1 #ifndef STAN_MATH_PRIM_MAT_FUN_WELFORD_VAR_ESTIMATOR_HPP
2 #define STAN_MATH_PRIM_MAT_FUN_WELFORD_VAR_ESTIMATOR_HPP
28 Eigen::VectorXd delta(q -
_m);
30 _m2 += delta.cwiseProduct(q -
_m);
welford_var_estimator(int n)
Independent (input) and dependent (output) variables for gradients.
(Expert) Numerical traits for algorithmic differentiation variables.
void sample_mean(Eigen::VectorXd &mean)
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
void add_sample(const Eigen::VectorXd &q)
void sample_variance(Eigen::VectorXd &var)