object CollapsedGibbs

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Type Members

  1. type Block = List[Variable[_]]
  2. type BlockInfo = (Block, List[Factor[Double]])
  3. type BlockSamplerCreator = (BlockInfo) ⇒ BlockSampler

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  4. def apply(strategy: String, collapseParameters: Seq[Int], dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs with AnytimeProbQuerySampler with ChainApplyBlockingGibbs

    Create an anytime collapsed Gibbs sampler using the given strategy, parameters, dependent universes and algorithm, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  5. def apply(strategy: String, dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs with AnytimeProbQuerySampler with ChainApplyBlockingGibbs

    Create an anytime collapsed Gibbs sampler using the given strategy (with default parameters), given dependent universes and algorithm, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  6. def apply(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the default strategy with default paramters, given dependent universes and algorithm, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  7. def apply(strategy: String, collapseParameters: Seq[Int], burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the given number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  8. def apply(strategy: String, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the given strategy, number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  9. def apply(burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the default strategy with default parameters, given number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  10. def apply(strategy: String, collapseParameters: Seq[Int], targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the given strategy, parameters, and target elements.

  11. def apply(strategy: String, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the given strategy and target elements.

  12. def apply(targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create an anytime collapsed Gibbs sampler using the given target elements.

  13. def apply(strategy: String, collapseParameters: Seq[Int], dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs with OneTimeProbQuerySampler with ChainApplyBlockingGibbs

    Create a one-time collapsed Gibbs sampler using the given strategy and parameters, dependent universes and algorithm, the number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  14. def apply(strategy: String, dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs with OneTimeProbQuerySampler with ChainApplyBlockingGibbs

    Create a one-time collapsed Gibbs sampler using the given strategy, dependent universes and algorithm, the number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  15. def apply(dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double, mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the default strategy with default parameters, given dependent universes and algorithm, the number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  16. def apply(strategy: String, collapseParameters: Seq[Int], mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the specified strategy and parameters, number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  17. def apply(strategy: String, mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the given strategy, number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

    Create a one-time collapsed Gibbs sampler using the given strategy, number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements. Uses the default params for the strategy.

  18. def apply(mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the given number of samples, the number of samples to burn in, the sampling interval, the BlockSampler generator, and target elements.

  19. def apply(strategy: String, collapseParameters: Seq[Int], mySamples: Int, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the specified strategy and parameters, and the given number of samples and target elements.

  20. def apply(strategy: String, mySamples: Int, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the given strategy for collapsing, number of samples, and target elements.

    Create a one-time collapsed Gibbs sampler using the given strategy for collapsing, number of samples, and target elements. Uses the default params for the strategy.

  21. def apply(mySamples: Int, targets: Element[_]*)(implicit universe: Universe): CollapsedProbQueryGibbs

    Create a one-time collapsed Gibbs sampler using the given number of samples and target elements.

    Create a one-time collapsed Gibbs sampler using the given number of samples and target elements. This sampler will use the default collapsing strategy (Heuristic) and default params for that strategy.

  22. final def asInstanceOf[T0]: T0
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  23. def clone(): AnyRef
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  24. final def eq(arg0: AnyRef): Boolean
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  26. def finalize(): Unit
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  27. final def getClass(): Class[_]
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  28. def hashCode(): Int
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  29. final def isInstanceOf[T0]: Boolean
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  30. final def ne(arg0: AnyRef): Boolean
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  31. final def notify(): Unit
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  32. final def notifyAll(): Unit
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  33. def probability[T](target: Element[T], value: T): Double

    Use Gibbs sampling to compute the probability that the given element has the given value.

  34. def probability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

    Use Gibbs sampling to compute the probability that the given element satisfies the given predicate.

  35. final def synchronized[T0](arg0: ⇒ T0): T0
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  36. def toString(): String
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  37. final def wait(): Unit
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  38. final def wait(arg0: Long, arg1: Int): Unit
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  39. final def wait(arg0: Long): Unit
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