%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname BoundIRT %global packver 0.0.1 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.0.1 Release: 1%{?dist}%{?buildtag} Summary: Fit Bounded Continuous Item Response Theory Models to Data License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.5 Requires: R-core >= 3.5 BuildRequires: R-CRAN-RcppParallel >= 5.0.1 BuildRequires: R-CRAN-rstantools >= 2.6.0 BuildRequires: R-CRAN-rstan >= 2.18.1 BuildRequires: R-CRAN-StanHeaders >= 2.18.0 BuildRequires: R-CRAN-BH >= 1.66.0 BuildRequires: R-CRAN-RcppEigen >= 0.3.3.3.0 BuildRequires: R-CRAN-Rcpp >= 0.12.0 BuildRequires: R-methods BuildRequires: R-CRAN-mvtnorm BuildRequires: R-CRAN-rmutil BuildRequires: R-CRAN-MASS BuildRequires: R-CRAN-rstantools Requires: R-CRAN-RcppParallel >= 5.0.1 Requires: R-CRAN-rstantools >= 2.6.0 Requires: R-CRAN-rstan >= 2.18.1 Requires: R-CRAN-Rcpp >= 0.12.0 Requires: R-methods Requires: R-CRAN-mvtnorm Requires: R-CRAN-rmutil Requires: R-CRAN-MASS Requires: R-CRAN-rstantools %description Bounded continuous data are encountered in many areas of test application. Examples include visual analogue scales used in the measurement of personality, mood, depression, and quality of life; item response times from tests with item deadlines; confidence ratings; and pain intensity ratings. Using this package, item response theory (IRT) models suitable for bounded continuous item scores can be fitted to data within a Bayesian framework. The package draws on posterior sampling facilities provided by R-package 'rstan' (Stan Development Team, 2025). Available models include the Beta IRT model by Noel and Dauvier (2007), the continuous response model by Samejima (1973), the unbounded normal model by Mellenbergh (1994), and the Simplex IRT model by Flores et al. (2020). All models can be fitted with or without zero-one inflation (Molenaar et al., 2022). Model fit comparisons can be conducted using the Watanabe–Akaike information criterion (WAIC), the deviance information criterion (DIC), and the fully marginalized likelihood (i.e., Bayes factors). %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}