Class

com.github.jonnylaw.model

MetropState

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case class MetropState(ll: LogLikelihood, params: Parameters, state: Vector[State], accepted: Int) extends Serializable with Product

The state of the metropolis-hastings algorithms

ll

the log-likelihood of the observations given the latent state and the current parameters

params

the current set of parameters

state

the proposed path of the state from the particle filter

accepted

the total number of accepted moves in the metropolis hastings algorithm

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Instance Constructors

  1. new MetropState(ll: LogLikelihood, params: Parameters, state: Vector[State], accepted: Int)

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    ll

    the log-likelihood of the observations given the latent state and the current parameters

    params

    the current set of parameters

    state

    the proposed path of the state from the particle filter

    accepted

    the total number of accepted moves in the metropolis hastings algorithm

Value Members

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

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  2. final def ##(): Int

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

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  4. val accepted: Int

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    the total number of accepted moves in the metropolis hastings algorithm

  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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

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  8. def finalize(): Unit

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

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  10. final def isInstanceOf[T0]: Boolean

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  11. val ll: LogLikelihood

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    the log-likelihood of the observations given the latent state and the current parameters

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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  15. val params: Parameters

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    the current set of parameters

  16. val state: Vector[State]

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    the proposed path of the state from the particle filter

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

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  18. final def wait(): Unit

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

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

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