1 #ifndef STAN__MCMC__ADAPT__DIAG__E__NUTS__BETA
2 #define STAN__MCMC__ADAPT__DIAG__E__NUTS__BETA
15 template <
typename M,
class BaseRNG>
22 std::ostream* o = &std::cout, std::ostream*
e = 0):
void complete_adaptation(double &epsilon)
void disengage_adaptation()
double accept_stat() const
void learn_stepsize(double &epsilon, double adapt_stat)
sample transition(sample &init_sample)
adapt_diag_e_nuts(M &m, BaseRNG &rng, std::ostream *o=&std::cout, std::ostream *e=0)
stepsize_adaptation stepsize_adaptation_
virtual void disengage_adaptation()
sample transition(sample &init_sample)
double e()
Return the base of the natural logarithm.
var_adaptation var_adaptation_
fvar< T > log(const fvar< T > &x)
bool learn_variance(Eigen::VectorXd &var, const Eigen::VectorXd &q)