dk.bayes.learn.lds

GenericLDSLearn

Related Doc: package lds

object GenericLDSLearn extends LDSMStep

Default implementation of GenericLDSMStep. It supports one dimensional linear dynamical system only, where both state and observations are 1-D real vectors.

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LDSMStep, AnyRef, Any
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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

    Definition Classes
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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 finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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

    Definition Classes
    AnyRef

  13. def newA(sStats: IndexedSeq[DenseCanonicalGaussian]): Double

    sStats

    Sufficient statistics, marginals of transition factors (time t-1, time t)

    Definition Classes
    GenericLDSLearn → LDSMStep

  14. def newC(sStats: IndexedSeq[(DenseCanonicalGaussian, Double)]): Double

    M-step

    M-step

    sStats

    Sufficient statistics. Seq of Tuple2[marginal of prior factor, observed value]

    Definition Classes
    GenericLDSLearn → LDSMStep

  15. def newPi(sStats: IndexedSeq[DenseCanonicalGaussian]): Double

    sStats

    Sufficient statistics, marginals of prior factors

    Definition Classes
    GenericLDSLearn → LDSMStep

  16. def newQ(sStats: IndexedSeq[DenseCanonicalGaussian]): Double

    sStats

    Sufficient statistics, marginals of transition factors (time t-1, time t)

    Definition Classes
    GenericLDSLearn → LDSMStep

  17. def newR(sStats: IndexedSeq[(DenseCanonicalGaussian, Double)]): Double

    sStats

    Sufficient statistics. Seq of Tuple2[marginal of prior factor, observed value]

    Definition Classes
    GenericLDSLearn → LDSMStep

  18. def newV(sStats: IndexedSeq[DenseCanonicalGaussian]): Double

    E[x2] - E[x]2

    sStats

    Sufficient statistics, marginals of prior factors

    Definition Classes
    GenericLDSLearn → LDSMStep

  19. final def notify(): Unit

    Definition Classes
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  20. final def notifyAll(): Unit

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

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  22. def toString(): String

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  23. final def wait(): Unit

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

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

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Inherited from LDSMStep

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