%global __brp_check_rpaths %{nil} %global packname rsurface %global packver 1.1.0 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 1.1.0 Release: 3%{?dist}%{?buildtag} Summary: Design of Rotatable Central Composite Experiments and ResponseSurface Analysis License: MIT + file LICENSE 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 BuildArch: noarch BuildRequires: R-grDevices BuildRequires: R-CRAN-plotly BuildRequires: R-CRAN-rsm BuildRequires: R-stats Requires: R-grDevices Requires: R-CRAN-plotly Requires: R-CRAN-rsm Requires: R-stats %description Produces tables with the level of replication (number of replicates) and the experimental uncoded values of the quantitative factors to be used for rotatable Central Composite Design (CCD) experimentation and a 2-D contour plot of the corresponding variance of the predicted response according to Mead et al. (2012) design_ccd(), and analyzes CCD data with response surface methodology ccd_analysis(). A rotatable CCD provides values of the variance of the predicted response that are concentrically distributed around the average treatment combination used in the experimentation, which with uniform precision (implied by the use of several replicates at the average treatment combination) improves greatly the search and finding of an optimum response. These properties of a rotatable CCD represent undeniable advantages over the classical factorial design, as discussed by Panneton et al. (1999) and Mead et al. (2012) among others. %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}