%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}