case class NDimensionalNormalDistribution[D](mean: EuclideanVector[D], cov: SquareMatrix[D])(implicit evidence$2: NDSpace[D]) extends MultivariateNormalDistributionLike[EuclideanVector[D], SquareMatrix[D]] with Product with Serializable
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- @deprecated
- Deprecated
(Since version 0.13.0) Please use MultivariateNormalDistribution instead. This class wil be removed in future versions.
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Instance Constructors
- new NDimensionalNormalDistribution(mean: EuclideanVector[D], cov: SquareMatrix[D])(implicit arg0: NDSpace[D])
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##(): Int
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- final def ==(arg0: Any): Boolean
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- final def asInstanceOf[T0]: T0
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- def clone(): AnyRef
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- protected[lang]
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- val cov: SquareMatrix[D]
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- def dim: Int
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- final def eq(arg0: AnyRef): Boolean
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- def finalize(): Unit
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- final def isInstanceOf[T0]: Boolean
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- Any
- def logpdf(x: EuclideanVector[D]): Double
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- def mahalanobisDistance(x: EuclideanVector[D]): Double
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- val mean: EuclideanVector[D]
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- final def notifyAll(): Unit
- Definition Classes
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- @native()
- def pdf(x: EuclideanVector[D]): Double
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- def principalComponents: Seq[(EuclideanVector[D], Double)]
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- def sample()(implicit rand: Random): EuclideanVector[D]
- Definition Classes
- NDimensionalNormalDistribution → MultivariateNormalDistributionLike
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
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- def toMultivariateNormalDistribution: MultivariateNormalDistribution
- final def wait(): Unit
- Definition Classes
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- final def wait(arg0: Long, arg1: Int): Unit
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- final def wait(arg0: Long): Unit
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