File R-MEDseq.spec of Package R-MEDseq

# Automatically generated by CRAN2OBS
# 
# Spec file for package MEDseq 
# 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  MEDseq 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.4.2 
Release:        0 
Summary:        Mixtures of Exponential-Distance Models with Covariates 
Group:          Development/Libraries/Other 
License:        GPL (>= 3) 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         MEDseq_1.4.2.tar.gz 
Requires:       R-base 
Requires:	R-matrixStats
Requires:	R-seriation
Requires:	R-stringdist
Requires:	R-TraMineR
Requires:	R-WeightedCluster
Requires:	R-ca
Requires:	R-colorspace
Requires:	R-foreach
Requires:	R-gclus
Requires:	R-qap
Requires:	R-registry
Requires:	R-TSP
Requires:	R-vegan
Requires:	R-RColorBrewer
Requires:	R-progressr
Requires:	R-future
Requires:	R-doFuture
Requires:	R-fastcluster
Requires:	R-vegclust
Requires:	R-lme4
Requires:	R-margins
Requires:	R-future.apply
Requires:	R-globals
Requires:	R-iterators
Requires:	R-digest
Requires:	R-listenv
Requires:	R-parallelly
Requires:	R-Rdpack
Requires:	R-minqa
Requires:	R-nloptr
Requires:	R-reformulas
Requires:	R-rlang
Requires:	R-Rcpp
Requires:	R-RcppEigen
Requires:	R-prediction
Requires:	R-data.table
Requires:	R-permute
Requires:	R-rbibutils
 
# %%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-matrixStats
BuildRequires: 	R-seriation
BuildRequires: 	R-stringdist
BuildRequires: 	R-TraMineR
BuildRequires: 	R-WeightedCluster
BuildRequires: 	R-ca
BuildRequires: 	R-colorspace
BuildRequires: 	R-foreach
BuildRequires: 	R-gclus
BuildRequires: 	R-qap
BuildRequires: 	R-registry
BuildRequires: 	R-TSP
BuildRequires: 	R-vegan
BuildRequires: 	R-RColorBrewer
BuildRequires: 	R-progressr
BuildRequires: 	R-future
BuildRequires: 	R-doFuture
BuildRequires: 	R-fastcluster
BuildRequires: 	R-vegclust
BuildRequires: 	R-lme4
BuildRequires: 	R-margins
BuildRequires: 	R-future.apply
BuildRequires: 	R-globals
BuildRequires: 	R-iterators
BuildRequires: 	R-digest
BuildRequires: 	R-listenv
BuildRequires: 	R-parallelly
BuildRequires: 	R-Rdpack
BuildRequires: 	R-minqa
BuildRequires: 	R-nloptr
BuildRequires: 	R-reformulas
BuildRequires: 	R-rlang
BuildRequires: 	R-Rcpp-devel
BuildRequires: 	R-RcppEigen-devel
BuildRequires: 	R-prediction
BuildRequires: 	R-data.table
BuildRequires: 	R-permute
BuildRequires: 	R-rbibutils
 
Suggests:	R-knitr
Suggests:	R-rmarkdown
Suggests:	R-viridisLite
%description 
Implements a model-based clustering method for categorical life-course 
sequences relying on mixtures of exponential-distance models introduced 
by Murphy et al. (2021) <doi:10.1111/rssa.12712>. A range of flexible 
precision parameter settings corresponding to weighted generalisations 
of the Hamming distance metric are considered, along with the potential 
inclusion of a noise component. Gating covariates can be supplied in 
order to relate sequences to baseline characteristics and sampling 
weights are also accommodated. The models are fitted using the EM 
algorithm and tools for visualising the results are also provided. 
 
%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} 
%{rlibdir}/%{packname}/CITATION
%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
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog 
openSUSE Build Service is sponsored by