Class

infcalcs

GWeight

Related Doc: package infcalcs

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case class GWeight(p: Pair[Double], bt: Tree[Bin]) extends Weight with Product with Serializable

Weight whose weights are generated from a Gaussian probability distribution

p

(mu, sigma) for calculating the Gaussian probability

bt

Tree of Bin instances defining signal space

Linear Supertypes
Serializable, Serializable, Product, Equals, Weight, AnyRef, Any
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Inherited
  1. GWeight
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Weight
  7. AnyRef
  8. Any
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Visibility
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Instance Constructors

  1. new GWeight(p: Pair[Double], bt: Tree[Bin])

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    p

    (mu, sigma) for calculating the Gaussian probability

    bt

    Tree of Bin instances defining signal space

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. val bt: Tree[Bin]

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    Tree of Bin instances defining signal space

  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef

  8. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  10. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  11. val label: String

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    Unique label identifying the weighting function.

    Unique label identifying the weighting function.

    Definition Classes
    GWeight → Weight

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

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    Definition Classes
    AnyRef

  13. final def notify(): Unit

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    Definition Classes
    AnyRef

  14. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  15. val p: Pair[Double]

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    (mu, sigma) for calculating the Gaussian probability

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

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    Definition Classes
    AnyRef

  17. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  20. def weightTable[A](ct: CTable[A])(implicit arg0: Numeric[A]): CTable[Double]

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    Applies the weights to a infcalcs.tables.CTable, generating a new infcalcs.tables.CTable

    Applies the weights to a infcalcs.tables.CTable, generating a new infcalcs.tables.CTable

    Note that the weights must be normalized to the existing distribution of data among the row dimension of the contingency table using the Weight.reWeight function

    Definition Classes
    Weight

  21. val weights: List[Double]

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    Raw weights to be applied to data.

    Raw weights to be applied to data.

    Definition Classes
    GWeight → Weight

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Weight

Inherited from AnyRef

Inherited from Any

Ungrouped