Class

io.github.mandar2812.dynaml.probability.mcmc

HyperParameterHMC

Related Doc: package mcmc

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abstract class HyperParameterHMC[Model <: GloballyOptWithGrad, Distr <: ContinuousDistr[Double]] extends RandomVariable[Map[String, Double]]

Hamiltonian Markov Chain Monte Carlo algorithm, equipped with reversible Metropolis Hastings updates.

Model

Any type which implements the GloballyOptimizable trait i.e. the GloballyOptimizable.energy() method.

Distr

A breeze distribution type for hyper-parameter priors.

Linear Supertypes
RandomVariable[Map[String, Double]], Serializable, Serializable, AnyRef, Any
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  1. HyperParameterHMC
  2. RandomVariable
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Instance Constructors

  1. new HyperParameterHMC(system: Model, hyper_prior: Map[String, Distr], proposal: ContinuousRVWithDistr[DenseVector[Double], ContinuousDistr[DenseVector[Double]]], burnIn: Long)

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    system

    The model whose hyper-parameters are to be sampled.

    hyper_prior

    A mean field prior measure over the system hyper-parameters. Represented as a Map.

Abstract Value Members

  1. abstract val sample: DataPipe[Unit, Map[String, Double]]

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    Generate a sample from the random variable

    Generate a sample from the random variable

    Definition Classes
    RandomVariable

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](other: RandomVariable[Domain1]): RandomVariable[(Map[String, Double], 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

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

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    Definition Classes
    AnyRef → Any

  5. def >[OtherDomain](transformation: DataPipe[Map[String, Double], OtherDomain]): MeasurableFunction[Map[String, Double], OtherDomain, RandomVariable[Map[String, Double]]]

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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

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. val burnIn: Long

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  8. def clone(): AnyRef

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

  9. def draw: Map[String, Double]

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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): IIDRandomVariable[Map[String, Double], RandomVariable[Map[String, Double]]]

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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
    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 RandomVariable[Map[String, Double]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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