Trait

io.github.mandar2812.dynaml.models

StochasticProcessModel

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trait StochasticProcessModel[T, I, Y, W] extends Model[T, I, Y]

High Level description of a stochastic process based predictive model.

T

The underlying data structure storing the training & test data.

I

The type of the index set (i.e. Double for time series, DenseVector for GP regression)

Y

The type of the output label

W

Implementing class of the posterior distribution

Linear Supertypes
Model[T, I, Y], AnyRef, Any
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Abstract Value Members

  1. abstract def dataAsSeq(data: T): Seq[(I, Y)]

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    Convert from the underlying data structure to Seq[(I, Y)] where I is the index set of the GP and Y is the value/label type.

  2. abstract val g: T

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    The training data

    The training data

    Attributes
    protected
    Definition Classes
    Model
  3. abstract def predict(point: I): Y

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    Predict the value of the target variable given a point.

    Predict the value of the target variable given a point.

    Definition Classes
    Model
  4. abstract def predictiveDistribution[U <: Seq[I]](test: U): W

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    Calculates posterior predictive distribution for a particular set of test data points.

    Calculates posterior predictive distribution for a particular set of test data points.

    test

    A Sequence or Sequence like data structure storing the values of the input patters.

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
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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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    protected[java.lang]
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    @throws( ... )
  6. def data: T

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    Definition Classes
    Model
  7. def dataAsIndexSeq(data: T): Seq[I]

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    Convert from the underlying data structure to Seq[I] where I is the index set of the GP

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

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    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

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    Definition Classes
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  10. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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    Any
  14. final def ne(arg0: AnyRef): Boolean

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  18. def toString(): String

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  19. final def wait(): Unit

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    @throws( ... )
  20. final def wait(arg0: Long, arg1: Int): Unit

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

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Inherited from Model[T, I, Y]

Inherited from AnyRef

Inherited from Any

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