File R-activityGCMM.spec of Package R-activityGCMM

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# Spec file for package activityGCMM 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
# discussed with upstream. 
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%global packname  activityGCMM 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.1.1 
Release:        0 
Summary:        Circular Mixed Effect Mixture Models of Animal Activity Patterns 
Group:          Development/Libraries/Other 
License:        GPL (>= 2) 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         activityGCMM_1.1.1.tar.gz 
Requires:       R-base 
Requires:	R-mclust
Requires:	R-runjags
Requires:	R-circular
Requires:	R-overlap
Requires:	R-mvtnorm
Requires:	R-coda
 
# %%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-mclust
BuildRequires: 	R-runjags
BuildRequires: 	R-circular
BuildRequires: 	R-overlap
BuildRequires: 	R-mvtnorm
BuildRequires: 	R-coda
 
%description 
Bayesian parametric generalized circular mixed effect mixture models 
(GCMMs) for estimating animal activity patterns from camera trap data 
and other nested data structures using 'JAGS', including automatic 
Bayesian k-cluster selection and random circular intercepts for nested 
data. The GCMM function automatically selects the number of components 
for the mixture model (supporting up to 4 mixture components) based on 
a Bayesian linear finite normal mixture model and fits a Bayesian 
parametric circular mixed effect mixture model with one or two random 
effects as random circular intercepts with a a von Mises or wrapped 
Cauchy distribution. Provides graphs of the combined mixture model or 
separate mixture components. Functionality is provided to allow 
quantitative comparisons between model parameters. See Campbell et al. 
(in press) It's time to expand our analyses of animal activity; 
Campbell et al. (in press) Temporal and microspatial niche 
partitioning; Campbell et al. (in press) A novel approach to comparing 
animal activity patterns. News, updates, and tutorials will be 
available on www.atlasgoldenwolf.org/stats and 
www.github.com/LizADCampbell . 
 
%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