File R-mlergm.spec of Package R-mlergm

# Automatically generated by CRAN2OBS
# 
# Spec file for package mlergm 
# 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  mlergm 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        0.8.1 
Release:        0 
Summary:        Multilevel Exponential-Family Random Graph Models 
Group:          Development/Libraries/Other 
License:        GPL-3 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         mlergm_0.8.1.tar.gz 
Requires:       R-base 
Requires:	R-ergm
Requires:	R-network
Requires:	R-stringr
Requires:	R-GGally
Requires:	R-ggplot2
Requires:	R-cowplot
Requires:	R-reshape2
Requires:	R-plyr
Requires:	R-lpSolve
Requires:	R-sna
Requires:	R-statnet.common
Requires:	R-gtable
Requires:	R-rlang
Requires:	R-scales
Requires:	R-robustbase
Requires:	R-coda
Requires:	R-trust
Requires:	R-lpSolveAPI
Requires:	R-rle
Requires:	R-purrr
Requires:	R-memoise
Requires:	R-tibble
Requires:	R-magrittr
Requires:	R-Rdpack
Requires:	R-knitr
Requires:	R-cli
Requires:	R-dplyr
Requires:	R-ggstats
Requires:	R-lifecycle
Requires:	R-progress
Requires:	R-RColorBrewer
Requires:	R-S7
Requires:	R-tidyr
Requires:	R-isoband
Requires:	R-vctrs
Requires:	R-withr
Requires:	R-Rcpp
Requires:	R-glue
Requires:	R-stringi
Requires:	R-generics
Requires:	R-pillar
Requires:	R-R6
Requires:	R-tidyselect
Requires:	R-forcats
Requires:	R-patchwork
Requires:	R-evaluate
Requires:	R-highr
Requires:	R-xfun
Requires:	R-yaml
Requires:	R-cachem
Requires:	R-crayon
Requires:	R-hms
Requires:	R-prettyunits
Requires:	R-rbibutils
Requires:	R-DEoptimR
Requires:	R-farver
Requires:	R-labeling
Requires:	R-viridisLite
Requires:	R-pkgconfig
Requires:	R-cpp11
Requires:	R-fastmap
Requires:	R-utf8
 
# %%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-ergm-devel
BuildRequires: 	R-network
BuildRequires: 	R-stringr
BuildRequires: 	R-GGally
BuildRequires: 	R-ggplot2
BuildRequires: 	R-cowplot
BuildRequires: 	R-reshape2
BuildRequires: 	R-plyr
BuildRequires: 	R-lpSolve
BuildRequires: 	R-sna
BuildRequires: 	R-statnet.common
BuildRequires: 	R-gtable
BuildRequires: 	R-rlang
BuildRequires: 	R-scales
BuildRequires: 	R-robustbase
BuildRequires: 	R-coda
BuildRequires: 	R-trust
BuildRequires: 	R-lpSolveAPI-devel
BuildRequires: 	R-rle
BuildRequires: 	R-purrr
BuildRequires: 	R-memoise
BuildRequires: 	R-tibble
BuildRequires: 	R-magrittr
BuildRequires: 	R-Rdpack
BuildRequires: 	R-knitr
BuildRequires: 	R-cli
BuildRequires: 	R-dplyr
BuildRequires: 	R-ggstats
BuildRequires: 	R-lifecycle
BuildRequires: 	R-progress
BuildRequires: 	R-RColorBrewer
BuildRequires: 	R-S7
BuildRequires: 	R-tidyr
BuildRequires: 	R-isoband
BuildRequires: 	R-vctrs
BuildRequires: 	R-withr
BuildRequires: 	R-Rcpp-devel
BuildRequires: 	R-glue
BuildRequires: 	R-stringi
BuildRequires: 	R-generics
BuildRequires: 	R-pillar
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BuildRequires: 	R-evaluate
BuildRequires: 	R-highr
BuildRequires: 	R-xfun
BuildRequires: 	R-yaml
BuildRequires: 	R-cachem
BuildRequires: 	R-crayon
BuildRequires: 	R-hms
BuildRequires: 	R-prettyunits
BuildRequires: 	R-rbibutils
BuildRequires: 	R-DEoptimR
BuildRequires: 	R-farver
BuildRequires: 	R-labeling
BuildRequires: 	R-viridisLite
BuildRequires: 	R-pkgconfig
BuildRequires: 	R-cpp11-devel
BuildRequires: 	R-fastmap
BuildRequires: 	R-utf8
 
Suggests:	R-RColorBrewer
Suggests:	R-knitr
Suggests:	R-rmarkdown
%description 
Estimates exponential-family random graph models for multilevel network 
data, assuming the multilevel structure is observed. The scope, at 
present, covers multilevel models where the set of nodes is nested 
within known blocks. The estimation method uses Monte-Carlo maximum 
likelihood estimation (MCMLE) methods to estimate a variety of 
canonical or curved exponential family models for binary random graphs. 
MCMLE methods for curved exponential-family random graph models can be 
found in Hunter and Handcock (JCGS, 2006). The package supports 
parallel computing, and provides methods for assessing goodness-of-fit 
of models and visualization of networks. 
 
%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
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog