org.apache.spark.mllib.stat.distribution

MultivariateGaussian

class MultivariateGaussian extends Serializable

:: DeveloperApi :: This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution. In the event that the covariance matrix is singular, the density will be computed in a reduced dimensional subspace under which the distribution is supported. (see http://en.wikipedia.org/wiki/Multivariate_normal_distribution#Degenerate_case)

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@Since( "1.3.0" ) @DeveloperApi()
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Instance Constructors

  1. new MultivariateGaussian(mu: Vector, sigma: Matrix)

    mu

    The mean vector of the distribution

    sigma

    The covariance matrix of the distribution

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    @Since( "1.3.0" )

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  14. def logpdf(x: Vector): Double

    Returns the log-density of this multivariate Gaussian at given point, x

    Returns the log-density of this multivariate Gaussian at given point, x

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    @Since( "1.3.0" )

  15. val mu: Vector

    The mean vector of the distribution

    The mean vector of the distribution

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    @Since( "1.3.0" )

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. def pdf(x: Vector): Double

    Returns density of this multivariate Gaussian at given point, x

    Returns density of this multivariate Gaussian at given point, x

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    @Since( "1.3.0" )

  20. val sigma: Matrix

    The covariance matrix of the distribution

    The covariance matrix of the distribution

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    @Since( "1.3.0" )

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

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