%global packname mboost %global packver 2.9-3 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 2.9.3 Release: 1%{?dist} Summary: Model-Based Boosting License: GPL-2 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.2.0 Requires: R-core >= 3.2.0 BuildRequires: R-CRAN-partykit >= 1.2.1 BuildRequires: R-CRAN-stabs >= 0.5.0 BuildRequires: R-methods BuildRequires: R-stats BuildRequires: R-parallel BuildRequires: R-Matrix BuildRequires: R-survival BuildRequires: R-splines BuildRequires: R-lattice BuildRequires: R-CRAN-nnls BuildRequires: R-CRAN-quadprog BuildRequires: R-utils BuildRequires: R-graphics BuildRequires: R-grDevices Requires: R-CRAN-partykit >= 1.2.1 Requires: R-CRAN-stabs >= 0.5.0 Requires: R-methods Requires: R-stats Requires: R-parallel Requires: R-Matrix Requires: R-survival Requires: R-splines Requires: R-lattice Requires: R-CRAN-nnls Requires: R-CRAN-quadprog Requires: R-utils Requires: R-graphics Requires: R-grDevices %description Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data. %prep %setup -q -c -n %{packname} find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \; [ -d %{packname}/src ] && find %{packname}/src -type f -exec \ sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true %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 find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \; %files %{rlibdir}/%{packname}