File R-nestedLogit.spec of Package R-nestedLogit
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# Spec file for package nestedLogit
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%global packname nestedLogit
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 0.3.2
Release: 0
Summary: Nested Dichotomy Logistic Regression Models
Group: Development/Libraries/Other
License: GPL (>= 2)
URL: http://cran.r-project.org/web/packages/%{packname}
Source: nestedLogit_0.3.2.tar.gz
Requires: R-base
Requires: R-broom
Requires: R-car
Requires: R-dplyr
Requires: R-effects
Requires: R-stringr
Requires: R-tibble
Requires: R-backports
Requires: R-cli
Requires: R-generics
Requires: R-glue
Requires: R-lifecycle
Requires: R-purrr
Requires: R-rlang
Requires: R-tidyr
Requires: R-carData
Requires: R-abind
Requires: R-Formula
Requires: R-pbkrtest
Requires: R-quantreg
Requires: R-lme4
Requires: R-scales
Requires: R-magrittr
Requires: R-pillar
Requires: R-R6
Requires: R-tidyselect
Requires: R-vctrs
Requires: R-colorspace
Requires: R-survey
Requires: R-estimability
Requires: R-insight
Requires: R-stringi
Requires: R-pkgconfig
Requires: R-minqa
Requires: R-nloptr
Requires: R-reformulas
Requires: R-Rcpp
Requires: R-RcppEigen
Requires: R-numDeriv
Requires: R-doBy
Requires: R-utf8
Requires: R-SparseM
Requires: R-MatrixModels
Requires: R-farver
Requires: R-labeling
Requires: R-RColorBrewer
Requires: R-viridisLite
Requires: R-mitools
Requires: R-RcppArmadillo
Requires: R-cpp11
Requires: R-withr
Requires: R-cowplot
Requires: R-Deriv
Requires: R-ggplot2
Requires: R-modelr
Requires: R-microbenchmark
Requires: R-DBI
Requires: R-Rdpack
Requires: R-gtable
Requires: R-isoband
Requires: R-S7
Requires: R-rbibutils
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse}
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BuildRequires: R-DBI
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BuildRequires: R-S7
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Suggests: R-carData
Suggests: R-geomtextpath
Suggests: R-ggplot2
Suggests: R-ggeffects
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%description
Provides functions for specifying and fitting nested dichotomy logistic
regression models for a multi-category response and methods for
summarising and plotting those models. Nested dichotomies are
statistically independent, and hence provide an additive decomposition
of tests for the overall 'polytomous' response. When the dichotomies
make sense substantively, this method can be a simpler alternative to
the standard 'multinomial' logistic model which compares response
categories to a reference level. See: J. Fox (2016), "Applied
Regression Analysis and Generalized Linear Models", 3rd Ed., ISBN
1452205663.
%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}/WORDLIST
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%changelog
