Author: Stan Development Team
Date: 2018-09-12

# Using the Stan Math C++ Library

#### Stan Development Team

#### 2018-09-12

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

    LinkingTo: StanHeaders

in the DESCRIPTION file of another package (possibly with a minimum version). 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` with something like

    STANHEADERS_SRC = `"$(R_HOME)/bin$(R_ARCH_BIN)/Rscript" --vanilla \
      -e "cat(system.file('include', 'src', package = 'StanHeaders'))"`
    PKG_CPPFLAGS = -I"$(STANHEADERS_SRC)"

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 included headers

    // [[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 the same vector
    }
    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