[R-pkg-devel] How to obtain intercept of intercept-only glm in Fortran?

[Michael Weylandt]

This is very cool, but I wonder if it isn't over-kill for the larger
problem.

In general, calculating the coefficient of an intercept-only GLM is just
calculating (a transformation of) the MLE of a univariate exponential
family distribution. (Things may be a bit trickier if the GLM also involves
weights and offsets, not just an intercept, but I'm assuming it doesn't.)

OP: Can you clarify why you want to invoke R's entire GLM machinery as
opposed to just using the closed form solutions?

Michael

On Sat, May 11, 2019 at 7:23 AM Ivan Krylov <krylov.r00t using gmail.com> wrote:

> On Fri, 10 May 2019 16:17:42 +0000
> "Wang, Zhu" <wangz1 using uthscsa.edu> wrote:
>
> > Are there any examples or links for me to follow through more closely?
>
> Calling R functions from C++ is described at
> <http://dirk.eddelbuettel.com/code/rcpp/Rcpp-quickref.pdf> and
> elsewhere in Rcpp documentation. An example follows:
>
> --------------8<--------------glmfit.cpp--------------8<--------------
> #include <algorithm>
> #include <Rcpp.h>
> using namespace Rcpp;
>
> extern "C" double intercept_glm(size_t n, const double * response) {
>         // access functions from default environment
>         Function glm_fit("glm.fit"), coef("coef");
>
>         // intercept-only model: response ~ 1
>         NumericVector x(n);
>         x.fill(1);
>
>         // I couldn't find a way to wrap a double* into a NumericVector
>         // without copying anything, sorry; perhaps someone else
>         // can offer a solution
>         NumericVector y(n);
>         std::copy_n(response, n, y.begin());
>
>         // call the R function, convert the result back
>         return as<double>(coef(glm_fit(x, y)));
> }
> --------------8<--------------glmfit.cpp--------------8<--------------
>
> Since this function is extern "C" and uses only primitive C types, it
> should be fairly easy to call from Fortran. (C is the lingua franca of
> programming languages). Fortran-C interoperability is well described in
> "Modern Fortran Explained" by Metcalf et al. Here is the Fortran side
> of the code:
>
> --------------8<--------------callglm.f90--------------8<--------------
> subroutine callglm(ret)
> use, intrinsic :: iso_c_binding, only: c_size_t, c_double
> ! using iso_c_binding here
> ! - to get correct type of ret when R calls the function
> ! - to convert variables before calling C function
> implicit none
> ! using F77-style arguments to match expectations of .Fortran()
> real(c_double), intent(out) :: ret
> ! toy data to compare against R code later
> real :: y(10) = [10, 11, 20, 9, 10, 8, 11, 45, 2, 3]
>  ! the interface block declares an extern "C" function
>  interface
>   ! double intercept_glm(size_t n, const double * response)
>   function intercept_glm(n, response) bind(c)
>    use, intrinsic :: iso_c_binding
>    real(c_double) :: intercept_glm
>    integer(c_size_t), value :: n
>    real(c_double) :: response(*)
>   end function
>  end interface
>
>  ! call the function as you would call any other function
>  ret = intercept_glm(int(size(y), c_size_t), real(y, c_double))
> end subroutine
> --------------8<--------------callglm.f90--------------8<--------------
>
> For a quick test, make sure that you have Rcpp installed and run:
>
> # adjust R version and path if your library is elsewhere
> PKG_CPPFLAGS='-g -I ~/R/x86_64-pc-linux-gnu-library/3.3/Rcpp/include' \
>         R CMD SHLIB callglm.f90 glmfit.cpp
> R
> library(Rcpp)
> dyn.load('callglm.so') # change extension if needed
> .Fortran('callglm', ret=numeric(1))
> # $ret
> # [1] 12.9
> coef(glm.fit(rep(1, 10), c(10, 11, 20, 9, 10, 8, 11, 45, 2, 3)))
> # [1] 12.9
>
> To use this in a package, place both files in the src/ subdirectory of
> your package and add LinkingTo: Rcpp in the DESCRIPTION.
>
> --
> Best regards,
> Ivan
>
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