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File R-mcmsupply.spec of Package R-mcmsupply

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# Spec file for package mcmsupply 
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%global packname  mcmsupply 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.1.1 
Release:        0 
Summary:        Estimating Public and Private Sector Contraceptive Market Supply Shares 
Group:          Development/Libraries/Other 
License:        MIT + file LICENSE 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         mcmsupply_1.1.1.tar.gz 
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# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
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Suggests:	R-knitr
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%description 
Family Planning programs and initiatives typically use nationally 
representative surveys to estimate key indicators of a country’s family 
planning progress. However, in recent years, routinely collected family 
planning services data (Service Statistics) have been used as a 
supplementary data source to bridge gaps in the surveys. The use of 
service statistics comes with the caveat that adjustments need to be 
made for missing private sector contributions to the contraceptive 
method supply chain. Evaluating the supply source of modern 
contraceptives often relies on Demographic Health Surveys (DHS), where 
many countries do not have recent data beyond 2015/16. Fortunately, in 
the absence of recent surveys we can rely on statistical model-based 
estimates and projections to fill the knowledge gap. We present a 
Bayesian, hierarchical, penalized-spline model with multivariate-normal 
spline coefficients, to account for across method correlations, to 
produce country-specific,annual estimates for the proportion of modern 
contraceptive methods coming from the public and private sectors. This 
package provides a quick and convenient way for users to access the DHS 
modern contraceptive supply share data at national and subnational 
administration levels, estimate, evaluate and plot annual estimates 
with uncertainty for a sample of low- and middle-income countries. 
Methods for the estimation of method supply shares at the national 
level are described in Comiskey, Alkema, Cahill (2022) 
<arXiv:2212.03844>. 
 
%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
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data-raw
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/model
 
%changelog
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