Samplers System
The sampler system within MOOSE provides an API for creating samples of distributions, primarily for use with the Stochastic Tools module.
Available Objects
- Stochastic Tools App
- AISActiveLearningAdaptive Importance Sampler with Gaussian Process Active Learning.
- ActiveLearningMonteCarloSamplerMonte Carlo Sampler for active learning with surrogate model.
- AdaptiveImportanceAdaptive Importance Sampler.
- AffineInvariantDESPerform Affine Invariant Ensemble MCMC with differential sampler.
- AffineInvariantStretchSamplerPerform Affine Invariant Ensemble MCMC with stretch sampler.
- CSVSamplerSampler that reads samples from CSV file.
- Cartesian1DProvides complete Cartesian product for the supplied variables.
- CartesianProductProvides complete Cartesian product for the supplied variables.
- CartesianProductSamplerProvides complete Cartesian product for the supplied variables.
- IndependentGaussianMHPerform M-H MCMC sampling with independent Gaussian propoposals.
- InputMatrixSampler that utilizes a sampling matrix defined at input.
- LatinHypercubeLatin Hypercube Sampler.
- MonteCarloMonte Carlo Sampler.
- MonteCarloSamplerMonte Carlo Sampler.
- MorrisSamplerMorris variance-based sensitivity analysis Sampler.
- NestedMonteCarloMonte Carlo sampler for nested loops of parameters.
- PMCMCBaseParallel Markov chain Monte Carlo base.
- ParallelSubsetSimulationParallel Subset Simulation sampler.
- QuadratureQuadrature sampler for Polynomial Chaos.
- QuadratureSamplerQuadrature sampler for Polynomial Chaos.
- SobolSobol variance-based sensitivity analysis Sampler.
- SobolSamplerSobol variance-based sensitivity analysis Sampler.
- VectorPostprocessorSamplerThe sampler uses vector postprocessors as inputs.