GibbsWishart

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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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6. 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. def gibbsSamples(mod: Model, priorV: InverseGamma, priorW: InverseWishart, initParams: Parameters, observations: Array[Data]): Process[State]

    

    Do some gibbs samples

11. def hashCode(): Int

    

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14. final def notify(): Unit

    

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15. final def notifyAll(): Unit

    

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16. def sampleObservationMatrix(priorV: InverseGamma, mod: Model, state: Array[(Time, DenseVector[Double])], observations: Array[Data]): Rand[DenseMatrix[Double]]

    

    Sample a diagonal observation covariance matrix from the d-inverse Gamma Prior

17. def sampleSystemMatrix(priorW: InverseWishart, mod: Model, state: Array[(Time, DenseVector[Double])]): InverseWishart

    

    Sample the system covariance matrix using an Inverse Wishart prior on the system covariance matrix

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

    

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20. final def wait(): Unit

    

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

    

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

    

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23. def wishartStep(mod: Model, priorV: InverseGamma, priorW: InverseWishart, observations: Array[Data])(state: State): Rand[State]