c

breeze.stats.mcmc

ArbitraryMetropolisHastings

case class ArbitraryMetropolisHastings[T](logLikelihood: (T) ⇒ Double, proposal: (T) ⇒ Rand[T], logProposalDensity: (T, T) ⇒ Double, init: T, burnIn: Long = 0, dropCount: Int = 0)(implicit rand: RandBasis = Rand) extends BaseMetropolisHastings[T] with Product with Serializable

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Inherited
  1. ArbitraryMetropolisHastings
  2. Product
  3. Equals
  4. BaseMetropolisHastings
  5. TracksStatistics
  6. Process
  7. MetropolisHastings
  8. Rand
  9. Serializable
  10. Serializable
  11. AnyRef
  12. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ArbitraryMetropolisHastings(logLikelihood: (T) ⇒ Double, proposal: (T) ⇒ Rand[T], logProposalDensity: (T, T) ⇒ Double, init: T, burnIn: Long = 0, dropCount: Int = 0)(implicit rand: RandBasis = Rand)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def aboveOneCount: Long
    Definition Classes
    BaseMetropolisHastings → TracksStatistics
  5. def aboveOneFrac: Double
    Definition Classes
    TracksStatistics
  6. def acceptanceCount: Long
    Definition Classes
    BaseMetropolisHastings → TracksStatistics
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. val burnIn: Long
  9. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate() @throws( ... )
  10. def condition(p: (T) ⇒ Boolean): Rand[T]
    Definition Classes
    Rand
  11. def draw(): T

    Gets one sample from the distribution.

    Gets one sample from the distribution. Equivalent to sample()

    Definition Classes
    BaseMetropolisHastings → Rand
  12. def drawOpt(): Option[T]

    Overridden by filter/map/flatmap for monadic invocations.

    Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here

    Definition Classes
    Rand
  13. val dropCount: Int
  14. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. def filter(p: (T) ⇒ Boolean): Rand[T]
    Definition Classes
    Rand
  16. def flatMap[E](f: (T) ⇒ Rand[E]): Rand[E]

    Converts a random sampler of one type to a random sampler of another type.

    Converts a random sampler of one type to a random sampler of another type. Examples: randInt(10).flatMap(x => randInt(3 * x.asInstanceOf[Int]) gives a Rand[Int] in the range [0,30] Equivalently, for(x <- randInt(10); y <- randInt(30 *x)) yield y

    f

    the transform to apply to the sampled value.

    Definition Classes
    Rand
  17. def foreach(f: (T) ⇒ Unit): Unit

    Samples one element and qpplies the provided function to it.

    Samples one element and qpplies the provided function to it. Despite the name, the function is applied once. Sample usage: 

     for(x <- Rand.uniform) { println(x) }

    f

    the function to be applied

    Definition Classes
    Rand
  18. def get(): T
    Definition Classes
    Rand
  19. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  20. val init: T
  21. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  22. def likelihood(x: T): Double
    Definition Classes
    MetropolisHastings
  23. def likelihoodRatio(start: T, end: T): Double
    Definition Classes
    MetropolisHastings
  24. def logLikelihood(x: T): Double
    Definition Classes
    BaseMetropolisHastings → MetropolisHastings
  25. val logLikelihood: (T) ⇒ Double
  26. def logLikelihoodRatio(start: T, end: T): Double
    Definition Classes
    MetropolisHastings
  27. val logProposalDensity: (T, T) ⇒ Double
  28. def logTransitionProbability(start: T, end: T): Double
    Definition Classes
    ArbitraryMetropolisHastings → MetropolisHastings
  29. def map[E](f: (T) ⇒ E): Rand[E]

    Converts a random sampler of one type to a random sampler of another type.

    Converts a random sampler of one type to a random sampler of another type. Examples: uniform.map(_*2) gives a Rand[Double] in the range [0,2] Equivalently, for(x <- uniform) yield 2*x

    f

    the transform to apply to the sampled value.

    Definition Classes
    Rand
  30. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  31. def nextDouble: Double
    Attributes
    protected
    Definition Classes
    MetropolisHastings
  32. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  33. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  34. def observe(x: T): ArbitraryMetropolisHastings[T]

    Force the "next" draw to be x, and return a new process.

    Force the "next" draw to be x, and return a new process.

    Definition Classes
    ArbitraryMetropolisHastings → Process
  35. val proposal: (T) ⇒ Rand[T]
  36. def proposalDraw(x: T): T
    Definition Classes
    ArbitraryMetropolisHastings → MetropolisHastings
  37. implicit val rand: RandBasis
    Definition Classes
    BaseMetropolisHastings → MetropolisHastings
  38. def rejectionCount: Long
    Definition Classes
    TracksStatistics
  39. def rejectionFrac: Double
    Definition Classes
    TracksStatistics
  40. def sample(n: Int): IndexedSeq[T]

    Gets n samples from the distribution.

    Gets n samples from the distribution.

    Definition Classes
    Rand
  41. def sample(): T

    Gets one sample from the distribution.

    Gets one sample from the distribution. Equivalent to get()

    Definition Classes
    Rand
  42. def samples: Iterator[T]

    An infinitely long iterator that samples repeatedly from the Rand

    An infinitely long iterator that samples repeatedly from the Rand

    returns

    an iterator that repeatedly samples

    Definition Classes
    Rand
  43. def samplesVector[U >: T](size: Int)(implicit m: ClassTag[U]): DenseVector[U]

    Return a vector of samples.

    Return a vector of samples.

    Definition Classes
    Rand
  44. def step(): (T, Process[T])

    Draw a sample and the next step of the process along with it.

    Draw a sample and the next step of the process along with it.

    Definition Classes
    Process
  45. def steps: Iterator[T]

    Returns an Iterator that automatically moves the Process along as next is called

    Returns an Iterator that automatically moves the Process along as next is called

    Definition Classes
    Process
  46. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  47. def total: Long
    Definition Classes
    BaseMetropolisHastings → TracksStatistics
  48. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  49. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  50. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  51. def withFilter(p: (T) ⇒ Boolean): Rand[T]
    Definition Classes
    Rand

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

Inherited from Product

Inherited from Equals

Inherited from BaseMetropolisHastings[T]

Inherited from TracksStatistics

Inherited from Process[T]

Inherited from MetropolisHastings[T]

Inherited from Rand[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped