= 1.5.3 BuildRequires: R-CRAN-ars >= 0.6 BuildRequires: R-CRAN-strucchange BuildRequires: R-stats BuildRequires: R-MASS BuildRequires: R-CRAN-mvtnorm Requires: R-CRAN-corpcor >= 1.6.9 Requires: R-CRAN-vars >= 1.5.3 Requires: R-CRAN-ars >= 0.6 Requires: R-CRAN-strucchange Requires: R-stats Requires: R-MASS Requires: R-CRAN-mvtnorm %description Vector autoregressive (VAR) model is a fundamental and effective approach for multivariate time series analysis. Shrinkage estimation methods can be applied to high-dimensional VAR models with dimensionality greater than the number of observations, contrary to the standard ordinary least squares method. This package is an integrative package delivering nonparametric, parametric, and semiparametric methods in a unified and consistent manner, such as the multivariate ridge regression in Golub, Heath, and Wahba (1979) , a James-Stein type nonparametric shrinkage method in Opgen-Rhein and Strimmer (2007) , and Bayesian estimation methods using noninformative and informative priors in Lee, Choi, and S.-H. Kim (2016) and Ni and Sun (2005) . %prep %setup -q -c -n %{packname} %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}