%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  actuary
%global packver   0.1.2
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          0.1.2
Release:          1%{?dist}%{?buildtag}
Summary:          Actuarial Functions and Utilities

License:          MIT + file LICENSE
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 4.1.0
Requires:         R-core >= 4.1.0
BuildArch:        noarch
BuildRequires:    R-CRAN-dplyr 
BuildRequires:    R-CRAN-dtplyr 
BuildRequires:    R-CRAN-forcats 
BuildRequires:    R-CRAN-furrr 
BuildRequires:    R-CRAN-future 
BuildRequires:    R-CRAN-gamlss.dist 
BuildRequires:    R-CRAN-ggplot2 
BuildRequires:    R-CRAN-ggtext 
BuildRequires:    R-grDevices 
BuildRequires:    R-CRAN-MASS 
BuildRequires:    R-CRAN-pracma 
BuildRequires:    R-CRAN-progress 
BuildRequires:    R-CRAN-purrr 
BuildRequires:    R-CRAN-rlang 
BuildRequires:    R-CRAN-scales 
BuildRequires:    R-stats 
BuildRequires:    R-CRAN-tidyr 
BuildRequires:    R-CRAN-yardstick 
Requires:         R-CRAN-dplyr 
Requires:         R-CRAN-dtplyr 
Requires:         R-CRAN-forcats 
Requires:         R-CRAN-furrr 
Requires:         R-CRAN-future 
Requires:         R-CRAN-gamlss.dist 
Requires:         R-CRAN-ggplot2 
Requires:         R-CRAN-ggtext 
Requires:         R-grDevices 
Requires:         R-CRAN-MASS 
Requires:         R-CRAN-pracma 
Requires:         R-CRAN-progress 
Requires:         R-CRAN-purrr 
Requires:         R-CRAN-rlang 
Requires:         R-CRAN-scales 
Requires:         R-stats 
Requires:         R-CRAN-tidyr 
Requires:         R-CRAN-yardstick 

%description
Provides actuarial modeling tools for Monte Carlo loss simulations, loss
reserving, and reinsurance layer loss calculations. It enables users to
generate stochastic loss datasets with customisable frequency and severity
distributions, fit development patterns to claim triangles, and calculate
reinsurance losses for occurrence and aggregate layers with user-defined
retentions, limits, and reinstatements. For development pattern selection,
the package includes a machine learning approach that evaluates multiple
reserving models using holdout validation to identify the best-fitting
pattern based on predictive accuracy, this is based on the algorithm
described in Richman, R and Balona, C
(2020)<https://www.ssrn.com/abstract=3697256>.

%prep
%setup -q -c -n %{packname}

# fix end of executable files
find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;
# prevent binary stripping
[ -d %{packname}/src ] && find %{packname}/src -type f -exec \
  sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true
[ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \
  sed -i 's@-g0@@g' {} \; || true
# don't allow local prefix in executable scripts
find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \;

%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
# remove buildroot from installed files
find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \;

%files
%{rlibdir}/%{packname}