Computes a variational approximation to posterior from posterior samples. More...
#include "update_impls.hpp"
Public Types | |
| using | typed_map_ = typed_map< Policy, I, Ts... > |
 Public Types inherited from Update< ParameterMatching, Policy, FilterValueType< O, Ts... >, I, O, Ts... > | |
| using | typed_map_ = typed_map< Policy, I, Ts... > |
Public Member Functions | |
| typed_map_ | operator() (FilterValueType< O, Ts... > &result) |
| Public Member Functions inherited from Update< ParameterMatching, Policy, FilterValueType< O, Ts... >, I, O, Ts... > | |
| typed_map_ | operator() (FilterValueType< O, Ts... > &result) |
| Calls derived implementation. More... | |
Additional Inherited Members | |
| Public Attributes inherited from Update< ParameterMatching, Policy, FilterValueType< O, Ts... >, I, O, Ts... > | |
| upp_t< Policy, I, O, Ts... > & | f |
Detailed Description
template<template< typename > class Policy, typename I, typename O, typename... Ts>
struct ParameterMatching< Policy, FilterValueType< O, Ts... >, I, O, Ts... >
Computes a variational approximation to posterior from posterior samples.
Given samples from the posterior (e.g., as computed by importance sampling or MCMC methods), parameter_matching computes a factorized functional approximation to the posterior suitable for use in message passing or as a new prior distribution for filtering applications.
parameter_matching assumes that the posterior factors as \(p(z_1,...|x) = \prod_{n \geq 1} p_{\psi_n'}(z_n)\), where each component of the density has the same functional form as its counterpart in the prior. The algorithms to compute the optimal parameters \(\psi_n'\) are left up to the implementation.
- Template Parameters
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Policy I O Ts
The documentation for this struct was generated from the following file:
- lib/update/update_impls.hpp
