50#ifndef GUM_WEIGHTED_INFERENCE_H
51#define GUM_WEIGHTED_INFERENCE_H
69 template <
typename GUM_SCALAR >
102#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
Class representing the minimal interface for Bayesian network with no numerical data.
Class for assigning/browsing values to tuples of discrete variables.
SamplingInference(const IBayesNet< GUM_SCALAR > *bn)
default constructor
WeightedSampling(const IBayesNet< GUM_SCALAR > *bn)
Default constructor.
Instantiation draw_(GUM_SCALAR *w, Instantiation prev) override
draws a sample according to Weighted sampling
Instantiation burnIn_() override
draws a defined number of samples without updating the estimators
~WeightedSampling() override
Destructor.
gum is the global namespace for all aGrUM entities
This file contains general methods for simulation-oriented approximate inference.
Implementation of Weighted Sampling for inference in Bayesian networks.