Template Class CRejectionSamplingCapable

Class Documentation

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
class CRejectionSamplingCapable

A base class for implementing rejection sampling in a generic state space. See the main method CRejectionSamplingCapable::rejectionSampling To use this class, create your own class as a child of this one and implement the desired virtual methods, and add any required internal data.

Public Types

using TParticle = CProbabilityParticle<TStateSpace, STORAGE>

Public Functions

virtual ~CRejectionSamplingCapable() = default

Virtual destructor

inline void rejectionSampling(size_t desiredSamples, std::vector<TParticle> &outSamples, size_t timeoutTrials = 1000)

Generates a set of N independent samples via rejection sampling.

Parameters:

  • desiredSamples – The number of desired samples to generate

  • outSamples – The output samples.

  • timeoutTrials – The maximum number of rejection trials for each generated sample (i.e. the maximum number of iterations). This can be used to set a limit to the time complexity of the algorithm for difficult probability densities. All will have equal importance weights (a property of rejection sampling), although those samples generated at timeout will have a different importance weights.

Protected Functions

virtual void RS_drawFromProposal(TStateSpace &outSample) = 0

Generates one sample, drawing from some proposal distribution.

virtual double RS_observationLikelihood(const TStateSpace &x) = 0

Returns the NORMALIZED observation likelihood (linear, not exponential!!!) at a given point of the state space (values in the range [0,1]).