File R-PrInDT.spec of Package R-PrInDT
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# Spec file for package PrInDT
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# esp. Description and Summary. Improvements in that area should be
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%global packname PrInDT
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 2.0.2
Release: 0
Summary: Prediction and Interpretation in Decision Trees for Classification and Regression
Group: Development/Libraries/Other
License: GPL-2
URL: http://cran.r-project.org/web/packages/%{packname}
Source: PrInDT_2.0.2.tar.gz
Requires: R-base
Requires: R-party
Requires: R-splitstackshape
Requires: R-stringr
Requires: R-gdata
Requires: R-gtools
Requires: R-mvtnorm
Requires: R-modeltools
Requires: R-strucchange
Requires: R-coin
Requires: R-zoo
Requires: R-sandwich
Requires: R-data.table
Requires: R-cli
Requires: R-glue
Requires: R-lifecycle
Requires: R-magrittr
Requires: R-rlang
Requires: R-stringi
Requires: R-vctrs
Requires: R-libcoin
Requires: R-matrixStats
Requires: R-multcomp
Requires: R-TH.data
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse}
# # Three others commonly needed
# BuildRequires: tex(ae.sty)
# BuildRequires: tex(fancyvrb.sty)
# BuildRequires: tex(inconsolata.sty)
# BuildRequires: tex(natbib.sty)
# %else
# BuildRequires: texlive
# %endif
# BuildRequires: texinfo
BuildRequires: fdupes
BuildRequires: R-base
BuildRequires: R-party
BuildRequires: R-splitstackshape
BuildRequires: R-stringr
BuildRequires: R-gdata
BuildRequires: R-gtools
BuildRequires: R-mvtnorm
BuildRequires: R-modeltools
BuildRequires: R-strucchange
BuildRequires: R-coin
BuildRequires: R-zoo
BuildRequires: R-sandwich
BuildRequires: R-data.table
BuildRequires: R-cli
BuildRequires: R-glue
BuildRequires: R-lifecycle
BuildRequires: R-magrittr
BuildRequires: R-rlang
BuildRequires: R-stringi
BuildRequires: R-vctrs
BuildRequires: R-libcoin
BuildRequires: R-matrixStats
BuildRequires: R-multcomp
BuildRequires: R-TH.data
%description
Optimization of conditional inference trees from the package 'party'
for classification and regression. For optimization, the model space is
searched for the best tree on the full sample by means of repeated
subsampling. Restrictions are allowed so that only trees are accepted
which do not include pre-specified uninterpretable split results (cf.
Weihs & Buschfeld, 2021a). The function PrInDT() represents the basic
resampling loop for 2-class classification (cf. Weihs & Buschfeld,
2021a). The function RePrInDT() (repeated PrInDT()) allows for repeated
applications of PrInDT() for different percentages of the observations
of the large and the small classes (cf. Weihs & Buschfeld, 2021c). The
function NesPrInDT() (nested PrInDT()) allows for an extra layer of
subsampling for a specific factor variable (cf. Weihs & Buschfeld,
2021b). The functions PrInDTMulev() and PrInDTMulab() deal with
multilevel and multilabel classification. In addition to these PrInDT()
variants for classification, the function PrInDTreg() has been
developed for regression problems. Finally, the function PostPrInDT()
allows for a posterior analysis of the distribution of a specified
variable in the terminal nodes of a given tree. In version 2,
additionally structured sampling is implemented in functions
PrInDTCstruc() and PrInDTRstruc(). In these functions, repeated
measurements data can be analyzed, too. Moreover, multilabel 2-stage
versions of classification and regression trees are implemented in
functions C2SPrInDT() and R2SPrInDT() as well as interdependent
multilabel models in functions SimCPrInDT() and SimRPrInDT(). Finally,
for mixtures of classification and regression models functions
Mix2SPrInDT() and SimMixPrInDT() are implemented. Most of these
extensions of PrInDT are described in Buschfeld & Weihs (2025Fc).
References: -- Buschfeld, S., Weihs, C. (2025Fc) "Optimizing decision
trees for the analysis of World Englishes and sociolinguistic data",
Cambridge Elements. -- Weihs, C., Buschfeld, S. (2021a) "Combining
Prediction and Interpretation in Decision Trees (PrInDT) - a Linguistic
Example" <doi:10.48550/arXiv.2103.02336>; -- Weihs, C., Buschfeld, S.
(2021b) "NesPrInDT: Nested undersampling in PrInDT"
<doi:10.48550/arXiv.2103.14931>; -- Weihs, C., Buschfeld, S. (2021c)
"Repeated undersampling in PrInDT (RePrInDT): Variation in
undersampling and prediction, and ranking of predictors in ensembles"
<doi:10.48550/arXiv.2108.05129>.
%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
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%changelog
