%global __brp_check_rpaths %{nil} %global packname essHist %global packver 1.2.2 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 1.2.2 Release: 3%{?dist}%{?buildtag} Summary: The Essential Histogram License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 2.15.3 Requires: R-core >= 2.15.3 BuildRequires: R-CRAN-Rcpp >= 0.12.5 BuildRequires: R-graphics BuildRequires: R-stats BuildRequires: R-grDevices BuildRequires: R-utils Requires: R-CRAN-Rcpp >= 0.12.5 Requires: R-graphics Requires: R-stats Requires: R-grDevices Requires: R-utils %description Provide an optimal histogram, in the sense of probability density estimation and features detection, by means of multiscale variational inference. In other words, the resulting histogram servers as an optimal density estimator, and meanwhile recovers the features, such as increases or modes, with both false positive and false negative controls. Moreover, it provides a parsimonious representation in terms of the number of blocks, which simplifies data interpretation. The only assumption for the method is that data points are independent and identically distributed, so it applies to fairly general situations, including continuous distributions, discrete distributions, and mixtures of both. For details see Li, Munk, Sieling and Walther (2016) . %prep %setup -q -c -n %{packname} %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 %files %{rlibdir}/%{packname}