# Using the Stan Math C++ Library

#### Stan Development Team

#### 2019-01-28

The StanHeaders package contains no R functions. To use the Stan Math Library in other packages, it is sufficient to specify

    LinkingTo: StanHeaders (>= 2.18.1)

in the DESCRIPTION file of another package and

    CXX_STD = CXX14

in the src/Makevars and src/Makevars.win files. If, in addition, the other package needs to utilize the MCMC, optimization, variational inference, or parsing facilities of the Stan Library, then it is also necessary to include the `src` directory of StanHeaders in the other package’s `PKG_CPPFLAGS` in the src/Makevars and src/Makevars.win files with something like

    STANHEADERS_SRC = $(shell "$(R_HOME)/bin$(R_ARCH_BIN)/Rscript" -e "message()" \
        -e "cat(system.file('include', 'src', package = 'StanHeaders', mustWork = TRUE))" \
        -e "message()" | grep "StanHeaders")
    PKG_CPPFLAGS = -I"$(STANHEADERS_SRC)"

in which case there should be a `SystemRequirements: GNU make` in the package’s DESCRIPTION file.

The following is a minimal example of using the Stan Math library via `Rcpp::sourceCpp`: to minimize the function \(\left(\mathbf{x} - \mathbf{a}\right)^\top \left(\mathbf{x} - \mathbf{a}\right)\)

    // [[Rcpp::depends(BH)]]
    // [[Rcpp::depends(RcppEigen)]]
    // [[Rcpp::depends(StanHeaders)]]
    #include <Rcpp.h>
    #include <RcppEigen.h>
    #include <stan/math.hpp>  // pulls in everything; could be more specific with includes

    // [[Rcpp::export]]
    double f(Eigen::VectorXd x, Eigen::VectorXd a) {  // objective function in doubles
      return stan::math::dot_self( (x - a).eval() );  // dot_self() is a dot product with self
    }
    stan::math::var f(Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1> x, Eigen::VectorXd a) {
      return stan::math::dot_self( (x - stan::math::to_var(a)).eval() );  // same but with vars
    }
    // [[Rcpp::export]]
    std::vector<double> g(Eigen::VectorXd x, Eigen::VectorXd a) {  // gradient by AD using Stan
      auto x_var = stan::math::to_var(x);
      std::vector<stan::math::var> theta;
      std::vector<double> grad;
      for (int k = 0; k < x.rows(); k++) theta.push_back(x_var.coeff(k));
      stan::math::var lp = f(x_var, a);
      lp.grad(theta, grad);
      return grad;
    }

    optim(rnorm(3), fn = f, gr = g, a = c(1, 2, 3), method = "BFGS")$par  # Rcpp exported f and g
    #> [1] 1 2 3