DenseCanonicalGaussian

Value Members

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

   Definition Classes

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

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3. final def ##(): Int

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4. def *(that: DenseCanonicalGaussian)(implicit multOp: multOp[DenseCanonicalGaussian]): DenseCanonicalGaussian

   Definition Classes

   NumericOps

5. def /(that: DenseCanonicalGaussian)(implicit divideOp: divideOp[DenseCanonicalGaussian]): DenseCanonicalGaussian

   Definition Classes

   NumericOps

6. final def ==(arg0: AnyRef): Boolean

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

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8. final def asInstanceOf[T0]: T0

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9. def clone(): AnyRef

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   protected[java.lang]

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   @throws( ... )

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

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11. def extend(size: Int, startIndex: Int): DenseCanonicalGaussian

    Extends the scope of Gaussian.

    Extends the scope of Gaussian. It is useful for * and / operations on Gaussians with different variables.

    size

    The size of extended Gaussian

    startIndex

    The position of this Gaussian in the new extended Gaussian

12. def finalize(): Unit

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    protected[java.lang]

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    @throws( classOf[java.lang.Throwable] )

13. val g: Double

    See Canonical Gaussian definition

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

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15. def getLogP(): Double

    Returns logarithm of normalisation constant.

16. val h: Matrix

    See Canonical Gaussian definition

17. final def isInstanceOf[T0]: Boolean

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18. val k: Matrix

    See Canonical Gaussian definition

19. def marginal(varIndexes: Int*): DenseCanonicalGaussian

    Marginalise out all variables except of the variables at given indexes

20. def marginal(varIndex1: Int, varIndex2: Int): DenseCanonicalGaussian

    Marginalise out all variables except of the variables at a given indexes

21. def marginal(varIndex: Int): DenseCanonicalGaussian

    Marginalise out all variables except of the variable at a given index

22. def marginalise(varIndex: Int): DenseCanonicalGaussian

    Returns gaussian integral marginalising out the variable at a given index

23. lazy val mean: Matrix

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

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25. final def notify(): Unit

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26. final def notifyAll(): Unit

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27. def pdf(x: Matrix): Double

    Returns the value of probability density function for a given value of vector x.

28. def pdf(x: Double): Double

    Returns the value of probability density function for a given value of x.

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

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30. def toGaussian(): Gaussian

31. lazy val variance: Matrix

32. final def wait(): Unit

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

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

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35. def withEvidence(varIndex: Int, varValue: Double): DenseCanonicalGaussian

    Returns canonical gaussian given evidence.