File R-studyStrap.spec of Package R-studyStrap
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%global packname studyStrap
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 1.0.0
Release: 0
Summary: Study Strap and Multi-Study Learning Algorithms
Group: Development/Libraries/Other
License: MIT + file LICENSE
URL: http://cran.r-project.org/web/packages/%{packname}
Source: studyStrap_1.0.0.tar.gz
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%description
Implements multi-study learning algorithms such as merging, the
study-specific ensemble (trained-on-observed-studies ensemble) the
study strap, the covariate-matched study strap, covariate-profile
similarity weighting, and stacking weights. Embedded within the 'caret'
framework, this package allows for a wide range of single-study
learners (e.g., neural networks, lasso, random forests). The package
offers over 20 default similarity measures and allows for specification
of custom similarity measures for covariate-profile similarity
weighting and an accept/reject step. This implements methods described
in Loewinger, Kishida, Patil, and Parmigiani. (2019)
<doi:10.1101/856385>.
%prep
%setup -q -c -n %{packname}
# the next line is needed, because we build without --clean in between two packages
rm -rf ~/.R
%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
%fdupes -s %{buildroot}%{rlibdir}
#%%check
#%%{_bindir}/R CMD check %%{packname}
%files
%dir %{rlibdir}/%{packname}
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%license %{rlibdir}/%{packname}/LICENSE
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%doc %{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%changelog
