%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname seqHMM %global packver 2.0.0 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 2.0.0 Release: 1%{?dist}%{?buildtag} Summary: Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series License: GPL (>= 2) URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 4.1.0 Requires: R-core >= 4.1.0 BuildRequires: R-CRAN-TraMineR >= 2.2.7 BuildRequires: R-CRAN-Rcpp >= 0.12.0 BuildRequires: R-CRAN-checkmate BuildRequires: R-CRAN-cli BuildRequires: R-CRAN-data.table BuildRequires: R-CRAN-future.apply BuildRequires: R-CRAN-ggplot2 BuildRequires: R-CRAN-ggseqplot BuildRequires: R-graphics BuildRequires: R-grDevices BuildRequires: R-grid BuildRequires: R-CRAN-gridBase BuildRequires: R-CRAN-igraph BuildRequires: R-CRAN-lhs BuildRequires: R-CRAN-Matrix BuildRequires: R-methods BuildRequires: R-CRAN-nloptr BuildRequires: R-CRAN-numDeriv BuildRequires: R-CRAN-patchwork BuildRequires: R-CRAN-progressr BuildRequires: R-CRAN-RcppHungarian BuildRequires: R-CRAN-rlang BuildRequires: R-stats BuildRequires: R-utils BuildRequires: R-CRAN-RcppArmadillo Requires: R-CRAN-TraMineR >= 2.2.7 Requires: R-CRAN-Rcpp >= 0.12.0 Requires: R-CRAN-checkmate Requires: R-CRAN-cli Requires: R-CRAN-data.table Requires: R-CRAN-future.apply Requires: R-CRAN-ggplot2 Requires: R-CRAN-ggseqplot Requires: R-graphics Requires: R-grDevices Requires: R-grid Requires: R-CRAN-gridBase Requires: R-CRAN-igraph Requires: R-CRAN-lhs Requires: R-CRAN-Matrix Requires: R-methods Requires: R-CRAN-nloptr Requires: R-CRAN-numDeriv Requires: R-CRAN-patchwork Requires: R-CRAN-progressr Requires: R-CRAN-RcppHungarian Requires: R-CRAN-rlang Requires: R-stats Requires: R-utils %description Designed for estimating variants of hidden (latent) Markov models (HMMs), mixture HMMs, and non-homogeneous HMMs (NHMMs) for social sequence data and other categorical time series. Special cases include feedback-augmented NHMMs, Markov models without latent layer, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models as well as initial, transition and emission probabilities in NHMMs. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and HMMs. For NHMMs, methods for computing average causal effects and marginal state and emission probabilities are available. Models are estimated using maximum likelihood via the EM algorithm or direct numerical maximization with analytical gradients. Documentation is available via several vignettes, and Helske and Helske (2019, ). For methodology behind the NHMMs, see Helske (2025, ). %prep %setup -q -c -n %{packname} # fix end of executable files find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \; # prevent binary stripping [ -d %{packname}/src ] && find %{packname}/src -type f -exec \ sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true [ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \ sed -i 's@-g0@@g' {} \; || true # don't allow local prefix in executable scripts find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \; %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 # remove buildroot from installed files find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \; %files %{rlibdir}/%{packname}