SvdSampler

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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. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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

   

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7. def equals(arg0: Any): Boolean

   

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8. def ffbs(mod: Model, ys: Vector[Data], p: Parameters): Rand[Vector[(Double, DenseVector[Double])]]

   

   Perform forward filtering backward sampling

9. def finalize(): Unit

   

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

    

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11. def hashCode(): Int

    

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12. def initialise(filtered: Array[SvdFilter.State]): State

    

13. def intervalState(sampled: Seq[Seq[(Double, DenseVector[Double])]], interval: Double = 0.95): Seq[(Double, (DenseVector[Double], DenseVector[Double]))]

    

14. final def isInstanceOf[T0]: Boolean

    

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15. def meanState(sampled: Seq[Seq[(Double, DenseVector[Double])]]): Seq[List[Double]]

    

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

    

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17. final def notify(): Unit

    

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18. final def notifyAll(): Unit

    

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19. def rnorm(mu: DenseVector[Double], d: DenseVector[Double], u: DenseMatrix[Double]): Rand[DenseVector[Double]]

    

    Simulate from a normal distribution given the right vectors and singular values of the covariance matrix

    Simulate from a normal distribution given the right vectors and singular values of the covariance matrix

    mu

    the mean of the multivariate normal distribution

    d

    the square root of the diagonal in the SVD of the Error covariance matrix C_t

    u

    the right vectors of the SVDfilter

    returns

    a DenseVector sampled from the Multivariate Normal distribution with mean mu and covariance u d^{2 u}T

20. def sample(mod: Model, w: DenseMatrix[Double], st: Vector[SvdFilter.State]): Vector[(Double, DenseVector[Double])]

    

    Given a vector containing the SVD filtered results, perform backward sampling

    Given a vector containing the SVD filtered results, perform backward sampling

    mod

    a DLM specification

    w

    the system error matrix

21. def step(mod: Model, sqrtWInv: DenseMatrix[Double])(st: SvdFilter.State, ss: State): State

    

    Perform a single step in the backward sampler using the SVD

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

    

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23. def toString(): String

    

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24. final def wait(): Unit

    

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

    

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

    

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