File R-eefAnalytics.spec of Package R-eefAnalytics

# Automatically generated by CRAN2OBS
# 
# Spec file for package eefAnalytics 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
# discussed with upstream. 
# 
# Copyright (c) 2025 SUSE LINUX GmbH, Nuernberg, Germany. 
# 
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# published by the Open Source Initiative. 
#  
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%global packname  eefAnalytics 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.1.5 
Release:        0 
Summary:        Robust Analytical Methods for Evaluating Educational Interventions using Randomised Controlled Trials Designs 
Group:          Development/Libraries/Other 
License:        AGPL (>= 3) 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         eefAnalytics_1.1.5.tar.gz 
Requires:       R-base 
Requires:	R-R2jags
Requires:	R-ggplot2
Requires:	R-lme4
Requires:	R-mvtnorm
Requires:	R-coda
Requires:	R-MCMCvis
Requires:	R-cli
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-lifecycle
Requires:	R-rlang
Requires:	R-S7
Requires:	R-scales
Requires:	R-vctrs
Requires:	R-withr
Requires:	R-minqa
Requires:	R-nloptr
Requires:	R-reformulas
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Requires:	R-overlapping
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Requires:	R-rjags
Requires:	R-abind
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Requires:	R-stringr
Requires:	R-glue
Requires:	R-testthat
Requires:	R-Rdpack
Requires:	R-StanHeaders
Requires:	R-inline
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Requires:	R-farver
Requires:	R-labeling
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Requires:	R-viridisLite
Requires:	R-magrittr
Requires:	R-stringi
Requires:	R-checkmate
Requires:	R-matrixStats
Requires:	R-posterior
Requires:	R-callr
Requires:	R-desc
Requires:	R-processx
Requires:	R-rbibutils
Requires:	R-brio
Requires:	R-digest
Requires:	R-evaluate
Requires:	R-jsonlite
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Requires:	R-crayon
Requires:	R-generics
Requires:	R-numDeriv
Requires:	R-utf8
Requires:	R-pkgconfig
 
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Suggests:	R-knitr
Suggests:	R-rmarkdown
Suggests:	R-testthat
%description 
Analysing data from evaluations of educational interventions using a 
randomised controlled trial design. Various analytical tools to perform 
sensitivity analysis using different methods are supported (e.g. 
frequentist models with bootstrapping and permutations options, 
Bayesian models). The included commands can be used for simple 
randomised trials, cluster randomised trials and multisite trials. The 
methods can also be used more widely beyond education trials. This 
package can be used to evaluate other intervention designs using 
Frequentist and Bayesian multilevel models. 
 
%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
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%{rlibdir}/%{packname}/doc
%{rlibdir}/%{packname}/examples
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/jags
 
%changelog