Add exp_quad_chol function

[rtrangucci]

Summary:

Generate the cholesky factor of an exponentiated quadratic covariance matrix.

Description:

The prim implementation will look something like this:

template<typename T_x, typename T_alpha, typename T_rho, typename T_sigma>
Eigen::Matrix exp_quad_chol(std::vector<T_x> x,
                            T_alpha alpha,
                            T_rho rho,
                            T_sigma sigma) {
  check_positive("exp_quad_chol", "marginal variance", alpha);
  check_positive("exp_quad_chol", "length-scale", rho);
  check_positive("exp_quad_chol", sigma);
  typedef typename stan::return_type<T_x, T_alpha, T_rho, T_sigma>::type T_scal;
  Eigen::Matrix<T_scal, -1, -1> cov = cov_exp_quad(x, alpha, rho);
  for (int i = 0; i < cov.rows(); ++i)
    cov(i, i) = cov(i, i) + square(sigma);
  Eigen::Matrix<T_scal, -1, -1> L_cov = cholesky_decompose(cov);
  return L_cov
}

Additional Information:

Will need to be coupled with a rename of the parameters in cov_exp_quad. See #495.

Current Version:

v2.14.0

[betanalpha]

For adding the diagonal you’ll want to use Eigen as much as possible, in particular to cast sigma^2 to a diagonal matrix and add it on one go.

…

On Mar 3, 2017, at 3:53 PM, Rob Trangucci ***@***.***> wrote: Summary: Generate the cholesky factor of an exponentiated quadratic covariance matrix. Description: The prim implementation will look something like this: template<typename T_x, typename T_alpha, typename T_rho, typename T_sigma> Eigen::Matrix exp_quad_chol(std::vector<T_x> x, T_alpha alpha, T_rho rho, T_sigma sigma) { check_positive("exp_quad_chol", "marginal variance", alpha); check_positive("exp_quad_chol", "length-scale", rho); check_positive("exp_quad_chol", sigma); typedef typename stan::return_type<T_x, T_alpha, T_rho, T_sigma>::type T_scal; Eigen::Matrix<T_scal, -1, -1> cov = cov_exp_quad(x, alpha, rho); for (int i = 0; i < cov.rows(); ++i) cov(i, i) = cov(i, i) + square(sigma); Eigen::Matrix<T_scal, -1, -1> L_cov = cholesky_decompose(cov); return L_cov } Additional Information: Will need to be coupled with a rename of the parameters in cov_exp_quad. Current Version: v2.14.0 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#501>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABdNlizC2k4e6l69ghbslbeXugMJ1mq6ks5riH3jgaJpZM4MSvBV>.

[bob-carpenter]

Is there an expression template in Eigen to view a single scalar as a diagonal matrix? I know there's a way to view a vector as a diagonal matrix. Can't do this with a C++ cast either way, but I assume Michael was speaking loosely here.

…

On Mar 4, 2017, at 9:57 AM, Michael Betancourt ***@***.***> wrote: For adding the diagonal you’ll want to use Eigen as much as possible, in particular to cast sigma^2 to a diagonal matrix and add it on one go. > On Mar 3, 2017, at 3:53 PM, Rob Trangucci ***@***.***> wrote: > > Summary: > > Generate the cholesky factor of an exponentiated quadratic covariance matrix. > > Description: > > The prim implementation will look something like this: > > template<typename T_x, typename T_alpha, typename T_rho, typename T_sigma> > Eigen::Matrix exp_quad_chol(std::vector<T_x> x, > T_alpha alpha, > T_rho rho, > T_sigma sigma) { > check_positive("exp_quad_chol", "marginal variance", alpha); > check_positive("exp_quad_chol", "length-scale", rho); > check_positive("exp_quad_chol", sigma); > typedef typename stan::return_type<T_x, T_alpha, T_rho, T_sigma>::type T_scal; > Eigen::Matrix<T_scal, -1, -1> cov = cov_exp_quad(x, alpha, rho); > for (int i = 0; i < cov.rows(); ++i) > cov(i, i) = cov(i, i) + square(sigma); > Eigen::Matrix<T_scal, -1, -1> L_cov = cholesky_decompose(cov); > return L_cov > } > Additional Information: > > Will need to be coupled with a rename of the parameters in cov_exp_quad. > > Current Version: > > v2.14.0 > > — > You are receiving this because you are subscribed to this thread. > Reply to this email directly, view it on GitHub <#501>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABdNlizC2k4e6l69ghbslbeXugMJ1mq6ks5riH3jgaJpZM4MSvBV>. > — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or mute the thread.