| getConvergenceThreshold() | hops::RunBase< Model, Proposal > | |
| getData() | hops::RunBase< Model, Proposal > | |
| getFisherWeight() | hops::RunBase< Model, Proposal > | |
| getMarkovChainType() | hops::RunBase< Model, Proposal > | |
| getMaxRepetitions() | hops::RunBase< Model, Proposal > | |
| getNumberOfChains() | hops::RunBase< Model, Proposal > | |
| getNumberOfSamples() | hops::RunBase< Model, Proposal > | |
| getProblem() | hops::RunBase< Model, Proposal > | |
| getRandomSeed() | hops::RunBase< Model, Proposal > | |
| getSamplingUntilConvergence() | hops::RunBase< Model, Proposal > | |
| getStartingPoints() | hops::RunBase< Model, Proposal > | |
| getStepSize() | hops::RunBase< Model, Proposal > | |
| getThinning() | hops::RunBase< Model, Proposal > | |
| getUseRounding() | hops::RunBase< Model, Proposal > | |
| init() | hops::RunBase< Model, Proposal > | inline |
| RunBase(MarkovChainType markovChainType, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1) | hops::RunBase< Model, Proposal > | inline |
| RunBase(const Problem< Model > &problem, MarkovChainType markovChainType=MarkovChainType::HitAndRun, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1) | hops::RunBase< Model, Proposal > | inline |
| RunBase(Proposal m_proposal, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1) | hops::RunBase< Model, Proposal > | inline |
| RunBase(const Problem< Model > &problem, Proposal m_proposal, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1) | hops::RunBase< Model, Proposal > | inline |
| RunBase()=default | hops::RunBase< Model, Proposal > | |
| sample() | hops::RunBase< Model, Proposal > | inline |
| sample(unsigned long numberOfSamples, unsigned long thinning=1) | hops::RunBase< Model, Proposal > | inline |
| setConvergenceThreshold(double convergenceThreshold) | hops::RunBase< Model, Proposal > | |
| setFisherWeight(double fisherWeight) | hops::RunBase< Model, Proposal > | |
| setMarkovChainType(MarkovChainType markovChainType) | hops::RunBase< Model, Proposal > | |
| setMaxRepetitions(double maxRepetitions) | hops::RunBase< Model, Proposal > | |
| setNumberOfChains(unsigned long numberOfChains) | hops::RunBase< Model, Proposal > | |
| setNumberOfSamples(unsigned long numberOfSamples) | hops::RunBase< Model, Proposal > | |
| setProblem(const Problem< Model > &problem) | hops::RunBase< Model, Proposal > | |
| setRandomSeed(double randomSeed) | hops::RunBase< Model, Proposal > | |
| setSamplingUntilConvergence(bool sampleUntilConvergence) | hops::RunBase< Model, Proposal > | |
| setStartingPoints(const std::vector< Eigen::VectorXd > &startingPoints) | hops::RunBase< Model, Proposal > | |
| setStepSize(double stepSize) | hops::RunBase< Model, Proposal > | |
| setThinning(unsigned long thinning) | hops::RunBase< Model, Proposal > | |
| setUseRounding(bool useRounding) | hops::RunBase< Model, Proposal > | |
| tune(RunBase &run, AcceptanceRateTuner::param_type ¶meters) | hops::RunBase< Model, Proposal > | friend |
| tune(RunBase &run, ExpectedSquaredJumpDistanceTuner::param_type ¶meters) | hops::RunBase< Model, Proposal > | friend |
| tune(RunBase &run, SimpleExpectedSquaredJumpDistanceTuner::param_type ¶meters) | hops::RunBase< Model, Proposal > | friend |
