Trait

io.github.mandar2812.dynaml.probability

RandomVarWithDistr

Related Doc: package probability

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trait RandomVarWithDistr[Domain, +Dist <: Density[Domain] with Rand[Domain]] extends RandomVariable[Domain] with HasDistribution[Domain]

A random variable which has a computable probability density.

Domain

The set over which the random variable takes its values.

Dist

A breeze probability density defined on the Domain

Self Type
RandomVarWithDistr[Domain, Dist]
Linear Supertypes
HasDistribution[Domain], RandomVariable[Domain], Serializable, Serializable, AnyRef, Any
Known Subclasses
AbstractGaussianRV, AbstractStudentsTRandVar, BinomialRV, BlockedMESNRV, ContinuousDistrMixture, ContinuousDistrRV, ContinuousRVWithDistr, DiscreteDistrRV, DiscreteRVWithDistr, EncodedContDistrRV, GaussianRV, GenericContinuousMCMC, IIDContinuousRVDistr, IIDDiscreteRVDistr, IIDRandomVarDistr, MatrixNormalRV, MatrixTRV, MeasurableDistrRV, MultGaussianPRV, MultGaussianRV, MultStudentsTPRV, MultStudentsTRV, MultinomialRV, RejectionSamplingScheme, StudentsTRV, UniformRV
Ordering
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  2. By Inheritance
Inherited
  1. RandomVarWithDistr
  2. HasDistribution
  3. RandomVariable
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract val sample: DataPipe[Unit, Domain]

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    Generate a sample from the random variable

    Generate a sample from the random variable

    Definition Classes
    RandomVariable

  2. abstract val underlyingDist: Dist

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    The actual probability density function is represented as a breeze Density object.

    The actual probability density function is represented as a breeze Density object.

    Definition Classes
    RandomVarWithDistr → HasDistribution

Concrete 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. def :*[Domain1, Dist1 <: Density[Domain1] with Rand[Domain1]](other: RandomVarWithDistr[Domain1, Dist1]): RandomVarWithDistr[(Domain, Domain1), GenericDistribution[(Domain, Domain1)]]

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    Cartesian product with another random variables which has a defined probability distribution.

  4. def :*[Domain1](other: RandomVariable[Domain1]): RandomVariable[(Domain, Domain1)]

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    Outputs the cartesian product between two random variables.

    Outputs the cartesian product between two random variables.

    Domain1

    The domain of the other random variable

    other

    The random variable which forms the second component of the cartesian product.

    Definition Classes
    RandomVariable

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

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    Definition Classes
    AnyRef → Any

  6. def >[OtherDomain](transformation: DataPipe[Domain, OtherDomain]): MeasurableFunction[Domain, OtherDomain, RandomVariable[Domain]]

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    Transform the current random variable on Domain to a morphed random variable on OtherDomain

    Transform the current random variable on Domain to a morphed random variable on OtherDomain

    Definition Classes
    RandomVariable

  7. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  8. def clone(): AnyRef

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

  9. def draw: Domain

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    Alias for sample.run()

    Alias for sample.run()

    Definition Classes
    RandomVariable

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

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    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  12. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  14. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  15. def iid(n: Int): RandomVariable[Stream[Domain]] with IIDRandomVariable[Domain, RandomVarWithDistr[Domain, Dist]]

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    Create an iid random variable from the current (this)

    Create an iid random variable from the current (this)

    n

    The number of iid samples of the base random variable.

    Definition Classes
    RandomVarWithDistr → RandomVariable

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  18. final def notify(): Unit

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    Definition Classes
    AnyRef

  19. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

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

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    Definition Classes
    AnyRef

  21. def toString(): String

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    Definition Classes
    AnyRef → Any

  22. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from HasDistribution[Domain]

Inherited from RandomVariable[Domain]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped