File R-quantilogram.spec of Package R-quantilogram

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# Spec file for package quantilogram 
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%global packname  quantilogram 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        3.1.1 
Release:        0 
Summary:        Cross-Quantilogram 
Group:          Development/Libraries/Other 
License:        GPL (>= 3) 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         quantilogram_3.1.1.tar.gz 
Requires:       R-base 
Requires:	R-ggplot2
Requires:	R-np
Requires:	R-quantreg
Requires:	R-rlang
Requires:	R-scales
Requires:	R-cli
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-lifecycle
Requires:	R-S7
Requires:	R-vctrs
Requires:	R-withr
Requires:	R-cubature
Requires:	R-quadprog
Requires:	R-SparseM
Requires:	R-MatrixModels
Requires:	R-farver
Requires:	R-glue
Requires:	R-labeling
Requires:	R-R6
Requires:	R-RColorBrewer
Requires:	R-viridisLite
Requires:	R-Rcpp
Requires:	R-cpp11
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
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# BuildRequires:  tex(ae.sty) 
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# %else 
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# BuildRequires:  texinfo 
BuildRequires:  fdupes 
BuildRequires:  R-base 
BuildRequires: 	R-ggplot2
BuildRequires: 	R-np
BuildRequires: 	R-quantreg
BuildRequires: 	R-rlang
BuildRequires: 	R-scales
BuildRequires: 	R-cli
BuildRequires: 	R-gtable
BuildRequires: 	R-isoband
BuildRequires: 	R-lifecycle
BuildRequires: 	R-S7
BuildRequires: 	R-vctrs
BuildRequires: 	R-withr
BuildRequires: 	R-cubature
BuildRequires: 	R-quadprog
BuildRequires: 	R-SparseM
BuildRequires: 	R-MatrixModels
BuildRequires: 	R-farver
BuildRequires: 	R-glue
BuildRequires: 	R-labeling
BuildRequires: 	R-R6
BuildRequires: 	R-RColorBrewer
BuildRequires: 	R-viridisLite
BuildRequires: 	R-Rcpp-devel
BuildRequires: 	R-cpp11-devel
 
Suggests:	R-knitr
Suggests:	R-rmarkdown
Suggests:	R-SparseM
%description 
Estimation and inference methods for the cross-quantilogram. The 
cross-quantilogram is a measure of nonlinear dependence between two 
variables, based on either unconditional or conditional quantile 
functions.  It can be considered an extension of the correlogram, which 
is a correlation function over multiple lag periods that mainly focuses 
on linear dependency.  One can use the cross-quantilogram to detect the 
presence of directional predictability from one time series to another. 
This package provides a statistical inference method based on the 
stationary bootstrap.  For detailed theoretical and empirical 
explanations, see Linton and Whang (2007) for univariate time series 
analysis and Han, Linton, Oka and Whang (2016) for multivariate time 
series analysis.  The full references for these key publications are as 
follows: (1) Linton, O., and Whang, Y. J. (2007). The quantilogram: 
with an application to evaluating directional predictability.  Journal 
of Econometrics, 141(1), 250-282 <doi:10.1016/j.jeconom.2007.01.004>; 
(2) Han, H., Linton, O., Oka, T., and Whang, Y. J. (2016).  The 
cross-quantilogram: measuring quantile dependence and testing 
directional predictability between time series. Journal of 
Econometrics, 193(1), 251-270 <doi:10.1016/j.jeconom.2016.03.001>. 
 
%prep 
%setup -q -c -n %{packname} 
# the next line is needed, because we build without --clean in between two packages 
rm -rf ~/.R  
 
 
%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 
%fdupes -s %{buildroot}%{rlibdir} 
 
#%%check 
#%%{_bindir}/R CMD check %%{packname} 
 
%files 
%dir %{rlibdir}/%{packname} 
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog 
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