object ParticleGibbs extends Serializable

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  15. def sample(n: Int, mod: Dglm, ys: Vector[Data], p: DlmParameters): Rand[(Double, Vector[(Double, DenseVector[Double])])]

    Sample the conditioned state from the Particle Gibbs Sampler

    Sample the conditioned state from the Particle Gibbs Sampler

    n

    the number of particles to use in the particle filter

  16. def sampleState(states: Vector[Vector[(Double, DenseVector[Double])]], weights: Vector[Double]): Rand[Vector[(Double, DenseVector[Double])]]

    Using the weights at time T (the end of all observations) sample a path from the collection of paths

    Using the weights at time T (the end of all observations) sample a path from the collection of paths

    states

    a collection of paths with ancestory, the outer list is of length T, theinner length N

    weights

    particle weights at time T

    returns

    a single path

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