Value Members

1.  final def !=(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

2.  final def ##(): Int

   Definition Classes

   AnyRef → Any

3.  final def ==(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

4.  def apply(x: DenseVector[Double]): Double

   Definition Classes

   ContinuousDistr → Density

5.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

6.  def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

7.  def condition(p: (DenseVector[Double]) ⇒ Boolean): Rand[DenseVector[Double]]

   Definition Classes

   Rand

8.  val cov: DenseMatrix[Double]
9.  def draw(): DenseVector[Double]

   Draw from a multivariate gaussian using eigen decomposition which is often more stable than using the cholesky decomposition

   Draw from a multivariate gaussian using eigen decomposition which is often more stable than using the cholesky decomposition

   Definition Classes

   MultivariateGaussianSvd → Rand

10.  def drawOpt(): Option[DenseVector[Double]]

    Definition Classes

    Rand

11.  final def eq(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

12.  def filter(p: (DenseVector[Double]) ⇒ Boolean): Rand[DenseVector[Double]]

    Definition Classes

    Rand

13.  def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

14.  def flatMap[E](f: (DenseVector[Double]) ⇒ Rand[E]): Rand[E]

    Definition Classes

    Rand

15.  def foreach(f: (DenseVector[Double]) ⇒ Unit): Unit

    Definition Classes

    Rand

16.  def get(): DenseVector[Double]

    Definition Classes

    Rand

17.  final def getClass(): Class[_]

    Definition Classes

    AnyRef → Any

18.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

19.  def logApply(x: DenseVector[Double]): Double

    Definition Classes

    ContinuousDistr → Density

20.  def logNormalizer: Double

    Definition Classes

    MultivariateGaussianSvd → ContinuousDistr

21.  def logPdf(x: DenseVector[Double]): Double

    Definition Classes

    ContinuousDistr

22.  def map[E](f: (DenseVector[Double]) ⇒ E): Rand[E]

    Definition Classes

    Rand

23.  def mean: DenseVector[Double]
24.  def mode: DenseVector[Double]
25.  val mu: DenseVector[Double]
26.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

27.  lazy val normalizer: Double

    Definition Classes

    ContinuousDistr

28.  final def notify(): Unit

    Definition Classes

    AnyRef

29.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

30.  def pdf(x: DenseVector[Double]): Double

    Definition Classes

    ContinuousDistr

31.  def sample(n: Int): IndexedSeq[DenseVector[Double]]

    Definition Classes

    Rand

32.  def sample(): DenseVector[Double]

    Definition Classes

    Rand

33.  def samples: Iterator[DenseVector[Double]]

    Definition Classes

    Rand

34.  def samplesVector[U >: DenseVector[Double]](size: Int)(implicit m: ClassTag[U]): DenseVector[U]

    Definition Classes

    Rand

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

    Definition Classes

    AnyRef

36.  def unnormalizedLogPdf(x: DenseVector[Double]): Double

    Definition Classes

    MultivariateGaussianSvd → ContinuousDistr

37.  def unnormalizedPdf(x: DenseVector[Double]): Double

    Definition Classes

    ContinuousDistr

38.  def variance: DenseMatrix[Double]
39.  final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

41.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

42.  def withFilter(p: (DenseVector[Double]) ⇒ Boolean): Rand[DenseVector[Double]]

    Definition Classes

    Rand