sampling

Type Members

1. class AnytimeElementSampler extends ElementSampler with UnweightedSampler with AnytimeProbQuerySampler

   

   Anytime Element sampler.

2. trait AnytimeMPESampler extends AnytimeSampler with AnytimeMPE

   

   Anytime sampling algorithms that compute MPE.

3. class AnytimeMetropolisHastings extends MetropolisHastings with UnweightedSampler with AnytimeProbQuerySampler

   

   Anytime Metropolis-Hastings sampler.

4. class AnytimeMetropolisHastingsAnnealer extends MetropolisHastingsAnnealer with AnytimeMPESampler

   

   Anytime Metropolis-Hastings annealer.

5. trait AnytimeProbEvidenceSampler extends AnytimeSampler with AnytimeProbEvidence

   

   Anytime sampling algorithms that compute probability of evidence.

6. trait AnytimeProbQuerySampler extends AnytimeProbQuery with AnytimeSampler

   

   Anytime sampling algorithms that compute conditional probability of query elements.

7. trait AnytimeSampler extends Algorithm with Anytime with Sampler

   

   Anytime sampling algorithms.

8. trait BaseProbQuerySampler[U[_]] extends BaseProbQueryAlgorithm[U]

   

   A base trait for sampling algorithms that compute conditional probabilities of queries, and that use the projection of all the samples of a target variable to calculate the distribution of that variable or the expectation of a function on that variable.

   A base trait for sampling algorithms that compute conditional probabilities of queries, and that use the projection of all the samples of a target variable to calculate the distribution of that variable or the expectation of a function on that variable. Generic type U is either Element or Reference.

9. abstract class BaseUnweightedSampler extends Sampler

   

   Samplers that use samples without weights.

10. case class DisjointScheme(choices: (Double, () ⇒ ProposalScheme)*) extends ProposalScheme with Product with Serializable

    

    A proposal scheme that chooses between different proposal schemes, each with a probability.

    A proposal scheme that chooses between different proposal schemes, each with a probability.

    choices

    A variable list of pairs of probabilities and proposal schemes.

11. abstract class ElementSampler extends BaseUnweightedSampler

    

    An abstract class to generates samples from the marginal distribution of an element.

12. case class FinalScheme(element: () ⇒ Element[_]) extends ProposalScheme with Product with Serializable

    

    A proposal scheme that consists of proposing a single element.

    A proposal scheme that consists of proposing a single element.

    element

    The element to propose

13. class ForwardWeighter extends LikelihoodWeighter

    

14. abstract class Importance extends WeightedSampler

    

    Importance samplers.

15. class LikelihoodWeighter extends AnyRef

    

    A class that implements sampling via likelihood weighting on a set of elements.

16. abstract class MetropolisHastings extends BaseUnweightedSampler

    

    Metropolis-Hastings samplers.

17. abstract class MetropolisHastingsAnnealer extends MetropolisHastings with MPEAlgorithm

    

    Metropolis-Hastings based Annealer.

18. class OneTimeElementSampler extends ElementSampler with UnweightedSampler with OneTimeProbQuerySampler

    

    One-time Element sampler.

19. trait OneTimeMPESampler extends OneTimeSampler with OneTimeMPE

    

    One-time sampling algorithms that compute probability of evidence.

20. class OneTimeMetropolisHastings extends MetropolisHastings with UnweightedSampler with OneTimeProbQuerySampler

    

    One-time Metropolis-Hastings sampler.

21. class OneTimeMetropolisHastingsAnnealer extends MetropolisHastingsAnnealer with OneTimeMPESampler

    

    One-time Metropolis-Hastings annealer.

22. trait OneTimeProbEvidenceSampler extends OneTimeSampler with OneTimeProbEvidence

    

    One-time sampling algorithms that compute probability of evidence.

23. trait OneTimeProbQuerySampler extends ProbQueryAlgorithm with OneTimeSampler with OneTimeProbQuery

    

    One-time sampling algorithms that compute conditional probability of query elements.

24. trait OneTimeSampler extends Sampler with OneTime

    

    One-time sampling algorithms.

25. abstract class ProbEvidenceSampler extends ProbEvidenceAlgorithm with Sampler

    

    Algorithm that computes probability of evidence using forward sampling.

    Algorithm that computes probability of evidence using forward sampling. The evidence is specified as NamedEvidence. Only the probability of this evidence is computed. Conditions and constraints that are already on elements are considered part of the definition of the model.

26. trait ProbQuerySampler extends BaseProbQuerySampler[Element]

    

    Sampling algorithms that compute conditional probabilities of queries on elements, and that use the projection of all the samples of a target variable to calculate the distribution of that variable or the expectation of a function on that variable.

27. sealed abstract class ProposalScheme extends AnyRef

    

    Class that describes proposal schemes used in Metropolis-Hastings algorithms.

28. trait Sampler extends Algorithm

    

    A trait for sampling algorithms.

29. class Schedule extends AnyRef

    

    The schedule class determines the annealing schedule in the annealer.

30. case class SwitchScheme[T, U](firstElems: () ⇒ (Element[T], Element[U]), rest: Option[ProposalScheme]) extends ProposalScheme with Product with Serializable

    

    Proposes switching the randomness of two elements and optionally continues with another proposal scheme.

    Proposes switching the randomness of two elements and optionally continues with another proposal scheme.

    firstElems

    The two elements whose randomness is switched.

    rest

    The optional proposal scheme.

31. case class TypedScheme[T](first: () ⇒ Element[T], rest: (T) ⇒ Option[ProposalScheme]) extends ProposalScheme with Product with Serializable

    

    A proposal scheme that proposes a first element and optionally continues with another proposal scheme based on the value of the first element.

    A proposal scheme that proposes a first element and optionally continues with another proposal scheme based on the value of the first element.

    first

    The first element to propose.

    rest

    An optional proposal scheme that is invoked conditioned on the value of the first element.

32. case class UntypedScheme(first: () ⇒ Element[_], rest: Option[ProposalScheme]) extends ProposalScheme with Product with Serializable

    

    A proposal scheme that proposes a first element and optionally continues with another proposal scheme.

    A proposal scheme that proposes a first element and optionally continues with another proposal scheme.

    first

    The first element to propose.

    rest

    An optional proposal scheme that is invoked after the first element is proposed.

33. trait UnweightedSampler extends BaseUnweightedSampler with ProbQuerySampler

    

34. abstract class WeightedSampler extends ProbQuerySampler with Sampler

    

    Samplers that use weighted samples.