ParticleFilter

Abstract Value Members

abstract def filterStream(t0: Time)(particles: Int): Flow[Data, PfState, NotUsed]

Run a filter over a stream of data
implicit abstract def g: Monad[G]
abstract val mod: Model
abstract def resample: Resample[State, G]

Concrete Value Members

final def !=(arg0: Any): Boolean

Definition Classes
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final def ##(): Int

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final def ==(arg0: Any): Boolean

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final def asInstanceOf[T0]: T0

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def clone(): AnyRef

Attributes
protected[java.lang]
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@throws( ... )
final def eq(arg0: AnyRef): Boolean

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def equals(arg0: Any): Boolean

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def filter(data: Vector[Data])(particles: Int): G[(LogLikelihood, Vector[StateSpace])]

A particle filter to be ran over observed data to return the log-likelihood and a proposed value of the path by sampling from the distribution of the paths
A particle filter to be ran over observed data to return the log-likelihood and a proposed value of the path by sampling from the distribution of the paths
data
the initial time of the data
particles
the number of particles to use in the particle approximation to the filtering distribution
returns
G[(LogLikelihood, Vector[State])] The log likelihood and a sample from the posterior of the filtering distribution inside of a computational context, G, which can be a Future for async computation or Id for sequential computation
def finalize(): Unit

Attributes
protected[java.lang]
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Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

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def hashCode(): Int

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def initialiseState(particles: Int, t0: Time): PfState
final def isInstanceOf[T0]: Boolean

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def llFilter(data: Vector[Data])(n: Int): G[LogLikelihood]

Filter a collection of data and return an estimate of the loglikelihood
final def ne(arg0: AnyRef): Boolean

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final def notify(): Unit

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final def notifyAll(): Unit

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def stepFilter(s: PfState, y: Data): G[PfState]
final def synchronized[T0](arg0: ⇒ T0): T0

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def toString(): String

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final def wait(): Unit

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

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@throws( ... )
final def wait(arg0: Long): Unit

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@throws( ... )

Related Docs: object ParticleFilter | package model

trait ParticleFilter[G[_]] extends AnyRef

Abstract Value Members

abstract def filterStream(t0: Time)(particles: Int): Flow[Data, PfState, NotUsed]

implicit abstract def g: Monad[G]

abstract val mod: Model

abstract def resample: Resample[State, G]

Concrete Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def filter(data: Vector[Data])(particles: Int): G[(LogLikelihood, Vector[StateSpace])]

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

def initialiseState(particles: Int, t0: Time): PfState

final def isInstanceOf[T0]: Boolean

def llFilter(data: Vector[Data])(n: Int): G[LogLikelihood]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def stepFilter(s: PfState, y: Data): G[PfState]

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from AnyRef

Inherited from Any

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