%global __brp_check_rpaths %{nil}
%global packname  forecastSNSTS
%global packver   1.3-0
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          1.3.0
Release:          3%{?dist}%{?buildtag}
Summary:          Forecasting for Stationary and Non-Stationary Time Series

License:          GPL (>= 2)
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.2.3
Requires:         R-core >= 3.2.3
BuildRequires:    R-CRAN-Rcpp 
Requires:         R-CRAN-Rcpp 

%description
Methods to compute linear h-step ahead prediction coefficients based on
localised and iterated Yule-Walker estimates and empirical mean squared
and absolute prediction errors for the resulting predictors. Also,
functions to compute autocovariances for AR(p) processes, to simulate
tvARMA(p,q) time series, and to verify an assumption from Kley et al.
(2019), Electronic of Statistics, forthcoming. Preprint
<arXiv:1611.04460>.

%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}