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MCKL
Monte Carlo Kernel Library
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Particle Markov chain Monte Carlo mutation. More...
#include <mckl/algorithm/pmcmc.hpp>
Public Types | |
| using | eval_type = std::function< double(typename Particle< T >::rng_type &, param_type &)> |
| using | param_type = Param |
| using | pf_type = SMCSampler< T, U > |
| using | prior_type = std::function< double(const param_type &)> |
| using | size_type = typename Particle< T >::size_type |
| using | state_type = T |
Public Member Functions | |
| template<typename Prior , typename... Args> | |
| PMCMCMutation (std::size_t N, std::size_t M, Prior &&prior, Args &&... args) | |
| PMCMCMutation< Param, T, U > | clone () const |
| std::size_t | operator() (std::size_t iter, param_type ¶m) |
| pf_type & | pf () |
| pf_type & | pf () const |
| template<typename Prior > | |
| void | prior (Prior &&prior) |
| void | reset () |
| template<typename Eval > | |
| std::size_t | update (Eval &&eval) |
| Add a new evaluation object for the update step. More... | |
Particle Markov chain Monte Carlo mutation.
| using mckl::PMCMCMutation< Param, T, U >::eval_type = std::function<double(typename Particle<T>::rng_type &, param_type &)> |
| using mckl::PMCMCMutation< Param, T, U >::param_type = Param |
| using mckl::PMCMCMutation< Param, T, U >::pf_type = SMCSampler<T, U> |
| using mckl::PMCMCMutation< Param, T, U >::prior_type = std::function<double(const param_type &)> |
| using mckl::PMCMCMutation< Param, T, U >::size_type = typename Particle<T>::size_type |
| using mckl::PMCMCMutation< Param, T, U >::state_type = T |
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1.8.13