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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: Dlm, ys: Vector[Data], p: DlmParameters, advState: (SvdState, Double) ⇒ SvdState): Rand[Vector[SamplingState]]

   Perform forward filtering backward sampling using the SVD of the covariance matrix

9.  def ffbsDlm(mod: Dlm, ys: Vector[Data], p: DlmParameters): Rand[Vector[SamplingState]]

   Perform FFBS for a DLM using the SVD

10.  def finalize(): Unit

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11.  final def getClass(): Class[_]

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12.  def hashCode(): Int

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13.  def initialise(filtered: Array[SvdState]): SamplingState
14.  def intervalState(sampled: Seq[Seq[(Double, DenseVector[Double])]], interval: Double = 0.95): Seq[(Double, (DenseVector[Double], DenseVector[Double]))]
15.  final def isInstanceOf[T0]: Boolean

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16.  def meanState(sampled: Seq[Seq[SamplingState]]): Seq[List[Double]]
17.  final def ne(arg0: AnyRef): Boolean

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18.  final def notify(): Unit

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19.  final def notifyAll(): Unit

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20.  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

21.  def sample(mod: Dlm, st: Vector[SvdState], sqrtW: DenseMatrix[Double]): Vector[SamplingState]

    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

    st

    the filtered state

22.  def step(mod: Dlm, sqrtW: DenseMatrix[Double])(st: SvdState, ss: SamplingState): SamplingState

    Perform a single step in the backward sampler using the SVD

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

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24.  def toString(): String

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25.  final def wait(): Unit

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

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27.  final def wait(arg0: Long): Unit

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