File R-actfts.spec of Package R-actfts
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# Spec file for package actfts
# This file is auto-generated using information in the package source,
# esp. Description and Summary. Improvements in that area should be
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%global packname actfts
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 0.3.0
Release: 0
Summary: Autocorrelation Tools Featured for Time Series
Group: Development/Libraries/Other
License: MIT + file LICENSE
URL: http://cran.r-project.org/web/packages/%{packname}
Source: actfts_0.3.0.tar.gz
Requires: R-base
Requires: R-openxlsx
Requires: R-plotly
Requires: R-reactable
Requires: R-tseries
Requires: R-xts
Requires: R-forecast
Requires: R-lifecycle
Requires: R-colorspace
Requires: R-fracdiff
Requires: R-generics
Requires: R-ggplot2
Requires: R-lmtest
Requires: R-magrittr
Requires: R-Rcpp
Requires: R-timeDate
Requires: R-urca
Requires: R-withr
Requires: R-zoo
Requires: R-RcppArmadillo
Requires: R-cli
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Requires: R-lazyeval
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Requires: R-promises
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Requires: R-quantmod
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Requires: R-pillar
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Requires: R-fastmap
Requires: R-knitr
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Requires: R-yaml
Requires: R-curl
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Requires: R-openssl
Requires: R-later
Requires: R-otel
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Requires: R-cpp11
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# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse}
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BuildRequires: R-tseries
BuildRequires: R-xts
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Suggests: R-dplyr
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Suggests: R-rmarkdown
Suggests: R-testthat
%description
The 'actfts' package provides tools for performing autocorrelation
analysis of time series data. It includes functions to compute and
visualize the autocorrelation function (ACF) and the partial
autocorrelation function (PACF). Additionally, it performs the
Dickey-Fuller, KPSS, and Phillips-Perron unit root tests to assess the
stationarity of time series. Theoretical foundations are based on Box
and Cox (1964) <doi:10.1111/j.2517-6161.1964.tb00553.x>, Box and
Jenkins (1976) <isbn:978-0-8162-1234-2>, and Box and Pierce (1970)
<doi:10.1080/01621459.1970.10481180>. Statistical methods are also
drawn from Kolmogorov (1933) <doi:10.1007/BF00993594>, Kwiatkowski et
al. (1992) <doi:10.1016/0304-4076(92)90104-Y>, and Ljung and Box (1978)
<doi:10.1093/biomet/65.2.297>. The package integrates functions from
'forecast' (Hyndman & Khandakar, 2008)
<https://CRAN.R-project.org/package=forecast>, 'tseries' (Trapletti &
Hornik, 2020) <https://CRAN.R-project.org/package=tseries>, 'xts' (Ryan
& Ulrich, 2020) <https://CRAN.R-project.org/package=xts>, and 'stats'
(R Core Team, 2023)
<https://stat.ethz.ch/R-manual/R-devel/library/stats/html/00Index.html>.
Additionally, it provides visualization tools via 'plotly' (Sievert,
2020) <https://CRAN.R-project.org/package=plotly> and 'reactable'
(Glaz, 2023) <https://CRAN.R-project.org/package=reactable>. The
package also incorporates macroeconomic datasets from the U.S. Bureau
of Economic Analysis: Disposable Personal Income (DPI)
<https://fred.stlouisfed.org/series/DPI>, Gross Domestic Product (GDP)
<https://fred.stlouisfed.org/series/GDP>, and Personal Consumption
Expenditures (PCEC) <https://fred.stlouisfed.org/series/PCEC>.
%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
%license %{rlibdir}/%{packname}/LICENSE
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%{rlibdir}/%{packname}/doc
%{rlibdir}/%{packname}/figures
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%changelog
