%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname dsp %global packver 1.2.0 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 1.2.0 Release: 1%{?dist}%{?buildtag} Summary: Dynamic Shrinkage Process and Change Point Detection License: GPL (>= 3) 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-coda BuildRequires: R-CRAN-fda BuildRequires: R-graphics BuildRequires: R-grDevices BuildRequires: R-CRAN-Matrix BuildRequires: R-CRAN-MCMCpack BuildRequires: R-methods BuildRequires: R-CRAN-msm BuildRequires: R-CRAN-pgdraw BuildRequires: R-CRAN-Rcpp BuildRequires: R-CRAN-RcppZiggurat BuildRequires: R-CRAN-spam BuildRequires: R-CRAN-progress BuildRequires: R-stats BuildRequires: R-CRAN-stochvol BuildRequires: R-CRAN-BayesLogit BuildRequires: R-CRAN-truncdist BuildRequires: R-CRAN-mgcv BuildRequires: R-CRAN-purrr BuildRequires: R-CRAN-rlang BuildRequires: R-CRAN-lifecycle BuildRequires: R-CRAN-glue BuildRequires: R-CRAN-RcppArmadillo BuildRequires: R-CRAN-RcppEigen Requires: R-CRAN-coda Requires: R-CRAN-fda Requires: R-graphics Requires: R-grDevices Requires: R-CRAN-Matrix Requires: R-CRAN-MCMCpack Requires: R-methods Requires: R-CRAN-msm Requires: R-CRAN-pgdraw Requires: R-CRAN-Rcpp Requires: R-CRAN-RcppZiggurat Requires: R-CRAN-spam Requires: R-CRAN-progress Requires: R-stats Requires: R-CRAN-stochvol Requires: R-CRAN-BayesLogit Requires: R-CRAN-truncdist Requires: R-CRAN-mgcv Requires: R-CRAN-purrr Requires: R-CRAN-rlang Requires: R-CRAN-lifecycle Requires: R-CRAN-glue %description Provides efficient Markov chain Monte Carlo (MCMC) algorithms for dynamic shrinkage processes, which extend global-local shrinkage priors to the time series setting by allowing shrinkage to depend on its own past. These priors yield locally adaptive estimates, useful for time series and regression functions with irregular features. The package includes full MCMC implementations for trend filtering using dynamic shrinkage on signal differences, producing locally constant or linear fits with adaptive credible bands. Also included are models with static shrinkage and normal-inverse-Gamma priors for comparison. Additional tools cover dynamic regression with time-varying coefficients and B-spline models with shrinkage on basis differences, allowing for flexible curve-fitting with unequally spaced data. Some support for heteroscedastic errors, outlier detection, and change point estimation. Methods in this package are described in Kowal et al. (2019) , Wu et al. (2024) , Schafer and Matteson (2024) , and Cho and Matteson (2024) . %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}