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scalismo.statisticalmodel

DiscreteLowRankGaussianProcess

Related Docs: class DiscreteLowRankGaussianProcess | package statisticalmodel

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object DiscreteLowRankGaussianProcess extends Serializable

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Type Members

  1. case class Eigenpair[D <: Dim, DO <: Dim](eigenvalue: Float, eigenfunction: DiscreteVectorField[D, DO]) extends Product with Serializable

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  2. type KLBasis[D <: Dim, DO <: Dim] = Seq[Eigenpair[D, DO]]

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Value Members

  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. def apply[D <: Dim, DO <: Dim](mean: DiscreteVectorField[D, DO], klBasis: KLBasis[D, DO])(implicit arg0: NDSpace[D], arg1: NDSpace[DO]): DiscreteLowRankGaussianProcess[D, DO]

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  5. def apply[D <: Dim, DO <: Dim](domain: DiscreteDomain[D], gp: LowRankGaussianProcess[D, DO])(implicit arg0: NDSpace[D], arg1: NDSpace[DO]): DiscreteLowRankGaussianProcess[D, DO]

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    Creates a new DiscreteLowRankGaussianProcess by discretizing the given gaussian process at the domain points.

  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  8. def createUsingPCA[D <: Dim](domain: DiscreteDomain[D], fields: Seq[VectorField[D, D]])(implicit arg0: NDSpace[D]): DiscreteLowRankGaussianProcess[D, D]

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    Creates a new DiscreteLowRankGaussianProcess, where the mean and covariance matrix are estimated from the given sample of continuous vector fields using Principal Component Analysis.

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

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def regression[D <: Dim, DO <: Dim](gp: DiscreteLowRankGaussianProcess[D, DO], trainingData: IndexedSeq[(PointId, Vector[DO], NDimensionalNormalDistribution[DO])])(implicit arg0: NDSpace[D], arg1: NDSpace[DO]): DiscreteLowRankGaussianProcess[D, DO]

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    Discrete implementation of LowRankGaussianProcess.regression

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

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  20. def toString(): String

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  21. final def wait(): Unit

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

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

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