File R-boutliers.spec of Package R-boutliers

# Automatically generated by CRAN2OBS
# 
# Spec file for package boutliers 
# 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) 2026 SUSE LINUX GmbH, Nuernberg, Germany. 
# 
# All modifications and additions to the file contributed by third parties 
# remain the property of their copyright owners, unless otherwise agreed 
# upon. The license for this file, and modifications and additions to the 
# file, is the same license as for the pristine package itself (unless the 
# license for the pristine package is not an Open Source License, in which 
# case the license is the MIT License). An "Open Source License" is a 
# license that conforms to the Open Source Definition (Version 1.9) 
# published by the Open Source Initiative. 
#  
# Please submit bugfixes or comments via http://bugs.opensuse.org/ 
# 
 
%global packname  boutliers 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        2.1.3 
Release:        0 
Summary:        Outlier Detection and Influence Diagnostics for Meta-Analysis 
Group:          Development/Libraries/Other 
License:        GPL-3 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         boutliers_2.1-3.tar.gz 
Requires:       R-base 
Requires:	R-metafor
Requires:	R-metadat
Requires:	R-numDeriv
Requires:	R-mathjaxr
Requires:	R-pbapply
Requires:	R-digest
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
# # Three others commonly needed 
# BuildRequires:  tex(ae.sty) 
# BuildRequires:  tex(fancyvrb.sty) 
# BuildRequires:  tex(inconsolata.sty) 
# BuildRequires:  tex(natbib.sty) 
# %else 
# BuildRequires:  texlive 
# %endif 
# BuildRequires:  texinfo 
BuildRequires:  fdupes 
BuildRequires:  R-base 
BuildRequires: 	R-metafor
BuildRequires: 	R-metadat
BuildRequires: 	R-numDeriv
BuildRequires: 	R-mathjaxr
BuildRequires: 	R-pbapply
BuildRequires: 	R-digest
 
%description 
Computational tools for outlier detection and influence diagnostics in 
meta-analysis (Noma et al. (2025) <doi:10.1101/2025.09.18.25336125>). 
Bootstrap distributions of influence statistics are computed, and 
explicit thresholds for identifying outliers are provided. These 
methods can also be applied to the analysis of influential centers or 
regions in multicenter or multiregional clinical trials (Aoki, Noma and 
Gosho (2021) <doi:10.1080/24709360.2021.1921944>, Nakamura and Noma 
(2021) <doi:10.5691/jjb.41.117>). 
 
%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
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog