Gibbs

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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

   

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

5. def apply(burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): ProbQueryGibbs with AnytimeProbQuerySampler with ChainApplyBlockingGibbs

   

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

6. def apply(targets: Element[_]*)(implicit universe: Universe): ProbQueryGibbs with AnytimeProbQuerySampler with ChainApplyBlockingGibbs

   

   Create an anytime Gibbs sampler using the given target elements.

7. 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): ProbQueryGibbs with OneTimeProbQuerySampler with ChainApplyBlockingGibbs

   

   Create a one-time Gibbs sampler using the 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.

8. def apply(mySamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator, targets: Element[_]*)(implicit universe: Universe): ProbQueryGibbs with OneTimeProbQuerySampler with ChainApplyBlockingGibbs

   

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

9. def apply(mySamples: Int, targets: Element[_]*)(implicit universe: Universe): ProbQueryGibbs with OneTimeProbQuerySampler with ChainApplyBlockingGibbs

   

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

10. final def asInstanceOf[T0]: T0

    

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11. def clone(): AnyRef

    

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    protected[java.lang]

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12. final def eq(arg0: AnyRef): Boolean

    

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13. def equals(arg0: Any): Boolean

    

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14. def finalize(): Unit

    

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15. final def getClass(): Class[_]

    

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16. def hashCode(): Int

    

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17. final def isInstanceOf[T0]: Boolean

    

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18. final def ne(arg0: AnyRef): Boolean

    

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19. final def notify(): Unit

    

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20. final def notifyAll(): Unit

    

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21. def probability[T](target: Element[T], value: T): Double

    

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

22. 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.

23. final def synchronized[T0](arg0: ⇒ T0): T0

    

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24. def toString(): String

    

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25. final def wait(): Unit

    

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26. final def wait(arg0: Long, arg1: Int): Unit

    

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27. final def wait(arg0: Long): Unit

    

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